1,720,999 research outputs found
“Can we use vignettes to address response-scale heterogeneity in the EQ-5D? Not if but how”
Full text linkKnott et al. (2016) focus on the issue of differential item functioning (DIF) in the EQ-5D. To address this issue, they recommend employing anchoring vignettes as ‘perhaps the most viable method worth pursuing in the immediate future, in terms of both time and cost...particularly if adjustments can be formulated using vignette responses from external samples’. I believe the Knott et al. idea of using vignettes for addressing DIF in the EQ-5D is very good. Therefore, in this commentary I do not question whether it is sensible to try using vignettes but instead I focus on how to do it. Indeed, I am somewhat sceptical about some of the conclusions put forward by the authors. Moreover, in the light of recent iterature, I will provide some methodological advice on how to implement anchoring vignettes at the survey stage
Are bad health and pain making us grumpy? An empirical evaluation of reporting heterogeneity in rating health system responsiveness
Full text linkThis paper considers the influence of patients’ characteristics on their evaluation of a health system’s responsiveness, that is, a system’s ability to respond to the legitimate expectations of potential users regarding non-health enhancing aspects of care (Valentine et al. 2003a). Since responsiveness is evaluated by patients on a categorical scale, their selfevaluation can be affected by the phenomenon of reporting heterogeneity (Rice et al. 2012).
A few studies have investigated how standard socio-demographic characteristics influence the reporting style of health care users with regard to the question of the health system’s responsiveness (Sirven et al. 2012, Rice et al. 2012). However, we are not aware of any studies that focus explicitly on the influence that both the patients’ state of health and their experiencing of pain have on the way in which they report on system responsiveness. This
paper tries to bridge this gap by using data regarding a sample of patients hospitalized in four Local Health Authorities (LHA) in Italy’s Emilia-Romagna region between 2010 and 2012.
These patients have evaluated 27 different aspects of the quality of care, concerning five domains of responsiveness (communication, social support, privacy, dignity and quality of facilities). Data have been stratified into five sub-samples, according to these domains. We estimate a generalized ordered probit model (Terza, 1985), an extension of the standard ordered probit model which permits the reporting behaviour of respondents to be modelled as a function of certain respondents’ characteristics, which in our analysis are represented by the variables “state of health” and “pain”. Our results suggest that unhealthier patients are more likely to report a lower level of responsiveness, all other things being equal, while patients experiencing pain are more likely to make use of the extreme categories of responsiveness,
that is, to choose the category “completely dissatisfied” or the category “completely satisfied”. These results hold across all five domains of responsiveness
How does fiscal decentralization affect within-regional disparities in well-being? Evidence from health inequalities in Italy
Full text linkHow do hospital-specialty characteristics influence health system responsiveness? An empirical evaluation of in-patient care in the Italian Region of Emilia-Romagna
Full text linkSeveral studies of health system responsiveness focus on the demand-side by investigating the association between socio-demographic 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 two-step procedure. First, we use patients’ self-reported data to derive five 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. Secondly, we run cross-sectional regressions in order 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
Struttura di mercato e tecnologia: un’analisi empirica del Servizio sanitario nazionale italiano
No full textL’accelerazione dello sviluppo tecnologico e la tendenza verso il decentramento dell’intervento pubblico, caratteristiche dei mercati sanitari negli ultimi decenni, hanno contribuito ad accrescere l’autonomia decisionale dei soggetti che operano in questi mercati, rendendone il funzionamento simile a quello dei settori industriali tradizionali. Un riferimento standard dell’economia industriale sulla relazione tra la tecnologia e la struttura di mercato è offerto dal contributo di Sutton (1991, 1998), secondo il quale i settori industriali assumono configurazioni differenti in termini di concentrazione di mercato a seconda della diversa incidenza delle spese di R&S e di pubblicità e dell’omogeneità dei prodotti in essi offerti. L’obiettivo di questo lavoro
è testare empiricamente alcune delle relazioni evidenziate da Sutton nell’ambito di uno specifico contesto economico, quello delle prestazioni sanitarie offerte dal Servizio sanitario nazionale italiano.
