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L K Schreier

Publications and source records attributed to L K Schreier.

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↗

The clinical algorithm nosology: a method for comparing algorithmic guidelines.

Concern regarding the cost and quality of medical care has led to a proliferation of competing clinical practice guidelines. No technique has been described for determining objectively the degree of similarity between alternative guidelines for the same clinical problem. The authors describe the development of the Clinical Algorithm Nosology (CAN), a new method to compare one form of guideline: the clinical algorithm. The CAN measures overall design complexity independent of algorithm content, qualitatively describes the clinical differences between two alternative algorithms, and then scores the degree of similarity between them. CAN algorithm design-complexity scores correlated highly with clinicians' estimates of complexity on an ordinal scale (r = 0.86). Five pairs of clinical algorithms addressing three topics (gallstone lithotripsy, thyroid nodule, and sinusitis) were selected for interrater reliability testing of the CAN clinical-similarity scoring system. Raters categorized the similarity of algorithm pathways in alternative algorithms as "identical," "similar," or "different." Interrater agreement was achieved on 85/109 scores (80%), weighted kappa statistic, k = 0.73. It is concluded that the CAN is a valid method for determining the structural complexity of clinical algorithms, and a reliable method for describing differences and scoring the similarity between algorithms for the same clinical problem. In the future, the CAN may serve to evaluate the reliability of algorithm development programs, and to support providers and purchasers in choosing among alternative clinical guidelines.

Algorithms↗