UHR Volume 11 (2006) OCR

TAH ' S HEALTH n Annual Review Volume 11 www.uhreview.com Utah's Health: An Annual Review | The University of Utah Governor Scott M. Matheson Center For Healthcare Studies 1901 E. South Campus Drive, Room 2120, Salt Lake City, UT 84112-9153 © 2006 The University of Utah. All Rights Reserved. Introduction and Editor's Note I am pleased to release the eleventh volume of Utah's Health: An Annual Review􀀑􁄠 th e Utah's Health editorial board consists of students from many educational disciplines who work with faculty supervisors and community peer reviewers to publish a scholarly health research journal. As a scientific journal, Utah's Health is dedicated to publishing original health-related research and reporting and analyzing health-related data. It also promotes health policy dialogue at both state and national levels. In addition to aiding students, researchers, legislators, and health-related professionals, Utah's Health also serves as a health education resource to the general public. I invite the public to access our new website, www.uhreview.com, now an available reference in addition to our printed journals. Consistent with previous editions, Volume XI comprises three main sections: Original Research Articles, Special Topics Articles, and a Data Section. Various students, physicians, statisticians, and other healthcare and community professionals throughout Utah have contributed to the original research section. th is year's articles cover a wide variety of subject matter ranging from a study of African-American infant mortality rates to Utah's first statewide assessment of patient safety events. The Special Topics Section contains articles extraordinarily timely or uniquely specific to Utah. This year's special topics include an article addressing the increasing number of refugees in Utah and implications for the state's healthcare system, an article describing the health-related challenges of the Avian bird flu, and a height-weight study of Utah's school children. This year's special topics also feature a health policy subsection with articles addressing 2006 Utah state legislative action regarding health-related policy issues. The Data Section contains pages analyzing a variety of health statistical trends in Utah and the U.S. Because some topics did not have updated data since last year's publication, some pages that were included in Volume X are not included in Volume XI. Editors invite readers to refer to Volume X for data pages that were not published in Volume XI. Many deserve credit for the successful publication of Utah's Health, Volume XI. I would like to thank a stalwart group of volunteer advisory board members that assisted student editors in reviewing and editing articles and data. I thank the editorial board, executive editors, and production team for their diligent work in moving Volume XI from start to finish. I also wish to thank faculty advisor Richard Sperry, M.D., for his continued support of Utah's Health􀀑􁄠 Perhaps most importantly, Utah's Health wishes to give an extremely well-deserved thanks to Dr. Robert Huefner. Dr. Huefner, who will begin his last year of phased retirement next year, will be stepping down from his role as Utah's Health faculty advisor in the near future, a role he has served in since the journal's first publication 13 years ago. Speaking for the many students that have participated in different editions of the journal, we wish to sincerely thank you, Dr. Huefner, for sharing your unique vision, expertise and intellect with the University of Utah. Adam Reiser, Editor-in-Chief, Volume XI, 2006 Authors and Contributors Erica Baiden is a third year medical student at the University of Utah School of Medicine. Erica would like to thank the Department of Family and Preventive Medicine and the Utah Department of Health Maternal. Child, and Infant Health Department for supporting her research. Susan L. Beck, PhD, is an Associate Professor and Associate Dean for Academic Affairs at the University of Utah College of Nursing. Karen A. Coats, BS, CHES, is a Health Program Specialist in the Heart Disease and Stroke Prevention Program, Bureau of Health Promotion at the Utah Department of Health. Steve Donnelly, PhD, is employed by Healthlnsight. William N. Dudley, PhD, is the Director of Applied Statistics at the University College of Nursing. Michael Friedrichs, MS, is the lead Epidemiologist in the Bureau of Health Promotion at the Utah Department of Health. Steven Hillam, BS, is a graduate student in Exercise Science at Brigham Young University. Paul Hougland, MD, is employed with the Utah Department of Health Office of Health Care Statistics. Greg Jaboin, AB, is the Health Policy Research Analyst for Utah Issues, Center for Poverty Research and Action. LaDene Larsen, RN, is the Director of the Bureau of Health Promotion at the Utah Department of Health. Jenifer Lloyd, DVM, MSPH, is a Project Facilitator for the University of Utah Health Sciences Center's Division of General Pediatrics. Carol Masheter, PhD, is employed with the Utah Department of Health Office of Health Care Statistics. Augustino Mayai is a lost boy of Sudan. He graduated from the University of Utah in 2006, only five years after arriving in America, and will begin a doctoral program in the fall of 2007. William McMahon, MD, is a Professor of Psychiatry, Pediatrics, Psychology and Educational Psychology at the University of Utah Health Sciences Center Department of Psychiatry. Ray M. Merrill, PhD, MPH, is a Professor of Biostatistics and Epidemiology in the Health Science Department at Brigham Young University. Judith Miller, PhD, is an Assistant Professor of Child & Adolescent Psychiatry at the University of Utah Health Sciences Center Department of Psychiatry. Kimberly S. Mueller, MS, recently received her Masters of Public Health from the University of Utah. She has worked as medical social worker for nine years. Jonathan Nebeker, MD, is an Assistant Professor of Geriatrics at the University of Utah School of Medicine. Karen Nellist, MPH, is an Information Analyst in the Bureau of Health Promotion at the Utah Department of Health. Stephen Pickard, MBA, is employed with PEGUS Research, Inc. Robert Rolfs, MD, MPH, is the State Epidemiologist for Utah. Michael P. Silver, MPH, is employed with Healthlnsight. Doug Springmeyer, JD, is an Assistant Attorney General for the State of Utah. Gail L. Towsley, MS, is a doctoral candidate at the University of Utah College of Nursing. Rebecca Utz, PhD, is an Assistant Professor of Sociology at the University of Utah. She is a social demographer with interests in health and aging. Joan L. Ware, RN, MSPH, is a consultant to Women's Health Council for the National Association of Chronic Disease Directors and past Program Manager of the Heart Disease and Stroke Prevention Program at the Utah Department of Health. George L. White, Jr. PhD, MSPH, is Professor and Director of the Public Health Program, Department of Family and Preventive Medicine at the University of Utah School of Medicine. Scott D. Williams, MD, MPH, is Vice President for medical affairs at Health Insight. Wu Xu, PhD, Is the Director of the Utah Department of Health Office of Health Care Statistics. Judith Zimmerman, PhD, is a Program Manager for the Child Development Clinic and the Utah Registry of Autism and Developmental Disabilities, Bureau of Children with Special Health Care Needs, Utah Department of Health. Table of Contents Utah's Health: An Annual Review | Volume X I | Original Research Articles Chart Review to Determine Associated Risk Factors Related to Peripartum Mortality in Utah's African American Infants Erica Baiden, MSII; George L. White, Jr., PhD, MSPH; Lois Bloebaum, BSN; Pete Barnard, CNM Quality Care in Utah Nursing Homes: Urban vs. Rural Gail L. Towsley, MS; William N. Dudley, PhD; Susan L. Beck, PhD Analysis of Surveillance Data of Three Sexually Transmitted Diseases and Hepatitis C in a Selected Population in Salt Lake County Kimberly S. Mueller, MSSA Patient Safety Events in Utah: The First Statewide Assessment Wu Xu, PhD; Steven Pickard, MBA; Michael P. Silver, MPH; Paul Hougland, MD; Carol Masheter, PhD; Steve Donnelly, PhD; Jonathan Nebeker, MD; Matthew Samore, MD; Scott D. Williams, MD, MPH Religion and Bodyweight in Utah Ray M. Merrill, PhD, MPH; Steven Hillam, BS Developmental Screening Practices and Autism Awareness of Utah's Primary Care Physicians: 2004 Survey Results Jenifer Chapman Lloyd, DVM, MSPH; Judith Pinborough Zimmerman, PhD; William McMahon, MD; Judith Miller, PhD Special Topics Articles The Health and Health Care Needs of a Refugee Population: The Lost Boys of Sudan Rebecca L. Utz, PhD; Augustino Mayai Utah School Children Height and Weight Measurement Project, 1993 and 2002 Karen Nellist, MPH; Karen A. Coats, BS, CHES; Michael Friedrichs, MS; Joan L. Ware, RN, MSPH; LaDene Larsen, RN Pandemic Influenza: Background and Challenges for Preparedness Robert T. Rolfs, MD, MPH Health Policy A Case Study: Public Health Legislation HB 129 George L. White, Jr., PhD, MSPH; Doug Springmeyer, JD 2006 Utah Legislative Review Jen Jankowski Health Savings Accounts: Banking on Better Healthcare? Greg Jaboin, AB June 2006 10 16 24 32 40 51 66 72 78 87 89 96 2006 Utah Health Data Review Health Services Directory 101 182 Utah's Health: An Annual Review Original Research 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Chart Review to Determine Associated Risk Factors Related to Peripartum Mortality in Utah's African American Infants Erica Baiden, MSII; George L. White Jr., PhD, MSPH; Lois Bloebaum, BSN; Pete Barnard, CNM CORRESPONDENCE: Erica Baiden University o f Utah School o f Medicine [phone] [e-mail] Abstract Though the U.S. infant mortality rate has steadily declined, the disparity among African Americans continues to persist and has increased over time. The national trend mirrors that of the african americans residing in Utah even when grouped in similar socioeconomic strata. As such, further analysis of infant mortality data, particularly by race and ethnicity in Utah, is needed to reduce these types of health outcome disparities. The Utah African American infant mortality rate for 2001-2003 was 18.1/1000 live births. In comparison, the general infant mortality rate for Utahns was 2.0/1000 live births. Pre-pregnancy maternal Body Mass Index (BMI), maternal education status, alcohol use, prenatal care, and Medicaid status were all predisposing risk factors for African American infant mortality in Utah. It is important to realize that disparities in birth outcomes are not only the result of complications during pregnancy, but also include differential exposures encountered throughout a woman's life. this holds true for african american women residing in Utah, who are unique in that they are typically isolated from one another physically by distance, mentally by culture, and emotionally by apprehension. Therefore, it is not only important for health care providers to ask African American women about their social support network, but also incorporate African American women in a women's health/prenatal social group. Infant mortality is one of the best and most accepted indicators of a community's health status and can also provide a means to analyze the degree to which community health services meet the needs of infants and women. When compared against the rest of the nation, pregnant women in Utah continue to seek prenatal care at a much lower rate. Although both Caucasian women and African American women in Utah seek prenatal care at a similar low rate, African American infants have a mortality rate twice that of Caucasian infants. This study will assist in the identification of the significant maternal and infant characteristics that appear to be associated with higher infant mortality rates in Utah's African American population. Further analysis of infant mortality data particularly by race and ethnicity in Utah is needed to reduce these types of health outcome disparities. Recommendations for further health care intervention are in this study. Methods Data were abstracted from the medical records and hospital discharge summaries of African American women in Utah who experienced infant death from 2001-2003. A standardized table was prepared consisting of various maternal and infant characteristics not only to make database entry easier, but also to make sure significant features were captured in each case. Data were also abstracted from the 2001-2003 linked birth and death certificates of the African American infants who died under one year of age. Again, a standardized table aided in data collection and organization. Access 10 African American Infant Mortality © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW to the medical records from the facilities where the death occurred were gained through written requests from the Utah Department of Health Reproductive Program. The maternal records and infant deaths were then de-identified and organized into the following three categories: Perinatal Conditions, Injuries/Diseases, and Congenital Anomalies. The infant mortality rate was then calculated and analyzed across several potential risk factors of infant mortality using Epi Info™ (version 3.2.2).1* These risk factors included maternal age, maternal marital status, maternal education status, infant birth weight and gestational age, and the status of prenatal care. Data regarding live births of African Americans were obtained from Utah's Indicator-Based Information System for Public Health or IBIS.2* This information was used as a comparison group. The data collected from IBIS, hospital records, linked birth and death certificates, and the Utah Department of Health State Review of Perinatal Infant Deaths were all used in analyzing the findings.2 A referent group in each category was chosen based on their higher infant survival outcomes. The data obtained from IBIS and the chart abstractions are not within the same time periods and thus puts limitations on the ability to compare data. Also, though published in 2003, the Utah Department of Health State Review of Infant Deaths consisted of data from 1995 to 1998. Methods of outreach within the African American community were discussed with members of the Utah Department of Health's Reproductive Health Program and the State of Utah Division of Community Development, Office of Black Affairs. Results Eighteen African American infant deaths occurred in Utah during the time period of 2001-2003. This resulted in an infant mortality rate of 18.1/1000 African American births in Utah. This rate is about nine times higher than that of the general Utah population whose rate was 2.0/1000 births. In both the general Utah population and the African American community of women who experienced infant mortality, the maternal age range of 20-29 was consistent with a better outcome of infant survival, see figures 1 and 2. The infant mortality rate by level of education was higher for African American mothers with more than a high school education than that of african american mothers who had less than a high school education. th is trend was not exhibited among the mothers of the general Utah population, as their rate of infant mortality decreased as the level of education increased. In nulliparous women in the general Utah population, the infant mortality rate was slightly higher than that of multiparous women. However, in African American women residing in Utah, being nulliparous (6.2/1000 live births) seemed to have a protective value over that of being multiparous (16.6/1000), but the rates were not statistically significant. In the general Utah population, a pre-pregnancy BMI of 29.1 or greater was linked with an increased rate of infant mortality compared to a pre-pregnancy BMI of 19.8 or less. Among Utah African American mothers, however, a BMI of 29.1 or greater was associated with an infant mortality rate of 21.9/1000 live births, and a BMI below 19.8 was associated with an infant mortality rate of 24.5/1000 live births. Please see figures 1 and 2. One of the most statistically significant risk factors of infant mortality in Utah African Americans was the lack of prenatal care (375/1000). Infant males consistently experienced higher rates of infant mortality in both groups. The infant mortality rate for plurality at birth increased as the number of gestations increased. th is trend was also consistent between the two groups. th e rate of tobacco and alcohol use among Utah african americans during pregnancy was higher than that of the general Utah population. Prematurity, placental anomalies and perinatal microbial infections were among the leading causes of death within african american infants. 