Richard F. Averill

The Relationship Between Severity of Illness and Hospital Length of Stay and Mortality

To address the question of quantification of severity of illness on a wide scale, the Computerized Severity Index (CSI) was developed by a research team at the Johns Hopkins University. This article describes an initial assessment of some aspects of the validity and reliability of the CSI on a sample of 2,378 patients within 27 high-volume DRGs from five teaching hospitals. The 27 DRGs predicted 27% of the variation in LOS, while DRGs adjusted for Admission CSI scores predicted 38% and DRGs adjusted for Maximum CSI scores throughout the hospital stay predicted 54% of this variation. Thus, the Maximum CSI score increased the predictability of DRGs by 100%. We explored the impact of including a 7-day cutoff criterion along with the Maximum CSI score similar to a criterion used in an alternative severity of illness measure. The DRG/Maximum CSI scores predictive power increased to 63% when the 7-day cutoff was added to the CSI definition. The Admission CSI score was used to predict in-hospital mortality and correlated R = 0.603 with mortality. The reliability of Admission and Maximum CSI data collection was high, with agreement of 95% and kappa statistics of 0.88 and 0.90, respectively.

Clinical Risk Groups (CRGs): A classification system for risk-adjusted capitation-based payment and health care management

ObjectiveTo 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 SourcesWe 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. ResultsWe 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. ConclusionCRGs 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.

AUTOGRP: an interactive computer system for the analysis of health care data.

AUTOGRP is an interactive computer system designed to facilitate rapid analysis of complex medical information. AUTOGRP allows the clinical or administrative expertise of the user to be combined with sophisticated computer techniques to permit rapid information retrieval, hypothesis testing, development of norms, and identification of deviant cases. This interaction yields results of a uniquely high statistical and medical quality. AUTOGRP has been used to aid in understanding the process of patient care management in a variety of settings in order to enhance the effectiveness of decision-making from both a medical and management point of view.

Achieving cost control, care coordination, and quality improvement through incremental payment system reform.

The healthcare reform goal of increasing eligibility and coverage cannot be realized without simultaneously achieving control over healthcare costs. The reform of existing payment systems can provide the financial incentive for providers to deliver care in a more coordinated and efficient manner with minimal changes to existing payer and provider infrastructure. Pay for performance, best practice pricing, price discounting, alignment of incentives, the medical home, payment by episodes, and provider performance reports are a set of payment reforms that can result in lower costs, better coordination of care, improved quality of care, and increased consumer involvement. These reforms can produce immediate Medicare annual savings of

A cost benefit analysis of continued stay certification.

10 billion and create the framework for future savings by establishing financial incentives for long-term provider behavior changes that can lead to lower costs.

Pay for performance: an excellent idea that simply needs implementation.

A large portion of the resources of the Professional Standards Review Organization Program have been directed toward the review of inpatients to determine their need for continued hospitalization. The primary goal of this review process is the containment of hospital costs through the elimination of unnecessary patient hospitalization. A cost benefit analysis of this review process shows that the potential financial savings accrued are unlikely to offset the costs associated with the review procedure.

Paying for Outcomes, Not Performance: Lessons from the Medicare Inpatient Prospective Payment System

Pay for performance cannot consist of a one-size-fits-all approach. Variation in quality and cost of care is best measured using a single “value” (quality/cost) score that is decomposed into component cost and quality for every health care encounter type. Economic incentives must be enough to focus the providers attention on each score part. Tools exist that improve the overall “value” of health care. We need agreement on an overall pay for performance approach together with a toolbox (not an approved list) of scientifically validated tools that payers, providers, and consumers can choose to build the incentives needed for pay for performance.

Reforming the primary care physician payment system: eliminating E & M codes and creating the financial incentives for an "advanced medical home".

Drawing on lessons learned from the implementation of the Medicare Inpatient Prospective Payment System (IPPS), the authors propose principles for the design and implementation of a hospital payment system based on paying for outcomes.

The clinical development of an ambulatory classification system: version 2.0 Ambulatory Patient Groups.

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.

Bundling Post-Acute Care Services into MS-DRG Payments

In 1995, the Health Care Financing Administration submitted a Report to congress recommending the Ambulatory Patient Groups (APGs), or an APG-like patient classification system, be used as the basis of a Medicare outpatient prospective payment system(PPS). Version 2.0 of APGs has been developed in anticipation of its potential use in a Medicare outpatient PPS.The development process and final structure of Version 2.0 of the APGs is described.