The Ambulatory Patient Groups (APGs) are a patient classification system that was designed to be used as the basis of an Outpatient Prospective Payment System (OPPS). Although 6 major non-Medicare payers had implemented an APG-based OPPS between 1995 and 2000, the implementation of the Ambulatory Payment Classification (APC)-based Medicare OPPS shifted the focus of outpatient payment reform among payers to APC-based systems. Unfortunately, the APC OPPS is not really a prospective payment system and has become essentially a variant of a fee-for-service system. As a result, most major non-Medicare payers have rejected APCs as a model for outpatient payment reform and a renewed interest in the original APG OPPS design has occurred. This article reviews the basic components of an OPPS, compares and contrasts an APG- and APC-based OPPS, describes the differences between APG, Version 2.0, and APG, Version 3.0, and summarizes the key policy decisions payers will need to make in implementing an OPPS.
The problem faced by primary care physicians is that they can only maintain or increase their (inflation adjusted) incomes by increasing the volume of visits and associated services. The fundamental flaw in a fee-for-service system is that only paying for individual services creates incentives for more services. This article offers a very different approach to paying primary care physicians that will result in both significantly higher incomes for these underpaid professionals together with incentives for creating a medical home.
In response to concerns over the equity of diagnosis-related group (DRG)-based prospective payment, the New Jersey Department of Health conducted a Severity of Illness evaluation study in which severity of illness, DRG, and uniform cost information were collected for 76,798 patients in 25 hospitals. Severity of illness was measured using the Computerized Severity Index (CSI) and was found to be a significant determinant of hospital cost in 76 DRGs that accounted for 41.4 percent of the total direct hospital patient care costs and 27 percent of the patients. The addition of CSI severity levels to the 76 DRGs reduced the coefficient of variation of cost in these DRGs by 17.4 percent and improved the overall reduction in variance of cost within the 76 DRGs by 38.2 percent. The change in total hospital payments due to the addition of severity for the 76 DRGs varied from a positive 5.71 percent to a negative 5.48 percent. These results demonstrate that a severity adjustment to this subset of DRGs would result in a more equitable DRG-based prospective payment system.
The article ‘Do pneumonia readmissions flagged as potentially preventable by the 3M PPR software have more process of care problems?’ by Borzecki et al concluded that ‘PPR categorization did not reflect expected differences in quality of care’.1 Unfortunately, the design of the study was based on a misinterpretation of the meaning of the potentially preventable readmissions (PPR) categorisation as well as its intended use.
Following discharge of a patient with pneumonia, there are three possible outcomes: the patient is readmitted for a condition that is categorised as a PPR, for a condition that is categorised as a non-PPR or the patient is not readmitted. A readmission is categorised as a PPR if there was a reasonable expectation that it could have …
To develop Clinical Risk Groups (CRGs), a claims-based classification system for risk adjustment that assigns each individual to a single mutually exclusive risk group based on historical clinical and demographic characteristics to predict future use of healthcare resources. STUDY DESIGN/DATA SOURCES: We developed CRGs through a highly iterative process of extensive clinical hypothesis generation followed by evaluation and verification with computerized claims-based databases containing inpatient and ambulatory information from 3 sources: a 5% sample of Medicare enrollees for years 1991-1994, a privately insured population enrolled during the same time period, and a Medicaid population with 2 years of data.We created a system of 269 hierarchically ranked, mutually exclusive base-risk groups (Base CRGs) based on the presence of chronic diseases and combinations of chronic diseases. We subdivided Base CRGs by levels of severity of illness to yield a total of 1075 groups. We evaluated the predictive performance of the full CRG model with R2 calculations and obtained values of 11.88 for a Medicare validation data set without adjusting predicted payments for persons who died in the prediction year, and 10.88 with a death adjustment. A concurrent analysis, using diagnostic information from the same year as expenditures, yielded an R2 of 42.75 for 1994.CRGs performance is comparable to other risk adjustment systems. CRGs have the potential to provide risk adjustment for capitated payment systems and management systems that support care pathways and case management.
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