1 * Epi Info™ is a public domain software package designed for the global community of public health practitioners and researchers. It provides for easy form and database construction, data entry, and analysis with epidemiologic statistics, maps, and graphs. 2 *The IBIS database only contained records up to and including 2002 © 2006 The University o f Utah. All rights reserved. African American Infant Mortality 11 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Discussion Prenatal care is a crucial aspect of the health and well being of a mother and child during pregnancy. Many studies emphasize the importance of obtaining prenatal care in the first trimester of pregnancy and continuing throughout its duration in order to reduce complications of pregnancy and the prevalence of infant mortality. From 1995-1998, only 5 of the 707 women in the general Utah population who did not receive prenatal care experienced an infant death. This led to an infant death rate of 7.1/1000 births. In comparison, we observed a death rate of 375/1000 births in the African American women we studied in Utah. Thus, African women who did not obtain any prenatal care during pregnancy had a 35 times greater risk of experiencing infant mortality compared to the general Utah population who only had a risk of 0.2 if prenatal care was not obtained. However, traditional prenatal care, though essential is not adequate enough to improve birth outcomes (Fiscella, 1996). Prenatal care targeted to African Americans should include and be responsive to issues surrounding maternal and local stressors, health care service barriers, and methods to comply with various treatments. Many women, especially African American women sometimes put these things aside though obligations to work or to take care of the family are ever present (Geronimus, 2001). Medicaid is a vital resource in terms of health care coverage for many women of color though Medicaid eligibility is restrictive and limited (Wyn, 2004). In our study population, Medicaid eligibility was not necessarily beneficial in improving infant mortality outcomes. Instead, receiving Medicaid benefits was associated with an infant mortality rate of 43.7/1000 births. In both the African American women studied and the general Utah population observed, 20 to 29 year olds consistently had positive birth outcomes and experienced the fewest instances of infant mortality. Nevertheless, in a study by Arlene Geronimus (2001), Caucasian teenage mothers who typically have the highest infant mortality rate among whites had better birth outcomes than African American mothers in their 20s and 30s (Geronimus, 2001). This age group of African American women is also the group that tends to be at an economic advantage over other African American women. The rate of tobacco use among Utah's African American mothers was 13.2/1000 births. The rate of alcohol use among Utah's African American mothers was 103.4/1000 births. This rate was not only statistically significant, but also considerably higher than that of the general Utah population of mothers. This may be due to the fact that products such as alcohol and tobacco are disproportionately targeted towards the African American community (Collins, 2000). For example, according to Michael Lu, UCLA professor of Obstetrics and Gynecology, African American non-smokers, have an infant mortality rate of 13.2 compared to that of Caucasian smokers who have a rate of 9.2 (Lu, 2004). Another interesting finding was the correlation between infant mortality and education. The rate of infant mortality among women in the general Utah population decreased as the level of maternal education increased. Our results showed that as the level of education increased in African American women, so did the rate of infant mortality. This finding could be due to the fact that in Utah, 34% of African American women had post high school education, compared to 53% of white women. Haynatzka et al (2002) suggest that black infants born to college-educated parents have a higher infant mortality rate and lower birth weights than white infants born to similarly college educated parents (Haynatzka, 2002). It is unknown and unfortunate how and why black women uniquely succumb to a host of complex interactions socially, environmentally, and biologically. But this distinction is a considerable barrier in eliminating the many health disparities faced in this community. Reducing the infant mortality disparity in the African American population cannot be achieved by implementing any single clinical intervention; it will require a collection of efforts. However more preventive and comprehensive strategies in conjunction with more effective methods of outreach within african american communities will help. 12 African American Infant Mortality © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Conclusion The U.S. as a nation has experienced significant declines in the overall rate of infant mortality. However, these reductions have not benefited African Americans. Furthermore, this trend is not likely to change in the near future (Sing and Yu, 1995). Compared with other developed countries, the infant mortality rate of the United States remains among the highest. This is possibly due to the high rate of infant mortality seen in some of the U.S. minority populations (Sing and Yu, 1995). However, it is a misconception to presume that minority status is associated with lower socioeconomic status in the United states and thus minorities are more likely to experience a higher infant mortality rate. according to Lillie-Blanton et al, when comparing the infant mortality rates of African Americans to that of Caucasians, African Americans continued to show evidence of higher infant mortality regardless of socioeconomic stratum (Lillie-Blanton et al, 1996). The findings in our report, however, are subject to a few limitations. First, the number of African American infant mortalities experienced in Utah is small, and trends should be interpreted with caution. Second, the data the chart abstractions were from a different time period than that were available through IBIS. Unfortunately, the data for 2003 is not available through IBIS. Another limitation encountered was the number of infants who had both African American and Caucasian parents. Finally, the Utah Department of Health state review of infant deaths, though published in 2003, only included data for the state of Utah from 1995 to 1998. These were the most recently published data which were limited to perinatal conditions. Nevertheless, health disparities within the African American community exist. The health care community thus should exert its efforts to establish a network between health care experts and the minority communities that will foster trust and encourage healthy behaviors such as seeking early and continuous prenatal care. Health care providers and researchers should realize that disparities in birth outcomes are the result of differential exposures incurred throughout a woman's life and not just during pregnancy (Lu, 2004). Making improvements in collaboration with partners outside the health arena may maximize the amount of support a woman receives for her health and well being. Hogan et al (2001) propose that individual and population risk factors are best addressed through advocacy and social and community arenas outside of medical intervention (Hogan, 2001). Thus, African American churches and businesses in Utah should be more readily utilized when implementing modes of outreach and education. Community and health professionals should work together to promote preventive and primary care, provide nutrition education and intervention, family planning, and encourage breast feeding. These methods of intervention will further facilitate cooperation between the health care provider and patient that promote reproductive health in the african american community. While it is true that other US racial and ethnic minorities have suffered economic hardships and social discrimination, few if any, have faced them standing on an economic and cultural base that was systematically undermined by the larger society (Lu, 2004). References Berger, C.S. (2001). Infant Mortality: A Reflection of the Quality of Health. Health Social Work, 26, 277-282. Collins, J.W. et al. (2000). Low-Income African-American Mother's Perception of Exposure to Racial Discrimination and Infant Birth Weight. Epidemiology, 11(3), 337-339. Dean, A.G., et al. (2004) Epi Info™. Atlanta: Centers for Disease Control and Prevention. Fiscella, K. (1996). Racial Disparities in Preterm Births: The Role of Urogenital Infections. Public Health Reports, 111, 104-113. © 2006 The University o f Utah. All rights reserved. African American Infant Mortality 13 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Geronimus, A.T. (2001) Understanding Eliminating Racial Inequalities in Women's Health in the United States: The Role of the Weathering Conceptual Framework. JAMWA, 56, 133-136. Haggard, Lois. (2003). Utah Health Status by Race and Ethnicity. Utah Department o f Health. Haynatzka, V (2002). Racial and ethnic disparities in infant mortality rates-60 largest U.S. Cities, 1995-1998. MMRWMorb Mort Wkly Rep, 51, 329-32, 343. Hogan, VK. et al. (2001). A Public Health Framework for Addressing Black and White Disparities in Preterm Delivery. JAMWA, 56, 177-180. yasu, S. et al. (2002). Infant Mortality and Low Birth Weight Among Black and White Infants-United States, 1980-2000. CDC: MMWR, 51(27), 589-592. Kaplan, J.B., and Bennett, T. (2003). Use of Race and Ethnicity in Biomedical Publication. JAMA, ;289(20), 2709-2716. Krieger, N. (1999). Embodying Inequality: A Review of Concepts, Measures, and Methods for Studying Health Consequences of Discrimination. International Journal o f Health Services, 29(2), 295-352. Lillie-Blanton, M. et al. (1996). Racial Differences in Health: Not Just Black and White,But Shades of Gray. Annual Review o f Public Health Disparities in Women's Health Coverage, 17, 411-48. Lukacs, S.L. and Schoendorf, K.C.(2004). Racial/Ethnic Disparities in Neonatal Mortality: United States, 1989-2001. CDC: MMWR, 53(29), 655-658. Lu, M. (2004). Racial-Ethnic Disparities in Birth Outcomes: A New Prospective. DPSWH Archives. http://128.248.232.90/archives/mchb/dpswh/august2004/accessible_files/frame Sing, G.K. and Yu, S.M. (1995). Infant Mortality in the United States: Trends, Differentials,and Projections, 1950 through 2010. American Journal o f Public Health, 85, 957-964. Utah Health Status Update (1998): Infant Mortality Review. Utah Department o f Health. Utah Perinatal Mortality and Review Program (2000). Maternal Child Health Title V Block Grant, in Department of Health and Human services. Wyn, R. et al. (2004). Kaiser Women's Health Survey: Racial and Ethnic and Access to Care. Kaiser Family Foundation, March 2004. Figure 1: Death Rate/1000 Live Births Infant Mortality Percentages by Maternal Characteristics of Women in Utah, 1995-1998 u Pre-pregnancy BMI <19.8 Alcohol Use D Some College/College Grad ^ No Prenatal Care 14 African American Infant Mortality © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Figure 2: Death Rate/1000 Live Births Infant Mortality Percentages by Maternal Characteristics of African American Women in Utah, 2001-2003 350 300 250 200 150 100 50 |-| Pre-pregnancy BMI <19.8 |-| Some College/College Grad |-| Medicaid |-| A lco ho l Use |-| No Prenatal Care © 2006 The University o f Utah. All rights reserved. African American Infant Mortality 15 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Quality Care in Utah Nursing Homes: Urban vs. Rural Gail L. Towsley, MS; William N. Dudley, PhD; Susan L. Beck, PhD CORRESPONDENCE: Gail L. Towsley, MS University o f Utah College o f Nursing 10 S. 2000 East Rm. 515 Salt Lake City, UT 84112 [phone] [e-mail] Abstract Quality Care in Utah Nursing Homes: Urban vs. Rural Close to 40% of 17,000 U.S. nursing homes are located in rural areas. In the geographic context of rural areas, quality of care may not just be related to staffing levels, but the feasibility and opportunity to provide essential services to rural elderly, an underserved population. The focus of this study was to describe Utah nursing homes and to examine differences in market and organizational characteristics and quality performance measures by location, as well as to examine predictors of quality. The Online Survey Certification and Reporting (OSCAR) system available in the year 2004 and 2005 were evaluated. T-tests were conducted to test differences based on location, market and organizational characteristics, and quality performance measures. Regression models were constructed to examine predictors of quality. Utah nursing homes (N=92) averaged 84 total beds. Median occupancy rates fell below the rest of the nation (68.78% vs. 88.33%). Utah nursing homes averaged about 10 total deficiencies (violations of regulations), including an average of 4.25 health deficiencies. RN hours per resident per day were significantly lower in rural areas. Further examination of RN and non nurse staffing levels on care quality is warranted. Introduction In the U.S. over 1.5 million older adults depend upon 17,000 nursing homes for 24 hour basic nursing care and skilled care that includes specialized services such as rehabilitation. Almost 40% of nursing homes are located in rural areas (NNHS, 1999). Over 9 million people age 65 and over live in rural counties (Institute of Medicine, 2005), and rural elders tend to be older, poorer, and have more physical limitations than their urban counterparts. Larger proportions of rural residents aged 75 and older utilize nursing homes than do urban elders. Specifically, in the year 2000, 82 of 1000 persons > age 75 resided in urban nursing homes compared to 121 of 1000 persons > age 75 in remote areas (Phillips, Hawes, & Leyk Williams, 2004). Yet, rural nursing homes lack resources that enable them to thrive financially and provide quality care. Despite the addition of aggregated facility and resident data, sufficient information pertaining to rural nursing homes is lacking (Coburn, 2002; Phillips, & McLeroy, 2004). The objective of this study was to describe Utah nursing homes and examine the effect of location (urban/rural) on market and organizational characteristics and quality performance measures (staffing and deficiencies). The focus of this study was threefold: to describe Utah nursing homes, to compare urban and rural nursing homes, and to examine predictors of quality outcomes, specifically, health deficiencies. 