How improving access times had unforeseen consequences: a case study in a Dutch hospital

Oskar Roemeling*, Kees Ahaus, Folkert van Zanten, Martin Land, Patrick Wennekes

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
47 Downloads (Pure)

Abstract

Objectives
To investigate the consequences of increasing capacity to reduce access times, and to explore how patient waiting times and use of physical capacity were influenced by variability.

Design
A retrospective case study that combines both primary and secondary data. Secondary data were retrieved from a hospital database to establish inflow and outflow of patients, utilisation of resources and available capacity, realised access times and the weekly number of new patients seen over 1 year. Primary data consisted of field notes, onsite visits and observations, and semistructured interviews.

Setting
A secondary care facility, that is, a rheumatology department, in a large Dutch hospital.

Participants Analyses are based on secondary patient data from the hospital database, and the responses of the interviews with physicians, nurses and Lean Six Sigma project leaders.

Results
The study shows that artificial variability was increased by managerial decisions to add capacity and to allow an increased inflow of new patients. This, in turn, resulted in undesirable and significant fluctuations in access times. We argue that we witnessed a new multiplier effect that typifies the fluctuations.

Conclusions
Adding capacity resources to reduce access times might appear an obvious and effective solution. However, the outcomes were less straightforward than expected, and even led to new artificial variability. The study reveals a phenomenon that is specific to service environments, and especially healthcare, and has detrimental consequences for access times.
Original languageEnglish
Article number031244
Number of pages9
JournalBMJ Open
Volume9
Issue number9
Early online date6-Sep-2019
DOIs
Publication statusPublished - Sep-2019

Keywords

  • patient waiting times
  • variability
  • buffers
  • hospitals
  • PATIENT FLOW
  • CARE
  • VARIABILITY
  • SERVICE
  • MANAGEMENT
  • IMPACT

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