Trial Summary
What is the purpose of this trial?Racial and ethnic inequities in health care quality have been described across a broad range of clinical settings, patient populations, and outcomes. Our overarching goal is to eradicate health care inequities through evidence-based interventions. The objectives of this proposal are to develop and test the impact of two interventions on overcoming clinician implicit bias and mitigating inequities in the management of pain among children seeking care in the emergency department for the treatment of appendicitis or long bone fractures.
Will I have to stop taking my current medications?
The trial does not specify whether participants need to stop taking their current medications.
What data supports the effectiveness of this treatment for reducing clinician bias in pain treatment?
Research shows that providing personalized feedback and virtual interactions with patients can significantly reduce treatment bias in clinicians, leading to more equitable pain care. Additionally, electronic health record-based clinical decision support has been effective in improving prescription practices, suggesting its potential to enhance pain treatment decisions.
12345Is the treatment for reducing clinician bias in pain treatment safe for humans?
The treatment, which includes electronic health record-embedded clinical decision support, has been associated with safer prescribing practices, such as reducing risky opioid regimens. However, there are concerns about the validation of these systems, as flawed predictions could potentially harm patients.
678910How does this treatment differ from other treatments for pain management?
This treatment is unique because it focuses on reducing clinician bias through a virtual perspective-taking intervention, which provides personalized feedback and interactions with virtual patients to address racial and socioeconomic disparities in pain care, rather than directly altering the medication or dosage given to patients.
125611Eligibility Criteria
This trial is for clinicians at Children's National Hospital Emergency Department. It aims to address racial and ethnic inequities in pain management among children with appendicitis or broken bones by targeting clinician implicit bias.Inclusion Criteria
All Children's National Hospital Emergency Department clinicians
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Intervention
Clinicians receive monthly 'Equity Report Cards' and real-time clinical decision support for pain management
24 months
Monthly visits (virtual)
Follow-up
Participants are monitored for safety and effectiveness after intervention
4 weeks
Participant Groups
The study tests two interventions: department-level audit and feedback, plus electronic health record-embedded clinical decision support, to see if they can reduce healthcare inequalities in emergency pain treatment.
1Treatment groups
Experimental Treatment
Group I: Department-level audit and feedback and electronic health record-embedded clinical decision supportExperimental Treatment1 Intervention
Clinicians will receive monthly pooled, department-level 'Equity Report Cards' that will provide aggregate information on clinical data stratified by patient race/ethnicity. Subsequently, for all visits that may be related to appendicitis or long bone fracture, clinicians will then receive real-time, electronic health record-embedded clinical decision support regarding pain management.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Children's National HospitalWashington, United States
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Who Is Running the Clinical Trial?
Children's National Research InstituteLead Sponsor
References
A randomized controlled trial testing a virtual perspective-taking intervention to reduce race and socioeconomic status disparities in pain care. [2022]We conducted a randomized controlled trial of an individually tailored, virtual perspective-taking intervention to reduce race and socioeconomic status (SES) disparities in providers' pain treatment decisions. Physician residents and fellows (n = 436) were recruited from across the United States for this two-part online study. Providers first completed a bias assessment task in which they made treatment decisions for virtual patients with chronic pain who varied by race (black/white) and SES (low/high). Providers who demonstrated a treatment bias were randomized to the intervention or control group. The intervention consisted of personalized feedback about their bias, real-time dynamic interactions with virtual patients, and videos depicting how pain impacts the patients' lives. Treatment bias was re-assessed 1 week later. Compared with the control group, providers who received the tailored intervention had 85% lower odds of demonstrating a treatment bias against black patients and 76% lower odds of demonstrating a treatment bias against low SES patients at follow-up. Providers who received the intervention for racial bias also showed increased compassion for patients compared with providers in the control condition. Group differences did not emerge for provider comfort in treating patients. Results suggest an online intervention that is tailored to providers according to their individual treatment biases, delivers feedback about these biases, and provides opportunities for increased contact with black and low SES patients, can produce substantial changes in providers' treatment decisions, resulting in more equitable pain care. Future studies should examine how these effects translate to real-world patient care and the optimal timing/dose of the intervention.
The interaction of patient race, provider bias, and clinical ambiguity on pain management decisions. [2022]Although racial disparities in pain care are widely reported, much remains to be known about the role of provider and contextual factors. We used computer-simulated patients to examine the influence of patient race, provider racial bias, and clinical ambiguity on pain decisions. One hundred twenty-nine medical residents/fellows made assessment (pain intensity) and treatment (opioid and nonopioid analgesics) decisions for 12 virtual patients with acute pain. Race (black/white) and clinical ambiguity (high/low) were manipulated across vignettes. Participants completed the Implicit Association Test and feeling thermometers, which assess implicit and explicit racial biases, respectively. Individual- and group-level analyses indicated that race and ambiguity had an interactive effect on providers' decisions, such that decisions varied as a function of ambiguity for white but not for black patients. Individual differences across providers were observed for the effect of race and ambiguity on decisions; however, providers' implicit and explicit biases did not account for this variability. These data highlight the complexity of racial disparities and suggest that differences in care between white and black patients are, in part, attributable to the nature (ie, ambiguity) of the clinical scenario. The current study suggests that interventions to reduce disparities should differentially target patient, provider, and contextual factors.
Targeted Intervention to Increase Awareness of Opioid Overprescribing Significantly Reduces Narcotic Prescribing Within an Academic Orthopaedic Practice. [2021]To evaluate the impact of a targeted intervention focused on increasing awareness of opioid overprescribing within an academic orthopaedic practice.
Targeted messaging to improve the adoption of clinical decision support for prescription drug monitoring program use. [2023]Clinical decision support (CDS) can prevent medical errors and improve patient outcomes. Electronic health record (EHR)-based CDS, designed to facilitate prescription drug monitoring program (PDMP) review, has reduced inappropriate opioid prescribing. However, the pooled effectiveness of CDS has exhibited substantial heterogeneity and current literature does not adequately detail why certain CDS are more successful than others. Clinicians regularly override CDS, limiting its impact. No studies recommend how to help nonadopters recognize and recover from CDS misuse. We hypothesized that a targeted educational intervention would improve CDS adoption and effectiveness for nonadopters. Over 10 months, we identified 478 providers consistently overriding CDS (nonadopters) and sent each up to 3 educational message(s) via email or EHR-based chat. One hundred sixty-one (34%) nonadopters stopped consistently overriding CDS and started reviewing the PDMP after contact. We concluded that targeted messaging is a low-resource way to disseminate CDS education and improve CDS adoption and best practice delivery.
Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use. [2021]Demographic characteristics have been found to influence pain management decisions, but limited focus has been placed on participants' reactions to feedback about their use of sex, race, or age to make these decisions. The present study aimed to examine the effects of providing feedback about the use of demographic cues to participants making pain management decisions. Participants (N = 107) viewed 32 virtual human patients with standardized levels of pain and provided ratings for virtual humans' pain intensity and their treatment decisions. Real-time lens model idiographic analyses determined participants' decision policies based on cues used. Participants were subsequently informed about cue use and completed feedback questions. Frequency analyses were conducted on responses to these questions. Between 7.4 and 89.4% of participants indicated awareness of their use of demographic or pain expression cues. Of those individuals, 26.9 to 55.5% believed this awareness would change their future clinical decisions, and 66.6 to 75.9% endorsed that their attitudes affect their imagined clinical practice. Between 66.6 and 79.1% of participants who used cues reported willingness to complete an online tutorial about pain across demographic groups. This study was novel because it provided participants feedback about their cue use. Most participants who used cues indicated willingness to participate in an online intervention, suggesting this technology's utility for modifying biases.
Clinically Inconsequential Alerts: The Characteristics of Opioid Drug Alerts and Their Utility in Preventing Adverse Drug Events in the Emergency Department. [2018]We examine the characteristics of clinical decision support alerts triggered when opioids are prescribed, including alert type, override rates, adverse drug events associated with opioids, and preventable adverse drug events.
Impact of multidisciplinary chart reviews on opioid dose reduction and monitoring practices. [2019]The Veterans Affairs (VA) Eastern Colorado Health Care System implemented an Opioid Safety Initiative (OSI); this included multidisciplinary chart reviews of patients with chronic, non-malignant pain on high-dose opioid therapy to provide safety recommendations to prescribers through the electronic medical record. Our study objective was to evaluate the impact of these documented recommendations. Outcomes included change in total daily opioid dose, concurrent prescribing of opioids and benzodiazepines, adherence to local VA/Veterans Integrated Service Network (VISN) policy, and monitoring practices.
