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Management Science
Article
Data sources: UnpayWall
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Apollo
Article . 2017
Data sources: Apollo
Management Science
Article . 2017 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Gatekeepers at Work: An Empirical Analysis of a Maternity Unit

Authors: Freeman, M; Savva, N; Scholtes, S;

Gatekeepers at Work: An Empirical Analysis of a Maternity Unit

Abstract

We use a detailed operational and clinical data set from a maternity hospital to investigate how workload affects decisions in gatekeeper-provider systems, where the servers act as gatekeepers to specialists but may also attempt to serve customers themselves, albeit with a probability of success that is decreasing in the complexity of the customers’ needs. We study the effect of workload during a service episode on gatekeepers’ service configuration decisions and the rate at which gatekeepers refer customers to a specialist. We find that gatekeeper-providers (midwives in our context) make substantial use of two levers to manage their workload (measured as patients per midwife): they ration resource-intensive discretionary services (epidural analgesia) for customers with noncomplex service needs (mothers with spontaneous onset of labor) and, at the same time, increase the rate of specialist referral (physician-led delivery) for customers with complex needs (mothers with pharmacologically induced labor). The workload effect in the study unit is surprisingly large and comparable in size to those for leading clinical risk factors: when workload increases from two standard deviations below to two standard deviations above the mean, noncomplex cases are 28.8% less likely to receive an epidural, leading to a cost reduction of 8.7%, while complex cases are 14.2% more likely to be referred for a physician-led delivery, leading to a cost increase of 2.6%. These observations are consistent with overtreatment at both high and low workload levels, albeit for different types of patients, and suggest that smoothing gatekeeper workload would reduce variability in customer service experience.This paper was accepted by Serguei Netessine, operations management.

Country
United Kingdom
Related Organizations
Keywords

330, 38 Economics, JM, Health Services, 35 Commerce, Management, Tourism and Services, 46 Information and Computing Sciences, Clinical Research, Health service, Econometrics, LWL

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
121
Top 1%
Top 10%
Top 1%
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