Cited by 26Electronic Health Records SystemsClinical Reasoning and Diagnostic SkillsMachine Learning in Healthcare

Effect of Electronic Health Record Clinical Decision Support on Contextualization of Care

Open access
Weiner, Saul J., Schwartz, Alan, Weaver, Frances, Galanter, William, Olender, Sarah, Kochendorfer, Karl, Binns-Calvey, Amy, Saini, Ravisha +4 more·2022·JAMA Network Open

Abstract

Importance: Contextualizing care is a process of incorporating information about the life circumstances and behavior of individual patients, termed contextual factors, into their plan of care. In 4 steps, clinicians recognize clues (termed contextual red flags), clinicians ask about them (probe for context), patients disclose contextual factors, and clinicians adapt care accordingly. The process is associated with a desired outcome resolution of the presenting contextual red flag. Objective: To determine whether contextualized clinical decision support (CDS) tools in the electronic health record (EHR) improve clinician contextual probing, attention to contextual factors in care planning, and the presentation of contextual red flags. Design, Setting, and Participants: This randomized clinical trial was performed at the primary care clinics of 2 academic medical centers with different EHR systems. Participants were adults 18 years or older consenting to audio record their visits and their physicians between September 6, 2018, and March 4, 2021. Patients were randomized to an intervention or a control group. Analyses were performed on an intention-to-treat basis. Interventions: Patients completed a previsit questionnaire that elicited contextual red flags and factors and appeared in the clinician’s note template in a contextual care box. The EHR also culled red flags from the medical record, included them in the contextual care box, used passive and interruptive alerts, and proposed relevant orders. Main Outcomes and Measures: Proportion of contextual red flags noted at the index visit that resolved 6 months later (primary outcome), proportion of red flags probed (secondary outcome), and proportion of contextual factors addressed in the care plan by clinicians (secondary outcome), adjusted for study site and for multiple red flags and factors within a visit. Results: Four hundred fifty-two patients (291 women [65.1%]; mean [SD] age, 55.6 [15.1] years) completed encounters with 39 clinicians (23 women [59.0%]). Contextual red flags were not more likely to resolve in the intervention vs control group (adjusted odds ratio [aOR], 0.96 [95% CI, 0.57-1.63]). However, the intervention increased both contextual probing (aOR, 2.12 [95% CI, 1.14-3.93]) and contextualization of the care plan (aOR, 2.67 [95% CI, 1.32-5.41]), controlling for whether a factor was identified by probing or otherwise. Across study groups, contextualized care plans were more likely than noncontextualized plans to result in improvement in the presenting red flag (aOR, 2.13 [95% CI, 1.38-3.28]). Conclusions and Relevance: This randomized clinical trial found that contextualized CDS did not improve patients’ outcomes but did increase contextualization of their care, suggesting that use of this technology could ultimately help improve outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT03244033

AI snapshot

Written from the paper’s full text.

TL;DR

In a 27-month randomized multicenter trial of 452 audio-recorded primary care encounters, customized EHR clinical decision support (CDS) did not significantly improve patient outcomes but did improve contextualization of care. Contextualized care plans were themselves associated with better prospectively defined red-flag outcomes.

Key findings

  • The intervention did not significantly affect the primary outcome of red-flag improvement/resolution at 4-6 months (aOR 0.96 [95% CI, 0.57-1.63]; P = .88) or worsening (aOR 1.31 [95% CI, 0.84-2.04]; P = .86).
  • Clinicians in the intervention group were more likely to probe contextual red flags (59.4% vs 50.2%; aOR 2.12 [95% CI, 1.14-3.93]; P = .02) and to incorporate contextual factors into care plans (57.7% vs 50.1%; aOR 2.67 [95% CI, 1.32-5.41]; P = .006).
  • Across groups, contextualized plans were associated with higher likelihood of improved red flags (aOR 2.13 [95% CI, 1.38-3.28]; P = .001) and lower likelihood of worsened red flags (aOR 0.67 [95% CI, 0.45-0.99]; P = .046).
  • When the EHR populated a contextual care box or activated alerts before the visit, probing increased (aOR 3.64 [95% CI, 1.18-11.20]; P = .02), incorporation into care plans increased (aOR 11.27 [95% CI, 2.27-55.85]; P = .003), and red flags were less likely to worsen at 4 months (aOR 0.19 [95% CI, 0.05-0.73]; P = .02), though not more likely to improve (aOR 0.75 [95% CI, 0.30-1.89]; P = .55).