Impact of the Opioid Safety Initiative on opioid-related prescribing in veterans. [2021]The Veterans Health Administration (VHA) designed the Opioid Safety Initiative (OSI) to help decrease opioid prescribing practices associated with adverse outcomes. Key components included disseminating a dashboard tool that aggregates electronic medical record data to audit real-time opioid-related prescribing and identifying a clinical leader at each facility to implement the tool and promote safer prescribing. This study examines changes associated with OSI implementation in October 2013 among all adult VHA patients who filled outpatient opioid prescriptions. Interrupted time series analyses controlled for baseline trends and examined data from October 2012 to September 2014 to determine the changes after OSI implementation in prescribing of high-dosage opioid regimens (total daily dosages >100 morphine equivalents [MEQ] and >200 MEQ) and concurrent benzodiazepines. Across VHA facilities nationwide, there was a decreasing trend in high-dosage opioid prescribing with 55,722 patients receiving daily opioid dosages >100 MEQ in October 2012, which decreased to 46,780 in September 2014 (16% reduction). The OSI was associated with an additional decrease, compared to pre-OSI trends, of 331 patients per month (95% confidence interval [CI] -378 to -284) receiving opioids >100 MEQ, a decrease of 164 patients per month (95% CI -186 to -142) receiving opioids >200 MEQ, and a decrease of 781 patients per month (95% CI -969 to -593) receiving concurrent benzodiazepines. Implementation of a national health care system-wide initiative was associated with reductions in outpatient prescribing of risky opioid regimens. These findings provide evidence for the potential utility of large-scale interventions to promote safer opioid prescribing.
A call for better validation of opioid overdose risk algorithms. [2023]Clinical decision support (CDS) systems powered by predictive models have the potential to improve the accuracy and efficiency of clinical decision-making. However, without sufficient validation, these systems have the potential to mislead clinicians and harm patients. This is especially true for CDS systems used by opioid prescribers and dispensers, where a flawed prediction can directly harm patients. To prevent these harms, regulators and researchers have proposed guidance for validating predictive models and CDS systems. However, this guidance is not universally followed and is not required by law. We call on CDS developers, deployers, and users to hold these systems to higher standards of clinical and technical validation. We provide a case study on two CDS systems deployed on a national scale in the United States for predicting a patient's risk of adverse opioid-related events: the Stratification Tool for Opioid Risk Mitigation (STORM), used by the Veterans Health Administration, and NarxCare, a commercial system.
The effect of electronic prescribing on medication errors and adverse drug events: a systematic review. [2022]The objective of this systematic review is to analyse the relative risk reduction on medication error and adverse drug events (ADE) by computerized physician order entry systems (CPOE). We included controlled field studies and pretest-posttest studies, evaluating all types of CPOE systems, drugs and clinical settings. We present the results in evidence tables, calculate the risk ratio with 95% confidence interval and perform subgroup analyses for categorical factors, such as the level of care, patient group, type of drug, type of system, functionality of the system, comparison group type, study design, and the method for detecting errors. Of the 25 studies that analysed the effects on the medication error rate, 23 showed a significant relative risk reduction of 13% to 99%. Six of the nine studies that analysed the effects on potential ADEs showed a significant relative risk reduction of 35% to 98%. Four of the seven studies that analysed the effect on ADEs showed a significant relative risk reduction of 30% to 84%. Reporting quality and study quality was often insufficient to exclude major sources of bias. Studies on home-grown systems, studies comparing electronic prescribing to handwriting prescribing, and studies using manual chart review to detect errors seem to show a higher relative risk reduction than other studies. Concluding, it seems that electronic prescribing can reduce the risk for medication errors and ADE. However, studies differ substantially in their setting, design, quality, and results. To further improve the evidence-base of health informatics, more randomized controlled trials (RCTs) are needed, especially to cover a wider range of clinical and geographic settings. In addition, reporting quality of health informatics evaluation studies has to be substantially improved.
Patient race and physicians' decisions to prescribe opioids for chronic low back pain. [2022]Nonwhite patients are less likely than white patients to have their pain adequately treated. This study examined the influence of patient race and patient verbal and nonverbal behavior on primary care physicians' treatment decisions for chronic low back pain in men. We randomly assigned physicians to receive a paper-based, clinical vignette of a chronic pain patient that differed in terms of patient race (white vs. black), verbal behavior ("challenging" vs. "non-challenging"), and nonverbal behavior (confident vs. dejected vs. angry). We employed a between-subjects factorial design and surveyed primary care physicians (N=382), randomly selected from the American Medical Association Physician Masterfile. The primary dependent measure was the physician's decision as to whether (s)he would switch the patient to a higher dose or stronger type of opioid. Logistic regression was used to determine the effects of patient characteristics on physicians' prescribing decisions. There was a significant interaction between patient verbal behavior and patient race on physicians' decisions to prescribe opioids. Among black patients, physicians were significantly more likely to state that they would switch to a higher dose or stronger opioid for patients exhibiting "challenging" behaviors (e.g., demanding a specific narcotic, exhibiting anger) compared to those exhibiting "non-challenging" behaviors (55.1%). For white patients there was an opposite pattern of results in which physicians were slightly more likely to escalate treatment for patients exhibiting "non-challenging" (64.3%) vs. "challenging" (54.5%) verbal behaviors. Results point to the need for better understanding of the way a complex interplay of non-clinical characteristics affects physician behavior in order to improve quality of pain management and other clinical decision-making.