[Developing quality indicators in hospitals: the COMPAQH project]. / Développement d'indicateurs de qualité au sein des établissements de santé: le projet COMPAQH.

BACKGROUND: To select a set of quality indicators (QI) in order to test them in a panel of 36 French hospitals METHODS: The COMPAQH (COordination for Measuring Performance and Assuring Quality in Hospitals) project is coordinated by the French National Institute for Medical Research and supported by the French Ministry of Health and the French National Evaluation and Accreditation Agency. This project has four objectives: (1) to select a set of QI -2003- (2) to implement them in 2004-2005 in a volunteer panel of hospitals (3) to compare the hospitals anonymously (4) to explore quality management implications. QI were selected with a four-step process: (1) Establishment of a list of national priorities for Quality Improvement in relation with the Ministry of Health. (2) setting up a potential list of QI regarding these priorities. The COMPAQH staff determined a preliminary set of 81 QI, based on data in the literature and evidence about the scientific soundness of quality measures and the effectiveness of methods for improving quality. (3) Evaluation of the preliminary list. Each QI was presented in a pamphlet describing its operational definition, rationale, methodology, workload and responsibility of data collection The hospital panel (representatives) ranked the 81 QI with a validated evaluation tool which contained four dimensions: Importance, Scientific acceptability, Feasibility, and Usability. (4) Development of a consensus on a final selection. Based on a structured voting process (Delphi method, two rounds), the hospital panel selected a comprehensive set of 42 QI among the 81. RESULTS: (1) Eight national priorities were defined: pain management, continuity of care, management of nutritional disorders, Iatrogenic risks (including nosocomial infections), patient satisfaction, follow-up of practice guidelines, management of human resources, accessibility. (2) A set of 42 QI were selected: a set of 6 core QI and 7 to 18 specific QI according to the hospital type. CONCLUSION: Such a set of QI provides a foundation for developing a quality measurement system in French hospitals. It requires a pragmatic view for implementing them and a coherence between the different objectives of use (internal and external use).

Economic evaluation of drug resistance genotyping for the adaptation of treatment in HIV-infected patients in the VIRADAPT study.

BACKGROUND: Costs of antiretroviral therapy for HIV-infected patients have increased at a time when most countries are attempting to contain health care costs. Part of this increase results from HIV drug resistance associated with virologic failure and a subsequent shift to more complex and costly therapies. Genotypic guided treatment is associated with better virologic outcome. However, it is not yet known whether it will be cost effective. METHODS: We present here an economic evaluation based on the results from the VIRADAPT study, a prospective, open-label, randomized trial comparing patients assigned to standard of care (n = 43), versus genotypic guided treatment (n = 64) for 6 months. Total follow-up for the extended trial was 1 year. Costs were computed from the viewpoint of the health care system. Hospitalization data were retrieved from the VIRADAPT study case report forms, costs were estimated from the cost of the corresponding diagnosis-related groups derived from the French national cost data base: these were actual costs and not charges. Data on the volume of tests prescribed, drugs, and clinic visits were retrieved from the VIRADAPT study database. The unit costs of tests and clinic visits were determined using the French national Social Security reimbursement price; costing of drugs used were based upon purchase price by either retail pharmacies or hospitals. Genotyping using TruGene HIV-1 assay was estimated at $500 per test from manufacturer's data (all figures in this paper are expressed in U.S. dollars). RESULTS: Total mean (standard deviation) yearly costs per patients were $20,412 (+/-$10, 129) in the standard of care group and $18,484 (+/-$9,652) in the genotyping group (p =.35). Drug costs represented 55% of total costs. There was a trend toward a decrease in drug costs in the genotyping arm (p =.07), the greatest reduction being in the decreased use of protease inhibitors in the genotyping arm. The additional expense of genotyping appeared to be offset by the savings obtained in drug costs. CONCLUSION: In our study, the cost of drug resistance testing is offset by a reduced use of protease inhibitors and their attendant costs. Although not reaching statistical significance, this trend in the reduction of drug costs and drug use presents a great interest for future trials.