Methods

  • Randomized multicenter clinical trial at 2 academic health centers in Chicago using 2 different EHRs (Cerner and Epic), with primary care attending clinicians and English-speaking adult patients; 452 visits were analyzed, involving 36 physicians and 3 advanced practice nurses.
  • Patients completed a previsit questionnaire about life challenges and carried a concealed audio recorder into visits; patients were randomized 2:3 to contextualized CDS (intervention) or usual care (control), and coders assessing red flags, probing, contextual factors, and 6-month outcomes were blinded to group.
  • The primary end point was the proportion of contextual red flags improved/resolved vs worsened/no change 6 months after the visit; secondary end points were clinician probing of red flags and incorporation of contextual factors into the care plan, analyzed with logistic mixed-effects models on an intention-to-treat basis using R, version 3.6, with two-sided P < .05.

Limitations

  • The paper states that some outcomes were inherently subjective, though blinded coders should not skew results; clinicians could not be blinded because they can tell when receiving contextualized CDS, so they might try harder independent of the CDS.
  • The paper states that the real intervention effect may be larger than found because control-group patients also completed the questionnaire, which may have primed them to raise contextual red flags and factors.
  • The paper notes that CDS impact is limited by available resources for helping patients with different contextual factors, and future work should assess effectiveness when patients do not have assistance completing the questionnaire, because CDS would then rely only on EHR-derived data.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1001/jamanetworkopen.2022.38231

Cites

20 of 20 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

6 of 13 cited sources checked · 3 supported · 0 flagged · accuracy not yet measured

  • Findingcitation

    Factors identified through probing were much more likely to be incorporated into care plans than those that were not (aOR, 61.65 [95% CI, 21.92-173.42]; P < .001).

    “As in past studies, factors identified through probing were additionally much more likely to be incorporated into care plans than those that were not (aOR, 61.65 [95% CI, 21.92-173.42]; P < .001) (Table 1 in eAppendix 6 in Supplement 2).17”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [17] Schwartz A, Weiner SJ, Binns-Calvey A, Weaver FM. Providers contextualise care more often when they discover patient context by asking: meta-analysis of three primary data sets. BMJ Qual Saf. 2016; 25(3): 159- 163. doi: 10.1136/bmjqs-2015-004283 26202131 source
  • Interpretationcitation

    The capacity of contextualized CDS to change outcomes is limited, to a varying degree, by the resources available to help patients and the contextual factor.

    “The capacity of contextualized CDS to change outcomes is limited, to a varying degree, by the resources available to help patients and the contextual factor.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [20] Binns-Calvey AE, Malhiot A, Kostovich CT,. Validating domains of patient contextual factors essential to preventing contextual errors: a qualitative study conducted at Chicago Area Veterans Health Administration sites. Acad Med. 2017; 92(9): 1287- 1293. doi: 10.1097/ACM.0000000000001659 28353498 source

      The Interpersonal/social support section (p. 2) asks how relationships and transportation affect patients’ health management, and Technology/Resources (p. 3) asks about technology use. Searches for contextualized clinical decision support, outcome changes, and limits imposed by available resources found no passage addressing the claimed relationship. (LLM, conf=0.70)

      Experimental — accuracy not yet measured
  • Premisecitation

    Contextualizing care is associated with partial or complete resolution of the presenting contextual red flag, a meaningful health care outcome.

