Investigation of Practice Facilitator Workflows for Enrollment Enhancement in ICD-Pieces Study

BACKGROUND: Care for patients with multi-morbidities is challenging and often suboptimal. Earlier detection of patients with coexisting Chronic Kidney Disease (CKD), diabetes and hypertension served by our health care systems will allow us to institute appropriate care for the right patient at the right time with the right intervention thereby providing the greatest benefit. Implementation of interventions to treat CKD, diabetes, and hypertension and to treat associated conditions should reduce cardiovascular mortality and morbidity, improve clinical status, and reduce hospitalization and costs. A collaborative model approach to care for patients with multiple chronic conditions using the unique and novel technology platform provided by Pieces (Parkland intelligent e-coordination and evaluation system) is being investigated via pragmatic clinical trial. OBJECTIVE: The main hypothesis is that patients with CKD, hypertension and diabetes who receive care with a collaborative model of primary care-subspecialty care enhanced by novel information technology (Pieces) will have fewer hospitalizations, readmissions, CV events and deaths than patients receiving standard medical care. METHODS: The study employs a prospective stratified cluster randomization design involving four healthcare systems which are the stratum: Parkland Healthcare Systems, Texas Health Resources (THR), North Texas Veterans Affairs, and ProHealth Connecticut. Each of the four healthcare systems are unique in the populations that they serve, the electronic medical records that they utilize, and the qualifications of the practice facilitators that they employ. Practice facilitators at each of the participating sites received training on how to leverage the enhanced resources provided by Pieces. The practice facilitators are a crucial link that ensure consistent incorporation of Pieces technology into the care of patients selected for the intervention group of the study. The four unique practice facilitator workflows were diagrammed and proofed for accuracy. Challenges in the process identified by the practice facilitator were also cataloged. Similarities and differences noted in the workflows allowed the identification of the highest yield areas for improvement. Comparison of each of the four unique workflows to the original, "generic" workflow as well as to each other helped identify challenges consistent across all of the systems as well as ones unique to each system. RESULTS: The major challenge identified by each practice facilitator was the accuracy of the generated confirmed and candidate patient lists that they have been receiving. This led to decreased patient enrollments and resulted in the practice facilitators performing a manual survey of each patient. The inaccuracy of the lists was an indictment of the patient selection algorithm and leads one to question if all candidate patients were being identified. Other challenges identified by every practice facilitator included initial resistance from PCPs, missed appointments, and obtaining labs prior to appointments. Individually, each practice facilitator identified challenges that were unique to their situation. These challenges included the inability to sign lab orders, high overall workloads for pharmacists, and the inability to determine if PCPs had taken note of protocol recommendations. CONCLUSION: Investigation and comparison of the practice facilitator workflows at each of the four healthcare systems aided in the identification of shortfalls and challenges that have hindered the patient enrollment process. These workflows will be useful in future pragmatic studies that utilize the EMR in the identification of a patient population. It is also generally instructive for studies that seek to utilize EMRs to identify patient populations. Despite the theoretical efficacy of informatics application in healthcare, there is still much progress to be made in this arena. Nevertheless, the study as a whole will be an important part of the growing collection of pragmatic trials due to their increased external validity compared to traditional explanatory trials. It will also ultimately be a valuable learning tool in the construct and execution of future pragmatic trials and hopefully demonstrate that a collaborative model of primary care-subspecialty care that leverages information technology can improve the quality of patient care.