Evidence map›Paper›PMID 28483886›Full record

Observational studyAnnals of family medicine2017

Harnessing Information Technology to Inform Patients Facing Routine Decisions: Cancer Screening as a Test Case.

Alex H Krist, Steven H Woolf, Camille Hochheimer, Roy T Sabo, Paulette Kashiri, Resa M Jones, Jennifer Elston Lafata, Rebecca S Etz, Shin-Ping Tu

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Annals of family medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 5 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

23 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  14. Effectiveness of Using Personal Health Records to Improve Recommended Breast Cancer Screening and Reduce Racial and Geographic Disparities Among Women.Journal of cancer education : the official journal of the American Association for Cancer Education · 2022
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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

9 authors.

Alex H KristDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia ahkrist@vcu.edu.
Steven H WoolfDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
Camille HochheimerDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
Roy T SaboDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
Paulette KashiriDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
Resa M JonesDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
Jennifer Elston LafataDivision of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina Chapel Hill, Chapel Hill, North Carolina.
Rebecca S EtzDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
Shin-Ping TuSchool of Public Health, University of Washington, Seattle, Washington.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTechnology could transform routine decision making by anticipating patients' information needs, assessing where patients are with decisions and preferences, personalizing educational experiences, facilitating patient-clinician information exchange, and supporting follow-up. This study evaluated whether patients and clinicians will use such a decision module and its impact on care, using 3 cancer screening decisions as test cases.

methodsTwelve practices with 55,453 patients using a patient portal participated in this prospective observational cohort study. Participation was open to patients who might face a cancer screening decision: women aged 40 to 49 who had not had a mammogram in 2 years, men aged 55 to 69 who had not had a prostate-specific antigen test in 2 years, and adults aged 50 to 74 overdue for colorectal cancer screening. Data sources included module responses, electronic health record data, and a postencounter survey.

resultsIn 1 year, one-fifth of the portal users (11,458 patients) faced a potential cancer screening decision. Among these patients, 20.6% started and 7.9% completed the decision module. Fully 47.2% of module completers shared responses with their clinician. After their next office visit, 57.8% of those surveyed thought their clinician had seen their responses, and many reported the module made their appointment more productive (40.7%), helped engage them in the decision (47.7%), broadened their knowledge (48.1%), and improved communication (37.5%).

conclusionsMany patients face decisions that can be anticipated and proactively facilitated through technology. Although use of technology has the potential to make visits more efficient and effective, cultural, workflow, and technical changes are needed before it could be widely disseminated.

Indexed as

Decision MakingDecision Making, Computer-AssistedEarly Detection of CancerPhysician-Patient RelationsAdultAgedBreast NeoplasmsColorectal NeoplasmsFeasibility StudiesFemaleHealth Knowledge, Attitudes, PracticeHumansInformation TechnologyMaleMass ScreeningMiddle Agedcomputer-assisteddecision makinghealth information technologypatient educationpractice-based researchprimary carescreening

Identifiers

PMID28483886
PMCPMC5422082

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.