ABSTRACT
This article describes a risk-adjustment method for profiling hospitals and physicians on key measures of clinical quality using readily available administrative data. By comparing actual and expected rates of mortality, complications, readmissions, and patient safety events, this method enables providers to identify both favorable and adverse outcomes performance.
Subject(s)
Outcome Assessment, Health Care/methods , Patient Readmission/statistics & numerical data , Quality Indicators, Health Care/standards , Quality of Health Care/statistics & numerical data , Risk Adjustment/methods , Benchmarking/standards , Diagnosis-Related Groups , Hospital Mortality , Humans , Models, Statistical , Postoperative Complications/classification , Postoperative Complications/epidemiology , Predictive Value of Tests , Reproducibility of Results , Risk Assessment , Risk Factors , United States/epidemiologyABSTRACT
Projecting revenues and expenses The second of a two-part series, this article discusses the projected revenues and expenses of a hypothetical ambulatory surgery center and analyzes the potential impact of a hypothetical new payment method by the Centers for Medicare & Medicaid Services.
Subject(s)
Accounts Payable and Receivable , Gastroenterology/economics , Group Practice/economics , Income/statistics & numerical data , Ophthalmology/economics , Podiatry/economics , Surgicenters/economics , Ambulatory Surgical Procedures/economics , Ambulatory Surgical Procedures/statistics & numerical data , Feasibility Studies , Gastroenterology/organization & administration , Humans , Insurance, Health, Reimbursement/statistics & numerical data , Insurance, Physician Services , Ophthalmology/organization & administration , Podiatry/organization & administration , Surgicenters/statistics & numerical data , United States , Workload/economics , Workload/statistics & numerical dataABSTRACT
Group practices seeking to increase income may consider investing in freestanding ambulatory surgery centers (ASCs) as advances in technology enable more procedures to be performed in an outpatient setting. The authors describe the background of ASCs, with an emphasis on the payment systems used by Medicare and private payers.
Subject(s)
Group Practice/organization & administration , Hospital-Physician Joint Ventures , Surgicenters/economics , Group Practice/economics , United StatesABSTRACT
OBJECTIVE: To describe the development and validation of a predictive model designed to identify and target HMO members who are likely to incur high costs. STUDY DESIGN: Split-sample multivariate regression analysis. PATIENTS AND METHODS: We studied enrollees in a 350000-member HMO with > or = 1 claim in 1998 and 1999. The prediction model uses a combination of clinical and behavioral vaiables and 1998 and 1999 claims data. The prediction model was applied and used to rank low-cost patients (1998 cost < dollars 2000) according to their estimated probability of incurring costs > or = dollars 2000 in 1999. For prospective testing, we applied our models to data that are not available in advance. The same prediction model was applied to rank a different set of low-cost patients (1999 cost < dollars 2000) according to estimated probability of incurring costs > or = dollars 2000 in 2000. Because the predictions were used for disease management purposes, the outcomes of a randomly selected control group not intervened on for the disease management program was analyzed. The predictive accuracy of the model was tested by comparing the percentages of "targeted" vs all low-cost patients who incurred high costs in the subsequent year. RESULTS: Of the low-cost, top-ranked 1998 patients, 47.8% incurred high (> or = dollars 2000) medical expenses in 1999 vs 14.2% of randomly selected patients who were low cost in 1998. Of the top-ranked 1999 patients, 39.7% incurred high costs in 2000 vs 12.2% of the randomly selected low-ranked patients. CONCLUSIONS: The prediction model successfully identifies low-cost, high-risk patients who are likely to incur high costs in the next 12 months.