Evidence map›Paper›PMID 36225966›Full record

ArticleMDM policy & practice

Integrating a Patient Decision Aid into the Electronic Health Record: A Case Report on the Implementation of BREASTChoice at 2 Sites.

Clara N Lee, Janessa Sullivan, Randi Foraker, Terence M Myckatyn, Margaret A Olsen, Crystal Phommasathit, Jessica Boateng, Katelyn L Parrish, Milisa Rizer, Tim Huerta and 1 more

Abstract readCase Reports
In one paragraph

Article in MDM policy & practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

11 authors.

Clara N LeeDepartment of Plastic and Reconstructive Surgery, College of Medicine, Division of Health Services Management and Policy, College of Public Health, The Ohio State University, Columbus, OH, USA.ORCID https://orcid.org/0000-0003-0514-9448
Janessa SullivanDivision of Plastic and Reconstructive Surgery, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, USA.ORCID https://orcid.org/0000-0003-1095-6412
Randi ForakerDivision of General Medical Sciences, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, USA.
Terence M MyckatynDivision of Plastic and Reconstructive Surgery, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, USA.
Margaret A OlsenDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, USA.ORCID https://orcid.org/0000-0001-7070-9320
Crystal PhommasathitOSU Comprehensive Cancer Center; The Ohio State University, Columbus, OH, USA.
Jessica BoatengDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, USA.ORCID https://orcid.org/0000-0003-0393-7897
Katelyn L ParrishDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, USA.
Milisa RizerDivision of Infectious Diseases, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, USA.
Tim HuertaDepartment of Biomedical Informatics, Washington University School of Medicine, Saint Louis, MO, USA.
Mary C PolitiDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, Saint Louis, MO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient decision aids can support shared decision making and improve decision quality. However, decision aids are not widely used in clinical practice due to multiple barriers. Integrating patient decision aids into the electronic health record (EHR) can increase their use by making them more clinically relevant, personalized, and actionable. In this article, we describe the procedures and considerations for integrating a patient decision aid into the EHR, based on the example of BREASTChoice, a decision aid for breast reconstruction after mastectomy. BREASTChoice's unique features include 1) personalized risk prediction using clinical data from the EHR, 2) clinician- and patient-facing components, and 3) an interactive format. Integrating a decision aid with patient- and clinician-facing components plus interactive sections presents unique deployment issues. Based on this experience, we outline 5 key implementation recommendations: 1) engage all relevant stakeholders, including patients, clinicians, and informatics experts; 2) explicitly and continually map all persons and processes; 3) actively seek out pertinent institutional policies and procedures; 4) plan for integration to take longer than development of a stand-alone decision aid or one with static components; and 5) transfer knowledge about the software programming from one institution to another but expect local and context-specific changes. Integration of patient decision aids into the EHR is feasible and scalable but requires preparation for specific challenges and a flexible mindset focused on implementation. Highlights: Integrating an interactive decision aid with patient- and clinician-facing components into the electronic health record could advance shared decision making but presents unique implementation challenges.We successfully integrated a decision aid for breast reconstruction after mastectomy called BREASTChoice into the electronic health record.Based on this experience, we offer these implementation recommendations: 1) engage relevant stakeholders, 2) explicitly and continually map persons and processes, 3) seek out institutional policies and procedures, 4) plan for it to take longer than for a stand-alone decision aid, and 5) transfer software programming from one site to another but expect local changes.

Indexed as

breast reconstructiondecision aiddecision supportelectronic health recordmastectomyshared decision making

Identifiers

PMID36225966
PMCPMC9549192

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.