Perry Mar

Discontinuation of Statins in Routine Care Settings: A Cohort Study

BACKGROUND Systematic data on discontinuation of statins in routine practice of medicine are limited. OBJECTIVE To investigate the reasons for statin discontinuation and the role of statin-related events (clinical events or symptoms believed to have been caused by statins) in routine care settings. DESIGN A retrospective cohort study. SETTING Practices affiliated with Brigham and Womens Hospital and Massachusetts General Hospital in Boston. PATIENTS Adults who received a statin prescription between 1 January 2000 and 31 December 2008. MEASUREMENTS Information on reasons for statin discontinuations was obtained from a combination of structured electronic medical record entries and analysis of electronic provider notes by validated software. RESULTS Statins were discontinued at least temporarily for 57 292 of 107 835 patients. Statin-related events were documented for 18 778 (17.4%) patients. Of these, 11 124 had statins discontinued at least temporarily; 6579 were rechallenged with a statin over the subsequent 12 months. Most patients who were rechallenged (92.2%) were still taking a statin 12 months after the statin-related event. Among the 2721 patients who were rechallenged with the same statin to which they had a statin-related event, 1295 were receiving the same statin 12 months later, and 996 of them were receiving the same or a higher dose. LIMITATIONS Statin discontinuations and statin-related events were assessed in practices affiliated with 2 academic medical centers. Utilization of secondary data could have led to missing or misinterpreted data. Natural-language-processing tools used to compensate for the low (30%) proportion of reasons for statin discontinuation documented in structured electronic medical record fields are not perfectly accurate. CONCLUSION Statin-related events are commonly reported and often lead to statin discontinuation. However, most patients who are rechallenged can tolerate statins long-term. This suggests that many of the statin-related events may have other causes, are tolerable, or may be specific to individual statins rather than the entire drug class. PRIMARY FUNDING SOURCE National Library of Medicine, Diabetes Action Research and Education Foundation, and Chinese National Key Program of Clinical Science.

Next generation terminology infrastructure to support interprofessional care planning

OBJECTIVE Develop a prototype of an interprofessional terminology and information model infrastructure that can enable care planning applications to facilitate patient-centered care, learn care plan linkages and associations, provide decision support, and enable automated, prospective analytics. DESIGN The study steps included a 3 step approach: (1) Process model and clinical scenario development, and (2) Requirements analysis, and (3) Development and validation of information and terminology models. RESULTS Components of the terminology model include: Health Concerns, Goals, Decisions, Interventions, Assessments, and Evaluations. A terminology infrastructure should: (A) Include discrete care plan concepts; (B) Include sets of profession-specific concerns, decisions, and interventions; (C) Communicate rationales, anticipatory guidance, and guidelines that inform decisions among the care team; (D) Define semantic linkages across clinical events and professions; (E) Define sets of shared patient goals and sub-goals, including patient stated goals; (F) Capture evaluation toward achievement of goals. These requirements were mapped to AHRQ Care Coordination Measures Framework. LIMITATIONS This study used a constrained set of clinician-validated clinical scenarios. Terminology models for goals and decisions are unavailable in SNOMED CT, limiting the ability to evaluate these aspects of the proposed infrastructure. CONCLUSIONS Defining and linking subsets of care planning concepts appears to be feasible, but also essential to model interprofessional care planning for common co-occurring conditions and chronic diseases. We recommend the creation of goal dynamics and decision concepts in SNOMED CT to further enable the necessary models. Systems with flexible terminology management infrastructure may enable intelligent decision support to identify conflicting and aligned concerns, goals, decisions, and interventions in shared care plans, ultimately decreasing documentation effort and cognitive burden for clinicians and patients.