The risk of lumbar puncture in pediatric patients with cardiac and-or pulmonary disease.
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Biomedical subjects
Publications and source records attributed to C Z Margolis.
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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.
This study aimed to test the usefulness and reliability of text-to-algorithm conversion in comparing competing clinical guidelines and defining their differences. Two pairs of competing guidelines for measles immunization, published in 1989 and 1994, were analyzed and compared. Five categories of differences were detected: differences in recommendations, excluded elements, logical inconsistencies, nonspecific phrases, and approaches to contraindications. On a scale of 0-10 (where identical=10), the overall comparison scores were 6.01 for the guidelines published in 1989 and 5.54 for the guidelines published in 1994. Text-to-algorithm conversions performed by three different persons on the 1989 guidelines were compared and found similar. Text-to-algorithm conversion is an important step in facilitating comparison of competing guidelines. It has the potential to assist in making rational and systematic choices between competing guidelines before actual field testing takes place. Physicians can use it to analyze and to learn a prose clinical guideline, to critique existing guidelines, and to simulate hypothetical patients for teaching and evaluating clinical management.
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An off-line system for automating the problem-oriented record implemented at Kibbutz Shuval is described. The Shuval problem-oriented record consists of acute and chronic problem lists, a preprinted data base collected by patients and nurses, problem-oriented plan flow sheets, problem-oriented progress notes and a regular record audit. The mean conversion time from a traditional record to a problem-oriented record was 17 min for a child's record and 25 min for an adult's. The automated problem-oriented record consists of three data processing forms that contain almost all data in the record. Transfer of data took, on the average, 10 min (range, 5 to 30 min) for a child's record. The following five types of analysis can be performed with the Shuval automated problem-oriented record: administrative, patient care, epidemiologic, demographic and clinical research. Coupled with the manual problem-oriented record, the Shuval automated record provides many advantages of an on-line problem-oriented record at considerably less cost.