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H N Sokol

Publications and source records attributed to H N Sokol.

2 recordsLinked to original sources

Is consensus reproducible? A study of an algorithmic guidelines development process.

The authors evaluated the reproducibility of a clinical algorithm consensus development process across three different physician panels at a health maintenance organization. Physician groups were composed of primary care internists, who were provided with identical selections from the medical literature and first-draft "seed" algorithms on the management of two common clinical problems: acute sinusitis and dyspepsia. Each panel used nominal group process and a modified Delphi method to create final algorithm drafts. To compare the clinical logic in the final algorithms, the authors applied a new qualitative and quantitative comparison method, the Clinical Algorithm Patient Abstraction (CAPA). Dyspepsia algorithms from all physician groups recommended empiric anti-acid therapy for most patients, favored endoscopy over barium swallow, and had very similar indications for endoscopy. The average CAPA comparison score among final physician algorithms was 6.1 on a scale of 0 (different) to 10 (identical). Sinusitis algorithms from all groups proposed empiric antibiotic therapy for most patients. Indications for sinus radiographs were similar between two algorithms (CAPA = 4.9), but differed significantly in the third, resulting in lower CAPA scores (average CAPA = 1.9, P < 0.03). The clinical similarity of the algorithms produced by these physician panels suggests a high level of reproducibility in this consensus-driven algorithm development process. However, the difference among the sinusitis algorithms suggests that physician consensus groups using a consensus process that a health maintenance organization can do with limited resources will produce some guidelines that vary due to differences in interpretation of evidence and physician experience.

Acute Disease↗

Algorithm-based clinical quality improvement. Clinical guidelines and continuous quality improvement.

Evidence documenting unexplained variation in clinical practices and outcomes has led to a proliferation of clinical practice guidelines in the hope that such efforts will lead to decreased variation, improved care, better outcomes, and lower costs. At Harvard Community Health Plan we have developed a clinical guideline development effort that focuses on the development of clinical algorithms and guidelines in a quality improvement model. The formal quality improvement process that we have described requires; (1) clear project definition and organization, (2) guideline development based on an understanding of patient needs, scientific evidence and clinical experience, (3) thorough analysis of potential problems with active implementation efforts, and (4) measurement and evaluation of results. By incorporating clinical guideline development into a quality improvement model and integrating such efforts with a total quality management strategy, we can substantially increase the likelihood of successfully implementing clinical practice guidelines and improving the quality of care that we deliver.

Algorithms↗