Evidence map›Paper›PMID 26911288›Full record

ArticleBMC medical informatics and decision making2016

Taxonomy of delays in the implementation of hospital computerized physician order entry and clinical decision support systems for prescribing: a longitudinal qualitative study.

Hajar Mozaffar, Kathrin M Cresswell, Lisa Lee, Robin Williams, Aziz Sheikh, NIHR ePrescribing Programme Team

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Implementation of Computerized Prescriber Order Entry Systems: A Review of Impacts, Barriers, and Facilitators.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2024
    Review
  6. Article
  7. Article
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hajar MozaffarCentre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Doorway number 3, Teviot Place, Edinburgh, EH8 9AG, UK. h.mozaffar@ed.ac.uk.
Kathrin M CresswellCentre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Doorway number 3, Teviot Place, Edinburgh, EH8 9AG, UK.
Lisa LeeCentre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Doorway number 3, Teviot Place, Edinburgh, EH8 9AG, UK.
Robin WilliamsInstitute for the Study of Science, Technology and Innovation, The University of Edinburgh, Doorway number 3, Teviot Place, Edinburgh, EH8 9AG, UK.
Aziz SheikhCentre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Doorway number 3, Teviot Place, Edinburgh, EH8 9AG, UK.
NIHR ePrescribing Programme Team

Funding

Department of Health RP-PG-1209-10099
6 · The paper itself

Abstract

backgroundImplementation delays are common in health information technology (HIT) projects. In this paper, we sought to explore the reasons for delays in implementing major hospital-based HIT, through studying computerized physician order entry (CPOE) and clinical decision support (CDS) systems for prescribing and to develop a provisional taxonomy of causes of implementation delays.

methodsWe undertook a series of longitudinal, qualitative case studies to investigate the implementation and adoption of CPOE and CDS systems for prescribing in hospitals in the U.K. We used a combination of semi-structured interviews from six case study sites and two whole day expert roundtable discussions to collect data. Interviews were carried out with users, implementers and suppliers of CPOE/CDS systems. We used thematic analysis to examine the results, drawing on perspectives surrounding the biography of artefacts.

resultsWe identified 15 major factors contributing to delays in implementation of CPOE and CDS systems. These were then categorized in a two-by-two delay classification matrix: one axis distinguishing tactical versus unintended causes of delay, and the second axis illustrating internal i.e., (the adopting hospital) versus external (i.e., suppliers, other hospitals, policymakers) related causes.

conclusionsOur taxonomy of delays in HIT implementation should enable system developers, implementers and policymakers to better plan and manage future implementations. More detailed planning at the outset, considering long-term strategies, sustained user engagement, and phased implementation approaches appeared to reduce the risks of delays. It should however be noted that whilst some delays are likely to be preventable, other delays cannot be easily avoided and taking steps to minimize these may negatively affect the longer-term use of the system.

Indexed as

Decision Support Systems, ClinicalElectronic PrescribingHospitalsHumansLongitudinal StudiesMedical Order Entry SystemsQualitative ResearchTime Factors

Identifiers

PMID26911288
PMCPMC4766744

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.