Evidence map›Paper›PMID 29146562›Full record

ArticleJournal of biomedical informatics2018

Multi-method laboratory user evaluation of an actionable clinical performance information system: Implications for usability and patient safety.

Benjamin Brown, Panos Balatsoukas, Richard Williams, Matthew Sperrin, Iain Buchan

Abstract readEvaluation Study
In one paragraph

Article in Journal of biomedical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Systematic review and narrative synthesis of computerized audit and feedback systems in healthcare.Journal of the American Medical Informatics Association : JAMIA · 2022
    Pooled it
  3. Pooled it
  4. Article
  5. Precision feedback: A conceptual model.Learning health systems · 2024
    Article
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  10. Review
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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

5 authors.

Benjamin BrownHealth e-Research Centre, Farr Institute of Health Informatics Research, Centre for Health Informatics, University of Manchester, Manchester, UK; NIHR Patient Safety Translational Research Centre Greater Manchester, University of Manchester, Manchester, UK. Electronic address: benjamin.brown@manchester.ac.uk.
Panos BalatsoukasHealth e-Research Centre, Farr Institute of Health Informatics Research, Centre for Health Informatics, University of Manchester, Manchester, UK.
Richard WilliamsHealth e-Research Centre, Farr Institute of Health Informatics Research, Centre for Health Informatics, University of Manchester, Manchester, UK; NIHR Patient Safety Translational Research Centre Greater Manchester, University of Manchester, Manchester, UK.
Matthew SperrinHealth e-Research Centre, Farr Institute of Health Informatics Research, Centre for Health Informatics, University of Manchester, Manchester, UK.
Iain BuchanHealth e-Research Centre, Farr Institute of Health Informatics Research, Centre for Health Informatics, University of Manchester, Manchester, UK; NIHR Patient Safety Translational Research Centre Greater Manchester, University of Manchester, Manchester, UK.

Funding

Medical Research Council MC_PC_13042Medical Research Council MR/K006665/1Wellcome Trust 104438/Z/14/Z
6 · The paper itself

Abstract

introductionElectronic audit and feedback (e-A&F) systems are used worldwide for care quality improvement. They measure health professionals' performance against clinical guidelines, and some systems suggest improvement actions. However, little is known about optimal interface designs for e-A&F, in particular how to present suggested actions for improvement. We developed a novel theory-informed system for primary care (the Performance Improvement plaN GeneratoR; PINGR) that covers the four principal interface components: clinical performance summaries; patient lists; detailed patient-level information; and suggested actions. As far as we are aware, this is the first report of an e-A&F system with all four interface components.

objectives(1) Use a combination of quantitative and qualitative methods to evaluate the usability of PINGR with target end-users; (2) refine existing design recommendations for e-A&F systems; (3) determine the implications of these recommendations for patient safety.

methodsWe recruited seven primary care physicians to perform seven tasks with PINGR, during which we measured on-screen behaviour and eye movements. Participants subsequently completed usability questionnaires, and were interviewed in-depth. Data were integrated to: gain a more complete understanding of usability issues; enhance and explain each other's findings; and triangulate results to increase validity.

resultsParticipants committed a median of 10 errors (range 8-21) when using PINGR's interface, and completed a median of five out of seven tasks (range 4-7). Errors violated six usability heuristics: clear response options; perceptual grouping and data relationships; representational formats; unambiguous description; visually distinct screens for confusable items; and workflow integration. Eye movement analysis revealed the integration of components largely supported effective user workflow, although the modular design of clinical performance summaries unnecessarily increased cognitive load. Interviews and questionnaires revealed PINGR is user-friendly, and that improved information prioritisation could further promote useful user action.

conclusionsComparing our results with the wider usability literature we refine a previously published set of interface design recommendations for e-A&F. The implications for patient safety are significant regarding: user engagement; actionability; and information prioritisation. Our results also support adopting multi-method approaches in usability studies to maximise issue discovery and the credibility of findings.

Indexed as

Patient SafetyUser-Computer InterfaceDecision Support Systems, ClinicalEye Movement MeasurementsFeasibility StudiesHumansMedical Records Systems, ComputerizedPatient Care ManagementPrimary Health CareQuality ImprovementSoftware DesignTask Performance and AnalysisClinical auditClinical decision supportClinical governanceClinical quality improvementClinical quality managementMedical auditUser interface design

Identifiers

PMID29146562
PMCPMC5766660

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.