Risk-adjusted capitation based on the Diagnostic Cost Group Model: an empirical evaluation with health survey information. (1/526)

OBJECTIVE: To evaluate the predictive accuracy of the Diagnostic Cost Group (DCG) model using health survey information. DATA SOURCES/STUDY SETTING: Longitudinal data collected for a sample of members of a Dutch sickness fund. In the Netherlands the sickness funds provide compulsory health insurance coverage for the 60 percent of the population in the lowest income brackets. STUDY DESIGN: A demographic model and DCG capitation models are estimated by means of ordinary least squares, with an individual's annual healthcare expenditures in 1994 as the dependent variable. For subgroups based on health survey information, costs predicted by the models are compared with actual costs. Using stepwise regression procedures a subset of relevant survey variables that could improve the predictive accuracy of the three-year DCG model was identified. Capitation models were extended with these variables. DATA COLLECTION/EXTRACTION METHODS: For the empirical analysis, panel data of sickness fund members were used that contained demographic information, annual healthcare expenditures, and diagnostic information from hospitalizations for each member. In 1993, a mailed health survey was conducted among a random sample of 15,000 persons in the panel data set, with a 70 percent response rate. PRINCIPAL FINDINGS: The predictive accuracy of the demographic model improves when it is extended with diagnostic information from prior hospitalizations (DCGs). A subset of survey variables further improves the predictive accuracy of the DCG capitation models. The predictable profits and losses based on survey information for the DCG models are smaller than for the demographic model. Most persons with predictable losses based on health survey information were not hospitalized in the preceding year. CONCLUSIONS: The use of diagnostic information from prior hospitalizations is a promising option for improving the demographic capitation payment formula. This study suggests that diagnostic information from outpatient utilization is complementary to DCGs in predicting future costs.  (+info)

Welfare gains from user charges for government health services. (2/526)

The World Bank's Financing health services in developing countries emphasizes demand-side issues--highlighting user fees, insurance, and the private sector as tools for strengthening the health sector. That approach is a major departure from the focus on the supply side--public sector spending, costs, management, and efficiency--that has dominated the international health finance agenda for many years. An important set of empirical papers by Paul Gertler and his co-authors coincided with the release of the policy paper. Gertler's work has questioned a policy of greater dependence on user fees by emphasizing the potential welfare costs to consumers of higher fees for medical services. Many health professionals have adopted the jargon of this new approach without understanding the underlying analysis. This article attempts to demystify the debate that has ensued by illustrating economists' idiosyncratic approach to welfare, explaining how the policy paper and Gertler differ, and suggesting alternative approaches to testing the feasibility of the policy paper's prescriptions.  (+info)

The influence of day of life in predicting the inpatient costs for providing care to very low birth weight infants. (3/526)

The purpose of this study was to test, refine, and extend a statistical model that adjusts neonatal intensive care costs for a very low birth weight infant's day of life and birth weight category. Subjects were 62 infants with birth weights below 1,501 g who were born and cared for in a university hospital until discharged home alive. Subjects were stratified into 250-g birth weight categories. Clinical and actual daily room and ancillary-resource costs for each day of care of each infant were tabulated. Data were analyzed by using a nonlinear regression procedure specifying two separate for modeling. The modeling was performed with data sets that both included and excluded room costs. The former set of data were used for generating a model applicable for comparing interhospital performances and the latter for comparing interphysician performances. The results confirm the existence of a strong statistical relationship between an infant's day of life and both total hospital costs and the isolated costs for ancillary-resource alone (P < 0.0001). A refined series of statistical models have been generated that are applicable to the assessment of either interhospital or interphysician costs associated with providing inpatient care to very low birth weight infants.  (+info)

Pharmacoeconomic analysis of selected antibiotics in lower respiratory tract infection. (4/526)

