Stability of hospital quality indicators over time: A multi-year observational study of German hospital data.

BACKGROUND

Retrospective hospital quality indicators can only be useful if they are trustworthy signals of current or future quality. Despite extensive longitudinal quality indicator data and many hospital quality public reporting initiatives, research on quality indicator stability over time is scarce and skepticism about their usefulness widespread.

OBJECTIVE

Based on aggregated, widely available hospital-level quality indicators, this paper sought to determine whether quality indicators are stable over time. Implications for health policy were drawn and the limited methodological foundation for stability assessments of hospital-level quality indicators enhanced.

METHODS

Two longitudinal datasets (self-reported and routine data), including all hospitals in Germany and covering the period from 2004 to 2017, were analysed. A logistic regression using Generalized Estimating Equations, a time-dependent, graphic quintile representation of risk-adjusted rates and Spearman's rank correlation coefficient were used.

RESULTS

For a total of eight German quality indicators significant stability over time was demonstrated. The probability of remaining in the best quality cluster in the future across all hospitals reached from 46.9% (CI: 42.4-51.6%) for hip replacement reoperations to 80.4% (CI: 76.4-83.8%) for decubitus. Furthermore, graphical descriptive analysis showed that the difference in adverse event rates for the 20% top performing compared to the 20% worst performing hospitals in the two following years is on average between 30% for stroke and AMI and 79% for decubitus. Stability over time has been shown to vary strongly between indicators and treatment areas.

CONCLUSION

Quality indicators were found to have sufficient stability over time for public reporting. Potentially, increasing case volumes per hospital, centralisation of medical services and minimum-quantity regulations may lead to more stable and reliable quality of care indicators. Finally, more robust policy interventions such as outcome-based payment, should only be applied to outcome indicators with a higher level of stability over time. This should be subject to future research.

Informations de copyright

Copyright: © 2023 Kollmann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

Nils Kollmann has a fulltime position with Helios IT Service GmbH, internal service provider for the development and implementation of digitization projects for Helios Health as Europe’s leading private hospital operator, as Consultant for Hospital Information Systems (HIS). Among other, Prof. Dr. Reinhard Busse has received research funding from the German Healthcare Innovation Fund for the “PROMoting Quality” project. Among other, Dr. Christoph Pross has received research funding from the German Research Foundation for the project “Quality of Care Transparency”. Next to his parttime research position at TU Berlin, Dr. Christoph Pross has a fulltime position with Stryker, a global medical technology company, as Director for Market Access, Health Economics and Government Affairs.