16 Quality Care in Utah Nursing Homes © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Nursing Home Characteristics Previous research indicates that factors likely to be influential in nursing home operations include market and organizational characteristics as well as quality performance measures. this study also examines how urban and rural locations are associated with market and organizational characteristics and quality performance measures. Organizational and market characteristics Organizational characteristics include facility size, type of ownership and affiliation with a chain organization and Medicare/Medicaid certification status. With regards to size, rural and western nursing homes are generally smaller (Rhoades, Potter, & Krauss, 1998), and are more likely to offer custodial care as opposed to skilled nursing or special care units (Shaughnessey, 1994). Larger nursing homes potentially have greater resources to draw upon when facing market demands such as low occupancy or Medicaid rates (Banaszak-Holl, Zinn, & Mor, 1996; Weech-Maldonado, Neff, & Mor, 2003). In addition, large proprietary homes are more likely to have more deficiencies (O'Neill, Harrington, Kitchener, & Saliba, 2003), which may imply lower quality care. Market characteristics that have been associated with nursing homes include nursing home competition, census/ occupancy rates, and special care units (SCUs). The American Health Care Association (AHCA) reported that the median nursing home occupancy rate in the U.S. in 2004 was 88.33% and that the median facility occupancy rate for Utah was 72.73%. Higher occupancy may be indicative of high care demand or a result of care quality. Almost 12% of homes with SCUs have a Medicaid census below 50%, whereas only 8.6% of nursing homes with a Medicaid census above 50% have SCUs (Zinn & Mor, 1994). This suggests that nursing homes with balanced pay sources may have more resources for SCUs; resources that may not be attainable for rural nursing homes. Rhoades, Potter, and Kraus (1998) reported fewer SCUs in rural areas. Quality Performance: Staffing hours and mix Research on quality care has largely focused on staffing levels, staffing mix, and facility deficiencies. The Center for Medicare and Medicaid Services (CMS) identified staffing thresholds (2.8 hours nurse aide and 1.3 hours licensed nursing per resident day), below which residents are potentially at risk for poor outcomes (Kramer & Fish, 2001). Phillips and colleagues (2003) reported that nursing homes, particularly ones in rural areas, were not likely to meet these thresholds. Staffing hours encompasses all employees (i.e. social work, nursing, maintenance) in the nursing home. Staffing mix refers to the ratio of number of hours worked by licensed nurses and to hours worked by nursing assistants in a 24 hour period. Similar to the CMS study, Schnelle and colleagues (2004) concurred that nursing assistant staffing above 2.8 hours per day lead to better quality. In addition, they found that nursing homes that reported the highest staffing levels, specifically nursing assistant staffing, displayed higher quality care on measures such as feeding assistance or incontinence care (Schnelle, Simmons, Harrington, et al. 2004). Deficiencies Certification surveys for Medicare and Medicaid certified nursing homes occur annually. Deficiencies are violations in 188 nursing home regulations and are judged based on scope and severity, and range from nursing care to physical environment. Severe deficiencies along with a large number of deficiencies and repeated deficiencies may be indicators of quality of care problems that result in monetary fines. A study of California nursing homes (N=1172) found that about one third of the homes received multiple deficiencies, and for-profit facilities averaged more deficiencies than non-profit homes (O'Neill, et al, 2003). Grabowski & Castle (2004) focused on persistent high and low quality of care. They examined deficiencies pertaining to pressure ulcers, use of restraints, tube feeding, and catheters. Although only a subset of nursing homes were considered high or low quality, a large proportion of homes had repeated deficiencies and low quality surveys (Grabowski & Castle, 2004). © 2006 The University o f Utah. All rights reserved. Quality Care in Utah Nursing Homes 17 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Quality and Rurality The relationship between staffing, deficiencies, and a rural location is unclear. An examination of deficiencies of nursing homes nationwide suggested that homes located in isolated areas have fewer health deficiencies, but that the pattern is inconsistent among regions (Phillips, Hawes, & Leyk Williams, 2003). Contrary to urban nursing home surveys which have resulted in more deficiencies but higher staffing levels, rural nursing home surveys have resulted in fewer deficiencies, but lower staffing levels (Phillips, Hawes, & Leyk Williams, 2004). Greater understanding of this paradox (a positive relationship between staffing levels and deficiencies) will be insightful for the industry. Recent research has indicated that a larger proportion of poorer rural counties subsequently contained lower tiered nursing homes (Mor, et al. 2004). Lower tiered nursing homes were defined as nursing homes that have a high proportion of Medicaid residents and more deficiencies (5.8 compared to 3.7 deficiencies) than upper tiered homes (Mor, et al. 2004). Typically, lower tiered nursing homes also had fewer registered nurses and proprietary homes had lower occupancy rates and a higher likelihood of changing ownership. Methods This descriptive study utilized a federal public use database: Online Survey Certification and Reporting system (OSCAR) data. Data were analyzed retrospectively to describe and compare urban and rural Utah nursing homes and to test relationships among variables. Specifically, Utah nursing homes located in urban and rural areas are described and the extent to which its urban or rural location was linked to market and organizational characteristics, and quality performance measures were examined. Sample This study included all Utah nursing homes identified in the OSCAR database that met the eligibility criteria: 1) the facility is licensed as a nursing home, 2) the nursing home is certified by Medicare or Medicaid, and 3) the nursing home's survey date fell between 1/1/04 and 6/15/05. Facilities were excluded from this study if the nursing home was not licensed as a nursing home, not Medicaid or Medicare certified, or if the nursing home's survey date in the OSCAR data was outside the date range specified above. Two facilities were excluded from the sample because they had three or fewer residents which skewed the staffing data and was not representative of Utah nursing homes. The final sample consisted of 92 nursing homes. Eligible nursing homes initially were classified into two locales: urban and rural. These geographic classifications, determined by zip code, were established through the use of Rural Urban Community Centers (RUCA's) and are based on urbanization, population, and daily commuting (Economic Research Service, 2004). When classifying areas for health related work, areas combined into two to four groupings is recommended (WWAMI Rural Health Research Center, 2002). Measures The Online Survey, Certification and Reporting (OSCAR) system is a historical database, which includes nursing facility characteristics, resident characteristics, and facility deficiencies on over 16,000 U.S. nursing homes and its residents. For example, OSCAR data provides information with regards to the number of Medicare certified beds, change in ownership, dedicated units such as Alzheimer's units, and the number of full time, part time, and contract staff. Facility information provided in the OSCAR database is completed by nursing facility designees and reviewed by the inspectors. Standard instructions of how to complete the questionnaires are provided to all nursing homes (American Health Care Association, 2003). Deficiency information is reported by inspectors and also recorded in the OSCAR database. Data are compiled during routine inspection surveys that are conducted at least every 15 months (average = 12 months) for Medicare and Medicaid certification. Nursing home inspectors can check the information provided, but no formal process to ensure data accuracy exists. 18 Quality Care in Utah Nursing Homes © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Organizational and Market variables Nursing home competition was computed using the Herfindahl index, a measure of market competition: HI = sum of squared market shares (based on resident days of care) of the nursing homes within each county (Weech-Maldonado, Neff, & Mor, 2003). Census/occupancy rates refer to the proportion of occupied beds on the initial day of the state inspection and Special Care Units (SCUs) are dedicated units that provide a particular type of care. Facility size is measured by the total number of beds. Ownership is documented as proprietary or nonproprietary and chain membership pertains to nursing homes affiliated with multifacility organizations. Quality measures Facility deficiencies are defined as violations of care standards and the number and type of deficiencies as reported on the OSCAR were examined. In addition, OSCAR data are a main source of staffing level information for all nursing homes. Staffing levels are reported for 14 days prior to the facility inspection. Staffing hours document the number of hours worked by employees in all departments the 14 days prior to inspection and were obtained from the OSCAR. Staffing mix pertains to the proportion of hours worked by registered nurses, licensed practical nurses, and nursing assistants 14 days prior to inspection. Staffing hours not including nurse hours were also examined. Reliability and validity of OSCAR data OSCAR data are completed by nursing home personnel without a formal procedure to validate data accuracy (AHCA, 2003). Standard instructions are provided to all facilities that complete this data. The nursing home inspectors can check the information provided and investigate suspicious information. although the lack of an auditing process decreases the reliability and validity of these data, they are the best available data source for health services research purposes. Data analysis Components of the OSCAR data were merged based on a unique nursing home identifier using SPSS 13.0. The dataset was modified to facilitate analysis by constructing variable and value labels. Data cleaning procedures, such as checking for duplicates were performed. th e distribution of scores on each variable were examined to determine out of range scores or missing data and were evaluated for assumptions of statistical tests. some cases had missing values for health deficiencies. When comparing the nursing home and survey date to the Medicare Nursing Home Compare website, it was determined that the missing values meant that the nursing home did not have a deficiency in that category. Thus, deficiency data for those homes were entered as zero. Descriptive statistics such as frequencies and measures of central tendency were obtained for each variable to describe the market and organizational characteristics and quality performance measures of Utah nursing homes. t-tests were conducted to examine relationships among location and market and organizational characteristics as well as quality performance measures. Location (urban/rural) was the independent variable and market, organizational, and quality variables were the dependent variables. Regression models were constructed to examine predictors of quality. Results Nursing Home Characteristics Utah nursing home characteristics are provided in Table 1. Of the 92 Utah nursing homes (74 urban, 18 rural), the average number of total beds was about 84 (range 10 to 223). Approximately 77% of nursing homes were dually certified (Medicare and Medicaid), 14% were certified by Medicare only, and 9% by Medicaid only. Most nursing homes (78.3%) were for-profit homes and part of a chain organization (64.1%). The median occupancy rate for Utah facilities was 68.78%. Twenty-eight facilities had Special Care Beds for individuals with Alzheimer's disease: 22 urban, 6 rural. © 2006 The University o f Utah. All rights reserved. Quality Care in Utah Nursing Homes 19 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Utah nursing homes averaged about 10 total deficiencies and about four of these were considered health deficiencies. Nationally, nursing homes average about 8 health deficiencies and about 90% of Utah nursing homes averaged 8 or fewer health deficiencies. Certified Nursing Assistant (CNA), Licensed nurse (LN), and Registered Nurse (RN) hours per resident per day, on average, were 2.44, .67, and .80 respectively. Urban and rural differences Although not significant, urban facilities generally were larger and had lower occupancy rates than rural facilities (87 beds vs. 72 beds). T-tests indicated that nursing homes in urban areas had higher Medicare occupancy (24.61%) than those in rural areas (12.60%), t (89.97) = 3.21, p=.002, and facilities in urban areas had lower Medicaid occupancy (50.89%) compared to facilities in rural areas (62%), t (80.42) = -2.66, p=.009. Not surprisingly, there was a positive association between competition and rural location. The more rural a facility was located, the larger the percentages of market share. Urban nursing homes averaged about 15% of the market share compared to 78% for rural facilities, t (19.29) = -8.39, p<.001. Thus, urban facilities have more competition than rural facilities. Finally, urban nursing homes had more RN hours per resident day than rural nursing homes, t (87.07) = 3.04, p=.003). Quality predictors A regression analysis was performed to see how well market, organizational, and staffing variables predicted health deficiencies. Because of the large number of potential predictors and the explanatory nature of the study, predictors were entered in step wise fashion with three blocks 1) organizational 2) market and 3) staffing and location. Variables included in the regression are designated in Table 1. Two models were estimated. In the first model, total beds (organizational block), Medicaid occupancy (market block) and non nursing staff (staffing and location block) remained in the model. The first model focused on all nursing homes and indicated that total beds, Medicaid occupancy, and non-nursing staff accounted for a significant amount of health deficiencies, R2 = .27, F (1, 88) = 11.03, p = .000. In the second model, Alzheimer's special care beds and Medicaid occupancy (market block) and non nursing staff (staffing and location block) remained in the model. This model included all nursing homes, but provides additional information about nursing homes with Alzheimer's beds. This model indicated that Alzheimer's beds, Medicaid occupancy, and non-nursing staff accounted for a significant amount of health deficiencies, R2 = .28, F (1, 88) = 11.56, p = .000. Discussion Market and organizational characteristics th is descriptive study examined urban and rural Utah nursing homes. When comparing Utah nursing home characteristics to nursing homes nationwide, Utah homes were smaller, had less occupancy, and fewer deficiencies. Nursing homes in this state averaged about 84 beds, which is consistent with previous studies that suggest that western and rural nursing homes are smaller (Rhoades, Potter, & Kraus, 1998). Nationally, nursing homes average about 105 beds (National Nursing Home Survey, 1999). Utah, on