Development and application of a composite score comprising multiple measures for organization performance measurement – an example of hospital ranking in treating DM pay-for-performance patients
Date Issued
2009
Date
2009
Author(s)
Chen, Tsung-Tai
Abstract
Background: With more and more P4P and public disclosure initiatives been established around the world, health care experts showed their interests in and debate on the facility rankings and composite score issues. Although some research had discussed about a composite score, there are still little empirical testing about exploring the hospital ranking differences using a P4P composite score and nationwide database. In brief, we still don’t clearly understand whether the choice of methodology will have larger impact on P4P hospital rankings based on composite score, especially when it consists of the risk-adjusted outcome measures. And the degree of uncertainty (reliability) and validity of every composite score method is also less compared in literature. For constructing composite score, the problems of small-volume facilities, and the issue of risk adjustment and accountability are needed also to work with the composite score. bjectives: We constructed and proved the characteristics of DM (Diabetes Mellitus) P4P latent score (including two IRT-based Models and PRIDIT Model) and non-latent score (including raw sum score, all-or-none score, QALYs saved score). According to the results, we summarized the important characteristics of latent and non-latent composite score (e.g. weighting mechanism), and made suggestions that how to supplement them to the structure aspect of P4P incentive design. ethods and Materials: Not only DM patients with age > 18 participating in P4P Add-On Program must had ICD 250 code, but also they had at least four numbers of visits in year 2007. Then, they were assigned to one specific physician through plurality lgorithm (accountability). DM P4P data were collected from the regular claim data of Bureau of National Health Insurance (NHI) for the period January 2005 to December 2007. DM patient outcome data, such as A1C values were retrieved from the Virtual Private Network (VPN) sponsored by NHI for the facilities or clinics self-reporting patients’ outcome. This research is a cross-sectional study. We first adjusted A1C level using GEE model then calculated composite scores using different algorithms. Then, comparison of different methods of P4P composite score were by three criteria, including agreement of hospital ranks, validity, and reliability. We also proposed sensitive results for avoiding the influence of small volume facilities on ranks. esults: For non-latent methods, we found that raw sum score were better than all-or-none score because of the higher validity, reliability, and higher correlation with latent score. Latent methods were superior to all of the non-latent methods because they are more excellent in validity and reliability than non-latent methods, and had specific weighting themes, as well as richer P4P policy implications. Among these latent scores, we found PRIDIT Model was superior to both IRT-based Models in validity, but opposite in reliability.onclusion: We integrated some necessary elements into our research of composite score such as risk adjustment, use of plurality algorithm (for assigning patients to one physician), and sensitivity analysis for making our study stricter. We also proposed according their own characteristics how the appropriate timing of implementing different latent scores is, and how to supplement to the structure of P4P incentive design.
Subjects
composite score
pay-for-performance
Diabetes Mellitus
hospital ranking
validity and reliability
SDGs
Type
thesis
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