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Integrating Contextual Factors Into Clinical Decision Support

Integrating Contextual Factors Into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03244033
Enrollment
452
Registered
2017-08-09
Start date
2018-09-01
Completion date
2021-11-12
Last updated
2023-01-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Decision Support Systems, Clinical, Diagnostic Errors, Medical Errors

Keywords

context, contextual error, contextual care, electronic medical record, clinical decision support

Brief 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. 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

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.

Interventions

OTHERContextual clinical decision support

Incorporation of contextual data into EHR clinical decision support alerts

BEHAVIORALContextual survey

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

Sponsors

Agency for Healthcare Research and Quality (AHRQ)
CollaboratorFED
Loyola University
CollaboratorOTHER
University of Illinois at Chicago
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Outcomes Assessor)

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

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.

Design outcomes

Primary

MeasureTime frameDescription
Resolution of Contextual Red Flags6-9 months following index visitProportion of red flags noted at index visit that have resolved

Secondary

MeasureTime frameDescription
Probing of Contextual Red FlagsAt index visitProportion of red flags which the examining physician probes
Planning for Contextual FactorsAt index visitProportion of contextual factors identified during visit that are incorporated into care plan

Countries

United States

Participant flow

Recruitment details

570 patients were assessed for eligibility to participate across the clinics at the two sites. 118 declined to participate and were not randomized.

Participants by arm

ArmCount
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. Contextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts Contextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care
177
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. Contextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care
275
Total452

Baseline characteristics

CharacteristicContextual Survey OnlyTotalContextual Survey + Contextual CDS
Age, Customized
Adult (18 and older)
275 Participants452 Participants177 Participants
Clinic Site
Site 1
160 Participants278 Participants118 Participants
Clinic Site
Site 2
115 Participants174 Participants59 Participants
Race and Ethnicity Not Collected0 Participants
Region of Enrollment
United States
275 participants452 participants177 participants
Sex: Female, Male
Female
182 Participants293 Participants111 Participants
Sex: Female, Male
Male
93 Participants159 Participants66 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 1770 / 275
other
Total, other adverse events
0 / 1770 / 275
serious
Total, serious adverse events
0 / 1770 / 275

Outcome results

Primary

Resolution of Contextual Red Flags

Proportion of red flags noted at index visit that have resolved

Time frame: 6-9 months following index visit

Population: Red flags identified in visits of participants.

ArmMeasureCategoryValue (COUNT_OF_UNITS)
Contextual Survey + Contextual CDSResolution of Contextual Red FlagsRed flag worsened83 Red flags
Contextual Survey + Contextual CDSResolution of Contextual Red FlagsRed flag improved/resolved116 Red flags
Contextual Survey + Contextual CDSResolution of Contextual Red FlagsRed flag unchanged or mixed163 Red flags
Contextual Survey OnlyResolution of Contextual Red FlagsRed flag improved/resolved240 Red flags
Contextual Survey OnlyResolution of Contextual Red FlagsRed flag worsened99 Red flags
Contextual Survey OnlyResolution of Contextual Red FlagsRed flag unchanged or mixed201 Red flags
Comparison: Logistic mixed effects regression modeling likelihood of red flag improved/resolved (vs. not) during outcome period with fixed effects of intervention, site, and whether contextual factor was incorporated into care plan, and random effects of patient and provider. Red flags may be clustered in patients; patients are clustered in providers.p-value: 0.9196% CI: [0.57, 1.64]Mixed Models Analysis
Secondary

Planning for Contextual Factors

Proportion of contextual factors identified during visit that are incorporated into care plan

Time frame: At index visit

ArmMeasureCategoryValue (COUNT_OF_UNITS)
Contextual Survey + Contextual CDSPlanning for Contextual FactorsPlan contextualized for factor221 Contextual factors
Contextual Survey + Contextual CDSPlanning for Contextual FactorsPlan not contextualized for factor162 Contextual factors
Contextual Survey OnlyPlanning for Contextual FactorsPlan contextualized for factor255 Contextual factors
Contextual Survey OnlyPlanning for Contextual FactorsPlan not contextualized for factor254 Contextual factors
Comparison: Logistic mixed effects regression modeling likelihood of provider incorporating contextual factor into care plan (vs. not) at visit with fixed effects of intervention, site, whether red flag was select on pre-visit questionnaire, whether audiorecorder was visible to provider, whether factor was identified by provider probe, whether factor was revealed by patient, and random effects of patient and provider. Red flags may be clustered in patients; patients are clustered in providers.p-value: 0.00695% CI: [1.32, 5.41]Mixed Models Analysis
Secondary

Probing of Contextual Red Flags

Proportion of red flags which the examining physician probes

Time frame: At index visit

ArmMeasureCategoryValue (COUNT_OF_UNITS)
Contextual Survey + Contextual CDSProbing of Contextual Red FlagsProbed215 Red flags
Contextual Survey + Contextual CDSProbing of Contextual Red FlagsNot probed147 Red flags
Contextual Survey OnlyProbing of Contextual Red FlagsNot probed269 Red flags
Contextual Survey OnlyProbing of Contextual Red FlagsProbed271 Red flags
Comparison: Logistic mixed effects regression modeling likelihood of provider probing red flag (vs. not) during visit with fixed effects of intervention, site, \\whether red flag was select on pre-visit questionnaire, and whether audiorecorder was visible to provider, and random effects of patient and provider. Red flags may be clustered in patients; patients are clustered in providers.p-value: 0.0295% CI: [1.13, 3.86]Mixed Models Analysis

Source: ClinicalTrials.gov · Data processed: Feb 11, 2026