Operational efficiency vs clinical safety, care appropriateness, timeliness, and access to health care

Marques, Rui Cunha; Nunes, Alexandre Morais

doi:10.1007/s11123-020-00578-6

Cited by 24 publications

(27 citation statements)

References 90 publications

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“…Studies already account for the patient characteristics, delays in treatment effects, and heterogeneous environments. For example, Ferrier and Trivitt (2013) include condition-specific post-discharge mortality rates in assessing US hospitals, and Ferreira et al (2020) account for various environmental factors in evaluating the efficiency of Portuguese hospitals.…”

Section: Discussionmentioning

confidence: 99%

“…The outcome quality indicators used in SubCATs 20 and 21 are comparable to those in Class 1. Ferreira et al (2020), who incorporate composite indexes capturing appropriateness, timeliness, and accessibility of care in a second stage, justify their two-stage approach based on their previous findings that the separability condition holds for Portuguese hospitals (see Ferreira and Marques 2019). 7 Roth et al ( 2019), using a two-stage approach, are the only ones who assume that quality and efficiency represent different dimensions of hospital performance (SubCAT 22).…”

Section: Hospital Studies Including Cross-provider Studiesmentioning

confidence: 99%

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Health care quality in nonparametric efficiency studies: a review

Sommersguter-Reichmann

2021

Cent Eur J Oper Res

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Scientists are increasingly considering quality in nonparametric frontier efficiency studies in health care. There are many ways to include quality in efficiency analyses. These approaches differ, among other things, in the underlying assumptions about the influence of quality on the attainable efficiency frontier and the distribution of inefficiency scores. The aim is to provide an overview of how scholars have taken quality into account in nonparametric frontier efficiency studies and, at the same time, to address the underlying assumptions on the relationship between efficiency and quality. To this end, we categorized empirical efficiency studies according to the methodological approaches and quality dimensions and collected the quality indicators used. We performed a Web of Science search for studies published in journals covered by the Science Citation Index Expanded, the Social Sciences Citation Index, and the Emerging Sources Citation Index between 1980 and 2020. Of the 126 studies covered in this review, 78 are one-stage studies that incorporate quality directly into the efficiency model and thus assume that quality impacts the attainable efficiency frontier. Forty-four articles are two-stage studies that consider quality in the first and the second stage or the second stage only. Four studies do not assume a priori a specific association between efficiency and quality. Instead, they test for this relationship empirically. Outcome quality is by far the most frequently incorporated quality dimension. While most studies consider structural quality as an environmental variable in the second stage, they include outcome quality predominantly directly in the efficiency model. Process quality is less common.

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Section: Discussionmentioning

confidence: 99%

Section: Hospital Studies Including Cross-provider Studiesmentioning

confidence: 99%

Health care quality in nonparametric efficiency studies: a review

Sommersguter-Reichmann

2021

Cent Eur J Oper Res

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“…GRA models have been successfully applied in many fields, such as engineering [55], environmental science [56], and management [57]. For healthcare management studies, GRA models have been applied to study patient satisfaction [27,29,64], healthcare service quality [28,64,65], performance [62], efficiency [66,67], healthcare resource allocations [68], etc.…”

Section: Application and Advantages Of Gra Modelsmentioning

confidence: 99%

Ranking the Healthcare Resource Factors for Public Satisfaction with Health System in China—Based on the Grey Relational Analysis Models

Peng

Tang

Chen

et al. 2021

IJERPH

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(1) Background: Public satisfaction with the health system is a very important comprehensive indicator. Given the limited healthcare resources in a society, it is always important for policymakers to have full information about the priority and the ranking order of the factors of healthcare resources for improving public satisfaction. (2) Methods: Grey Relational Analysis (GRA) is advantageous for satisfaction analysis because satisfaction is a “grey concept” of “having a clear boundary but vague connotation”. The data were from the CGSS and the China Health Statistics Yearbook (2013 and 2015), with a total of 15,969 samples (average satisfaction score = 68.5, age = 51.9, female = 49.4%). (3) Results: The government’s percentage of total expenditure on healthcare was ranked as the most important factor for public satisfaction with the health system in China in both 2013 and 2015. The second most important factor changed from “Out-of-pocket percentage of individuals” in 2013 to “Hospital beds per thousand populations” in 2015. Meanwhile, “Healthcare workforce per thousand populations” increased from the least important factor in 2013 to the 3rd in 2015. Disparities in the ranking orders of the factors among regions of China were identified too. (4) Conclusions: The analysis results suggest that during recent years the priority of Chinese residents’ healthcare satisfaction for healthcare resources has shifted on the national level from economic affordability to more intensive “people-centered” services, while the regional disparities and gaps need to receive more attention and be further improved in the healthcare reform of next round.

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“…In this context, the Data Envelopment Analysis (DEA) methodology has been broadly accepted and applied to the efficiency assessment of healthcare systems and specifically to hospitals [ [5] , [6] , [7] , [8] ].…”

Section: Introductionmentioning

confidence: 99%