Effect of Electronic Health Record Clinical Decision Support on Contextualization of Care
Open accessAbstract
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
Cites
Statistics
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
- Findingown data
When the EHR populated the CCB or activated alerts for red flags before the visit, the likelihood of the clinician probing the red flag increased significantly (aOR, 3.64 [95% CI, 1.18-11.20]; P = .02).
“When the EHR populated the CCB or activated alerts for red flags before the start of the visit (ie, from the patient questionnaire or EHR triggers), the likelihood of the clinician probing the red flag increased significantly (aOR, 3.64 [95% CI, 1.18-11.20]; P = .02)”
Quote in the paperSubstantial claim - Findingown data
Customized clinical decision support (CDS) tools did not improve patient outcomes in this randomized clinical trial.
“In this randomized clinical trial that included 452 audio-recorded patient encounters, customized CDS tools did not improve patients’ outcomes but significantly improved contextualization of their care.”
- Also stated in: § Outcomes · plain
“For the primary end point, the study group did not have additional significant impact on outcomes beyond its impact on plans (adjusted odds ratio [aOR] for improvement, 0.96 [95% CI, 0.57-1.63; P = .88]; aOR for worsening, 1.31 [95% CI, 0.84-2.04; P = .86) (Table 4).”
- Also stated in: § Discussion · plain
“In this randomized clinical trial, CDS tools did not improve patient outcomes; however, these tools increased the likelihood that a physician would address relevant patient life context in their care plan.”
Quote in the paperSubstantial claim - Also stated in: § Outcomes · plain
- Findingown data
Factors selected by patients on the previsit questionnaire were not more likely to be incorporated into care plans (aOR, 1.42 [95% CI, 0.57-3.54]; P = .45).
“but factors selected by patients on the previsit questionnaire were not (aOR, 1.42 [95% CI, 0.57-3.54]; P = .45).”
Quote in the paperNot a substantial claim - Findingown data
Red flags selected on the previsit questionnaire were less likely to be probed than those expressed orally during the visit (aOR, 0.15 [95% CI, 0.07-0.30]; P < .001).
“In addition, red flags selected on the previsit questionnaire were less likely to be probed than those expressed orally during the visit (aOR, 0.15 [95% CI, 0.07-0.30]; P < .001) (Table 1 in eAppendix 6 in Supplement 2).”
Quote in the paperNot a substantial claim - Findingown data
Factors spontaneously revealed by patients were more likely to be incorporated into care plans (aOR, 8.55 [95% CI, 3.98-18.36]; P < .001).
“Factors spontaneously revealed by patients were also more likely to be incorporated (aOR, 8.55 [95% CI, 3.98-18.36]; P < .001)”
Quote in the paperNot a substantial claim - Findingown data
Physicians in the intervention group were more likely to probe red flags than physicians in the control group (aOR, 2.12 [95% CI, 1.14-3.93]; P = .02).
“Physicians in the intervention group were more likely to probe red flags than physicians in the control group (aOR, 2.12 [95% CI, 1.14-3.93]; P = .02) (Table 4).”
Quote in the paperSubstantial claim - Findingown data
Customized CDS tools significantly improved contextualization of care, measured as clinician incorporation of contextual factors into the care plan.
“In this randomized clinical trial that included 452 audio-recorded patient encounters, customized CDS tools did not improve patients’ outcomes but significantly improved contextualization of their care.”
- Also stated in: § Outcomes · plain
“Factors in the intervention group had a higher likelihood of incorporation into the care plan (aOR, 2.67 [95% CI, 1.32-5.41]; P = .006) (Table 4).”
- Also stated in: § Discussion · plain
“In this randomized clinical trial, CDS tools did not improve patient outcomes; however, these tools increased the likelihood that a physician would address relevant patient life context in their care plan.”
Quote in the paperSubstantial claim - Also stated in: § Outcomes · plain
- Findingown data
There was no effect of whether the recorder was visible or concealed on probing (aOR, 1.57 [95% CI, 0.63-3.96]; P = .34).
“There was no effect of whether the recorder was visible or concealed (aOR, 1.57 [95% CI, 0.63-3.96]; P = .34).”
Quote in the paperNot a substantial claim - Findingown data
When a factor was present, the likelihood of incorporating it into the care plan increased when the EHR populated the CCB or activated alerts (aOR, 11.27 [95% CI, 2.27-55.85]; P = .003).
“and when a factor was present, the likelihood of incorporating it into the care plan also increased (aOR, 11.27 [95% CI, 2.27-55.85]; P = .003).”
