The dynamic use of a balanced scorecard in an Italian public hospital.

PURPOSE: This paper aims to analyse the dynamic use of the balanced scorecard (BSC) in an Italian public hospital. DESIGN/METHODOLOGY/APPROACH: A longitudinal case study was conducted at an Italian public teaching hospital over a period of 5 years. The emergence of dynamic use of BSC was traced over a different combination of social, political, economic and organizational realities. A deeper understanding of these realities requires the adoption of a holistic approach to BSC use. Henri's types of system use (i.e., monitoring, attention focussing, strategic decision-making and legitimizing) frame this approach in a more concrete manner. FINDINGS: This study adds to the debate on whether BSC is used for aspects other than monitoring in public contexts. The case study offers the first example of a legitimizing use of the system and a first longitudinal case study that traces a dynamic use of BSC: the use evolves from monitoring and attention focussing to monitoring and legitimization. Norms, political parties and top managers play a determining role in this process. ORIGINALITY/VALUE: Through a longitudinal approach, this study presents how BSC can be a dynamic tool steered by legitimacy pressures. The longitudinal study explores how social, political, economic and organizational context shape the implementation and the revision of BSC affecting the use of the tool by top managers. The browse of this dynamism is supported by Henri's type of use along with an in-depth analysis of the BSC literature evolution in terms of its 'static, dynamic and expected' use.

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region.

BACKGROUND: The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. METHODS: A nonparametric approach-that is, multistage data envelopment analysis (DEA)-was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. RESULTS: On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). CONCLUSIONS: The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels.