Human-Centered Design of a Clinical Decision Support for Anemia Screening in Children with Inflammatory Bowel Disease

Human-Centered Design to Improve Care for Youths Experiencing Psychiatric Boarding

The number of children and adolescents presenting to hospitals with mental health conditions has increased markedly over the past decade. A dearth of pediatric mental health resources prevents delivering definitive psychiatric care to this population at many hospitals; thus, children and adolescents must wait at a medical facility until appropriate psychiatric care becomes available (an experience described as psychiatric "boarding"). Clinicians caring for youth experiencing psychiatric boarding report inadequate training and resources to provide high-quality care to this population, and patients and caregivers describe significant frustration with the current standard of care. Recognizing these issues and the unique emotional components associated with psychiatric boarding, we employed human-centered design (HCD) to improve our hospital's approach to caring for youth during this period. HCD is an approach that specifically prioritizes the assessment and integration of human needs, including emotional needs, as a means to inform change. We used an HCD framework encompassing 5 stages: (1) empathize with those affected by the issue at hand, (2) define the problem, (3) ideate potential solutions, (4) prototype potential solutions, and (5) test potential solutions. Through these stages, we elicited broad stakeholder engagement to develop and implement 2 primary interventions: A modular digital health curriculum to teach psychosocial skills to youth experiencing boarding and a comprehensive clinical practice guideline to optimize and standardize care across clinical environments at our hospital. This manuscript describes our experience applying HCD principles to this complex health care challenge.

A Provider-Facing Decision Support Tool for Prostate Cancer Screening in Primary Care: A Pilot Study

OBJECTIVES

 Our objective was to pilot test an electronic health record-embedded decision support tool to facilitate prostate-specific antigen (PSA) screening discussions in the primary care setting.

METHODS

 We pilot-tested a novel decision support tool that was used by 10 primary care physicians (PCPs) for 6 months, followed by a survey. The tool comprised (1) a risk-stratified algorithm, (2) a tool for facilitating shared decision-making (Simple Schema), (3) three best practice advisories (BPAs: <45, 45-75, and >75 years), and (4) a health maintenance module for scheduling automated reminders about PSA rescreening.

RESULTS

 All PCPs found the tool feasible, acceptable, and clear to use. Eight out of ten PCPs reported that the tool made PSA screening conversations somewhat or much easier. Before using the tool, 70% of PCPs felt confident in their ability to discuss PSA screening with their patient, and this improved to 100% after the tool was used by PCPs for 6 months. PCPs found the BPAs for eligible (45-75 years) and older men (>75 years) more useful than the BPA for younger men (<45 years). Among the 10 PCPs, 60% found the Simple Schema to be very useful, and 50% found the health maintenance module to be extremely or very useful. Most PCPs reported the components of the tool to be at least somewhat useful, with 10% finding them to be very burdensome.

CONCLUSION

 We demonstrated the feasibility and acceptability of the tool, which is notable given the marked low acceptance of existing tools. All PCPs reported that they would consider continuing to use the tool in their clinic and were likely or very likely to recommend the tool to a colleague.

Randomized Comparison of Electronic Health Record Alert Types in Eliciting Responses about Prognosis in Gynecologic Oncology Patients

OBJECTIVES

 To compare the ability of different electronic health record alert types to elicit responses from users caring for cancer patients benefiting from goals of care (GOC) conversations.

METHODS

 A validated question asking if the user would be surprised by the patient's 6-month mortality was built as an Epic BestPractice Advisory (BPA) alert in three versions-(1) Required on Open chart (pop-up BPA), (2) Required on Close chart (navigator BPA), and (3) Optional Persistent (Storyboard BPA)-randomized using patient medical record number. Meaningful responses were defined as "Yes" or "No," rather than deferral. Data were extracted over 6 months.

RESULTS

 Alerts appeared for 685 patients during 1,786 outpatient encounters. Measuring encounters where a meaningful response was elicited, rates were highest for Required on Open (94.8% of encounters), compared with Required on Close (90.1%) and Optional Persistent (19.7%) (p < 0.001). Measuring individual alerts to which responses were given, they were most likely meaningful with Optional Persistent (98.3% of responses) and least likely with Required on Open (68.0%) (p < 0.001). Responses of "No," suggesting poor prognosis and prompting GOC, were more likely with Optional Persistent (13.6%) and Required on Open (10.3%) than with Required on Close (7.0%) (p = 0.028).

