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1.
J Healthc Qual Res ; 39(3): 147-154, 2024.
Article En | MEDLINE | ID: mdl-38594161

BACKGROUND: Belgium initiated a hospital pay for performance (P4P) programme after a decade of fixed bonus budgets for "quality and safety contracts". This study examined the effect of P4P on hospital incentive payments, performance on quality measures, and the association between changes in quality performance and incentive payments over time. METHODS: The Belgian government provided information on fixed bonus budgets in 2013-2017 and hospital incentive payments as well as hospital performance on quality measures for the P4P programmes in 2018-2020. Descriptive analyses were conducted to map the financial repercussion between the two systems. A difference-in-difference analysis evaluated the association between quality indicator performance and received incentive payments over time. RESULTS: Data from 87 acute-care hospitals were analyzed. In the transition to a P4P programme, 29% of hospitals received lower incentive payments per bed. During the P4P years, quality performance scores increased yearly for 55% of hospitals and decreased yearly for 5% of hospitals. There was a significant larger drop in incentive payments for hospitals that scored above median with the start of the P4P programme. CONCLUSIONS: The transition from fixed bonus budgets for quality efforts to a new incentive payment in a P4P programme has led to more hospitals being financially impacted, although the effect is marginal given the small P4P budget. Quality indicators seem to improve over the years, but this does not correlate with an increase in reward per bed for all hospitals due to the closed nature of the budget.


Reimbursement, Incentive , Belgium , Humans , Quality Indicators, Health Care , Hospitals/standards , Economics, Hospital
2.
J Healthc Qual Res ; 39(2): 89-99, 2024.
Article En | MEDLINE | ID: mdl-38195377

INTRODUCTION: Today, primary care professionals' (PCPs) perspectives on hospital quality are unknown when evaluating hospital quality priorities. The aims of the present study were to identify key healthcare quality attributes from PCPs' perspective, to validate an instrument that measures PCPs' experiences of healthcare quality multidimensionally and to define hospital quality priorities based on PCPs' experiences. MATERIAL AND METHODS: Focus groups with PCPs were conducted to identify quality attributes through a qualitative in-depth analysis. A multicentre study of 18 hospitals was used to quantitatively assess construct, discriminant and criterion validity of the FlaQuM-Quickscan, an instrument that measures 'Healthcare quality for patients and kin' (part 1) and 'Healthcare quality for professionals' (part 2). To set quality priorities, scores on quality domains were analyzed descriptively and between-hospital variation was examined by evaluating differences in hospitals' mean scores on the quality domains using one-way Analysis of Variance (ANOVA). RESULTS: Identified key attributes largely corresponded with Lachman's multidimensional quality model. Including 'Communication' as a new quality domain was recommended. The FlaQuM-Quickscan was completed by 550 PCPs. Confirmatory factor analyses showed reasonable to good fit, except for the Root Mean Square Error of Approximation (RMSEA) in part 2. The 'Equity' domain scored the highest in parts 1 and 2. Domains 'Kin-centred care' and 'Accessibility and timeliness' scored the lowest in part 1 and 'Resilience' and 'Partnership and co-production' in part 2. Significant variation in hospitals' mean scores was observed for eleven domains in part 1 and sixteen domains in part 2. CONCLUSIONS: The results gained a better understanding of PCPs' perspective on quality. The FlaQuM-Quickscan is a valid instrument to measure PCPs' experiences of hospital quality. Identified priorities indicate that hospital management should focus on multifaceted quality strategies, including technical domains, person-and kin-centredness, core values and catalysts.


Hospitals , Quality of Health Care , Humans , Analysis of Variance , Focus Groups , Primary Health Care
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