RESUMO
Over the years, both government and the private sector have used a mix of regulatory controls and competitive market incentives to reduce the rate of spending and minimize excess capacity in health services. Despite these efforts, this study finds an oversupply of five medical technologies in Pennsylvania, which adds costs and raises concern over the quality of care provided by underused facilities. Moreover, as providers compete for network selection, many continue to expand their service capabilities. These findings emphasize the importance of ongoing assessment of the appropriate application, supply, and use of medical services.
Assuntos
Difusão de Inovações , Tecnologia de Alto Custo/estatística & dados numéricos , Cateterismo Cardíaco/economia , Cateterismo Cardíaco/estatística & dados numéricos , Coleta de Dados , Setor de Assistência à Saúde , Humanos , Unidades de Terapia Intensiva Neonatal/economia , Unidades de Terapia Intensiva Neonatal/estatística & dados numéricos , Litotripsia/economia , Litotripsia/estatística & dados numéricos , Imageamento por Ressonância Magnética/economia , Imageamento por Ressonância Magnética/estatística & dados numéricos , Ciência de Laboratório Médico , Transplante de Órgãos/economia , Transplante de Órgãos/estatística & dados numéricos , Pennsylvania/epidemiologia , Transferência de Tecnologia , Tecnologia de Alto Custo/economiaRESUMO
In response to continuing health care cost increases, many employers have expressed interest in a case-mix hospital payment system. They believe that such a system will more accurately reflect their utilization of health care resources and assist them in better controlling their costs. Therefore, using data generated by the Experimental Hospital Case Mix Payment Program of Blue Cross of Western Pennsylvania, this paper compares employer group costs based on an average cost per diagnostic case with costs based on an average cost per day. The analysis shows that by changing the basis of employer group costs from the traditional per diem method to one based on diagnostic case, while some groups may benefit in the form of lower costs, many groups would experience substantial increases to their costs. In a model explaining differences in employer group costs between the two payment methods, patient diagnosis was found to be the major explanatory factor, contributing to two thirds of the total explained variation. In addition, results indicated that a group's total admissions, mean patient age and gender, and a hospital's teaching status, location, bed size, occupancy rate, and mean ancillary costs influence the differences in a group's costs under the two methods.