PubMed · 8433632
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V L Patel, G J Groen. Reanalysis: recalibration versus replication.. https://doi.org/10.1177/0272989x9301300102
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The aim of this paper is to discuss the use of stochastic league tables approach in cost-effectiveness analysis of diabetes interventions. It addresses the common grounds and differences with other methods of presenting uncertainty to decision-makers. This comparison uses the cost-effectiveness results of medical guidelines for Dutch diabetes type 2 patients in primary and secondary care. Stochastic league tables define the optimum expansion pathway as compared to baseline, starting with the least costly and most cost-effective intervention mix. Multi-intervention cost-effectiveness acceptability curves are used as a way to represent uncertainty information on the cost-effectiveness of single interventions as compared to a single alternative. The stochastic league table for diabetes interventions shows that in case of low budgets treatment of secondary care patients is the most likely optimum choice. Current care options of diabetes complications are shown to be inefficient compared to guidelines treatment. With more resources available one may implement all guidelines and improve efficiency. The stochastic league table approach and multi-intervention cost-effectiveness acceptability curves in uncertainty analysis lead to similar results. In addition, the stochastic league table approach provides policy makers with information on affordability by budget level. It fulfils more adequately the information requirements to choose between interventions, using the efficiency criterion.
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BACKGROUND: Medication regimen attributes, such as the number of drugs, dosage frequency, administration instructions, and the prescribed dosage forms, have been shown to influence patient outcomes. No single tool for quantifying the complexity of general medication regimens has been published in the medical literature. OBJECTIVE: To develop and validate a tool to quantify the complexity of prescribed medication regimens. METHODS: Literature findings and the expertise of the authors were used for developing the tool. Eight pharmacy researchers helped in establishing the tool's face and content validity. The new tool was tested on 134 medication regimens from patients with moderate to severe chronic obstructive pulmonary disease. Six regimens with a spread of scores on the tool were presented to a 5-member expert panel that subjectively ranked these regimens to confirm the tool's criterion-related validity. The relationships between scores on the tool and various independent variables were tested to judge the tool's construct validity. Two raters scored 25 regimens using the tool to test its inter-rater and test-retest reliabilities. RESULTS: A 65-item Medication Regimen Complexity Index (MRCI) was developed. The expert panel had strong agreement (Kendall's W = 0.8; p = 0.001) on their individual rankings of the 6 regimens. The panel's consensus ranking had perfect correlation with the MRCI ranking. The total MRCI score had significant correlation with the number of drugs in the regimen (Spearman's Rho = 0.9; p < 0.0001), but not with the age and gender of the patients. Inter-rater and test-retest reliabilities for the total score and scores for individual sections on the MRCI were > or = 0.9. CONCLUSIONS: The MRCI is a reliable and valid tool for quantifying drug regimen complexity with potential applications in both practice and research.