Quote in the paperSubstantial claim - Findingown data
Across groups, contextualized plans were associated with a significantly lower likelihood of a worsened red flag outcome (aOR, 0.67 [95% CI, 0.45-0.99]; P = .046).
“and a significantly lower likelihood of a worsened red flag outcome (aOR, 0.67 [95% CI, 0.45-0.99]; P = .046).”
Quote in the paperSubstantial claim - Findingown data
When the red flag was the subject of an alert, it was less likely to have worsened 4 months later (aOR, 0.19 [95% CI, 0.05-0.73]; P = .02).
“In addition, when the red flag was the subject of an alert, it was less likely to have worsened 4 months later (aOR, 0.19 [95% CI, 0.05-0.73]; P = .02)”
Quote in the paperSubstantial claim - Findingown data
When the red flag was the subject of an alert, it was not more likely to have been improved (aOR, 0.75 [95% CI, 0.30-1.89]; P = .55), beyond the effect of whether the care plan had been contextualized.
“but not more likely to have been improved (aOR, 0.75 [95% CI, 0.30-1.89]; P = .55), beyond the effect of whether the care plan had been contextualized.”
Quote in the paperNot a substantial claim - Findingown data
There was no effect of whether the recorder was visible or concealed on incorporation into care plans (aOR, 0.86 [95% CI, 0.28-2.66]; P = .79).
“There was no effect of whether the recorder was visible or concealed (aOR, 0.86 [95% CI, 0.28-2.66]; P = .79).”
Quote in the paperNot a substantial claim - Findingown data
Across groups, contextualized plans were associated with a significantly higher likelihood of an improved red flag outcome (aOR, 2.13 [95% CI, 1.38-3.28]; P = .001).
“However, across groups, contextualized plans were associated with a significantly higher likelihood of an improved red flag outcome (aOR, 2.13 [95% CI, 1,38-3.28]; P = .001) (Table 1 in eAppendix 6 in Supplement 2)”
Quote in the paperSubstantial claim - Premisecitation
Clinicians address contextual factors 60% to 70% of the time.
“Clinicians address them 60% to 70% of the time, leaving substantial room for improvement.6,7”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [6] Weiner SJSA, Schwartz A, Sharma G,. Patient-centered decision making and health care outcomes: an observational study. Ann Intern Med. 2013; 158(8): 573- 579. doi: 10.7326/0003-4819-158-8-201304160-00001 23588745 source
- cites [7] Weiner SJ, Schwartz A, Weaver F,. Contextual errors and failures in individualizing patient care: a multicenter study. Ann Intern Med. 2010; 153(2): 69- 75. doi: 10.7326/0003-4819-153-2-201007200-00002 20643988 source
- Interpretationown data
The finding that physicians pay less attention to contextual red flags presented to them by CDS than those presented directly by the patient points to a limitation of this technology.
“The finding that physicians pay less attention to contextual red flags presented to them by CDS than those presented directly by the patient points to a limitation of this technology.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The study had 80% power to detect an absolute increase in contextualization rates from 50% to 75% with recordings from 192 intervention and 288 control patients.
“Based on the number of contextual red flags and factors we expected, we determined that to obtain 80% power to detect an absolute increase in contextualization rates when factors were present from 50% to 75%, we would need recordings from 192 intervention and 288 control patients (which also provides at least 80% power to detect the expected increase in probing).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [6] Weiner SJSA, Schwartz A, Sharma G,. Patient-centered decision making and health care outcomes: an observational study. Ann Intern Med. 2013; 158(8): 573- 579. doi: 10.7326/0003-4819-158-8-201304160-00001 23588745 source
- cites [16] Weiner SJ, Schwartz A, Sharma G,. Patient-collected audio for performance assessment of the clinical encounter. Jt Comm J Qual Patient Saf. 2015; 41(6): 273- 278. doi: 10.1016/S1553-7250(15)41037-2 25990893 source
- Premisecitation
Approximately 40% to 50% of patient presentations contain contextual factors.
“Although not all patient presentations contain contextual factors, approximately 40% to 50% do.6”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [6] Weiner SJSA, Schwartz A, Sharma G,. Patient-centered decision making and health care outcomes: an observational study. Ann Intern Med. 2013; 158(8): 573- 579. doi: 10.7326/0003-4819-158-8-201304160-00001 23588745 source
- Study design and conductreasoning
Because coders are blinded as to study group, the subjectivity of some outcomes should not skew the results.
“Because coders are blinded as to study group, this limitation should not skew the results.”