An interactive pharmacoeconomic model was designed to evaluate the effects of clinical response and adverse drug events on the comparative cost and cost-effectiveness of a relatively new antibiotic, clarithromycin, compared with those of six other antibiotics used to treat community-acquired lower respiratory tract infection. The cost and cost-effectiveness analyses were based don 12 randomized, double-blind, controlled clinical trials conducted between 1987 and 1992 in regionally distributed outpatient clinics in the United States. The trials enrolled a total of 2377 patients. Of the 2377, 1102 patients were treated for acute exacerbation of chronic bronchitis, 591 for pneumonia, and 201 for either of the two conditions. Safety data for one of the antibiotics was obtained from a trial of patients with sinusitis (N = 483). The antibiotics included in the analysis were amoxicillin/clavulanate, ampicillin, cefaclor, cefixime, cefuroxime, clarithromycin, and erythromycin. The main outcome measures were the costs of resources to achieve a clinical response, costs related to managing adverse drug events, and costs of antibiotic treatment from the perspective of managed care. The mean total cost per episode ranged from approximately $137 to $267. The drug acquisition cost typically contributed a small amount to the overall cost. For the cost-effectiveness analysis, in which complication-free cure was used as a proxy for patient satisfaction, the range of mean cost per complication-free cure varied from approximately $307 for clarithromycin to $612 for cefaclor. When ranked from most to least cost-effective, the order was as follows: clarithromycin, cefixime, amoxicillin/clavulanate, erythromycin, cefuroxime, ampicillin, and cefaclor. The costs associated with clinical management (including treatment failure) and managing adverse drug events significantly contribute to the total cost and cost-effectiveness of antibiotics in the outpatient setting. Cost-effectiveness analyses are valuable in analyzing the various costs associated with the treatment of lower respiratory tract infection (acute exacerbation of chronic bronchitis or pneumonia) and may be useful tools for physicians managing patients, members of pharmacy and therapeutics committees developing formularies, and medical staff implementing practice guidelines.  (+info)

Prevention of nonsteroidal anti-inflammatory drug-induced gastropathy: clinical and economic implications of a single-tablet formulation of diclofenac/misoprostol. (5/526)

Nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly used to manage arthritis. While controlling symptoms and improving quality of life, NSAID use is associated with gastroduodenal injury and a 2%-4% annual risk for symptomatic gastroduodenal ulceration, hemorrhage, and perforation. This requires clinicians to balance the efficacy of NSAIDs against the potential risk of serious gastrointestinal events. Identification and stratification of risk can help guide the optimal approach for arthritis management of individual patients or large populations such as managed care organizations. NSAID-induced gastroenteropathy carries considerable economic consequences; 46% of arthritis costs are related to managing serious adverse events. It is reasonable to assume that these costs may not be incurred if high-risk patients are recognized and optimally managed. Newer therapies with proven safety margins present an attractive option, especially for patients at higher risk. The single-tablet formulations of diclofenac and misoprostol (Arthrotec) offer an alternative in managing NSAID patients because of their inherent safety profile. Studies with diclofenac/misoprostol indicate its effectiveness in treating signs and symptoms of arthritis and in reducing the incidence of NSAID-induced gastroenteropathy. As such, this agent may provide improved medical and economic outcomes. This review discusses the clinical aspects of NSAID-induced gastroenteropathy, including available preventive therapies. Approaches to assessing patients' risk for developing complications, and the relationship of medical risk and economic outcomes, are also examined. Although not all patients require preventive therapy, patients with heightened risk may benefit clinically and economically from gastroprotective NSAIDs. Additional research or modeling may provide further insight into the economic implications of managing and preventing NSAID-induced gastroenteropathy.  (+info)

The cost-effectiveness of treatment with lamivudine and zidovudine compared with zidovudine alone: a comparison of Markov model and trial data estimates. (6/526)