average, had more for profit nursing home (78%) and homes that were affiliated with a chain organization (64%). The American Health Care Association (2005) reported that 66% of nursing homes nationwide were for-profit and 52% were affiliated with a chain organization. Utah nursing home occupancy rates were well below the national median (about 69% vs. 88%). Low occupancy rates may be a reflection of Utah's younger demographic profile and less need for nursing home care. Low occupancy rates, however, potentially present other issues, such as financial stability of the nursing home, which was not examined here. Quality performance measures (staffing and deficiencies) Nursing home staffing is one quality measure that has received much attention and staffing thresholds, while not yet mandated, consisting of 2.8 CNA hours and 1.3 licensed nurse hours per resident per day have been recommended to provide quality care (Kramer & Fish, 2001; Schnelle, Simmons, Harrington et al, 2004). Nursing homes in this study 20 Quality Care in Utah Nursing Homes © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW reported staffing levels close to these thresholds: 2.44 CNA hours and 1.47 total licensed nurse hours per resident per day. Total licensed nursing hours combined licensed practical/vocational nurses and registered nurses, and did not include nurse administration hours. Utah's average of about 4 health deficiencies is below the nation's average, which is 8. Furthermore, about 90% of Utah nursing homes averaged 8 or fewer health deficiencies. Phillips and colleagues (2003) found in their nationwide examination of nursing home deficiencies that homes located in remote areas have fewer health deficiencies, but that the pattern is inconsistent among regions. A corresponding finding was not prevalent among Utah nursing homes. Urban and rural differences Analyses of Utah nursing homes revealed that these homes differed by location. Of the organizational characteristics, none were statistically different by location, however, urban nursing homes averaged 87 beds compared to 72 beds in rural areas. Market characteristics that were statistically different included competition, Medicare occupancy, and Medicaid occupancy. Urban nursing homes faced more competition with other homes within their respective county, which theoretically may influence quality. However, no quality differences were found when examining health deficiencies and location. Despite that occupancy did not vary significantly across location, urban nursing homes averaged higher Medicare occupancy and rural homes averaged higher Medicaid occupancy. these results suggest that urban nursing homes provide more skilled services than rural homes. In addition, homes with a higher Medicaid occupancy potentially results in reduced revenues and places the facility at risk for financial instability. The examination of staffing hours revealed that urban nursing homes had twice the number of RN hours per resident day than rural homes. Fewer RN hours in rural homes may be a reflection of higher Medicaid occupancy and less need of skilled services and RNs. Alternatively, the need for RNs may be present, but not available in remote areas. Quality predictors The regression results indicate that nursing homes with more beds, a higher Medicaid occupancy, and fewer non nurse staff were more likely to have more deficiencies. Similarly, nursing homes with Alzheimer's beds, a higher Medicaid occupancy, and fewer non nurse staff were more likely to have more deficiencies. These results are similar to Mor and colleagues (2004) who found that nursing homes with a high proportion of Medicaid residents also had more deficiencies. In addition, O'Neill and associates (2003) found that large proprietary nursing homes had more deficiency citations. However, these studies do not completely explain our regression results and the potential influence of non nurse staffing levels. Nursing homes that have higher Medicaid occupancy are likely providing more custodial care as compared to skilled services. Likewise, providing care for residents with Alzheimer's disease requires a different skill set, such as behavior management, than when providing skilled care, such as intravenous injections. Non-nurse staffing levels may be more influential in these facilities in order to provide supportive care or carry out effective systems. Thus, non-nurse staffing levels may play a vital role to temperate or increase deficiencies. Strengths and Limitations This study describes Utah nursing homes, delineates their differences based on location, and begins to examine predictors of quality, which provides a foundation for future research. Because the sample included only Utah nursing homes, and deficiencies were used as the outcome variable, generalizing these findings to other states is limited. Nursing homes in other states may have different economic, demographic, and care acuity profiles. In addition, deficiencies are cited by state inspectors, therefore, deficiency citations may vary state to state. Nursing homes are multidimensional and complex. Other factors not examined here, such as financial viability, possibly contribute to care quality. © 2006 The University o f Utah. All rights reserved. Quality Care in Utah Nursing Homes 21 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Conclusion Utah nursing homes are smaller and have low occupancy rates compared to nursing homes nationwide. While Utah nursing homes are primarily located in urban areas, RN staffing levels are much lower in those located in rural areas. The reason for the lack of RN staffing is unclear. Further examination into the prevalence and access of RN's in rural areas and the care needs of remote areas would be helpful to determine if rural nursing homes residents are receiving appropriate care provision in their respective communities. Furthermore, non nurse staffing levels potentially play a critical role in nursing home quality. Non nurse staffing levels may be more influential in facilities that mainly offer custodial care, are larger, or provide Alzheimer's care. Health care providers may want to examine non nurse staffing levels and their contributions to providing quality care. References American Health Care Association. (2003). Research. Retrieved April 8, 2004 from http://www.ahca.org/research/index.html American Health Care Association (2005). Research. Retrieved January 12, 2006 from http://www.ahca.org/research/oscar_ oper.htm Angelelli, J., Mor, V., Intrator, O., Feng, Z., & Zinn, J. (2003). Oversight of nursing homes: Pruning the tree or just spotting bad apples? The Gerontologist, 43, 67-75. Banaszak-Holl, J., Zinn, J.S. & Mor, V (1996). The impact of market and organizational characteristics on nursing care facility service innovation: a resource dependency perspective. Health Services Research, 31, 97-117. Coburn, A. (2002). Rural long-term care: What do we need to know to improve policy and -programs? Journal o f Rural Health, 18, 256-269. Economic Research Service (2004). Briefing room: Measuring rurality: rural-urban commuting area codes. Retrieved April 11, 2004 from http://www.ers.usda.gov/Briefing/Rurality/RuralUrbanCommuningAreas/ Grabowski, D.C. & Castle, N.G. (2004). Nursing homes with persistent high and low quality. Medical Care Research Review, 61, 89-116. Institute of Medicine (2005). Quality through collaboration: The future o f rural health. Washington DC: The National Academies Press. Kramer, A. M., & Fish, R. (2001). "The relationship between nurse staffing levels and the quality o f nursing home care." In Appropriateness o f Minimum Nurse Staffing Ratios in Nursing Homes. Washington DC: Department of Health and Human Services, Health Care Financing Administration. Mor, V, Zinn, J., Angelelli, J., Teno, J.M., & Miller, S.C. (2004). Driven to tiers: Socioeconomic and racial disparities in the quality of nursing home care. Milbank Quarterly, 82, 227-56. National Nursing Home survey. Table 1. Number o f nursing homes, beds, current residents, and discharges. [Electronic data file]. (1999). Hyattsville, MD: National Center for Health Statistics. O'Neill, C., Harrington, C., Kitchener, M., & Saliba, D. (2003). Quality of care in nursing homes. Medical Care, 41, 1318-1330 Phillips, C. D., Hawes, C. & Leyk Williams, M. (2003). Nursing Homes in rural and urban areas, 2000. College Station, TX: Texas A & M University System Health Science Center, School of Rural Public Health, Southwest Rural Health Research Center. Phillips, C. D., Hawes, C., & Leyk Williams, M. (2004). Nursing home residents in rural and urban areas, 2001. College Station, TX: Texas A & M University System Health Science Center, School of Rural Public Health, southwest Rural health Research Center. Phillips, C. D., & McLeroy, K. R. (2004). Health in rural America: remembering the importance of place. Am J Public Health, 94, 1661-1663. Rhoades, J., Potter, D., & Kraus, N. (1998). Nursing homes-structure and selected characteristics, 1996. Rockville, MD: Agency for Health Care Policy and Research. MEPS Research Findings No 4., AHCPR Pub. No. 98-0006. Schnelle, J. F., Simmons, S. F., Harrington, C., Cadogan, M., Garcia, E., & Bates-Jensen, B. M. (2004). Relationship of nursing home staffing to quality of care. Health Services Research, 39, 225-249. 22 Quality Care in Utah Nursing Homes © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Shaughnessy, P.W. (1994). Changing institutional long term care to improve rural health care. In: Coward RT el al, eds. Health Services for Rural Elders, New York: Springer Publishing Weech-Maldonado, R., Neff, G. and Mor, V (2003a). Does quality of care lead to better financial performance?: the cae of the nursing home industry. Health Care Management Review, 28, 201-216. Weech-Maldonado, R., Neff, G. and Mor, V. (2003b). The relationship between quality of care and financial performance in nursing homes. Journal o f Health Care Finance, 29, 48-60. WWAMI Rural Health Research Center (2002). The use of RUCAs in health care. Retrieved April 23, 2004 from http://www.fammed.washington.edu/wwamirhrc/rucas/use_healthcare.html Zinn, J.S. & Mor, V (1994). Nursing home special care unites: Distribution by type, state, and facility characteristics. The Gerontologist, 3, 371-377. Table 1. Urban Rural differences o f Nursing Home characteristics Variable Urban (N=74) Mean (SD) Rural (N=18) Mean (SD) Total Mean (SD) p value of t-test Total Beds* 87.55 (50.89) 72.00 (26.85) 84.51 (7.44) 0.214 Special Care Beds--Alzheimer's* (see note) 28.64 (24.43) 21.0 (6.16) 27.0 (21.94) 0.46 Occupancy of Nursing Home* .70 (.19) .71 (.13) .70 (.18) 0.728 Medicare Occupancy* .25 (.29) .13 (.07) .22 (.27) .002** Medicaid Occupancy* .51 (.30) .62 (.10) .53 (.28) .009** Competition* .15 (.16) .78 (.31) .27 (.32) .000** Total Deficiencies (Health & Life Safety) 10.42 (6.07) 10.28 (3.20) 10.39 (5.6) 0.892 Health Deficiencies* 4.04 (3.99) 4.39 (2.62) 4.11 (3.75) 0.654 CNA hours (PRPD)* 2.48 (1.10) 2.28 (.53) 2.44 (1.01) 0.464 LN hours (PRPD)* .70 (.51) .53 (.22) .67 (.47) 0.18 RN hours (PRPD)* .89 (1.28) .40 (.23) .80 (1.16) .003** Total Nursing hours (PRPD) 1.59 (1.54) .94 (.22) 1.47 (1.41) .001** Non nursing Staff hours (PRPD)* 2.43 (1.22) 2.47 (.55) 2.44 (1.12) 0.885 Variable Urban (N=78) Percent Rural (N=18) Percent Total Percent p value o f X 2test Profit Status of Nursing Home (Not for profit/profit)* 16.2% / 83.8% 44.4% / 55.6% 21.7% / 78.3% .009** Part of a chain organization (not part of a chain/chain)* 35.1% / 64.9% 38.9% / 61.1% 35.9% / 64.1% 0.766 *variables included in regression **p > .05 Note: results reported is based on 28 nursing homes that had special care beds. © 2006 The University o f Utah. All rights reserved. Quality Care in Utah Nursing Homes 23 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Analysis of Surveillance Data for Three Sexually Transmitted Infections and Hepatitis C Virus In a Selected Population in Salt Lake County Kimberly S. Mueller, MSSA CORRESPONDENCE: Kimberly S. Mueller 801-733-0587 Kimberly, [e-mail] Abstract This surveillance study examined rates, demographics, and behavioral risk factors associated with three Sexually Transmitted Infections (STI's): Chlamydia trachomatis, Neisseria Gonorrhea, and Syphilis, as well as Hepatitis C (HCV) in a selected population in Salt Lake County. 184 participating individuals were obtained randomly from July- December, 2004 through advertising in the media and health-related organizations. The surveillance data consisted of data on individuals presenting to be tested for one of the three mentioned STI's and/or antibodies to HCV. While the study size was relatively small, final analysis revealed that rates of STI in the selected population were greatly elevated over that of the Salt Lake County in general from 2000-2004. This analysis of demographics and risk factors, such as sexual and prevention behaviors and patterns of drug use, provides insight and direction into future education and prevention efforts in this high risk group, particularly at the time of diagnosis and/or treatment for these infections. Introduction Because they are common over the course of a lifetime, sexually transmitted infections (STIs) are a key aspect of public health epidemiology and intervention. The total cost of treated STIs in the United States is estimated at $8-10 billion, exclusive of HIV (Tao, Irwin, & Kassler, 2000). Some of the complications of untreated STIs include infertility, pelvic inflammatory disease, ectopic pregnancy, and epididymitis. In some cases, they can even lead to death if untreated. However, diagnosis may be hampered by the fact that the infection is often asymptomatic. It has been reported that early detection and treatment of STIs may reduce the incidence of HIV by as much as 40% by reducing sores and lesions which may facilitate the spread of the virus (Cohen & Scribner, 2000). Widespread screening is generally not cost-effective, however, targeted screenings have been found to be cost-effective when prevalence rates are around 2- 6% (Val Valkengoed, Postma, Morre, van den Brule, Meijer, Bouter, & Boeke, 2001). The Institute of Medicine has recommended that all primary care medical providers counsel their patients, particularly young adult patients, about the nature and risk of STIs; however, data show most are not doing this often enough, if at all (Maheux, Haley, Rivard, & Gervais, 1999; Tao et al., 2000). Because of concerns about stigma and confidentiality, much screening, diagnosis, and treatment for STIs falls to community providers, such as emergency rooms, who are particularly ill-equipped to provide the kind of meaningful counseling interaction which might be expected to promote positive and long-lasting behavior changes, and public health clinics. Rates of substance use have been found to be higher in populations with STIs than in the general population (Atkan, Calkins, & Johnson, 2001). This is concerning because substance use has been suggested as a surrogate marker for being in at-risk situations (Fenaughty & Fisher, 1998; Fortenberry, 1998; Messiah, Bloch, & Blin, 1998). Specifically, the use of crack cocaine has been associated with the acquisition and transmission of STIs, not only through traditional 24 STIs & Hepatitis C in Salt Lake County © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW sexual routes, but also via oral sex, due to the presence of cracked lips and mouth sores (Hser, Chou, Hoffman, & Anglin, 1999). Hepatitis C virus (HCV) is the most common blood-borne disease, with an overall prevalence of approximately 1.8%, as 3.9 million Americans carry antibodies