Integrating Contextual Factors Into Clinical Decision Support

NCT ID: NCT03244033

Last Updated: 2023-01-10

Study Results

Results available

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Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

452 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-09-01

Study Completion Date

2021-11-12

Brief Summary

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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:

1. 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.
2. 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.
3. Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.

Detailed Description

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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:

1. 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.
2. 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.
3. 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.

Conditions

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Medical Errors Decision Support Systems, Clinical Diagnostic Errors

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

SINGLE

Outcome Assessors

Study Groups

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Contextual Survey + Contextual CDS

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.

Group Type EXPERIMENTAL

Contextual clinical decision support

Intervention Type OTHER

Incorporation of contextual data into EHR clinical decision support alerts

Contextual survey

Intervention Type BEHAVIORAL

Patients complete a survey asking about red flags that could signal contextual factors relevant to their care

Contextual Survey Only

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.

Group Type ACTIVE_COMPARATOR

Contextual survey

Intervention Type BEHAVIORAL

Patients complete a survey asking about red flags that could signal contextual factors relevant to their care

Interventions

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Contextual clinical decision support

Incorporation of contextual data into EHR clinical decision support alerts

Intervention Type OTHER

Contextual survey

Patients complete a survey asking about red flags that could signal contextual factors relevant to their care

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* 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.

Exclusion Criteria

* • Patients with emergent or unscheduled visits or who do not speak English.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Agency for Healthcare Research and Quality (AHRQ)

FED

Sponsor Role collaborator

Loyola University

OTHER

Sponsor Role collaborator

University of Illinois at Chicago

OTHER

Sponsor Role lead

Responsible Party

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Alan Schwartz

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Saul J Weiner, MD

Role: PRINCIPAL_INVESTIGATOR

University of Illinois at Chicago

Locations

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University of Illinois at Chicago

Chicago, Illinois, United States

Site Status

Loyola University Medical Center

Maywood, Illinois, United States

Site Status

Countries

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United States

References

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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.

Reference Type DERIVED
PMID: 36279133 (View on PubMed)

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

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R01HS025374

Identifier Type: AHRQ

Identifier Source: secondary_id

View Link

2017-0555

Identifier Type: -

Identifier Source: org_study_id

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