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Reducing potentially avoidable complications in patients with chronic diseases: the Prometheus Payment approach.

ABSTRACT: UNLABELLED: OBJECTIVE (OR STUDY QUESTION): To determine whether a new payment model can reduce current incidence of potentially avoidable complications (PACs) in patients with a chronic illness. DATA SOURCES/STUDY SETTING: A claims database of 3.5 million commercially insured members under age 65. STUDY DESIGN: We analyzed the database using the Prometheus Payment model's analytical software for six chronic conditions to quantify total costs, proportion spent on PACs, and their variability across the United States. We conducted a literature review to determine the feasibility of reducing PACs. We estimated the financial impact on a prototypical practice if that practice received payments based on the Prometheus Payment model. PRINCIPAL FINDINGS: We find that (1) PACs consume an average of 28.6 percent of costs for the six chronic conditions studied and vary significantly; (2) reducing PACs to the second decile level would save U.S.$116.7 million in this population; (3) current literature suggests that practices in certain settings could decrease PACs; and (4) using the Prometheus model could create a large potential incentive for a prototypical practice to reduce PACs. CONCLUSIONS: By extrapolating these findings we conclude that costs might be reduced through payment reform efforts. A full extrapolation of these results, while speculative, suggests that total costs associated to the six chronic conditions studied could decrease by 3.8 percent.

SUBMITTER: De Brantes F

PROVIDER: S-EPMC3029843 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Reducing potentially avoidable complications in patients with chronic diseases: the Prometheus Payment approach.

De Brantes Francois F Rastogi Amita A Painter Michael M

Health services research 20101201 6 Pt 2

<h4>Unlabelled</h4>OBJECTIVE (OR STUDY QUESTION): To determine whether a new payment model can reduce current incidence of potentially avoidable complications (PACs) in patients with a chronic illness.<h4>Data sources/study setting</h4>A claims database of 3.5 million commercially insured members under age 65.<h4>Study design</h4>We analyzed the database using the Prometheus Payment model's analytical software for six chronic conditions to quantify total costs, proportion spent on PACs, and thei ...[more]

PMID: 20662949

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Project description:BACKGROUND:Identifying patients at high risk of hospital preventable readmission is an essential step towards selecting those who might benefit from specific transitional interventions. OBJECTIVE:Derive and validate a predictive risk score for potentially avoidable readmission (PAR) based on analysis of readmissions, with a focus on medication. DESIGN/SETTING/PARTICIPANTS:Retrospective analysis of all hospital admissions to internal medicine wards between 2011 and 2014. Comparison between patients readmitted within 30 days and non-readmitted patients, as identified using a specially designed algorithm. Univariate and multivariate regression analyses of demographic data, clinical diagnoses, laboratory results, and the medication data of patients admitted during the first period (2011-2013), to identify factors associated with PAR. Using these, derive a predictive score with a regression coefficient-based scoring method. Subsequently, validate this score with a second cohort of patients admitted in 2013-2014. Variables were identified at hospital discharge. RESULTS:The derivation cohort included 7,317 hospital stays. Multivariate logistic regressions found significant associations with PAR for: [adjusted OR (95% CI)] hospital length of stay > 4 days [1.3 (1.1-1.7)], admission in previous 6 months [2.3 (1.9-2.8)], heart failure [1.3 (1.0-1.7)], chronic ischemic heart disease [1.7 (1.2-2.3)], diabetes with organ damage [2.2 (1.3-3.8)], cancer [1.4 (1.0-1.9)], metastatic carcinoma [1.9 (1.3-3.0)], anemia [1.2 (1.0-1.5)], hypertension [1.3 (1.1-1.7)], arrhythmia [1.3 (1.0-1.6)], hyperkalemia [1.4 (1.0-1.7)], opioid drug prescription [1.3 (1.1-1.6)], and acute myocardial infarction [0.6 (0.4-0.9)]. The PAR-Risk Score, derived from these results, demonstrated fair discriminatory and calibration power (C-statistic = 0.699; Brier Score = 0.069). The results for the validation cohort's operating characteristics were similar (C-statistic = 0.687; Brier Score = 0.064). CONCLUSION:This study identified routinely-available factors that were significantly associated with PAR. A predictive score was derived and internally validated.

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Reducing potentially avoidable complications in patients with chronic diseases: the Prometheus Payment approach.

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Reducing potentially avoidable complications in patients with chronic diseases: the Prometheus Payment approach.

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