The primary aim of this application is to build an analytic database infrastructure that will expand the capability of the Connecticut Center for Primary Care (CCPC) to conduct comparative effectiveness research (CER) on complex patients who are seen by the primary care clinicians in the CCPC Practice-Based Research Network (PBRN). The project is titled Building Infrastructure for Comparative Effectiveness Protocols (BICEP). The primary aim will be accomplished by combining Allscripts Electronic Health Record (EHR) data and electronic data from various ancillary data sources into a single analytic database that (1) links information from all sources by unique patient identifier, and (2) standardizes the meaning, coding, and location of data elements from all of these sources. Allscripts is a leading EHR system that has been implemented by ProHealth Physicians, whose 75 clinical practices with over 340,000 patients are part of the CCPC PBRN. Other data sources include ProHealth laboratory data, pharmacy claims data, pay for performance data, and historical patient records. The analytic database will group data in five primary categories: (1) patient characteristics;(2) diagnoses;(3) interventions and processes;(4) patient outcomes;and (5) system. This will result in a data infrastructure that provides an analytic database that can be used for CER with complex patients. A secondary aim of this application is to conduct a pilot study to demonstrate the feasibility and value of using the analytic database for conducting CER among complex patients. The study will be of complex patients with both hypertension and diabetes and will examine the combinations of processes that yield the best control of both conditions. The study will include development of novel statistical methods for assigning disease control scores to complex patients, identifying clinicians who set the """"""""benchmark"""""""" for success in controlling multiple diseases in complex patients, and identifying clinical interventions and processes that contribute to such clinicians'success.
Medical treatments for disease are generally proven through controlled clinical trials with restrictive eligibility criteria-. Effectiveness in the real world may be altered by many factors, including the existence of multiple conditions in a single patient, the """"""""complex"""""""" patient. CER on complex patients will be greatly enhanced by the combination of multiple medical data sources that allow the determination of combinations of interventions and processes that yield the best results in treating multiple conditions simultaneously.
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