Medical ErrorsNCT03244033
Integrating Contextual Factors Into Clinical Decision Support
A study testing Contextual clinical decision support and Contextual survey in people with Medical Errors and Decision Support Systems, Clinical, run by University of Illinois at Chicago at 2 sites in United States.
Trial summary
Preventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Medical Errors, Decision Support Systems, Clinical, Diagnostic Errors
- What is being tested?
- Contextual clinical decision support and Contextual survey
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 452 participants
- Where
- 2 sitesUnited States
- Study dates
- 1 Sep 2018to 12 Nov 2021
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- English-speaking adult patients presenting to outpatient primary care clinics for scheduled appointments who can be contacted in advance of their appointment and the clinicians (physicians or nurse practitioners) seeing those patients at those visits.
Who cannot join
- • Patients with emergent or unscheduled visits or who do not speak English.
Trial locations and contacts
2 sites in 1 country.
United States2 sites
University of Illinois at Chicago
Chicago, Illinois, 60612
Loyola University Medical Center
Maywood, Illinois, 60153
About this study
Official title: Integrating Contextual Factors Into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care
Preventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. An effective intervention would prompt clinicians to determine whether there are underlying contextual factors that could be addressed in the care plan, averting contextual error. This desirable process is termed contextual probing.
While clinical decision support (CDS) has been used to provide physicians with timely biomedical information at the point of care to prevent errors and promote appropriate care, this technology also affords an opportunity to draw physician attention to both contextual red flags and contextual factors in order to avert contextual errors. This study assesses the potential of "contextualized CDS" to improve contextualization of care through a randomized controlled intervention trial, with assessment measures of both patient health care outcomes and averted costs associated with overuse and misuse of medical services. The three hypotheses are that CDS:
- Reduces contextual error: CDS tools that inform clinicians of contextual factors and prompt them to explore contextual red flags should result in a reduction in contextual error.
- Improve health care outcomes: Contextualized CDS predicts improved health care outcomes defined as a partial or full resolution of the contextual red flag (e.g. elevated HgB A1c) after the index visit.
- Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.
Read the detailed description
The term patient context refers to the myriad contextual factors in patients' lives that complicate the application of research evidence to patient care. For instance, the inability of a patient to afford a medication for a particular condition is a contextual factor. Contextual factors can be addressed when correctly identified. Substituting a low cost generic for a high cost brand name medication may enable a patient to afford a medication. Addressing contextual factors in a care plan is termed contextualizing care. Conversely, the failure to address a contextual factor when it is feasible to so is a contextual error, because it results in an inappropriate plan of care. In sum, contextual errors are medical errors caused by inattention to patient context. They are common and linked to both diminished health care outcomes and an increase in health care costs related to overuse and misuse of medical services. These findings were determined using a validated method for coding audio recorded data called Content Coding for Contextualization of Care ("4C") collected during the encounters by both real patients, and by unannounced standardized patients (USPs) employing checklists.
Preventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. An effective intervention would prompt clinicians to determine whether there are underlying contextual factors that could be addressed in the care plan, averting contextual error. This desirable process is termed contextual probing.
While clinical decision support (CDS) has been used to provide physicians with timely biomedical information at the point of care to prevent errors and promote appropriate care, this technology also affords an opportunity to draw physician attention to both contextual red flags and contextual factors in order to avert contextual errors. This study assesses the potential of "contextualized CDS" to improve contextualization of care through a randomized controlled intervention trial, with assessment measures of both patient health care outcomes and averted costs associated with overuse and misuse of medical services. The three hypotheses are that CDS:
- Reduces contextual error: CDS tools that inform clinicians of contextual factors and prompt them to explore contextual red flags should result in a reduction in contextual error.
- Improve health care outcomes: Contextualized CDS predicts improved health care outcomes defined as a partial or full resolution of the contextual red flag (e.g. elevated HgB A1c) after the index visit.
- Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.
To test the hypotheses, patients who consent to participate will be randomized to usual care or care enhanced with contextualized CDS. Participants will audio record their visits, and the data will be coded using 4C. They will be followed several months after the index visit for assessment of outcomes by blinded assessors using an established tracking method. In addition, USPs presenting with cases containing complicating contextual factors that if overlooked result in overuse and misuse of medical services, will be employed to assess the third hypothesis, and to supplement the data obtained by observing the effects of contextual alerts on the care of real patients for the first hypothesis.
