The design and analysis of an informatics infrastructure to support clinical decision making in the management of opioid PCA infusions for palliative patients

Though medical advances in the last century now allow us to forestall death, many patients suffer from significant symptoms as they battle severe disease. Opioid medications are particularly effective when treating pain in these patients and infusion by the patient controlled analgesia (PCA) paradigm is commonly used in patients with severe disease. While PCA allows rapid titration yet individualized adjustment of opioid dose, it involves complex, high-stakes decisions. Unfortunately, clinicians complain that it is often difficult or impossible to find the data needed to make these decisions. A relevant data display could support clinical decisions by providing real-time up-to-date clinical data at the point of care. Literature synthesis and multiple modeling techniques were used to quantify the domain. An inductive, qualitative approach, including graphical mapping techniques, was used to build a foundational domain information model which was subsequently validated using a survey of domain experts. A gap analysis was performed, mapping concepts from the information model to the emerging HL7 FHIR standard. Modeling revealed a complex workflow, highlighted the bottleneck in information flow to providers at the point of care, and supported the premise that a relevant data display would be beneficial. The gap analysis showed that currently existing FHIR resources are capable of representing all relevant concepts from the domain information model needed for decision making in this complex use-case. Potential problems with FHIR implementation were identified and recommendations to address these are presented.