Evidence map›Paper›PMID 28339685›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2017

Information needs of generalists and specialists using online best-practice algorithms to answer clinical questions.

David A Cook, Kristi J Sorensen, Jane A Linderbaum, Laurie J Pencille, Deborah J Rhodes

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Emergency Department Clinician Perspectives on the Data Availability to Implement Clinical Decision Support Tools for Five Clinical Practice Guidelines.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018
    Article
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.

David A CookKnowledge Delivery Center, Mayo Clinic, Rochester, MN, USA.
Kristi J SorensenKnowledge Delivery Center, Mayo Clinic, Rochester, MN, USA.
Jane A LinderbaumKnowledge Delivery Center, Mayo Clinic, Rochester, MN, USA.
Laurie J PencilleKnowledge Delivery Center, Mayo Clinic, Rochester, MN, USA.
Deborah J RhodesKnowledge Delivery Center, Mayo Clinic, Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo better understand clinician information needs and learning opportunities by exploring the use of best-practice algorithms across different training levels and specialties.

methodsWe developed interactive online algorithms (care process models [CPMs]) that integrate current guidelines, recent evidence, and local expertise to represent cross-disciplinary best practices for managing clinical problems. We reviewed CPM usage logs from January 2014 to June 2015 and compared usage across specialty and provider type.

resultsDuring the study period, 4009 clinicians (2014 physicians in practice, 1117 resident physicians, and 878 nurse practitioners/physician assistants [NP/PAs]) viewed 140 CPMs a total of 81 764 times. Usage varied from 1 to 809 views per person, and from 9 to 4615 views per CPM. Residents and NP/PAs viewed CPMs more often than practicing physicians. Among 2742 users with known specialties, generalists ( N  = 1397) used CPMs more often (mean 31.8, median 7 views) than specialists ( N  = 1345; mean 6.8, median 2; P  < .0001). The topics used by specialists largely aligned with topics within their specialties. The top 20% of available CPMs (28/140) collectively accounted for 61% of uses. In all, 2106 clinicians (52%) returned to the same CPM more than once (average 7.8 views per topic; median 4, maximum 195). Generalists revisited topics more often than specialists (mean 8.8 vs 5.1 views per topic; P  < .0001).

conclusionsCPM usage varied widely across topics, specialties, and individual clinicians. Frequently viewed and recurrently viewed topics might warrant special attention. Specialists usually view topics within their specialty and may have unique information needs.

Indexed as

AlgorithmsDecision Support Systems, ClinicalInformation Seeking BehaviorMedical Staff, HospitalNurse PractitionersPhysician AssistantsCritical PathwaysMedicineRetrospective Studiesclinicalcritical pathwaysdecision support systemspoint-of-care learningpractice guidelines as topic

Identifiers

PMID28339685
PMCPMC7651958

What OpenQuestion holds

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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.