    “Contextualizing care is clinically important because it is associated with partial or complete resolution of the presenting contextual red flag, a meaningful health care outcome.5”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [5] Weiner S, Schwartz A, Altman L,. Evaluation of a patient-collected audio audit and feedback quality improvement program on clinician attention to patient life context and health care costs in the Veterans Affairs health care system. JAMA Netw Open. 2020; 3(7): e209644. doi: 10.1001/jamanetworkopen.2020.9644 32735338 PMC7395234 source
  • Premisecitation

    Efforts to improve contextualization of care through audit and feedback have achieved measurable but limited success.

    “Efforts to improve contextualization of care through audit and feedback have achieved measurable but limited success.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [5] Weiner S, Schwartz A, Altman L,. Evaluation of a patient-collected audio audit and feedback quality improvement program on clinician attention to patient life context and health care costs in the Veterans Affairs health care system. JAMA Netw Open. 2020; 3(7): e209644. doi: 10.1001/jamanetworkopen.2020.9644 32735338 PMC7395234 source
  • Interpretationcitation

    Contextualized CDS can guide contextually informed decision making by drawing on data specific to the life circumstances and behaviors of individual patients.

    “Just as CDS can guide biomedically focused decision-making by drawing on data from evidence-based guidelines and other forms of research evidence, it can also guide contextually informed decision making by drawing on data specific to the life circumstances and behaviors of individual patients.18”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [18] Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit Med. 2020; 3: 17. doi: 10.1038/s41746-020-0221-y 32047862 PMC7005290 source

      The Introduction says CDSS matches individual patient characteristics to a knowledge base to produce patient-specific recommendations. The Patient-facing decision support section describes records that can collect insurance coverage and patient-entered information, while the Operational impact section mentions collecting medication-adherence data. These passages support the use of individualized data, but do not establish that CDS uses patients’ life circumstances and behaviors to guide contextually informed decisions. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • May combine two claims. 6
  • Classified as probably not a substantial claim. 9
  • May combine two claims.

    Premisecitation

    In a large prior study, audit and feedback increased clinician attention to patient contextual factors from 67% to 72%, but 28% of contextual factors remained unaddressed.

    “Attention to patient contextual factors increased from 67% to 72%, with a greater likelihood of improved outcomes compared with a control group, resulting in an estimated cost savings of $25.2 million from avoided hospitalizations. Although the intervention was effective, 28% of contextual factors remained unaddressed.5”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [5] Weiner S, Schwartz A, Altman L,. Evaluation of a patient-collected audio audit and feedback quality improvement program on clinician attention to patient life context and health care costs in the Veterans Affairs health care system. JAMA Netw Open. 2020; 3(7): e209644. doi: 10.1001/jamanetworkopen.2020.9644 32735338 PMC7395234 source

      The Results report that clinicians addressed 67% of contextual factors before feedback and 72% afterward, leaving 28% unaddressed. They also report better outcomes for contextualized than noncontextualized care plans, and estimate $25.2 million in savings from avoided hospitalizations. The outcomes comparison was not described as a comparison with a control group. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    Patients were randomized 2:3 to either contextualized CDS or usual care using computer-generated randomization.

    “Patients were randomized 2:3 to either contextualized CDS (intervention) or usual care (control) using computer-generated randomization.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Study design and conductnone given

    For each red flag, coders prospectively defined the conditions under which the red flag would be considered improved or worsened.

    “For each red flag, coders prospectively defined the conditions under which the red flag would be considered improved or worsened in the future.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The ordered logit model produced the same conclusions as the primary model (proportional odds aOR associated with contextualized plan, 1.76 [95% CI, 1.23-2.50]; P = .002).

    “The ordered logit model produced the same conclusions (proportional odds aOR associated with contextualized plan, 1.76 [95% CI, 1.23-2.50]; P = .002).”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    It was not possible to blind clinicians to study group because the intervention is a set of novel CDS tools not available in usual care.

    “Although patients were blinded as to whether they were in the intervention or control group, it was not possible to blind clinicians because the intervention is a set of novel CDS tools that are not available in usual care.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim.