- Being tested
- Contextual clinical decision support, Contextual survey
- Keywords
- context, contextual error, contextual care, electronic medical record, clinical decision support
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Contextual clinical decision supportOther
Incorporation of contextual data into EHR clinical decision support alerts
Contextual surveyBehavioural
Patients complete a survey asking about red flags that could signal contextual factors relevant to their care
| Study group | Role | What they receive |
|---|---|---|
| Contextual Survey + Contextual CDS | Experimental | Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts. Receives: Other: Contextual clinical decision support; Behavioral: Contextual survey |
| Contextual Survey Only | Active comparator | Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts. Receives: Behavioral: Contextual survey |
What is being measured
The primary outcome is the main question the study is designed to answer.
Resolution of Contextual Red Flags
Proportion of red flags noted at index visit that have resolved
Measured: 6-9 months following index visit
Secondary outcomes (2)
Probing of Contextual Red Flags
Proportion of red flags which the examining physician probes
Measured: At index visit
Planning for Contextual Factors
Proportion of contextual factors identified during visit that are incorporated into care plan
Measured: At index visit
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Aug 2017
- Study start1 Sep 2018
- Primary completion12 Nov 2021
- Study completion12 Nov 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Medical ErrorsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 452 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Illinois at Chicago
- Sponsor type
- University, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ), Loyola University
- Responsible party
- Principal investigator, Alan Schwartz, University of Illinois at Chicago
- Investigators
- Saul J Weiner, MD, Principal investigator, University of Illinois at Chicago
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03244033
- Sponsor's protocol ID
- 2017-0555
- Other IDs
- R01HS025374
- Status last verified
- Apr 2022
- First submitted
- 31 Jul 2017
- Last updated
- 10 Jan 2023
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Weiner SJ, Schwartz A, Weaver F, Galanter W, Olender S, Kochendorfer K, Binns-Calvey A, Saini R, Iqbal S, Diaz M, Michelfelder A, Varkey A. Effect of Electronic Health Record Clinical Decision Support on Contextualization of Care: A Randomized Clinical Trial. JAMA Netw Open. 2022 Oct 3;5(10):e2238231. doi: 10.1001/jamanetworkopen.2022.38231.
PubMed 36279133
Study at a glance
From the registry record, last updated by the sponsor on 10 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Integrating Contextual Factors Into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care
- ClinicalTrials.gov ID
- NCT03244033
- Acronym / sponsor ID
- 2017-0555
- Keywords
- context, contextual error, contextual care, electronic medical record, clinical decision support
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 452 participants (actual)
- Lead sponsor
- University of Illinois at ChicagoUniversity, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ), Loyola University
- Study start
- 1 Sep 2018 (actual)
- Primary completion
- 12 Nov 2021 (actual)
- Study completion
- 12 Nov 2021 (actual)
- First posted
- 9 Aug 2017 (actual)
- Results
- Posted 10 Jan 2023
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Preventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. An effective intervention would prompt clinicians to determine whether there are underlying contextual factors that could be addressed in the care plan, averting contextual error. This desirable process is termed contextual probing.
While clinical decision support (CDS) has been used to provide physicians with timely biomedical information at the point of care to prevent errors and promote appropriate care, this technology also affords an opportunity to draw physician attention to both contextual red flags and contextual factors in order to avert contextual errors. This study assesses the potential of "contextualized CDS" to improve contextualization of care through a randomized controlled intervention trial, with assessment measures of both patient health care outcomes and averted costs associated with overuse and misuse of medical services. The three hypotheses are that CDS:
- Reduces contextual error: CDS tools that inform clinicians of contextual factors and prompt them to explore contextual red flags should result in a reduction in contextual error.
- Improve health care outcomes: Contextualized CDS predicts improved health care outcomes defined as a partial or full resolution of the contextual red flag (e.g. elevated HgB A1c) after the index visit.
- Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.
Detailed description
The term patient context refers to the myriad contextual factors in patients' lives that complicate the application of research evidence to patient care. For instance, the inability of a patient to afford a medication for a particular condition is a contextual factor. Contextual factors can be addressed when correctly identified. Substituting a low cost generic for a high cost brand name medication may enable a patient to afford a medication. Addressing contextual factors in a care plan is termed contextualizing care. Conversely, the failure to address a contextual factor when it is feasible to so is a contextual error, because it results in an inappropriate plan of care. In sum, contextual errors are medical errors caused by inattention to patient context. They are common and linked to both diminished health care outcomes and an increase in health care costs related to overuse and misuse of medical services. These findings were determined using a validated method for coding audio recorded data called Content Coding for Contextualization of Care ("4C") collected during the encounters by both real patients, and by unannounced standardized patients (USPs) employing checklists.
Preventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. An effective intervention would prompt clinicians to determine whether there are underlying contextual factors that could be addressed in the care plan, averting contextual error. This desirable process is termed contextual probing.
While clinical decision support (CDS) has been used to provide physicians with timely biomedical information at the point of care to prevent errors and promote appropriate care, this technology also affords an opportunity to draw physician attention to both contextual red flags and contextual factors in order to avert contextual errors. This study assesses the potential of "contextualized CDS" to improve contextualization of care through a randomized controlled intervention trial, with assessment measures of both patient health care outcomes and averted costs associated with overuse and misuse of medical services. The three hypotheses are that CDS:
- Reduces contextual error: CDS tools that inform clinicians of contextual factors and prompt them to explore contextual red flags should result in a reduction in contextual error.
- Improve health care outcomes: Contextualized CDS predicts improved health care outcomes defined as a partial or full resolution of the contextual red flag (e.g. elevated HgB A1c) after the index visit.
- Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.
To test the hypotheses, patients who consent to participate will be randomized to usual care or care enhanced with contextualized CDS. Participants will audio record their visits, and the data will be coded using 4C. They will be followed several months after the index visit for assessment of outcomes by blinded assessors using an established tracking method. In addition, USPs presenting with cases containing complicating contextual factors that if overlooked result in overuse and misuse of medical services, will be employed to assess the third hypothesis, and to supplement the data obtained by observing the effects of contextual alerts on the care of real patients for the first hypothesis.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Contextual Survey + Contextual CDS | Experimental | Other: Contextual clinical decision support, Behavioral: Contextual surveyContextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts. |
| Contextual Survey Only | Active comparator | Behavioral: Contextual surveyContextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- English-speaking adult patients presenting to outpatient primary care clinics for scheduled appointments who can be contacted in advance of their appointment and the clinicians (physicians or nurse practitioners) seeing those patients at those visits.
Key exclusion criteria (1 listed)
- • Patients with emergent or unscheduled visits or who do not speak English.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Contextual clinical decision supportIncorporation of contextual data into EHR clinical decision support alerts | Other | Contextual Survey + Contextual CDS |
| Contextual surveyPatients complete a survey asking about red flags that could signal contextual factors relevant to their care | Behavioural | Contextual Survey + Contextual CDS, Contextual Survey Only |
Primary outcome
Resolution of Contextual Red Flags
Time frame: 6-9 months following index visit
Proportion of red flags noted at index visit that have resolved
2 secondary outcomes
Probing of Contextual Red Flags
Time frame: At index visit
Planning for Contextual Factors
Time frame: At index visit
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Jan 2023.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Derived from this study: PubMed 36279133Weiner SJ, Schwartz A, Weaver F, Galanter W, Olender S, Kochendorfer K, Binns-Calvey A, Saini R, Iqbal S, Diaz M, Michelfelder A, Varkey A. Effect of Electronic Health Record Clinical Decision Support on Contextualization of Care: A Randomized Clinical Trial. JAMA Netw Open. 2022 Oct 3;5(10):e2238231. doi: 10.1001/jamanetworkopen.2022.38231.
- Individual participant dataSharing planned: No
Related trials for Medical Errors
Not yet recruiting
AI-Based Quality Control for Radiology Reporting
Radiology, Medical Errors
Not yet recruitingObservational study
Specialist Review of Harm Ratings for Clinical Responses Acronym: NOHARM
Patient Safety, Medical Errors
Recruiting
Pictographs for Preventing Wrong-Patient Errors in NICUs
Medical Errors, Electronic Medical Records
Recruiting
A Trial to Improve Family Clinical Note Access and Outcomes for Hospitalized Children
Hospitalized Child, Pediatric Patient Safety
Recruiting
Surgical Handwashing: Drying With One or Two Surgical Towels
Hand Hygiene, Surgical Wound Infection
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Saul J Weiner, MD principal investigator
University of Illinois at Chicago
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Contextual clinical decision support and Contextual survey in people with Medical Errors and Decision Support Systems, Clinical, run by University of Illinois at Chicago at 2 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 10 Jan 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 10 Jan 2023). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Resolution of Contextual Red Flags (time frame: 6-9 months following index visit). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03244033, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Jan 2023; AzTrials last refreshed its copy on 28 Oct 2026.