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Biomedical subjects

M L Ashcraft

Publications and source records attributed to M L Ashcraft.

13 recordsLinked to original sources
PubMed1993

A comprehensive payment model for short- and long-stay psychiatric patients.

In this article, a payment model is developed for a hospital system with both acute- and chronic-stay psychiatric patients. "Transition pricing" provides a balance between the incentives of an episode-based system and the necessity of per diem long-term payments. Payment is dependent on two new psychiatric resident classification systems for short- and long-term stays. Data on per diem cost of inpatient care, by day of stay, was computed from a sample of 2,968 patients from 100 psychiatric units in 51 Department of Veterans Affairs (VA) Medical Centers. Using a 9-month cohort of all VA psychiatric discharges nationwide (79,337 with non-chronic stays), profits and losses were simulated.

Acute Disease↗
PubMed1991

Measuring severity of illness: six severity systems and their ability to explain cost variations.

This paper presents results from a study that used a common set of patient records to compared how well different severity measurement systems are able to explain the variations in estimated costs among hospital patients. The systems examined were: APACHE II, MedisGroups, Computerized Severity Index (CSI), Disease Staging, Patient Management Categories (PMCs), and Acuity Index Method. In regressions on costs, all of the measures were found to improve upon DRGs for some types of cases but to offer little or no improvement for others. Indicators of maximum severity, especially Max CSI, explained greater proportions of cost variation than measures of admission severity and measures based on discharge abstracts. In most of the analyses, PMCs and Disease Staging yielded somewhat higher R2 values than the measures of admission severity.

Abstracting and Indexing↗
PubMed1990

A classification system for long-staying psychiatric patients.

Data on a sample of 890 Veteran's Administration long-staying psychiatric patients were studied to develop a classification system that explains actual daily resource use. Disturbed patients with lengths of stay of less than three years and those with psychotic conditions who are not withdrawn represent the two groups found to use significantly more resources in their daily care. The Long-Stay Psychiatric Patient Classification (LPPC) System, with six categories, explains 11.4% of the variability in per diem resource use and can be used for case-mix adjustment of payments for psychiatric care.

Data Interpretation, Statistical↗
PubMed1989

A psychiatric patient classification system. An alternative to diagnosis-related groups.

It is generally accepted that diagnosis-related groups (DRGs) for alcohol, drug, and mental disorders are inappropriate for inpatient prospective payment. To address this issue, the Veterans Administration (VA) supported a project to construct alternative classes that are more clinically meaningful, more homogeneous in their resource use, and that account for more variation in resource use among psychiatric and substance use cases than existing DRGs. This paper reports on this project. Using a data set containing universally available discharge data plus behavioral, social, and functional information obtained by a survey of 116,191 discharges from VA psychiatric beds, and with AUTOGRP as the classifying algorithm, a classification system was formed. Twelve psychiatric diagnostic groupings (PDGs) were identified, analogous to major diagnostic groups in the DRG system. Within each PDG, from 4 to 9 terminal groups of Psychiatric Patient Classes (PPCs) were formed and validated. The 12 substance abuse PPCs explain greater than 31% of the variation in length of stay; for the mental disorder PPCs the variance explanation is greater than 11%, a substantial improvement over DRGs that, for the same data set, explain less than 2 and 3%, respectively. With the addition of only 5 variables beyond those presently included in discharge data sets, greater precision for payment purposes can be achieved. Implications for adoption of this classification system are discussed.

Algorithms↗
PubMed1989

Measuring severity of illness: a comparison of interrater reliability among severity methodologies.

Methods for measuring illness severity are receiving increasing attention from payers, purchasers, and others interested in the equity and financial incentives of prospective payment systems, as well as from those concerned with the use of mortality rates and other outcomes to measure quality of care. Several methodologies have been proposed for measuring the severity of illness of patients admitted to hospitals. When choosing among the available measures, one characteristic of interest is reliability. In this paper, we present a comparative evaluation of interrater reliability among four severity measures--APACHE II, MedisGroups, Patient Management Categories (PMCs), and Disease Staging Q-Scale--as well as for the Diagnosis Related Groups (DRG) classification system. The results show APACHE II, MedisGroups, and DRGs to be highly reliable, with Inter-Rater Reliability Coefficient (RI) values greater than .8. PMCs and Disease Staging Q-Scale were able to achieve fair-to-good levels of reliability. Results are consistent regardless of which reliability statistics are used.

Evaluation Studies as Topic↗
PubMed1985

DRGs and psychiatry: work in progress.

A study is presented in which a number of variables describing psychiatric patients hospitalized within Veterans Administration Medical Centers are being investigated as potentially more predictive discriminators of resource consumption than the currently formulated diagnostic-related groups.

Diagnosis-Related Groups↗
PubMed1984

Length-of-stay variations within ICDA-8 diagnosis-related groups.