for the virus. HCV has become the leading cause of liver transplantation in the US (Kim, 2002; Wong, McQuillan, McHutchison, & Poynard, 2000). HCV is a developing concern for public health as an estimated 28,000-36,000 new infections occur annually in the United States, of which approximately 85% will develop into a chronic infection. Approximately 8,000-10,000 individuals die of HCV-related complications each year, and the death rate is expected to surpass that of AIDS if it is not contained (Rhoads, 2003). The prevalence of HCV is elevated in certain groups: 33% in a sample of alcoholics, 33% in a sample of cocaine users, and 18-40% in a sample of US Veterans, (Harsch, Pankiewicz, Bloom, Rainey, Cho, Sperry, & Stein, 2000; Kim, 2002; Rhoads, 2003). It is an infection that may be transmitted via sexual contact, but is more often transmitted via contact with contaminated blood, such as when sharing needles, cottons, cookers, or other injection drug works. Estimates of infection rates in injection drug users range from 5-75% within the first six months of injection drug use (Kew, Francois, Lavanchy, Margolis, Van Damme, Grob, Hallauher, Shouval, Leroux-Roels, & Meheus, 2004; Yen, Keeffe & Ahmed 2003). There is conflicting evidence on the transmission of HCV via such activities as skin piercing, tattoos, and sharing cocaine snorting straws. Nevertheless, these activities are associated with higher rates of HCV infection and this relationship certainly bears further study (Alter, 2002; Chou, Clark, & Hefland, 2004; Rhodes, 2003; Yen, et al, 2003). A decrease in the complications and progression of HCV can be accomplished through antiviral treatment, counseling, and immunization for other forms of hepatitis, but first the infection must be identified (Global Burden of Hepatitis C Working Group, 2004). The US Preventive Service Task Force has found insufficient evidence to recommend routine screening for HCV due to the lack of long term studies demonstrating this will lead to reductions in morbidity and/ or mortality. However, based on current knowledge, the Centers for Disease Control and Prevention (CDC) does recommend screening of high risk patients and those with markers for liver inflammation (Alter, Seeff, Bacon, Thomas, Rigsby, & De Bisceglie, 2004; Chou et al., 2004). As with STIs, there is definitely room for improvement with respect to general medical providers screening and testing their high-risk patients for HCV (Josset, Torre, Tavoclacci, Van Rossem-Magnani, Anselme, Merle, Godart, Libert, Ladner, & Czernichow, 2004). Chlamydia and gonorrhea are among the top five reported infectious diseases in Utah. Although recent surveillance has indicated that rates in Utah are consistent with or even below the rates mandated by Healthy People 2010, the rates of infection are still high in specific subpopulations (Contreras, Lloyd, & White, 2001). Because of the concern for monitoring these rates to assess public health performance, establish priorities, and track the rates of syphilis and Hepatitis C, two surveillance projects were undertaken. These projects were established to evaluate rates of infection in a group of individuals who may be at risk for acquiring STIs or HCV because of demographic-based or other risk factors. Methods This surveillance study consisted of data collected from July 12, 2004 - December 27, 2004 on individuals presenting to be tested for one of three sexually transmitted infections and/or antibodies to HCV. The CDC funded up to 300 tests of chlamydia, gonorrhea, and syphilis for purposes of gathering surveillance data on males (although females requesting the tests were not turned away). Simultaneously, a separate project was established to test up to 100 individuals for the presence of the antibody to Hepatitis C. Funding was provided through a CDC Epidemiology and Laboratory Capacity grant. The Hepatitis C data were analyzed separately in this study because even though the majority of HCV infections are not acquired via sexual transmission, both groups share many risk factors in common. Local health care providers were made aware of the availability of this testing. It was also advertised in the local media and on the UDOH and other © 2006 The University o f Utah. All rights reserved. STIs & Hepatitis C in Salt Lake County 25 2006 UTAH'S HEALTH: AN ANNUAL REVIEW websites. Any single test or combination of tests was offered to individuals based upon the results of their screening, or upon request. The blood and/or urine samples were gathered at the Utah AIDS Foundation on Monday evenings in conjunction with their existing HIV testing program and were offered at no charge, along with relevant screening, education, counseling, and follow up for treatment, if appropriate. A demographic and risk factor questionnaire was administered as part of the screening, although some individuals did not complete some or all of the questionnaire items. Confidential tests for chlamydial and gonorrheal infections were completed via urine samples provided by the test subjects and analyzed by the Utah Public health Laboratory. tests that were submitted during the initial phases of the project were analyzed using the GenProbe Pace II nucleic acid based test (NAT). In October 2004, the lab underwent a previously-planned conversion to the GenProbe Aptima assay, which is a nucleic acid amplification test (NAAT). Syphilis was assessed via blood samples analyzed by the same laboratory, using a rapid plasmin reagin enzyme immunoassay. th e presence of hepatitis C antibodies was assessed via an ELIs A assay performed at the Utah Public Health Lab, and positive tests were sent to Esoterix, where a recombinant immunoblot assay (RIBA) was performed to confirm the positive antibody results. All positive test results were reported to a Health Program Specialist at the Utah Department of Health, and treatment, partner notification, and/or referrals for additional testing/treatment (such as viral load testing to identify an active infection) were provided to the individual as appropriate. Results A total of 184 individuals took some or all of the offered STI tests (chlamydia, gonorrhea, syphilis) and most completed at least some of the questionnaire items. A majority of the individuals screened were men (78.1%), consistent with the original target group of the STI study. The ages ranged from 15-63, with no significant difference in age between males and females tested (p=0.36). The racial/ethnic makeup of the group was largely white, non-Hispanic, consistent with the demographics of the area in which the testing occurred. A slight majority of the group (55.6%) indicated they have insurance coverage, mainly through parents (26.5%) or employer-based health plans (62.2%). See Table 1. An analysis of risk factors indicates that in addition to having a wider range in number of partners in the last three months, the average number of sexual partners over that time frame was significantly greater for males than females (3.03 v. 1.62, p<0.05). Men having sex with men constituted roughly two-thirds of the men tested. Approximately 92 percent of the respondents indicated they had had sexual contact in the last three months, with approximately 51 percent reporting anal sex, 50 percent reporting vaginal sex, and 82 percent reporting oral sex. Prevention use was reported by 71 percent, with male condom use being far and away the most common method of prevention used (100% of those reporting use of prevention report condom use), indicating an opportunity to enhance education efforts on the use of alternative barrier prevention methods, such as female condoms (reported by 5.4% of respondents) and dental dams (reported by 0% of respondents). Use of prevention was not significantly associated with test result (p=0.86), and there was no significant difference in the use of prevention by gender (p=0.11). A previously-diagnosed STI was reported by 21 percent of respondents and having this previous experience was not significantly different by gender (p=0.13). In addition, having a previous experience with a sexually transmitted infection did not make a significant difference in use of prevention (p=0.16). Eighty-seven percent reported some level of alcohol and/or other substance use in the past month, with no significant difference in use by gender (p=0.48). The majority of respondents indicated use of alcohol (82.6%), although other mood-altering substances were reported as being often used as well, such as marijuana (27.7%), cocaine (10.3%), and methamphetamine (9.0%). In light of the potential for lowering inhibition, these figures raise concerns about both the actual practice of prevention and safe sex acts, as well as recall of such activities measured by this instrument. Lifetime injection drug use was reported by 12 percent of respondents, with 60 percent of them also reporting sharing needles. 26 STIs & Hepatitis C in Salt Lake County © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW When looking at individuals who returned a positive test result (13 individuals - 1 person who tested positive did not complete a questionnaire), rates of insurance coverage (53.9%), use of prevention (69.2%), and previously-diagnosed infections (18.2%) were similar to those who tested negative, although reported use of substances was universal in this group (100%) and approached, but did not reach statistical significance (p=0.12) when compared with those who tested negative. In addition, differences were not detected for age (p=0.43) or number of sexual partners in the last three months (p=0.82). The final counts and rates of infection for the STI testing program are as follows: chlamydia - 11 or 6.4 percent, gonorrhea - 2 or 1.2 percent, and syphilis - 1 or 0.6 percent (see Table 2). A total of 75 individuals took the anti-HCV test and completed at least some of the questionnaire items. A majority of the individuals screened were men (70.7%). Their ages ranged from 15-60, with no significant difference in age between males and females tested (p=0.76). The racial/ethnic makeup of this group was similar to that of the STI group. Only 40 percent of individuals indicated they have insurance coverage, mainly through parents (25%) or employer-based health plans (60.7%). See Table 1. An analysis of risk factors indicates that in addition to having a wider range in number of partners in the last three months (as many as 30 partners for one individual), the average number of sexual partners over that time frame approached significance for males v. females (3.51 v. 1.42, p=0.07). Ninety three percent of the respondents indicated they had had sexual contact in the last three months, with approximately 42 percent reporting anal sex, 65 percent reporting vaginal sex, and 81 percent reporting oral sex. Prevention use was reported by 60 percent, again with male condom use being far and away the most common method of prevention used (100% of those reporting use of prevention report condom use), while only one individual reported using a female condom. Use of prevention was not significantly associated with the HCV test result (p=0.18), and there was no significant difference in the use of prevention by sex (p=0.16). A previously-diagnosed STI was reported by 25 percent of respondents and having this previous experience was not significantly different by gender (p=1.0). As before, having a previous experience with a sexually transmitted infection did not make a significant difference in use of prevention (p=0.48). Regarding use of alcohol and other substances, 80 percent reported some level of use in the past month, with males significantly more likely to have used than females (p=0.02). The majority indicated use of alcohol (72.4%), and the use of other mood-altering substances was in excess of those seen in the STI group, such as marijuana (34.5%), cocaine (15.5%), poppers (13.8%) and methamphetamine (19.0%). Heroin use (widely associated with HCV and injection drug use) was reported by only 5 percent of respondents. Lifetime injection drug use was reported by 29 percent of respondents, and 55 percent of those who ever injected report sharing needles. For those individuals with a positive test result (10 individuals), different trends emerge. Only 20 percent reported insurance coverage, 40 percent reported using prevention, and 25 percent reported previously-diagnosed infections. Reported use of substances was nearly universal in this group (90%). Seventy percent of these individuals report lifetime injection drug use and of those, 83.3 percent report sharing needles. The small number of individuals in this group prevents further analyses. The final count and rate of infection in this testing program was 10 or 13.3 percent. Because only antibodies to HCV were tested in this group, it is impossible to ascertain whether these persons are experiencing acute, chronic, or cleared infections. A side by side comparison of demographic and risk factors for both groups tested may be found in Table 1. Discussion While this study size was relatively small, the final analysis reveals rates of STI in this at-risk group are greatly elevated over that of Salt Lake County in general from 2000-2004 (UDOH, 2005). The rate per 100,000 for gonorrhea is greater than 34 times the provisional rate of the general population in 2004; the rate for chlamydia is 31 times the provisional © 2006 The University o f Utah. All rights reserved. STIs & Hepatitis C in Salt Lake County 27 2006 UTAH'S HEALTH: AN ANNUAL REVIEW rate, and the rate for syphilis is 175 times the provisional rate (see Table 2). The rate of HCV antibodies found in this project is 7.4 times that of the general US population (13% v 2%). These results indicate a significant opportunity to expand STI and HCV education and testing services for high risk populations, many of whom have access to care through their existing health insurance coverage, but obviously preferred and benefited from the availability of government-sponsored services. these services help individuals who might otherwise avoid care access it in a more comfortable and trusted environment. th is phenomenon has been previously documented and illustrates the continuing need for publicly funded accessible and confidential STI services, particularly to reduce ER visits (Celum, Bolan, Krone, Code, Leone, Spaulding, Henry, Clarke, Smith, & Hook, 1997; Mehta, Shahan, & Zenilman, 2000). These community-based clinics serve a valuable role in targeting s TIs and may provide a greater public health impact if more fully integrated with the services offered by private providers. Responses in this study indicate there is room for improvement in the provision of s TI education and prevention services, as persons who have previously been infected are not more likely to use prevention. Education about various routes of transmission as well as use of appropriate prevention methods is of particular importance, especially given the high rates of oral sex reported in this study. th e high rates of condom use reported by those who use any type of prevention (if accurate) are encouraging, in spite of the current and remote infection rates. This may indicate a foundation of willingness to take preventive action, which may be enhanced to produce further reduction of rates. This may be particularly true with respect to promoting alternative barrier methods such as the female condom, which has seen some success in targeted educational programs (Artz, Macaluso, Brill, Kelaghan, Austin, Fleenor, Robey, & Hook, 2000). There is evidence that a variety of interventions can be utilized to create an effective framework of STI