Integrating Contextual Factors Into Clinical Decision Support

April 12, 2022 updated by: Alan Schwartz, University of Illinois at Chicago

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:

  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.

Study Overview

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:

  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.

Study Type

Interventional

Enrollment (Actual)

452

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Illinois
      • Chicago, Illinois, United States, 60612
        • University of Illinois at Chicago
      • Maywood, Illinois, United States, 60153
        • Loyola University Medical Center

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: 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.
Incorporation of contextual data into EHR clinical decision support alerts
Patients complete a survey asking about red flags that could signal contextual factors relevant to their care
Active Comparator: 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.
Patients complete a survey asking about red flags that could signal contextual factors relevant to their care

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Resolution of Contextual Red Flags
Time Frame: 6-9 months following index visit
Proportion of red flags noted at index visit that have resolved
6-9 months following index visit

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Probing of Contextual Red Flags
Time Frame: At index visit
Proportion of red flags which the examining physician probes
At index visit
Planning for Contextual Factors
Time Frame: At index visit
Proportion of contextual factors identified during visit that are incorporated into care plan
At index visit

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Saul J Weiner, MD, University of Illinois at Chicago

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 1, 2018

Primary Completion (Actual)

November 12, 2021

Study Completion (Actual)

November 12, 2021

Study Registration Dates

First Submitted

July 31, 2017

First Submitted That Met QC Criteria

August 4, 2017

First Posted (Actual)

August 9, 2017

Study Record Updates

Last Update Posted (Estimate)

January 10, 2023

Last Update Submitted That Met QC Criteria

April 12, 2022

Last Verified

April 1, 2022

More Information

Terms related to this study

Other Study ID Numbers

  • 2017-0555 (Other Identifier: M D Anderson Cancer Center)
  • R01HS025374 (U.S. AHRQ Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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