The relationship between hospital specialization and hospital efficiency

TY - JOUR

T1 - The relationship between hospital specialization and hospital efficiency

T2 - do different measures of specialization lead to different results?

AU - Lindlbauer, Ivonne

AU - Schreyögg, Jonas

PY - 2014/12

Y1 - 2014/12

N2 - This study investigated the relationship between hospital specialization and technical efficiency using different measures of specialization, including two novel approaches based on patient volumes rather than patient proportions. It was motivated by the observation that most studies to date have quantified hospital specialization using information about hospital patients grouped into different categories based on their diagnosis, and in doing so have used proportions-thus indirectly assuming that these categories are dependent on one other. In order to account for the diversification of organizations and the idea that hospitals can be specialized in terms of professional expertise or technical equipment within a given diagnosis category, we developed our two specialization measures based on patient volume in each category. Using a one-step stochastic frontier approach on randomly selected data from the annual reports of 1,239 acute care German hospitals for the years 2000 through 2010, we estimated the relationship of inefficiency to exogenous variables, such as specialization. The results show that specialization as quantified by our novel measures has effects on efficiency that are the opposite of those obtained using earlier measures of specialization. These results underscore the importance of always providing an exact definition of specialization when studying its effects. Additionally, a Monte Carlo simulation based on three scenarios is provided to facilitate the choice of a specialization measure for further analysis.

AB - This study investigated the relationship between hospital specialization and technical efficiency using different measures of specialization, including two novel approaches based on patient volumes rather than patient proportions. It was motivated by the observation that most studies to date have quantified hospital specialization using information about hospital patients grouped into different categories based on their diagnosis, and in doing so have used proportions-thus indirectly assuming that these categories are dependent on one other. In order to account for the diversification of organizations and the idea that hospitals can be specialized in terms of professional expertise or technical equipment within a given diagnosis category, we developed our two specialization measures based on patient volume in each category. Using a one-step stochastic frontier approach on randomly selected data from the annual reports of 1,239 acute care German hospitals for the years 2000 through 2010, we estimated the relationship of inefficiency to exogenous variables, such as specialization. The results show that specialization as quantified by our novel measures has effects on efficiency that are the opposite of those obtained using earlier measures of specialization. These results underscore the importance of always providing an exact definition of specialization when studying its effects. Additionally, a Monte Carlo simulation based on three scenarios is provided to facilitate the choice of a specialization measure for further analysis.

KW - Efficiency, Organizational

KW - Germany

KW - Hospitals, Special

KW - Monte Carlo Method

KW - Stochastic Processes

U2 - 10.1007/s10729-014-9275-1

DO - 10.1007/s10729-014-9275-1

M3 - SCORING: Journal article

C2 - 24595722

VL - 17

SP - 365

EP - 378

JO - HEALTH CARE MANAG SC

JF - HEALTH CARE MANAG SC

SN - 1386-9620

IS - 4

ER -