The number of bed days per inpatient episode, the length of stay (LOS), is a major indicator of hospital performance and a basic measure of patients' resource consumption. Hospital reimbursement on the basis of treated cases requires a system for accurately identifying case categories. Diagnosis Related Groups (DRGs) have been proposed for this purpose. An initial study to analyze variations in length of stay and resource consumption within DRGs is presented. Regression analysis of variation in ALOS for 7 DRGs, in terms of 8-10 independent variables not included in the classification scheme itself, was done. Results indicate that 30-65% of the large intra-DRG LOS variations are explainable by indicators of case complexity and severity despite the homogeneity claimed for the DRGs. For certain DRGs, such variations are also related to admission factors. Results indicate the need for more precise patient taxonomies than the ICDA-8-based DRGs.

Ancillary Services, Hospital↗
PubMed1983

Classification of hospitals based on measured output: the VA system.

Evaluation of hospital performance and improvement of resource allocation in hospital systems require a method for classifying hospitals on the basis of their output. Previous approaches to hospital classification relied largely on input characteristics. The authors propose and apply a procedure for classifying hospitals into groups where within-group hospitals are similar with respect to output. Direct measures of case-mix-adjusted discharges and outpatient visits are the principal measures of patient care output; other measures capture training and research functions. The component measures were weighted, and a composite output measure was calculated for each of the 162 hospitals in the Veterans Administration health care system. The output score then was used as the dependent variable in an Automatic Interaction Detector analysis, which partitioned the 162 hospitals into 10 groups, accounting for 85 per cent of the variance in the dependent variable. An extension of the output classification method is presented for illustration of how the difference between hospitals' actual operating costs and costs predicted on the basis of output can be used in defining isoefficiency groups.

Budgets↗
PubMed1983

Health maintenance organizations as Medicaid providers.

Evolution of a one-door, one-class system of medicine for all Americans was the professed goal of the social legislation of the 1960s. The development of health maintenance organizations (HMOs) was seen to be a major mechanism for assuring access to care and at the same time reducing the costs of social health programs. This has currently been reinforced by procompetitive proposals, which predict great efficiency resulting from the envisaged competition among organized systems of care. This article argues that established HMOs have no incentives to enroll Medicaid beneficiaries and that under current arrangements. Medicaid beneficiaries have no incentives to enroll in HMOs. As Medicaid programs across the states are cut, resulting in fewer benefits and more restricted physician payments, beneficiaries may have greater incentives to enroll in organized systems. Private physicians may also face greater incentives to develop HMOs to serve Medicaid beneficiaries. If that happens, however, a two-class system--one for the poor and one for others--will be institutionalized; and to assure minimum standards of care for the poor, more, not less, regulation will be required.

Health Maintenance Organizations↗
PubMed1980

HMO enrollment: who joins what and why: a review of the literature.

Enrollment in an HMO involves a simultaneous choice of insurance benefits and a provider system. Review of an extensive series of studies shows that breadth of coverage, lower cost, and assured access to benefits are key elements anticipated in the choice. But so too are the perceived limitations inherent in selection of a physician within a close-panel plan, and the inconvenience of centralized sites. For the design and evaluation of future policy, current knowledge based on past enrollment behavior offers only tentative suggestions.

Catchment Area, Health↗
PubMed1979

On the analysis of ambulatory utilization: an investigation of the roles of need, access and price as predictors of illness and preventive visits.

After separating ambulatory visits into those made in connection with illness or injury and preventive visits, the utilization patterns of a sample of families and individuals are analyzed. Need, in terms of perceived health status and the numbers of acute and chronic conditions, price, and access are found to be the best predictors of visit rates, but their roles in illness and preventive visit rates are different. The methodologically relevant findings indicate that individual self-reports and independent individual observations are required to identify relationships hidden by family member data, such as that between hospital episodes and ambulatory visits. The substantive findings indicate a substitutive relationship between illness and preventive visits, lend further evidence for relatively low price elasticity for illness visits and show that membership in a closed panel health maintenance organization increases preventive visit rate while price has little or no effect on it. The tentative policy implication--that it is not so much price as the characteristics of the usual source of care which appear to determine preventive services utilization--is discussed in the context of potential biases inherent in the sample.

Ambulatory Care↗
PubMed1978

Enrollment choices in different types of HMOs: a multivariate analysis.

Enrollment decisions of a sample of an employed population choosing among open-panel and closed-panel HMOs and Blue Cross/Blue Shield are analyzed. This report, unlike previous ones, overcomes some of the difficulties of bivariate analysis by the use of the multivariate logistic probability model, logit. The results show that there are four consistent predictors of enrollment choice: previous source of care as the measure of access; family life stage and chronic conditions per family member as indicators of health risk; per capita income as the measure of economic vulnerability; and health concern. Having a private physician as the source of care is the best single predictor, its absence predicting a higher probability of enrollment in the closed, and its presence in the open-panel HMO. Higher risk life stage families, younger and with more children, are more likely to join the open-panel plan than the closed or retain BC/BS; higher incomes and larger numbers of chronic conditions appear to have the same effects. Higher levels of health concern, on the other hand, predict a greater probability of choosing the closed-panel plan. The probability of enrollment in any HMO is predicted with more than 50 per cent accuracy for 60 per cent of the sample. Choice between open and closed-panel plans is predicted with an accuracy in excess of 50 per cent for 80 per cent, and with an accuracy greater than 90 per cent for over 10 per cent of potential enrollees. The applicability of this approach to HMO feasibility analysis and planning is clearly indicated.

Analysis of Variance↗