prevention which reduces stigma and promotes positive behavior change (Bloomfield, Kent, Campbell, Hanbrook, & Klausner, 2002; Cohen & Scribner, 2000). Some of these interventions might include home testing for STIs and expanded education and treatment in schools and jails. Regarding HCV infection, while effective treatment now exists to reduce the chronicity of the infection, lack of insurance coverage can often prevent individuals from obtaining the care they need in order to achieve a sustained virologic response. For example, the individuals who tested positive for anti-HCV in this study had lower rates of insurance coverage than the study population as a whole. Obviously, obtaining concrete medical services and antiviral treatment is the best approach to reducing the future morbidity, mortality, and spread of HCV; however, this care may be beyond the current resource capacity of the public health system. Nevertheless, persons identified with HCV infection can benefit from counseling and other services to make behavioral modifications and lifestyle adjustments which may reduce their own risk of future infection acquisition (including superinfection with differing HCV genotypes or strains), as well as reducing the risk of transmission to others (Alter, 2002; Alter et al., 2004; Herring, Page-Shafer, Tobler, & Delwart, 2004). Rates of substance use were high in both study groups, consistent with data reported elsewhere (Aktan et al., 2001). Again, this is cause for concern not only from the standpoint of the effects of the use of alcohol, marijuana and injected, mood-altering substances on lowering inhibitions and promoting risky behaviors, but also for the increased potential for transmission of HIV and other infections. To address these frequently comorbid conditions, guidelines have been published by the CDC and the Center for Substance Abuse Treatment (CSAT) which encourage the referral of patients treated for STIs for substance abuse treatment and vice versa (Aktan et al., 2001). Persons who are undergoing substance abuse treatment may present a critical opportunity to capitalize on a period of life reorganization and motivation for change by testing for STIs and HCV and teaching behavioral modifications to reduce future risk and transmission (Astone, Strauss, Vassilev, & Des Jarlais, 2003; Bachmann, Lewis, Allen, Schwebke, Leviton, Siegal, & Hook, 2000; Pollack, 2001; Samet, Mulvey, Zaremba & Plough, 1999). Regardless of concerns about treatment adherence in high risk groups, initiating antiviral therapy for HCV in medically appropriate candidates is recommended by Edlin (2002), who advocates that at least some antiviral treatment, coupled with targeted behavioral interventions, is better than 28 STIs & Hepatitis C in Salt Lake County © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW none. a major limitation of this study involves the single testing location that was provided and the self-selected group that patronizes this community-based organization and chose to participate in this study. Other limitations of this study include the self-reported nature of the data collected, the inherent limitations of a self-administered questionnaire, the relatively small numbers with which to calculate rates, and conceivably, the switch in chylamdia and gonorrhea assays which took place in the middle of the study. However, it is believed that increased sensitivity and specificity of the new assay probably helped to better identify true positive infections and improved the quality of the data. In a previous study of STI rates in Utah, Contreras et al. (2001) recommended targeting specific groups for intensive STI education and prevention efforts. While providing valuable information on the demographic and risk factors associated with this high-risk group, the analysis of this surveillance study indicates education and prevention efforts provided at the time of diagnosis and treatment of STIs may not be effectively influencing at-risk persons to change their unsafe behaviors, particularly with respect to the use of prevention methods. Future research and/or surveillance efforts are needed to further examine the use of prevention by type of sexual contact and use of substances concurrent with sexual contact, as the widespread use of these substances may be reducing inhibition and negatively influencing decision-making with respect to risky sexual behaviors. References Aktan, G. B., Calkins, R. F., & Johnson, D. R. (2001). Substance use, need, and demand for substance user treatment services in patients treated for sexually transmitted diseases in Michigan. Substance Use and Misuse, 32(12), 1651-1676. Allen, S. A., Spaulding, A. C., Osei, A. M., Taylor, L. E. , Cabral, A. M., & Rich, J. D. (2003). Treatment of chronic hepatitis C in a state correctional facility. Annals o f Internal Medicine, 138, 187-190. Alter, M. J. (2002). Prevention of spread of hepatitis C. Hepatology, 36, S93-S98. Alter, M. J., Seeff, L. B., Bacon, B. R., Thomas, D. L., Rigsby, M. O., & Di Bisceglie, A. M. (2004). Testing for hepatitis C virus infection should be routine for persons at increased risk for infection. Annals o f Internal Medicine, 141, 715-717. Artz, L., Macaluso, M., Brill, I., Kelaghan, J., Austin, H., Fleenor, M., Robey, L., & Hook III, E. W. (2000). Effectiveness of an intervention promoting the female condom to patients at sexually transmitted disease clinics. American Journal o f Public Health, 90(2), 237-244. Astone, J., Strauss, S. M., Vassilev, Z. P., & Des Jarlais, D. C. (2003). Provision of hepatitis C education in a nationwide sample of drug treatment programs. Drug Education, 33(1), 107-117. Bachmann, L. H., Lewis, I., Allen, R., Schwebke, J. R., Leviton, L. C., Siegal, H. A., & Hook III, E. W. (2000). Risk and prevalence of treatable sexually transmitted diseases at a Birmingham substance abuse treatment facility. American Journal of Public Health, 90(10), 1615-1618. Bloomfield, P. J., Kent, C., Campbell, D., Hanbrook, B. A, & Klausner, J. D. (2002). Community-based chlamydia and gonorrhea screening through the United States mail, San Francisco. Sexually Transmitted Diseases, 29(5), 294-297. Celum, C. L., Bolan, G., Krone, M., Code, K., Leone, P., Spaulding, C., Henry, K., Clarke, P., Smith, M., & Hook III, E. W. ( 1997). Patients attending STD clinics in an evolving health care environment: demographics, insurance coverage, preferences for STD services, and STD morbidity. Sexually Transmitted Diseases, 24(10), 599-605. Chou, R., Clark, E. C., & Helfand, M. (2004). Screening for hepatitis C virus infection: a review of the evidence for the US Preventive Services Task Force. Annals o f Internal Medicine, 140, 465-479. Cohen, D. A., & Scribner, R. (2000). An STD/HIV prevention intervention framework. AIDS Patient Care and STDs, 14(1), 37-45. Contreras, J. R., Lloyd, J. C., & White, G. L. (2001). An investigation of the incidence of Chlamydia trachomatis and Neisseria Gonorrhea in Utah, 1997-1999. Utah's Health, 8, 33-38. Edlin, B. R. (2002). Prevention and treatment of hepatitis C in injection drug users. Hepatology, 36, S210-S219. Fenaughty, A. M., & Fisher, D. G. (1998). High-risk sexual behavior among drug users: the utility of a typology of alcohol variables. Sexually Transmitted Diseases, 25(1), 38-43. © 2006 The University o f Utah. All rights reserved. STIs & Hepatitis C in Salt Lake County 29 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Fortenberry, J. D. (1998). Alcohol, drugs, and STD/HIV risk among adolescents. AIDS Patient Care and STDs, 12(10), 783-786. Global Burden of Hepatitis C Working Group. (2004). Global burden of disease (GBD) for hepatitis C. Journal o f Clinical Pharmacology, 44, 20-29. Harsch, H. H., Pankiewicz, J., Bloom, A. S., Rainey, C., Cho, J., Sperry, L., & Stein, E. A. (2000). Hepatitis C infection in cocaine users - a silent epidemic. Community Mental Health Journal, 36(3), 225-233. Herring, B. L., Page-Shafer, K., Tobler, L. H., & Delwart, E. L. (2004). Frequent hepatitis C superinfection in injection drug users. Journal o f Infectious Diseases, 190, 1396-1403. Hser, Y., Chou, C., Hoffman, V, & Anglin, M. D. (1999). Cocaine use and high-risk sexual behavior among STD clinic patients. Sexually Transmitted Diseases, 26(2), 82-86. Josset, V., Torre, J. P., Tavoclacci, M. P, Van Rossem-Magnani, V., Anselme, K., Merle, M., Godart, J., Libert, A., Ladner, J., & Czernichow, P. (2004). Efficiency of hepatitis C virus screening strategies in general practice. Gastroenterology and Clinial Biology, 28, 351-357. Kew, M., Francois, G., Lavanchy, D., Margolis, H., Van Damme, P., Grob, P., Hallauher, J., Shouval, D., Leroux-Roels, G., & Meheus, A. (2004). Prevention of hepatitis C virus infection. Journal o f Viral Hepatitis, 11, 198-205. Kim, W. R. (2002). The burden of hepatitis C in the United States. Hepatology, 36, S30-S34. Macalino, G. E., Viahow, D., Sanford-Colby S., Patel, S., Sabin, K., Salas, C., & Rich, J. D. (2004). Prevalence and incidence of HIV, hepatitis B virus, and hepatitis C virus infections among males in Rhode Island prisons. American Journal o f Public Health, 94(7), 1218-1223. Maheux, B., Haley, N., Rivard, M., & Gervais, A. (1999). Do physicians assess lifestyle health risks during general medical examinations? Journal o f the Canadian Medical Association, 160(13), 1830-1834. Mehta, S. D., Shahan, J., & Zenilman, J. M. (2000). Ambulatory STD management in an inner-city emergency department: descriptive epidemiology, care utilization patterns, and patient perceptions of local public STD clinics. Sexually Transmitted Diseases, 27(3), 154-158. Messiah, A., Bloch, J., & Blin, P. (1998). Alcohol or drug use and compliance with safer sex guidelines for STD/HIV infection: results from the French national survey on sexual behavior (ACSF) among heterosexuals. Sexually Transmitted Diseases, 25(3), 119-124. Pollack, H. A. (2001). Cost-effectiveness of harm reduction in preventing hepatitis C among injection drug users. Medical Decision Making, 21, 357-367. Rhoads, J. (2003). Natural history and epidemiology of hepatitis C. Journal o f the Association o f Nurses in AIDS Care, 14(suppl 5), 18S-25S. Samet, J. H., Mulvey, K. P., Zaremba, N., & Plough, A. (1999). HIV testing in substance abusers. American Journal o f Drug and Alcohol Abuse, 25(2), 269-280. Tao, G., Irwin, K. L., & Kassler, W. J. (2000). Missed opportunities to assess sexually transmitted diseases in US adults during routine medical checkups. American Journal o f Preventive Medicine, 18(2), 109-114. Utah Department of Health, Sexually Transmitted Disease Control Program. (n.d.). Retrieved January 29, 2005 from http://www. health.utah.gov/els/hivaids/std/std.htm. Van Valkengoed, I. G. M., Postma, M. J., Morre, S. A., van den Brule, A. J. C., Meijer, C. J. L. M., Bouter, L. M., & Boeke, A. J. P. (2001). Cost Effectiveness analysis of a population based screening programme for asymptomatic Chlyamydia trachomatis infections in women by means of home obtained urine specimens. Sexually Transmitted Infections, 77, 276-282. Wong, J. B., McQuillan, G. M., McHutchison, J. G., & Poynard, T. (2000). Estimating future hepatitis C morbidity, mortality, and costs in the United states. American Journal o f Public Health, 90, 1562-1569. Yen, T., Keeffe, E. B., & Ahmed, A. (2003). The epidemiology of hepatitis C virus infection. Journal o f Clinical Gastroenterology, 36(1), 47-53. 30 STIs & Hepatitis C in Salt Lake County © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Table 1: Summary o f Selected Demographic and Risk Factors for Study Populations Variable STI Group* HCV Group* Total Respondents: / (%) 184 75 Male 143 (78.1%) 53 (70.7%) Female 40 (21.9%) 22 (29.3%) Average Age/Range: / (%) Males 30.92/17-63 32.40/19-60 Females 29.40/15-54 33.18/15-54 # of Sex Partners, Average/Range: / (%) Males 3.03/0-30 3.52/0-30 Females 1.62/0-5 1.43/0-4 Have Medical Insurance: / (%) 100 (55.6%) 29 (39.7%) Males 76 (53.2%) 22 (42.3%) Females 25 (64.1%) 7 (33.3%) Recent Sexual Activity (last 3 mos): / (%) 169 (92.3%) 68 (93.1%) Vaginal 85 (50.3%) 45 (65.2%) Anal 86 (50.9%) 29 (42.0%) Oral 139 (82.3%) 56 (81.2%) Other 5 (3.0%) 1 (1.5%) Use of Prevention: / (%) 129 (71.3%) 44 (60.3%) Males 105 (74.5%) 34 (65.4%) Females 24 (61.5%) 10 (47.6%) Previous history of STI: / (%) 36 (20.7%) 17 (25.0%) Males 25 (17.8%) 12 (25.0%) Females 11 (29.0%) 5 (25.0%) Use of Substances (in last month): / (%) 155 (85.6%) 58 (79.5%) Males 122 (86.5%) 45 (86.5%) Females 32 (82.0%) 13 (61.9%) Alcohol 128 (82.6%) 42 (72.4%) Marijuana 43 (27.7%) 20 (34.5%) Tobacco 58 (37.4%) 26 (44.8%) Cocaine 16 (10.3%) 9 (15.5%) Poppers 12 (7.7%) 8 (13.8%) Acid 1 (0.7%) 1 (1.7%) Mushrooms 2 (1.3%) 1 (1.7%) Crystal/Meth 14 (9.0%) 11 (19.0%) Non-prescribed Rx meds 17 (11.0%) 10 (17.2%) OTC 32 (21.0%) 10 (17.2%) Heroin 3 (2.0%) 3 (5.2%) Ecstasy/Special K 3 (2.0%) 1 (1.7%) GHB 2 (1.3%) 1 (1.7%) Other 4 (2.6%) 5 (8.6%) Ever Inject Drugs: / (%) 21 (11.9%) 21 (29.2%) If Yes, Ever Share Needles: / (%) 12 (60.0%) 11 (55.0%) *Some totals reflect only the questionnaire data which was completed by the subject Table 2: Comparison o f STI Study to general Utah Rates per 100,000* STI Study 2000 2001 2002 2003 2004** GC 1169.59 19.3 17.2 27.7 28.85 33.97 CT 6432.75 148.54 186 224.26 229.1 207.52 Syp hilis *** 628.93 .1114.00 .43|1.00 .86|3.24 .54|3.65 .2113.37 * Rates per 100,000 population in this study and in Salt Lake County (per Utah Department of Health STD Control Program Statistics). ** provisional data *** rates are fo r primary and secondary | latent syphilis © 2006 The University o f Utah. All rights reserved. STIs & Hepatitis C in Salt Lake County 31 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Patient Safety Events in Utah, 2001: The First Statewide Assessment Wu Xu, Ph.D.; Stephen Pickard, M.B.A.; Michael P. Silver, M.P.H.; Paul Hougland, M.D.; Carol Masheter, Ph.D.; Steve Donnelly, Ph.D.; Jonathan Nebeker, M.D.; Matthew Samore, M.D.; Scott D. Williams, M.D., M.PH. CORRESPONDENCE: Carol Masheter, Ph.D. Information Analyst II Office o f Health Care Statistics Utah Department o f Health P.O. Box 144004 Salt Lake City, UT 84114-4004 801-538-6355 801-538-9916 (FAX) This first statewide assessment is based on review of 1,962 randomly selected medical charts from all acute care hospitals in Utah. We discovered that for every 100 admissions, approximately 18 patients experienced at least one patient safety event during their stay in the hospital. Eleven out of 100 patients experienced medical injuries prior to their hospital admissions. Five in-hospital deaths were confirmed as medical injury mortality. The weighted population estimate indicates that medical injuries in Utah that contributed to deaths (407, 95% CI: 75-1067) were the eighth leading cause of deaths in 2001, similar to the national estimate. Introduction The Institute of Medicine (IOM) report "To Err is Human" estimated that 44,000 to 98,000 people die annually in the United States hospitals due to medical errors (Kohn, Corrigan, & Donaldson, 2000). Based on this estimate, medical errors were the fifth or the eighth leading cause of death in the United States in 1997 and 1998 (National Vital Statistics Reports, 1999). These research findings have brought patient safety to the forefront as one of the major initiatives in quality improvement for the nation's healthcare system. The IOM's estimates of medical error mortality were based on two large studies conducted from 1984 to 1992. The Harvard Medical Practice Study provided the high end of estimate (n=98,000) based on examining medical records from 50 nonfederal acute care hospitals in New York in 1984 (Brennan et al., 1991). The low end of the IOM's estimates (n=44,000) was derived from the Utah/Colorado study conducted in 1992 (Gawande et al., 1999). The Utah sample for the 1992 study was collected from 19 out of 40 nonfederal acute care hospitals in Utah. Utah traditionally has been rated as one of the healthiest states in the nation according to most ranking systems and enjoys a respected reputation for shorter hospital stays and lower health care costs than the national average. The release of the IOM study impelled Utah health policy makers to determine the role and priority for a public health response. Public health focuses more on medical injuries that include a wider range of patient safety events than medical errors (Layde, Cortes & Teret, 2002). Taking an epidemiologic approach, a retrospective surveillance of statewide patient safety events was proposed to document the distribution and nature of injuries associated with medical care among hospital patients. In turn this assessment could inform state healthcare policy making. 