Evidence map›Paper›PMID 32734168›Full record

ArticleJAMIA open2020

Organizational diagnostics: a systematic approach to identifying technology and workflow issues in clinical settings.

Kim M Unertl, Laurie Lovett Novak, Courtney Van Houten, JoAnn Brooks, Andrew O Smith, Joyce Webb Harris, Taylor Avery, Christopher Simpson, Nancy M Lorenzi

Open access · goldAbstract read
In one paragraph

Article in JAMIA open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 35% of its field
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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

9 authors at 3 institutions in 1 country.

Kim M UnertlDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0003-0094-3677
Laurie Lovett NovakDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Courtney Van HoutenCenter for AI Research and Evaluation, IBM Watson Health, Cambridge, Massachusetts, USA.
JoAnn BrooksIndependent Scholar, Cambridge, Massachusetts, USA.
Andrew O SmithOperations Improvement, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Joyce Webb HarrisDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Taylor AveryStrategy and Innovation, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Christopher SimpsonDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Nancy M LorenziDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Vanderbilt University Medical Center · USFilm Independent · USIBM (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesHealthcare organizations need to rapidly adapt to new technology, policy changes, evolving payment strategies, and other environmental changes. We report on the development and application of a structured methodology to support technology and process improvement in healthcare organizations, Systematic Iterative Organizational Diagnostics (SIOD). SIOD was designed to evaluate clinical work practices, diagnose technology and workflow issues, and recommend potential solutions. MATERIALS AND

methodsSIOD consists of five stages: (1) Background Scan, (2) Engagement Building, (3) Data Acquisition, (4) Data Analysis, and (5) Reporting and Debriefing. Our team applied the SIOD approach in two ambulatory clinics and an integrated ambulatory care center and used SIOD components during an evaluation of a large-scale health information technology transition.

resultsDuring the initial SIOD application in two ambulatory clinics, five major analysis themes were identified, grounded in the data: putting patients first, reducing the chaos, matching space to function, technology making work harder, and staffing is more than numbers. Additional themes were identified based on SIOD application to a multidisciplinary clinical center. The team also developed contextually grounded recommendations to address issues identified through applying SIOD. DISCUSSION: The SIOD methodology fills a problem identification gap in existing process improvement systems through an emphasis on issue discovery, holistic clinic functionality, and inclusion of diverse perspectives. SIOD can diagnose issues where approaches as Lean, Six Sigma, and other organizational interventions can be applied.

conclusionThe complex structure of work and technology in healthcare requires specialized diagnostic strategies to identify and resolve issues, and SIOD fills this need.

Indexed as

process assessment (health care)process improvementsystems analysisworkflow

Identifiers

PMID32734168
PMCPMC7382633
OpenAlexW3025472689

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.