Search results

In this paper we propose a methodology for the estimation of customer satisfaction conceived as a latent variable specified in the American Customer Satisfaction Index (ACSI) structural model. The current proposal puts forward: the approaches of structural equations, since it involves the dual problem of indeterminacy of the latent scores and the normality assumed; the PLS approach, because of its drawbacks (shown in depth in the paper). The ACSI model will be estimated in a reduced rank regression (RRR) framework, showing that under a non restrictive hypothesis, shared by PLS, the structural model can be viewed as a RRR model between two blocks of manifest variables. Finally, in the paper an application is shown to assess the students’ satisfaction in respect to the service of a big real estate agency, operating in the houses‐to‐let market, in Bologna (Italy) for 2002.

The purpose of this paper is to propose a practical conceptualization of the balanced scorecard (BSC) to describe the mechanism producing creation of monetary value for hospitals in the territorial context of Lombardy region (Italy).

The authors propose a model‐building strategy that assigns key indicators to key performance areas, and identifies causal relationships between key performance areas. Second, the authors utilize a suitable statistical approach to estimate causal relationships among involved latent variables, taking into account the hierarchical structure of data. Utilizing a suitable data decomposition, the causal model is applied separately to the within data (hospitals) and to the between data (local health agencies).

In the measurement model a new latent construct (medical human capital) was found that resumes the amount of formal training and the performance of surgical staff in hospitals. The estimated causal models reflect the usual directional assumptions, supposed in a typical BSC causal scheme, with some differences. For local health agencies, fruits (financial measures) are strongly related to clinical processes (leaves) for which the medical human capital constitutes its unique trunk. However, for hospitals, fruits (financial measures) are directly linked to clinical processes and Patient Satisfaction.

The main limitations of this study are the lack of new independent data to validate the obtained causal structures and the limited number of indicators that reflect the deficiency of available information in regional administrative archives.

The present study may be useful to guide further efforts which attempt to conceptualize BSC in the health sector. As more information can be made available, other performance indicators can prove to be linked with this structure using the same methodology.

The purpose of this paper is to provide international data on the occurrence (and rates) of clinical errors, identified by type and consequence in the Lombardy region, and to assess empirically the association between hospital accreditation‐type measures and clinical error rates by merging hospital discharge records and medical malpractice claim data in the Lombardy region (Italy).

Data were drawn from the regional database collecting claims and demands for reimbursement declared by patients hospitalized in regional healthcare structures and regional archives collecting hospital discharge records. To model the variability of clinical errors rates, binomial negative regression models were applied. For improved interpretation of the results, a regression tree methodology was used.

The results demonstrated that the rate of readmission for the same major diagnostic category and the rate of discharges against medical advice significantly affect the incidence of errors causing patient death, whereas the rate of unscheduled surgical readmission in the operating room significantly affects the rate of surgical error.

The findings confirm that claims data is problematic in nature because of the limited number of claims generally emerging from administrative sources. The article proposes using proper regression models for count data, taking into account over‐dispersion and excess zeroes and classification tree methods for a better interpretation of empirical evidence.

Health structures where quality outcomes have a significant impact on clinical error rates should be monitored in depth, investigating the medical charts of involved patients to identify quality problems and problematic areas.

As a risk management strategy, the combined use of claims data and clinical administrative data is proposed to shed light on the more problematic, error‐prone areas, allowing regional stakeholders to receive relevant, highly cost‐effective and timely information and an in‐depth understanding of the problematic areas in the assessment of risk.

The purpose of this paper is to discuss strategies for benchmarking patient safety using Lombardy region administrative archives. Patient safety indicators and statistical methods are presented that allow risk adjustment. The analysis benchmarks regional health structures, focusing on two patient safety indicators: failure to rescue; and death in low mortality diagnostic related group.

Data were drawn from a research project promoted by the Italian Agency of Regional Health Services in 2002 to furnish statistical evidence regarding adverse events based on Agency for Healthcare Research and Quality indicators and methods. Hierarchical models for an equitable benchmark analyses are proposed.

Empirical analysis shows that hierarchical approaches, based on comparing health structures within homogenous specialties, disaggregates and moderates failure to rescue variabilities existing between hospitals, especially in oncology, intensive care and general medicine.

The paper proposes using hierarchical models for properly benchmarking health structures, resolving logistic regression drawbacks and limitations.

The paper strengthens the theory that accurate coding supported by software and administrative databases could provide a valuable and economical source for patient safety research.

The paper analyses and suggests strategies for consistent benchmark analyses based on patient safety outcomes, applicable to several situations and different health structure typologies.

The aim of this paper is the discussion and the dissemination of initiatives promoted by the Lombardy region for the construction of benchmarking systems between regional health structures of care utilizing administrative archives.

The paper focuses on relative effectiveness (specific effect of care on patients) in a benchmarking framework, considering the dimension of sentinel outcomes. From Lombardy Hospital Discharge Cards proxies of sentinel outcomes are identified, defined as “context indicators” useful for a benchmarking analysis.

First, the authors present outcomes and covariates at different levels (patient and healthcare structure) extracted from the Lombardy Hospital Discharge Cards for a benchmarking analysis. Second, empirical results show a consistent quota of outcome variability between structures of care and weak agreement between estimated rankings for context indicators. Finally, a slicing approach is suggested in order to apply an equitable comparison among healthcare structures.

The paper provides regional stakeholders with practical implications regarding available strategies (outcomes, statistical methodology, risk adjustment) for consistent processes of evaluation, in a benchmarking framework, based on existing regional administrative data.

After having presented available information contained in regional archives for a benchmark analysis, empirical results were discussed about context indicators, presenting indications and strategies for a refinement of the approach. From a methodological point of view, the utilization of multilevel models (improving methodological strategies adopted by international agencies) in large administrative databases is proposed.