Studies of health system responsiveness mostly focus on the demand side by investigating the association between sociodemographic characteristics of patients and their reported level of responsiveness. However, little is known about the influence of supply‐side factors. This paper addresses that research gap by analysing the role of hospital‐specialty characteristics in explaining variations in patients' evaluation of responsiveness from a sample of about 38,700 in‐patients treated in public hospitals within the Italian Region of Emilia‐Romagna. The analysis is carried out by adopting a 2‐step procedure. First, we use patients' self‐reported data to derive 5 measures of responsiveness at the hospital‐specialty level. By estimating a generalised ordered probit model, we are able to correct for variations in individual reporting behaviour due to the health status of patients and their experience of being in pain. Second, we run cross‐sectional regressions to investigate the association between patients' responsiveness and potential supply‐side drivers, including waiting times, staff workload, the level of spending on non‐clinical facilities, the level of spending on staff education and training, and the proportion of staff expenditure between nursing and administrative staff. Results suggest that responsiveness is to some extent influenced by the supply‐side drivers considered

How do hospital‐specialty characteristics influence health system responsiveness? An empirical evaluation of in‐patient care in the Italian region of Emilia‐Romagna

Robone, Silvana
;
2018

Abstract

Studies of health system responsiveness mostly focus on the demand side by investigating the association between sociodemographic characteristics of patients and their reported level of responsiveness. However, little is known about the influence of supply‐side factors. This paper addresses that research gap by analysing the role of hospital‐specialty characteristics in explaining variations in patients' evaluation of responsiveness from a sample of about 38,700 in‐patients treated in public hospitals within the Italian Region of Emilia‐Romagna. The analysis is carried out by adopting a 2‐step procedure. First, we use patients' self‐reported data to derive 5 measures of responsiveness at the hospital‐specialty level. By estimating a generalised ordered probit model, we are able to correct for variations in individual reporting behaviour due to the health status of patients and their experience of being in pain. Second, we run cross‐sectional regressions to investigate the association between patients' responsiveness and potential supply‐side drivers, including waiting times, staff workload, the level of spending on non‐clinical facilities, the level of spending on staff education and training, and the proportion of staff expenditure between nursing and administrative staff. Results suggest that responsiveness is to some extent influenced by the supply‐side drivers considered
2018
2017
Fiorentini, Gianluca; Robone, Silvana; Verzulli, Rossella
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/3997476
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