Evidence map›Paper›PMID 27107441›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2017

Ten key considerations for the successful optimization of large-scale health information technology.

Kathrin M Cresswell, David W Bates, Aziz Sheikh

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 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. The Implementation of Pharmacogenetics in the United Kingdom.Handbook of experimental pharmacology · 2023
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  8. Acceptance of Technologies for Aging in Place: A Conceptual Model.Journal of medical Internet research · 2021
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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

3 authors.

Kathrin M CresswellChief Scientist Office Postdoctoral Fellow, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK Kathrin.Beyer@ed.ac.uk.
David W BatesProfessor of Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, and Department of Health Policy and Management, Harvard School of Public Health, Boston MA, USA.
Aziz SheikhProfessor of Primary Care Research and Development and Co-Director, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK.

Funding

Chief Scientist OfficeDepartment of Health RP-PG-1209-10099Medical Research Council MC_PC_13040Medical Research Council MR/K007017/1
6 · The paper itself

Abstract

Implementation and adoption of complex health information technology (HIT) is gaining momentum internationally. This is underpinned by the drive to improve the safety, quality, and efficiency of care. Although most of the benefits associated with HIT will only be realized through optimization of these systems, relatively few health care organizations currently have the expertise or experience needed to undertake this. It is extremely important to have systems working before embarking on HIT optimization, which, much like implementation, is an ongoing, difficult, and often expensive process. We discuss some key organization-level activities that are important in optimizing large-scale HIT systems. These include considerations relating to leadership, strategy, vision, and continuous cycles of improvement. Although these alone are not sufficient to fully optimize complex HIT, they provide a starting point for conceptualizing this important area.

Indexed as

Diffusion of InnovationHealth Information SystemsLeadershipMeaningful UseMedical InformaticsQuality of Health CareUnited StatesHealth policy valueleadershipquality of health caresafety

Identifiers

PMID27107441
PMCPMC7654072

What OpenQuestion holds

Textmetadata
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.