Healthcare organization mergers and quality of care: Evidence from the Italian National Health Service
Andrea Mariani et al.
What the paper says
PurposeThe increasing frequency and relevance of mergers have significantly impacted the healthcare industry in recent decades. A recurring topic in the ensuing debate is whether and how hospitals achieve quality-of-care benefits post-merger. Italy offers a useful case study: with Italian hospital facilities adopting the National Outcomes Program (NOP) to measure quality of care, this research compares quality-of-care indicators reported by merged and non-merged public hospitals.Design/methodology/approachThe paper analyzes the impact of mergers on the quality of care among all Italian public hospitals (N = 466) during 2012-2019. Hospitals involved in mergers (N = 155) were compared to the control group through t-tests and a panel regression analysis of 13 indicators. To better isolate the Average Treatment Effect (ATE) of mergers on NOP indicators, the study develops a Difference-in-Differences model with a multiple-period estimator.FindingsResults generally show that hospitals improved their quality-of-care performance from pre- to post-merger. However, a more detailed comparison reveals a slight worsening of clinical outcomes and a significant deterioration in treatment processes in the post-merger period.Originality/valueThis study enriches the debate on HCO mergers by illustrating their complex impact on quality of care at the hospital facility level. Accordingly, both HCO managers and policymakers must carefully plan and monitor mergers to avoid disruption and ensure continuity in care. Limitations include a single-country focus and the use of 13 indicators selected from the broader set of over 190 quality-of-care measures published annually by the NOP.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.