    Study design and conductown data

    Research assistants who coded visits and tracked outcomes were blind to assignment.

    “After each encounter, research assistants (A.B.-C. and S.I.), who were blind to the assignment of each patient to the intervention or the control group, accessed the EHR and listened to the audio recording to identify contextual red flags”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Study design and conductnone given

    All analyses were performed on an intention-to-treat basis.

    “All analyses were performed on an intention-to-treat basis using R, version 3.6 (R Core Team).”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    Information about patients' life circumstances and behaviors is essential to identify and address in care planning to achieve desired outcomes; however, it is often overlooked.

    “Information about patients’ life circumstances and behaviors (ie, patient life context) is essential to identify and address in care planning to achieve desired outcomes; however, it is often overlooked.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Randomized assignments were available to research personnel responsible for activating the CDS tools immediately before the encounter, but those involved in coding visits and tracking outcomes were blinded.

    “Randomized assignments were available to research personnel responsible for activating the CDS tools immediately before the encounter, but those involved in coding visits and tracking outcomes were blinded.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationown data

    CDS improved contextualization of care, suggesting that the technology has the potential to improve patient outcomes.

    “This study found that CDS improved contextualization of care, suggesting that the technology has the potential to improve patient outcomes.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Study design and conductown data

    Patients did not differ between groups in demographic characteristics, numbers of red flags available before or during the visit, or whether they chose to reveal the audio recorder.

    “Table 2 presents unique patient characteristics by study group at the first visit; patients did not differ between groups in demographic characteristics, numbers of red flags available before or during the visit, or whether they chose to reveal the audio recorder or keep it concealed.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    Contextualized CDS has the advantage of being readily scalable.

    “Contextualized CDS has the advantage of being readily scalable.”
    Quote in the paperNot a substantial claim
12 of 12

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Alert outcome is described at both four and six months

    Minor

    The methods specify the exploratory effect of alerts on red flags six months later, whereas the corresponding result describes worsening four months later.

  • Seven repeat patients do not match the visit and patient totals

    Minor

    The paper reports 452 visits and 447 unique patients, a difference of 5 visits. If seven patients each had two visits in the study, the difference would be at least 7.

    Reported 7 · recomputed 5

  • Percentage revealing the audio recorder is incorrect

    Minor

    Table 2 lists 77 patients who revealed the recorder out of 447 patients overall. That is 17.2%, not 10.2%.

    Reported 10.2 · recomputed 17.225951

3 of 3

Cites

Flagged first, then by citations

Cited by

Still being checked.

Authors
Weiner, S. J., Schwartz, A., Weaver, F., Galanter, W., Olender, S., Kochendorfer, K., Binns-Calvey, A., Saini, R., Iqbal, S., Diaz, M., Michelfelder, A., & Varkey, A.
Affiliations
  • Edward Hines, Jr. VA Hospital (US)
  • University of Illinois Chicago (US)
  • Loyola University Chicago (US)
  • Department of Medicine, College of Medicine, University of Illinois Chicago
  • Dignity Health, Pacific Central Coast Health Centers, Arroyo Grande, California
  • Oak Street Health, East Point, Georgia
Corresponding author
Weiner, Saul J.
Venue
JAMA Network Open
Published
2022-10-24
Volume
5
Issue
10
Pages
e2238231
ISSN
2574-3805 (ISSN-L)
OpenAlex
W4307299474
Cited by
26
References
20
Citations by year
2026: 8 · 2025: 9 · 2024: 5 · 2023: 4
FWCI
3.38
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JAMA Network Open (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
Agency for Healthcare Research and Quality (1r01hs025374-01, R01 HS025374)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Keywords
contextual factors, care planning, electronic health record alerts, primary care, patient-clinician communication, patient-centered care, health information technology implementation
MeSH terms
Academic Medical Centers, Adult, Female, Humans, Middle Aged, Decision Support Systems, Clinical, Electronic Health Records

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