CONCLUSION

 Required alerts had response rates almost five times higher than optional alerts. Timing of alerts affects rates of meaningful responses and possibly the response itself. The alert with the most meaningful responses was also associated with the most interruptions and deferral responses. Considering tradeoffs in these metrics is important in designing clinical decision support to maximize success.

Addressing Alert Fatigue by Replacing a Burdensome Interruptive Alert with Passive Clinical Decision Support

BACKGROUND

Recognizing that alert fatigue poses risks to patient safety and clinician wellness, there is a growing emphasis on evaluation and governance of electronic health record clinical decision support (CDS). This is particularly critical for interruptive alerts to ensure that they achieve desired clinical outcomes while minimizing the burden on clinicians. This study describes an improvement effort to address a problematic interruptive alert intended to notify clinicians about patients needing coronavirus disease 2019 (COVID) precautions and how we collaborated with operational leaders to develop an alternative passive CDS system in acute care areas.

OBJECTIVES

Our dual aim was to reduce the alert burden by redesigning the CDS to adhere to best practices for decision support while also improving the percent of admitted patients with symptoms of possible COVID who had appropriate and timely infection precautions orders.

METHODS

Iterative changes to CDS design included adjustment to alert triggers and acknowledgment reasons and development of a noninterruptive rule-based order panel for acute care areas. Data on alert burden and appropriate precautions orders on symptomatic admitted patients were followed over time on run and attribute (p) and individuals-moving range control charts.

RESULTS

At baseline, the COVID alert fired on average 8,206 times per week with an alert per encounter rate of 0.36. After our interventions, the alerts per week decreased to 1,449 and alerts per encounter to 0.07 equating to an 80% reduction for both metrics. Concurrently, the percentage of symptomatic admitted patients with COVID precautions ordered increased from 23 to 61% with a reduction in the mean time between COVID test and precautions orders from 19.7 to -1.3 minutes.

CONCLUSION

CDS governance, partnering with operational stakeholders, and iterative design led to successful replacement of a frequently firing interruptive alert with less burdensome passive CDS that improved timely ordering of COVID precautions.

Behavioral Health Decision Support Systems and User Interface Design in the Emergency Department

OBJECTIVE

The objective of this qualitative study is to gauge physician sentiment about an emergency department (ED) clinical decision support (CDS) system implemented in multiple adult EDs within a university hospital system. This CDS system focuses on predicting patients' likelihood of ED recidivism and/or adverse opioid-related events.

METHODS

The study was conducted among adult emergency physicians working in three EDs of a single academic health system in Rhode Island. Qualitative, semistructured interviews were conducted with ED physicians. Interviews assessed physicians' prior experience with predictive analytics, thoughts on the alert's placement, design, and content, the alert's overall impact, and potential areas for improvement. Responses were aggregated and common themes identified.

RESULTS

Twenty-three interviews were conducted (11 preimplementation and 12 postimplementation). Themes were identified regarding each physician familiarity with predictive analytics, alert rollout, alert appearance and content, and on alert sentiments. Most physicians viewed these alerts as a neutral or positive EHR addition, with responses ranging from neutral to positive. The alert placement was noted to be largely intuitive and nonintrusive. The design of the alert was generally viewed positively. The alert's content was believed to be accurate, although the decision to respond to the alert's call-to-action was physician dependent. Those who tended to ignore the alert did so for a few reasons, including already knowing the information the alert contains, the alert offering information that is not relevant to this particular patient, and the alert not containing enough information to be useful.

CONCLUSION

Ultimately, this alert appears to have a marginally positive effect on ED physician workflow. At its most beneficial, the alert reminded physicians to deeply consider the care provided to high-risk populations and to potentially adjust their care and referrals. At its least beneficial, the alert did not affect physician decision-making but was not intrusive to the point of negatively impacting workflow.