The Consequences of Performance Measurement Systems in Multilevel Governance Health Systems: The Case of the Italian National Healthcare Service
- 1Department of Humanities and Social Sciences, University of Sassari, Sassari, Italy.
- 2Department of Economics and Business, University of Sassari, Sassari, Italy.
- 3Health Services Management Centre, School of Social Policy, University of Birmingham, Birmingham, UK.
Abstract
Background:: Performance measurement systems (PMSs) have become an essential component of health system reforms globally and are increasingly used to assess, reward and improve provider performance. While PMSs can be valuable tools for achieving desired health outcomes, their effectiveness depends on how they are designed, implemented, and used within complex multilevel governance structures. There is evidence that PMSs may also have unintended negative consequences. Drawing on new empirical evidence, the present study examines the consequences of PMSs implemented in multi-level governance systems through the analysis of the Italian National Healthcare Service (INHS), which exemplifies a decentralised health system with multiple levels of governance.
Methods:: The study employed a mixed methods approach combining quantitative and qualitative methods to examine the functional and dysfunctional consequences of PMSs in the INHS across three governance levels: (i) State-Regions, (ii) Regions-healthcare organisations, and (iii) Healthcare organisations-healthcare professionals.
Results:: We identified three key functional consequences. First, PMSs drive improvement by facilitating benchmarking, advocacy, and collaboration. Second, quantifying activities and services improves objectivity and transparency. Third, national PMSs provide a comprehensive view of performance across multiple dimensions and provide a more holistic understanding of how different aspects of the system interact. We confirmed previously reported dysfunctional consequences of PMSs found in other health systems and identified three new dysfunctional consequences in the INHS: Measurement Overload, Misconsideration, and Exploitation.
Conclusion:: Based on our analysis and existing literature, we propose ten key factors for strengthening performance measurement in the INHS. While this study offers novel evidence on the functional and dysfunctional consequences of PMSs in the Italian system, our research is context-specific, and the applicability of these factors to other multi-level health systems remains an area for future empirical testing.
Related
- Managing generative-AI health information resilience: human resource capabilities and multilevel public health governance
- Determinants of women's exposure to mass media and its influence on healthcare utilization in Somaliland: a multilevel analysis of SLDHS 2020 data.
- Usual preference for public healthcare services in India: a multilevel analysis
- Unpacking Ethical, Privacy, And Governance Risks in AI-IoT Based Healthcare Environments: A thematic analysis
- Balancing innovation and ethics: responsible governance of artificial intelligence hallucinations in healthcare.
BibTeX
@article{rotondo2026consequences,
title = {{The Consequences of Performance Measurement Systems in Multilevel Governance Health Systems: The Case of the Italian National Healthcare Service}},
author = {Federico Rotondo and Lucia Giovanelli and Nicoletta Fadda and Russell Mannion},
journal = {International Journal of Health Policy and Management},
year = {2026},
month = jun,
doi = {10.34172/ijhpm.9384},
url = {https://doi.org/10.34172/ijhpm.9384},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - The Consequences of Performance Measurement Systems in Multilevel Governance Health Systems: The Case of the Italian National Healthcare Service
AU - Federico Rotondo
AU - Lucia Giovanelli
AU - Nicoletta Fadda
AU - Russell Mannion
PY - 2026
DA - 2026/06/13
JO - International Journal of Health Policy and Management
DO - 10.34172/ijhpm.9384
UR - https://doi.org/10.34172/ijhpm.9384
AB - Background:: Performance measurement systems (PMSs) have become an essential component of health system reforms globally and are increasingly used to assess, reward and improve provider performance. While PMSs can be valuable tools for achieving desired health outcomes, their effectiveness depends on how they are designed, implemented, and used within complex multilevel governance structures. There is evidence that PMSs may also have unintended negative consequences. Drawing on new empirical evidence, the present study examines the consequences of PMSs implemented in multi-level governance systems through the analysis of the Italian National Healthcare Service (INHS), which exemplifies a decentralised health system with multiple levels of governance. Methods:: The study employed a mixed methods approach combining quantitative and qualitative methods to examine the functional and dysfunctional consequences of PMSs in the INHS across three governance levels: (i) State-Regions, (ii) Regions-healthcare organisations, and (iii) Healthcare organisations-healthcare professionals. Results:: We identified three key functional consequences. First, PMSs drive improvement by facilitating benchmarking, advocacy, and collaboration. Second, quantifying activities and services improves objectivity and transparency. Third, national PMSs provide a comprehensive view of performance across multiple dimensions and provide a more holistic understanding of how different aspects of the system interact. We confirmed previously reported dysfunctional consequences of PMSs found in other health systems and identified three new dysfunctional consequences in the INHS: Measurement Overload, Misconsideration, and Exploitation. Conclusion:: Based on our analysis and existing literature, we propose ten key factors for strengthening performance measurement in the INHS. While this study offers novel evidence on the functional and dysfunctional consequences of PMSs in the Italian system, our research is context-specific, and the applicability of these factors to other multi-level health systems remains an area for future empirical testing.
SN - 2322-5939
ER -