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1.
Health Care Manage Rev ; 47(4): 297-307, 2022.
Article in English | MEDLINE | ID: mdl-35135990

ABSTRACT

BACKGROUND: Hospitals are increasingly pursuing specialization as a strategy to operate efficiently while delivering high-quality care. To date, however, evidence is lacking on whether hospital specialization has a consistent effect on patients' experience of care or whether different specialization characteristics influence how specialization works. PURPOSE: This study investigates whether specialization characteristics, that is, the within-specialty concentration and the within-specialty urgency score, moderate the link between hospital specialization and patient experience of care. METHODOLOGY: We use patient-reported and administrative data from German hospitals between 2014 and 2017, with orthopedic and trauma care as the research setting. Our sample consists of 157,458 patient observations nested within 483 hospitals. We apply random-intercept multilevel modeling. RESULTS: Our results indicate that the effect of specialization on patient experience of care (a) decreases as the within-specialty concentration increases and (b) increases as the within-specialty urgency score increases. CONCLUSION: This study provides novel insights into the specialization characteristics that make hospital specialization in orthopedic and trauma care particularly effective at improving patient experiences. PRACTICE IMPLICATIONS: Although specialization is gaining popularity as a strategy for pooling scarce resources and facilitating high-quality health care, hospital managers and policymakers should consider that certain characteristics of specialization can influence the way that specialization works and how effective it is in improving patient experiences. Within the scope of orthopedic and trauma care, our study suggests that a low concentration of diagnoses within a service area and a high average level of medical urgency make specialization particularly effective at improving patient experiences.


Subject(s)
Hospitals , Specialization , Health Personnel , Humans , Patient Outcome Assessment , Quality of Health Care
2.
Health Care Manag Sci ; 23(4): 649-660, 2020 Dec.
Article in English | MEDLINE | ID: mdl-32936387

ABSTRACT

With hospital budgets remaining tight and healthcare expenditure rising due to demographic change and advances in technology, hospitals continue to face calls to contain costs and allocate their resources more efficiently. In this context, efficiency has emerged as an increasingly important way for hospitals to withstand competitive pressures in the hospital market. Doing so, however, can be challenging given unpredictable fluctuations in demand, a prime example of which are emergencies, i.e. urgent medical cases. The link between medical urgency and hospitals' efficiency, however, has been neglected in the literature to date. This study therefore aims to investigate the relationship between hospitals' urgency characteristics and their efficiency. Our analyses are based on 4094 observations from 1428 hospitals throughout Germany for the years 2015, 2016, and 2017. We calculate an average urgency score for each hospital based on all cases treated in that hospital per year and also investigate the within-hospital dispersion of medical urgency. To analyze the association of these urgency measures with hospitals' efficiency we use a two-stage double bootstrap data envelopment analysis approach with truncated regression. We find a negative relationship between the urgency score and hospital efficiency. When testing for non-linear effects, the results reveal a u-shaped association, indicating that having either a high or low overall urgency score is beneficial in terms of efficiency. Finally, our results reveal that higher within-hospital urgency dispersion is negatively related to efficiency.


Subject(s)
Efficiency, Organizational/statistics & numerical data , Emergency Medical Services/statistics & numerical data , Elective Surgical Procedures/statistics & numerical data , Germany , Hospital Administration , Hospitals , Humans , Patient Admission/statistics & numerical data
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