32 Patient Safety Events in Utah © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW The Utah Department of Health, partnering with investigators at HealthInsight, the University of Utah, the Missouri Department of Health and Senior Services and the University of Missouri-Columbia, received funding from the Agency for Healthcare Research and Quality (AHRQ) to implement such a project in Utah and Missouri (Hougland, 2003). The Utah Department of Health Institutional Review Board approved this project. This article is one of series of reports based on the results from the project (Hougland et al., in press; Longo et al., 2005; Masheter, Hougland & Xu, 2005). Sample, Definition and Method Sample This study was based on a stratified random sample that consisted of 1,962 medical charts representing 239,051 hospitalizations in 2001 from all 41 acute care hospitals in Utah (Utah Hospital Inpatient Discharge Database, 2001). Charts from small rural hospitals and charts with a length of stay greater than three days were over-sampled. each hospital contributed two strata with at least 30 total cases. A total of 82 sample weights were applied to the population estimates to adjust for the 82 sample strata. We conducted statistical tests on the sample and population's distributions of age and gender by the length of stay (<=3 days vs. >=4 days). The results (not reported here) showed that the means of age in the sample and the population were not significantly different from each other. However gender distribution in the sample was skewed toward females in the strata with greater than three days of hospital stay. Definitions In this analysis, the term patient safety event is interchangeable with the terms of medical injury or adverse event (AE). Initially, the project intended to examine AEs that occurred in the hospital setting. The project's national panel of experts developed an implicit definition of an AE for this study, as: an undesirable and unintended injury resulting from a medical intervention (an act of care provided by the hospital or by the omission of necessary care), rather than from patient's underlying disease process; and where such injury occurs during an inpatient hospital stay (i.e., subsequent to admission) and results in or leads to patient harm. The definition of patient harm was adopted from the Utah Administrative Rule R380-210, titled "Health Care Facility Patient Safety Program," with minor modifications. Patient harm means: death, prolonged hospital stay, or temporary or permanent impairment of body function or structure to a patient. The seriousness of harm should reflect changes that either resulted from or were necessitated by the injury event that require interventions such as (1) a change in monitoring the patient's condition; (2) a change in therapy; or (3) active medical or surgical treatment or attention, if an intervention is feasible or possible. These definitions were operationalized in terms of causality of an injury and degree of harm to a patient. The causality score was based on a 6-point scale from 1 (Virtually certain evidence for disease causation) to 6 (Virtually certain evidence for management causation). Reviewers were also given the choice "Unable to determine" if they felt their level of expertise was not adequate to assign a causality score. th e AEs included in the analysis had a causality score of 4 to 6, where 4 indicators "Case management causation more likely than disease"; 5 indicates "Moderate/strong evidence for management causation"; and 6 indicates "Virtually certain evidence for management causation." The measure of harm was adopted from Kivlahan and associates' study to code harm by increased severity of injury and resources used for treatment (Kivlahan et. al, 2002). The harm measures include Level A (e.g., no clinical change), © 2006 The University o f Utah. All rights reserved. Patient Safety Events in Utah 33 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Level B (e.g., minor change in condition), C (e.g., Vital signs changed), D (e.g., cardiac changes requiring intervention), E (e.g., cardiac/respiratory arrest) and F (death). Only events associated with a harm rating of Level B through Level F were included in the analysis. Although the primary focus of the study was AEs that occurred in the hospital, the medical-chart reviewers also recorded a "pre-admission AE" if they found that "an AE led to admission". The first part of definition for inpatient AEs, "an undesirable and unintended injury resulting from a medical intervention (an act of care provided by the hospital or by the omission of necessary care), rather than from patient's underlying disease process," was used for pre-admission AEs. The reviewers only recorded one pre-admission AE per medical chart, according to the implicit AE definition, and did not collect additional information on causality and harm for AEs that led to hospital admissions. Preventability of an AE was not examined in the nurse reviews. Method The chart review instrument was a modified version of the tool developed by the previous Harvard Medical Practice and Utah/Colorado studies (Thomas et al., 1999). Trained nurses from HealthInsight were the primary reviewers of the medical charts for this study. All held a degree from an accredited school of nursing and a current (RN or LPN) license in good standing. All nurse reviewers had at least three years of experience in medical record abstraction as reviewers for the Health Plan Employer Data and Information Set (HEDIS) performance measures. This previous experience included work with ICD-9-CM (the International Classification of Disease 9th Edition Clinical Modification) clinical coding, data collection, tool completion and subsequent data entry. They also received an additional 40 hours of specialized training and were required to demonstrate competency prior to beginning the chart review. Throughout the project the review coordinator monitored quality and consistency by reviewing the descriptions and ratings of identified AEs. Trained physicians, blinded to the results of initial nurse review, re-examined 153 of the nurses-reviewed charts. The sample of physician-reviewed charts was randomly selected from strata defined by the causality scores of nurse-detected inpatient AEs. The nurse-reviewed pre-admission AEs were not examined or verified by physician reviewers. The Kappa coefficient for physician and nurse review results at the chart level was 0.58 for AEs that occurred in the hospital and 0.36 for AEs that led to admission, which is considered moderate and fair agreement, respectively, by the Landis and Koch (1977) suggested interpretation of the kappa statistic. The inter-rater reliability between physician and nurse reviewers was comparable with the inter-rater judgment among physician reviewers in a previous study (Thomas, Studdert & Brennan, 2002). All charts with inpatient AEs that probably contributed to death were reviewed by a nurse reviewer first then verified by a physician reviewer and/or the medical director of this project. The project's medical director also used additional information from the death certificates to verify and confirm the causality of each death as medical injury. AEs were grouped into three categories: adverse drug events (ADEs), surgery-related AEs, and medical/other treatment-related AEs. Each AE was classified into one category in the following hierarchy: (1) ADE, (2) surgery AE or (3) medical/other AE. Based on these categories, the study describes estimates of statewide incidence, incidence rates per 100 hospital inpatient admissions, and incidence rates per 1,000 inpatient days of hospital stay. These estimates of medical injuries were compared with the statistics from other statewide population-based databases: (1) the Utah Death Certificate Database for leading causes of death and (2) the Utah Hospital Inpatient Discharge Database for leading reasons for hospitalization. We used a normal approximation method for the 95% confidence interval (95% CI) of population estimates of AEs and an exact binomial distribution method for low frequency events (medical injury deaths). The statistical software SAS 34 Patient Safety Events in Utah © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW version 8 was used for most of the analyses; Stata version 9.1 was used for the approximation of the 95% CI for medical injury mortality using the exact method. Findings Table 1 reports the key results from the statewide assessment of patient safety events among the 41 Utah acute care hospitals in 2001. The upper panel presents findings of the AEs acquired in the hospitals; the lower panel contains information on AEs that led to hospital admissions. Table 1. Number o f Adverse Events (AEs) and Estimated AE Rate for 41 Utah Acute Care Hospitals: 2001 Type of AEs Sample No. of Discharges* No. of AEs* Population Estimates Estimated Rate Per 100 Estimated Discharges Admissions Estimated Rate per 1,000 N 95% % 95% Inpatient Confidence Confidence Days Interval Interval AEs acquired in hospital All AEs acquired in hospital 403 606 41977 36941-47012 17.6% 15.5%-19.7% 47.4 Number of patients died due to AE 5 6 407 75-1067*** 0.17% 0.03%-0.44% 0.46 Adverse drug events (ADEs) 218 264 22786 19118-26454 9.5% 8.0%-11.1% 25.7 Surgery-related AEs 137 182 15340 12290-18388 6.4% 5.1%-7.7% 17.3 Medical and other AEs 125 160 11942 9404-14480 5.0% 3.9%-6.1% 13.5 AEs that led to admission** All AEs that led to admission 254 254 25918 21822-30014 10.8% 9.1%-12.6% n.a. Adverse drug events (ADEs) 91 91 9119 6657-11580 3.8% 2.8%-4.8% n.a. Surgery-related AEs 84 84 9463 6928-11998 4.0% 2.9%-5.0% n.a. Medical and other AEs 79 79 7336 5264-9408 3.1% 2.2%-3.9% n.a. Total cases in sample or population 1962 239051 100% 885312 Sources: The 2001 Utah Patient Safety Stratified Random Sample and Utah Hospital Inpatient Discharge Database. * One discharge may have two or more types of AEs. ** Only one AE that led to admission was recorded. ***Approximate confidence interval based on estimate rate in a sample of1,962 discharges Adverse Events Acquired in the Hospital Overall, the chart reviewers discovered 606 AEs acquired in the hospital among 403 inpatients from the sample of 1,962 medical charts. The weighted population estimates suggest that for every 100 admissions, approximately 18 patients (17.6%, 95% CI: 15.5%-19.7%) experienced at least one AE during their hospital stay. This estimate suggests that in 2001 approximately 41,977 (95% CI: 36,941-47,012) patients experienced various medical injuries in Utah hospitals. The reviewers and the project's medical director also identified and confirmed five deaths in the sample that could be attributed to medical care management. Because of the low frequency of the events, we used an exact binomial distribution method for estimating a 95% confidence interval. The weighted population estimate of the medical-injury mortality among all Utah inpatients in 2001 was 407 (95% CI: 75-1,067) or 0.17% (95% CI: 0.03%-0.44%) of the entire inpatient population. The reviewers determined three specific types of AEs. ADEs comprised the largest group of medical injuries acquired in the hospital (22,786; 9.5%), followed by surgery AEs (15,340; 6.4%) and medical and other AEs (11,942; 5.0%). Among all types of AEs, the percentage distribution of ADEs among all inpatients (95% CI: 8.0%-11.1%) was significantly higher than surgical AEs (95% CI: 5.1%-7.7%) and medical/other AEs (95% CI: 3.9%-6.1%). © 2006 The University o f Utah. All rights reserved. Patient Safety Events in Utah 35 2006 UTAH'S HEALTH: AN ANNUAL REVIEW The AE incidence rates were also measured in terms of AEs per 1,000 inpatient days of hospital stay. Number of days the patient stayed in the hospital could be considered the patient's "exposure" to the complicated health care system. The more interactions occurred or treatments that hospitals provided, the higher likelihood for a patient to experience an AE during a hospitalization (Andrews et al., 1997). For every 1,000 inpatient days in Utah in 2001, hospitalized patients experienced 47.4 AEs. Again, ADEs had the highest rate (25.7 per 1,000 days), followed by surgical AEs (17.3 per 1,000 days). Adverse Events That Led to Admissions The analysis of AEs that led to admission also included sample statistics and weighted population estimates (see Table 1 lower panel). The study detected 254 patients who arrived at the hospital with at least one AE that led to hospital admission. The numbers of discharges and AEs that led to admission were identical in this section, because the nurse reviewers were asked to record only one pre-admission AE per medical chart. The population estimate of patients with AEs that led to admission was 10.8% (95% CI: 9.1%-12.6%) of all hospitalized patients in Utah, which was equivalent to approximately 25,918 admissions (95% CI: 21,822-30,014) in 2001. The chart reviewers identified 79 to 91 cases with pre-admission AEs for each AE type. After weighting for the sample strata, the population estimate of patients with surgery-related AEs was the largest category (n=9,463, 95% CI: 6,928- 11,998) among the three AE groups. However the percentage distributions of the three types of pre-admission AEs were not statistically different from each other. DISCUSSION A Leading Cause of Death The estimates of statewide medical injuries were compared with other statewide population-based indicators in Table 2 and Table 3. Medical injury mortality was compared with the leading causes of death derived from the state death certificate database (Utah Death Certificate Database, 2001). We adopted the National Center for Health Statistics classification of the 50 leading causes of death as the reference categories, which was published on the Utah Indicator-based Information System for Public Health (Utah IBIS-PH, 2004). Table 2 shows that medical injuries that contributed to deaths were the eighth leading cause of deaths in Utah for 2001, making medical injury mortality a serious public health concern. A Leading Reason for Hospitalization Table 3 presents the commonly-used Major Diagnosis Categories (MDC) to classify the reasons for hospitalizations (Utah Health Data Committee, 2002). We provided a baseline of top six reasons for hospitalizations in all 41 study hospitals in 2001. The estimated number of AEs that led to admissions (n=25,918) was just below the top two reasons for hospitalizations in Utah: (1) pregnancies and childbirths (n=50,445), and (2) newborns (n=49,139). Assessing AEs that led to hospital admission was not a primary focus