L’analisi si basa su un data-set, fornito dal Ministero della salute, che raccoglie informazioni sulle prestazioni
sanitarie (sia in regime di ricovero ordinario che di day-hospital) offerte nel 2001 da tutte le strutture ospedaliere operanti nell’ambito del Servizio sanitario nazionale. I risultati sono in linea con le predizioni empiriche della teoria di Sutton, secondo le quali nei mercati a bassa intensità di R&S esiste un lower bound per la concentrazione d’equilibrio, e tale lower bound
converge monotonicamente a zero all’aumentare della dimensione del mercato (rapportata ai costi di set-up), indipendentemente dal livello di omogeneità del prodotto. Nei mercati ad alta intensità di R&S, invece, il lower bound alla concentrazione converge a un valore positivo diverso da zero all’aumentare della dimensione di mercato, mentre cresce a partire da zero all’aumentare del livello di omogeneità del prodotto
The Good Outcome of Bad News: A Field Experiment on Formatting Breast Cancer Screening Invitation Letters
No full textBy favoring early diagnosis, mammography screening decreases breast cancer mortality and treatment costs. However, participation in public screening programs is low in many countries. We ran a randomized field experiment to assess whether costless manipulations of the informational content (restricted or enhanced information) and the framing (gain or loss framing) of the invitation letter to the breast cancer screening program in Messina (Italy) affects participation. We show that giving enhanced loss-framed information about the risks of not having a mammography increases the take-up. This manipulation is most effective among subgroups with lower baseline take-ups, thereby reducing inequalities in screening. Finally, subjects exposed to this manipulation are much less likely to postpone the screening conditional on participation, revealing enhanced awareness about the risks related with delayed participation
Comparison of Parametric and Non-Parametric Adjustments using Vignettes for Self-Reported Data
No full textThe geography of hospital admission in a national health service with patient choice
No full textEach year about 20% of the 10 million hospital inpatients in Italy get admitted to hospitals outside the Local Health Authority of residence. In this paper we carefully explore this phenomenon and estimate gravity equations for ‘trade’ in hospital care using a Poisson pseudo-maximum likelihood method. Consistency of the PPML estimator is guaranteed under the null of independence provided that the conditional mean is correctly specified. In our case we find that patients' flows are affected by network autocorrelation. We correct for it by relying upon spatial filtering. Our results suggest that the gravity model is a good framework for explaining patient mobility in most of the examined diagnostic groups. We find that the ability to restrain patients' outflows increases with the size of the pool of enrollees. Moreover, the ability to attract patients' inflows is reduced by the size of pool of enroless for all LHAs except for the very big LHAs. For LHAs in the top quintile of size of enrollees, the ability to attract inflows increases with the size of the pool. Copyright (C) 2010 John Wiley & Sons, Ltd.patients' mobility , hospital care , gravity model , spatial filtering , Italian National Health Service ,
La responsiveness dei sistemi sanitari: un’analisi empirica sull’assistenza ospedaliera nel Servizio Sanitario Regionale dell’Emilia Romagna
Full text linkThe release of the World Health Report 2000 has brought to the fore the concept of responsiveness as an indicator of
health system performance. Responsiveness relates to a system’s ability to respond to the legitimate expectations of potential users about non-health enhancing aspects of care (Valentine et al. 2003). A few studies have investigated how standard socio-demographic characteristics (such as income or education) have an influence on the evaluation of responsiveness by health care users (Puentes Rosas et al. 2006, Sirven et al. 2012, Rice et al. 2012). However, we are not aware of any study investigating the relationship between the frequency with which patients use health services and their evaluation of responsiveness. This paper narrows this gap by using data regarding a sample of patients hospitalized
in 9 hospitals of Emilia Romagna, a Region of Italy.
The data have been collected by the Agency for Health Care and Social Services of Emilia Romagna between January
2010 and December 2012. We investigate a representative sample of about 2500 in-patients, who have been asked to
evaluate 29 different aspect of quality of care which refer to 6 domains of health system responsiveness
(communication, social support, privacy, dignity, waiting times and quality of facilities). We make use of this structure of the data by adopting a panel data regression model. The adoption of a panel model helps in controlling for individual heterogeneity, which otherwise could bias our results. Given that responsiveness is evaluated on an ordinal and categorical scale (going from “very dissatisfied” to “very satisfied”) we estimate a panel ordered logit model.
Our results suggest that if patients have already been hospitalized in the same ward over the last 5 years they evaluate responsiveness more positively compared to patients who have never been hospitalized before. However, this effect is statistically significant only if patients have been hospitalized in the last 6 months. More generally, the use of a proper methodology to investigate responsiveness at hospital level can allow a better identification of area of intervention for investments in staff training; moreover, it can allow to modify hospital characteristics which have a negative impact on
patients’ reporting of responsiveness
- …