In this paper, we present a Markov model for estimating the cost-effectiveness of combination therapy with lamivudine (LMV) and zidovudine (ZDV) compared with ZDV alone. We also compare the predictions of the Markov model for the impact of combination therapy on trial period costs with the actual impact of combination therapy on selected trial period costs estimated from data collected during the clinical trials. In the Markov model, disease stages were defined by CD4 cell count. Based on clinical trial data for patients with CD4 counts higher than 100 cells/mm3, the model assumed that the CD4 cell count level could be maintained above the level at the initiation of therapy for 6.5 months with monotherapy and for 18 months with combination therapy. After this period, transition rates for natural disease progression were used. Incremental lifetime costs and quality-adjusted life years gained with LMV/ZDV compared with ZDV alone were estimated for cohorts of patients initiating antiretroviral therapy at four different CD4 cell count stages. Cost per life year gained varied from $10,000 to $18,000, and cost per quality-adjusted life year gained varied from $14,000 to $27,000. In both cases, the combination therapy was more cost-effective when started earlier in disease progression. These estimates were not sensitive to changes in key parameter values. In addition, the model was used to estimate the impact of combination therapy on healthcare costs during the trial period; these estimated costs were compared with data on the cost of resource use collected during the clinical trial for hospital stays, unscheduled visits, medications, and outpatient procedures. Both the Markov model estimates and the trial data estimates for the trial period showed cost savings in other medical costs, though these were not large enough to completely offset the increased cost for antiretroviral therapy. The model estimates were more conservative than the estimates based on the trial data.  (+info)

Researching the public/private mix in health care in a Thai urban area: methodological approaches. (7/526)

The private health sector has been growing rapidly in many low and middle income countries, yet not enough is known about its sources of finance or characteristics of its users. Moreover, health care reform measures are leading to alterations in the mix of public and private finance and provision, increasing further the need for information. This paper presents and evaluates some research methods which can be used to collect information relevant to considering policies on the public/private mix. They comprise a household survey, a health diary and interview survey, a bed census, and a health resource survey. Each method is described as it was used in a study in a large urban setting in Thailand, and strengths and weaknesses of the methods are identified. The use of data to estimate the shares of public and private finance and provision, and particularly private sources of finance of public hospitals and public sources of finance for private hospitals, is demonstrated. Policy issues highlighted by the data are identified.  (+info)

The effects of group size and group economic factors on collaboration: a study of the financial performance of rural hospitals in consortia. (8/526)

STUDY QUESTIONS: To determine factors that distinguish effective rural hospital consortia from ineffective ones in terms of their ability to improve members' financial performance. Two questions in particular were addressed: (1) Do large consortia have a greater collective impact on their members? (2) Does a consortium's economic environment determine the degree of collective impact on members? DATA SOURCES AND STUDY SETTING: Based on the hospital survey conducted during February 1992 by the Robert Wood Johnson Hospital-Based Rural Health Care project of rural hospital consortia. The survey data were augmented with data from Medicare Cost Reports (1985-1991), AHA Annual Surveys (1985-1991), and other secondary data. STUDY DESIGN: Dependent variables were total operating profit, cost per adjusted admission, and revenue per adjusted admission. Control variables included degree of group formalization, degree of inequality of resources among members (group asymmetry), affiliation with other consortium group(s), individual economic environment, common hospital characteristics (bed size, ownership type, system affiliation, case mix, etc.), year (1985-1991), and census region dummies. PRINCIPAL FINDINGS: All dependent variables have a curvilinear association with group size. The optimum group size is somewhere in the neighborhood of 45. This reveals the benefits of collective action (i.e., scale economies and/or synergy effects) and the issue of complexity as group size increases. Across analyses, no strong evidence exists of group economic environment impacts, and the environmental influences come mainly from the local economy rather than from the group economy. CONCLUSION: There may be some success stories of collaboration among hospitals in consortia, and consortium effects vary across different collaborations. RELEVANCE/IMPACT: When studying consortia, it makes sense to develop a typology of groups based on some performance indicators. The results of this study imply that government, rural communities, and consortium staff and steering committees should forge the consortium concept by expanding membership in order to gain greater financial benefits for individual hospitals.  (+info)

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