Quote in the paperNot a substantial claim - Interpretationown data
This is the first study to demonstrate that CDS tools built into the EHR can decrease contextual errors.
“Although it has been previously established that contextual errors are common, that they adversely affect patient outcomes, and that clinicians can learn to make fewer of them with feedback,8 this is the first study, to our knowledge, to demonstrate that CDS tools built into the EHR can decrease contextual errors.”
Quote in the paperSubstantial claim - Premisecitation
Loss of control of a chronic condition, missed appointments, and frequent emergency department visits are contextual red flags that improve when their underlying contextual factors are addressed.
“Loss of control of a chronic condition, missed appointments, and frequent emergency department visits are all examples of contextual red flags that improve when their underlying contextual factors are addressed.6”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [6] Weiner SJSA, Schwartz A, Sharma G,. Patient-centered decision making and health care outcomes: an observational study. Ann Intern Med. 2013; 158(8): 573- 579. doi: 10.7326/0003-4819-158-8-201304160-00001 23588745 source
- Interpretationreasoning
The real effect of the intervention may be larger than what was found, because patients in both study groups completed the questionnaire, which may have primed control group patients to raise contextual red flags and factors.
“Finally, the real effect of the intervention may be larger than what was found, because we had patients in both study groups complete the questionnaire, which may have primed those in the control group to raise contextual red flags and factors.”
Quote in the paperNot a substantial claim - Interpretationown data
The lack of an effect of the visible recorder on clinician probing suggests that clinicians were not motivated to change their behavior just because they knew they were in a study.
“Furthermore, the lack of an effect of the visible recorder on clinician probing suggests that they were not motivated to change their behavior just because they knew they were in a study.”
Quote in the paperNot a substantial claim - Study design and conductcitation
Trained coders achieve approximately 85% interrater agreement about whether a care plan is contextualized.
“Trained coders achieve approximately 85% interrater agreement about whether a care plan is contextualized or not.15”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [15] Weiner SJ, Kelly B, Ashley N,. Content coding for contextualization of care: evaluating physician performance at patient-centered decision making. Med Decis Making. 2014; 34(1): 97- 106. doi: 10.1177/0272989X13493146 23784847 source
- May combine two claims. 6
- Classified as probably not a substantial claim. 9
May combine two claims.
PremisecitationIn 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 dataPatients 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 claimClassified as probably not a substantial claim.
Study design and conductnone givenFor 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 claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe 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 claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningIt 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 claimClassified as probably not a substantial claim.
Study design and conductown dataResearch 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 claimClassified as probably not a substantial claim.
Study design and conductnone givenAll 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 claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
Interpretationnone givenInformation 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 claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductnone givenRandomized 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 claimMay combine two claims.
Interpretationown dataCDS 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 claimMay combine two claims.
Study design and conductown dataPatients 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 claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenContextualized CDS has the advantage of being readily scalable.
“Contextualized CDS has the advantage of being readily scalable.”
Quote in the paperNot a substantial claim
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
MinorThe methods specify the exploratory effect of alerts on red flags six months later, whereas the corresponding result describes worsening four months later.
“the effect of the alerts on the red flags 6 months later.”
“when the red flag was the subject of an alert, it was less likely to have worsened 4 months later”
Seven repeat patients do not match the visit and patient totals
MinorThe 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
“Seven patients had 2 visits scheduled during the course of the study; each visit was individually randomized.”