of the study. However, the high proportion of patients in our sample who arrived at hospitals with pre-existing AEs was noteworthy. This finding points to the need for examining patient safety beyond hospitals. Medical injuries occur throughout the health care community. Those AEs that led to admissions could be the result of previous health care provided at physician offices, medical or dental clinics, previous hospital visits, nursing homes, as well as patient homes and residential facilities. Strategies to prevent medical injuries need to focus on all of these settings. Standards for Measuring Patient Safety Events The Harvard Medical Practice Study in 1984 reported that the rate of AEs was 3.7% of hospitalizations with 13.6 percent leading to death of the patients (Brennan et al. 1991). This Utah 2001 assessment found a higher percent of AEs (17.6%) 36 Patient Safety Events in Utah © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Table 2. Leading Causes o f Death and Estimated Medical Injuries That Contributed to Death: Utah, 2001 Rank Cause of Death* Deaths No. 1 Diseases of heart 2,875 2 Malignant neoplasms 2,304 3 Cerebrovascular diseases 867 4 Unintentional injuries 631 5 Chronic lower respiratory diseases 522 6 Diabetes mellitus 509 7 Influenza and pneumonia 412 Medical injuries that contributed to deaths (estimate) 407 8 Intentional self-harm (suicide) 316 9 Alzheimer's disease 314 10 Nephritis, nephrotic syndrome and nephrosis 177 Total number of deaths of Utah residents in 2001 12,607 Estimated number of population in Utah, 2001 2,305,652 Sources: Table 1. Utah Death Certificate Database, Population Estimates, and Inpatient Hospital Discharge Database Retrieved on February 2004 and March 14, 2006from Utah Department of Health, Center for Health Data, Indicator-based Information System for Public Health (IBIS-PH) at http://ibis.health.utah.gov/. * Causes of death were based on the classification determined by the National Center for Health Statistics. Table 3. Leading Reasons for Hospitalization and Estimated Adverse Events (AEs) That Led to Admission Among 41 Utah Acute Care Hospitals: 2001 Rank Major Diagnosis Category (MDC) Discharges 1 Pregnancy, childbirth and puerperium 2 Newborn and other neonates (perinatal period) N 50,445 49,139 AEs that led to admissions (estimate) 25,918 3 Circulatory system 24,559 4 Musculoskeletal system and connection tissue 19,887 5 Digestive system 16,624 6 Respiratory system 16,123 Total number of hospitalizations among Utah residents in 2001 231,581 Estimated number of population in Utah, 2001 2,305,652 Sources: Table 1. Utah Population Estimates and Inpatient Hospital Discharge Database Retrieved on February 2004 and March 14, 2006 from Utah Department of Health, Center for Health Data, Indicator-based Information System for Public Health (IBIS-PH) at http://ibis. health.utah.gov/. but a lower percent of AE mortality (0.17%) than the Harvard Medical Practice Study. We also detected a higher rate of surgical AEs (6.4%) than the 1992 Utah/Colorado study (1.7% to 2.1%) (Gawande et al. 1999). These differences might come from different definitions of the AEs, study populations, and study methods. Our study attempted to capture all medical injuries. The above researches focused on medical errors, a subset of medical injuries. Standardized measures of patient safety events are needed for an ongoing surveillance program. state public health agencies wish to use standardized measures and consistent methods to conduct periodical assessments on the same population and community. © 2006 The University o f Utah. All rights reserved. Patient Safety Events in Utah 37 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Policy Implication and Limitation State public health agencies and patient safety organizations can use statewide patient safety or medical injury surveillance to monitor trends and develop strategies for reducing these events. Until now, patient safety was a "missing category" in the traditional approach to assessing leading causes of deaths, leading reasons for hospitalizations, and other state public health injury surveillance systems. This first statewide assessment of patient safety events in Utah established a surveillance methodology and a baseline that will allow public health agencies to track facility reported medical injuries into the future. The statewide assessment also can be used for priority settings for patient safety improvements in Utah. Our study showed that ADE was the largest group of medical injuries among hospital patients. This evidence supports the Utah Department of Health's initial patient safety initiative, that is, to have implemented two administrative rules (R380-200 and R380-210) to require health care facilities to report inpatient sentinel events (severe harm due to medical care such as permanent harm and death) and ADEs since 2001. Our findings also indicate that current patient safety reporting systems in Utah are likely to suffer from underreporting. This assessment is consistent with a joint assessment previously made by the Utah Department of Health, Utah Hospitals and Health Systems Association, and HealthInsight (2003). A limitation of this assessment is lack of information on preventability of each adverse event detected by the nurse reviewers. Some of the events, such as some adverse drug reactions, might not be preventable at the point of patient care. Preventability study would also provide more actionable recommendations for system-wide patient safety improvement in hospitals. Defining the nature of a problem is a first and essential step towards strategizing solutions. All 41 acute care hospitals in Utah voluntarily participated in this assessment, indicating Utah hospitals' support the statewide patient safety initiative. Successful attempts to reduce medical injuries will require a variety of systems, organizations, and individuals (i.e., policy-makers, providers, patients, and researchers) to work together in order to learn about and prevent these injuries from occurring. Utah has been leading the nation in conducting patient safety research and innovation in large urban hospitals (Evans et al. 1991). This statewide assessment may increase broader awareness of the patient safety problem and assist dissemination of existing best practices to more hospitals in Utah. References Andrews, LB; Stocking, C; Krizek, T; et al. (1997) Alternative Strategy for Studying Adverse Events in Medical Care. Lancet. 349(9048), 309-313. Brennan, TA; Leape, LL; Laird, NM; Hebert, L; Localio, AR; Lawthers, AG; Newhouse, JP; Weiler, PC & Hiatt, HH. (1991). Incidence of Adverse Events and Negligence in Hospitalized Patients: Results of the Harvard Medical Practice Study I. New England Journal of Medicine, 324, 370-376. Evans, RS; Pestotnik, SL; Classen, DC, et al. (1991). Development of Computerized Adverse Drug Event Monitor. Procceedings of the Annual Symposium of Computer Applications in Medical Care, 1991, 23-27. Gawande, AA; Thomas, EJ; Zinner, MJ & Brennan, TA. (1999). The Incidence and Nature of Surgical Adverse Events in Colorado and Utah in 1992. Surgery, 126, 66-75. Hougland, P. (2003). Using Administrative Data to Identify Adverse Events. Utah's Health: An Annual Review, IX, 132. Hougland, P; Xu, W; Pickard, S; Masheter, C & Williams, SD. (In press). Performance of ICD-9-CM Codes as an Adverse Drug Event Surveillance System. Medical Care. Kivlahan, C; Sangster, W; Nelson, K; Buddenbaum, J & Lobenstein, K. (2002). Developing a Comprehensive Adverse Event Reporting System in an Academic Health Center. Joint Commission Journal of Quality Improvement, 28, 583-594. 38 Patient Safety Events in Utah © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Kohn, LT; Corrigan, JM & Donaldson, MS. (eds.) (2000). To Err Is Human: Building a Safer Health System. Committee on Quality of Health Care in America, Institute of Medicine, Washington, D.C: National Academy Press. Landis JR & Koch GG. (1977). The measurement of observer agreement for categorical data. Biometrics, 33:159-174. Layde, PM; Cortes, LM; Teret, SP; et al. (2002). Patient Safety Efforts Should Focus on Medical Injuries. Journal of the American Medical Association, 287, 1993-1997. Longo, DR; Hewett, JE; Ge, B &Schubert, S. (2005). The Long Road to Patient Safety: A Status Report on Patient Safety Systems. Journal of the American Medical Association, 294, 22, 2858-2865. Martin, JA; Smith, BL; Mathews, TJ & Venturea, SJ. (1999). National Vital Statistics Reports, Vol. 47, No. 25, October 5. Washington, D.C.: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics. Masheter, C; Hougland, P & Xu, W. (2005). Detection of Inpatient Health Care Associated Injuries: Comparing Two ICD-9-CM Code Classifications. In Henriksen K, Battles JB, Marks ES, Lewin DI, (eds.). Advances in Patient Safety: From Research to Implementation. Vol. 1, Research Findings, pp. 227-244. AHRQ Publication No. 05-0021-1. Rockville, MD: Agency for Healthcare Research and Quality, Washington, D.C Thomas, EJ; Studdert, MD & Brennan, TA. (2002). The reliability of medical record review fro estimating adverse event rates. Ann Intern Med, 136, 812-816. Thomas, EJ; Studdert, DM; Newhouse, JP; Zbar, BI; Howard, KM; Williams, EJ & Brennan, TA. (1999). Costs of Medical Injuries in Utah and Colorado. Inquiry, 36, 255-264. Utah Death Certificate Database. Retrieved on February 8, 2004 from Utah Department of Health, Center for Health Data, Indicator-Based Information System for Public Health website: http://ibis.health.utah.gov/. Utah Inpatient Hospital Discharge Database, 2001. Utah Department of Health Office of Health Care Statistics. Utah Department of Health, Utah Hospitals and Health Systems Association, Healthlnsight. (2003). Utah Rule Provides First Year of Patient Safety Data. Utah Patient Safety Update, 1(2), 1-2. Utah Health Data Committee (2002). 2001 Utah inpatient hospital utilization and charge profile: Facility details. Utah Department of Health Office of Health Care Statistics http://health.utah.gov/hda/Reports/st1book_01_ revised.pdf Utah's Indicator-based Information System for Public Health (IBIS-PH), Utah Department of Health. (2004). http://ibis.health.utah.gov/query/module_selection/mortality/MortSelection.html ACKNOWLEDGEMENT This project was supported by grant number U18 HS11885 from the Agency for Healthcare Research and Quality and the Utah/ Missouri Patient Safety Consortium. We appreciate the Utah Hospitals and Health Systems Association's assistance to recruit all Utah acute care hospitals to participate in this project. The abstract o f this paper was presented in poster form at the Agency for Healthcare Research and Quality's Patient Safety Research Conference, Washington D.C., March 2004. © 2006 The University o f Utah. All rights reserved. Patient Safety Events in Utah 39 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Religion and Body Weight in Utah Ray M. Merrill, PhD, MPH; Steven Hillam, BS CORRESPONDENCE: Ray M. Merrill, PhD Department o f Health Science 229-A Richards Building Brigham Young University Provo, Utah 84604 Email: [e-mail] Telephone: [phone] Facsimile: [phone] Abstract PURPOSE: To assess the association between religious preference, religious activity, and body weight among adults aged 18 years and older in Utah. METHODS: Analyses are based on data from the Utah Health Status Survey, conducted among adults in the years 2003-2004 (n=5,680), 2001 (n=7,108), and 1996 (n=6,188). Means were adjusted for age, sex, race, education, marital status, income, smoking, and exercise. Data on exercise was only available in the 2001 and 1996 surveys. RESULTS: Latter-day Saints (LDS or Mormons) were significantly heavier than Protestants, Catholics, those with other religious preference, or those with no religious preference. Mean BMI is 0.7 units (~ 4.6 lbs) heavier in LDS than in non-LDS in 2003-2004, 1.0 units (~ 6.1 lbs) heavier in 2001, and 0.8 units (~ 5.7 lbs) heavier in 1996 (Wald F p < 0.05 for each model). Among those who exercise, mean BMI is 0.6 units (~ 3.7 lbs) heavier in LDS than non-LDS in 2001 and 0.7 units (~ 4.8 lbs) heavier in 1996. Among those who do not exercise, mean BMI is 1.7 units (~ 10.5 lbs) heavier in LDS than non-LDS in 2001 and 0.9 units (~ 6.1 lbs) heavier in 1996 (Wald F p < 0.05 for each model). LDS were 14% (18% for males and 9% for females) more likely than non-LDS to be obese (BMI > 30) in 2003-2004, 26% (35% for males and 17% for females) more likely in 2001, and 34% (54% for males and 17% for females) more likely in 1996. CONCLUSION: Although the gap in BMI and body weight between LDS and non-LDS has narrowed in recent years, LDS remain significantly heavier than non-LDS in Utah. KEY WORDS: Body mass index, Diet, Exercise, Latter-day Saints, Mormons, Obesity, Smoking. Introduction In view of the sudden increase in weight levels worldwide, environmental causes (overeating, eating too many high-fat or refined sugary foods, reduced energy expenditure) must be the prime explanation. In the United States, poor diet and physical inactivity has almost overtaken tobacco as the primary cause of preventable death. In 2000, approximately 18.1% of total deaths in this country were explained by tobacco and 16.6% of total deaths were explained by poor diet and physical inactivity (1). Despite known health risks associated with obesity (such as type 2 diabetes, heart disease, some forms of cancer, and other disabling medical conditions) (2-5), increasing trends in obesity continue. In the United States, the percentage of the adult population considered obese by the body mass index (BMI) increased from 11.6% in 1990 to 23.1% in 2004 (6, 7). Unfortunately state efforts to respond to the obesity epidemic through obesity control legislation have been slow (8). 40 Religion and Body Weight in Utah © 2006 The University of Utah. All rights reserved. 2006 UTAH'S HEALTH: AN ANNUAL REVIEW Research has shown a protective influence of religion or spirituality on mortality, morbidity, and disability (9). Protective effects of religion or spirituality against cardiovascular disease, cancer, and other chronic conditions is largely influenced by the healthy lifestyle it encourages (9-11). However, some studies have associated religion with higher body weight. Data from the National Survey of Midlife Development in the United States found that religious denomination was significantly related to higher body weight in men but not in women after accounting for sociodemographic controls (12). Conservative Protestants were 1.13 BMI units heavier and Mainline Protestants 0.93 BMI units heavier than those with no religious preference (12). Data from two Southeastern New England communities in 1981-1984 found that church members were significantly more likely than non-church members to be overweight (BMI 26.8 vs. 26. 0, p < 0.001) (13). In addition, a 1998 survey identified a higher risk of obesity with being religious, regardless of the religious preference (14). In this study, the relationship between religious preference, church activity, and body weight in Utah was examined. METHODS This study is based upon Utah Health Status Survey conducted in 2003-2004, 2001, and 1996. These surveys are cross-sectional random surveys sponsored by the Utah Department of Health. Supervised interviews were conducted over the telephone by trained interviewers across 12 health districts which cover the state of Utah. Data was collected by the Gallop organization in 1996, Pegus Research, Inc., in 2001, and the Utah Department of Health, Survey Center in 2003- 2004 by incorporating a telephone survey instrument into a computer-assis