Percentage revealing the audio recorder is incorrect
MinorTable 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
“| Yes | 49 (18.1) | 28 (15.9) | 77 (10.2) |”
Cites
An overview of clinical decision support systems: Benefits, risks, and strategies for success
Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0221-y · Cited by 3,019 · see citing works
McCambridge, J., Witton, J., & Elbourne, D. R. (2014) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2013.08.015 · Cited by 2,748 · see citing works
Improving Outcomes with Clinical Decision Support: An Implementer's Guide, Second Edition
Osheroff, J. (2012) · doi:10.4324/9781498757461 · Cited by 517 · see citing works
Contextual Errors and Failures in Individualizing Patient Care
Weiner, S. J., Schwartz, A., Weaver, F., Goldberg, J., Yudkowsky, R., Sharma, G., Binns-Calvey, A., Preyss, B., M. Schapira, M., Persell, S. D., et al. (2010) · Annals of Internal Medicine · doi:10.7326/0003-4819-153-2-201007200-00002 · Cited by 214 · see citing works
Self-citationPatient-Centered Decision Making and Health Care Outcomes: An Observational Study
Weiner, S. J., Schwartz, A., Sharma, G., Binns-Calvey, A., Ashley, N., Kelly, B., Dayal, A., Patel, S., Weaver, F. M., & Harris, I. (2013) · Annals of Internal Medicine · doi:10.7326/0003-4819-158-8-201304160-00001 · Cited by 212 · see citing works
Self-citationEncyclopedia of Medical Decision Making
Kattan, M. W. (2009) · Sage eBooks · doi:10.4135/9781412971980 · Cited by 133 · see citing works
Contextualizing medical decisions to individualize care
Weiner, S. J. (2004) · Journal of General Internal Medicine · doi:10.1111/j.1525-1497.2004.30261.x · Cited by 125 · see citing works
Self-citationContextual Errors in Medical Decision Making: Overlooked and Understudied
Weiner, S. J., & Schwartz, A. (2015) · Academic Medicine · doi:10.1097/acm.0000000000001017 · Cited by 113 · see citing works
Self-citationContextualizing care: An essential and measurable clinical competency
Weiner, S. J. (2021) · Patient Education and Counseling · doi:10.1016/j.pec.2021.06.016 · Cited by 63 · see citing works
Self-citationWeiner, S., Schwartz, A., Altman, L., Ball, S., Bartle, B., Binns-Calvey, A., Chan, C., Falck-Ytter, C., Frenchman, M., Gee, B., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.9644 · Cited by 60 · see citing works
Self-citationWeiner, S. J., Kelly, B., Ashley, N., Binns-Calvey, A., Sharma, G., Schwartz, A., & Weaver, F. M. (2014) · Medical Decision Making · doi:10.1177/0272989x13493146 · Cited by 57 · see citing works
Self-citationSchwartz, A., Weiner, S. J., Binns-Calvey, A., & Weaver, F. M. (2016) · BMJ Quality & Safety · doi:10.1136/bmjqs-2015-004283 · Cited by 48 · see citing works
Self-citationCo, Z., Holmgren, A. J., Classen, D. C., Newmark, L. P., Seger, D. L., Danforth, M., & Bates, D. W. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa098 · Cited by 40 · see citing works
Weiner, S. J., Schwartz, A., Yudkowsky, R., et al. (2007) · Medical Decision Making · doi:10.1177/0272989x07306113 · Cited by 38 · see citing works
Self-citationPatient-collected audio for performance assessment of the clinical encounter
Weiner, S. J., Schwartz, A., Sharma, G., Binns-Calvey, A., Ashley, N., Kelly, B., & Weaver, F. M. (2015) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(15)41037-2 · Cited by 27 · see citing works
Self-citationBinns-Calvey, A. E., Malhiot, A., Kostovich, C. T., LaVela, S. L., Stroupe, K., Gerber, B. S., Burkhart, L., Weiner, S. J., & Weaver, F. M. (2017) · Academic Medicine · doi:10.1097/acm.0000000000001659 · Cited by 24 · see citing works
Self-citationListening to the Patient: A Typology of Contextual Red Flags in Disease Management Encounters
Binns–Calvey, A., Sharma, G., Ashley, N., Kelly, B., Weaver, F. M., & Weiner, S. J. (2020) · Journal of patient-centered research and reviews · doi:10.17294/2330-0698.1725 · Cited by 23 · see citing works
Self-citationWeiner, S. J., & Schwartz, A. (2015) · doi:10.1093/med/9780190228996.001.0001 · Cited by 19 · see citing works
Self-citationWeaver, F. M., Binns–Calvey, A., González, B., Kostovich, C. T., LaVela, S. L., Stroupe, K. T., Kelly, B., Ashley, N., Miskevics, S. A., Gerber, B. S., et al. (2019) · MDM Policy & Practice · doi:10.1177/2381468319852334 · Cited by 8 · see citing works
Self-citationAdvancing Health Equity by Avoiding Judgmentalism and Contextualizing Care
Weiner, S. J. (2021) · The AMA Journal of Ethic · doi:10.1001/amajethics.2021.91 · Cited by 7 · see citing works
Self-citation
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- 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
- Publisher
- American Medical Association (AMA)
- Published
- 2022-10-24
- Volume
- 5
- Issue
- 10
- Pages
- e2238231
- ISSN
- 2574-3805 (ISSN-L)
- PMC
- PMC9593230
- OpenAlex
- W4307299474
- Semantic Scholar
- f1b599432355858c345ccde4eafa816bd300f2d4
- 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
- gold
- doi.org
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-28.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-28.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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