Randomized Controlled Trials of Electronic Health Record Interventions: Design, Conduct, and Reporting Considerations

Applying human-centered design to the construction of a cirrhosis management clinical decision support system

BACKGROUND

Electronic health record (EHR)-based clinical decision support is a scalable way to help standardize clinical care. Clinical decision support systems have not been extensively investigated in cirrhosis management. Human-centered design (HCD) is an approach that engages with potential users in intervention development. In this study, we applied HCD to design the features and interface for a clinical decision support system for cirrhosis management, called CirrhosisRx.

METHODS

We conducted technical feasibility assessments to construct a visual blueprint that outlines the basic features of the interface. We then convened collaborative-design workshops with generalist and specialist clinicians. We elicited current workflows for cirrhosis management, assessed gaps in existing EHR systems, evaluated potential features, and refined the design prototype for CirrhosisRx. At the conclusion of each workshop, we analyzed recordings and transcripts.

RESULTS

Workshop feedback showed that the aggregation of relevant clinical data into 6 cirrhosis decompensation domains (defined as common inpatient clinical scenarios) was the most important feature. Automatic inference of clinical events from EHR data, such as gastrointestinal bleeding from hemoglobin changes, was not accepted due to accuracy concerns. Visualizations for risk stratification scores were deemed not necessary. Lastly, the HCD co-design workshops allowed us to identify the target user population (generalists).

CONCLUSIONS

This is one of the first applications of HCD to design the features and interface for an electronic intervention for cirrhosis management. The HCD process altered features, modified the design interface, and likely improved CirrhosisRx's overall usability. The finalized design for CirrhosisRx proceeded to development and production and will be tested for effectiveness in a pragmatic randomized controlled trial. This work provides a model for the creation of other EHR-based interventions in hepatology care.

Optimizing Uptake of Multimodal Pain Management After Surgery Using the Electronic Health Record

This quality improvement study evaluates the effect of an electronic health record intervention on multimodal pain management following surgery in 2 randomized clinical trials.

Clinical decision support and electronic interventions to improve care quality in chronic liver diseases and cirrhosis

Significant quality gaps exist in the management of chronic liver diseases and cirrhosis. Clinical decision support systems-information-driven tools based in and launched from the electronic health record-are attractive and potentially scalable prospective interventions that could help standardize clinical care in hepatology. Yet, clinical decision support systems have had a mixed record in clinical medicine due to issues with interoperability and compatibility with clinical workflows. In this review, we discuss the conceptual origins of clinical decision support systems, existing applications in liver diseases, issues and challenges with implementation, and emerging strategies to improve their integration in hepatology care.

A behavioral intervention to promote use of multimodal pain medication for hospitalized patients: A randomized controlled trial

BACKGROUND

The use of nonsteroidal anti-inflammatory drugs (NSAIDs) can reduce pain and has become a core strategy to decrease opioid use, but there is a lack of data to describe encouraging use when admitting patients using electronic health record systems.

OBJECTIVE

Assess an electronic health record system to increase ordering of NSAIDs for hospitalized adults.

DESIGNS, SETTINGS AND PARTICIPANTS

We performed a cluster randomized controlled trial of clinicians admitting adult patients to a health system over a 9-month period. Clinicians were randomized to use a standard admission order set.

INTERVENTION

Clinicians in the intervention arm were required to actively order or decline NSAIDs; the control arm was shown the same order but without a required response.

MAIN OUTCOME AND MEASURES

The primary outcome was NSAIDs ordered and administered by the first full hospital day. Secondary outcomes included pain scores and opioid prescribing.

RESULTS

A total of 20,085 hospitalizations were included. Among these hospitalizations, patients had a mean age of 58 years, and a Charlson comorbidity score of 2.97, while 50% and 56% were female and White, respectively. Overall, 52% were admitted by a clinician randomized to the intervention arm. NSAIDs were ordered in 2267 (22%) interventions and 2093 (22%) control admissions (p = .10). Similarly, there were no statistical differences in NSAID administration, pain scores, or opioid prescribing. Average pain scores (0-5 scale) were 3.36 in the control group and 3.39 in the intervention group (p = .46). There were no differences in clinical harms.

CONCLUSIONS AND RELEVANCE

Requiring an active decision to order an NSAID at admission had no demonstrable impact on NSAID ordering. Multicomponent interventions, perhaps with stronger decision support, may be necessary to encourage NSAID ordering.

Electronic Health Record-Nested Reminders for Serum Lithium Level Monitoring in Patients With Mood Disorder: Randomized Controlled Trial

BACKGROUND

Clinical guidelines recommend regular serum lithium monitoring every 3 to 6 months. However, in the real world, only a minority of patients receive adequate monitoring.

OBJECTIVE

This study aims to examine whether the use of the electronic health record (EHR)-nested reminder system for serum lithium monitoring can help achieve serum lithium concentrations within the therapeutic range for patients on lithium maintenance therapy.

METHODS

We conducted an unblinded, single-center, EHR-nested, parallel-group, superiority randomized controlled trial comparing EHR-nested reminders with usual care in adult patients receiving lithium maintenance therapy for mood disorders. The primary outcome was the achievement of therapeutically appropriate serum lithium levels between 0.4 and 1.0 mEq/L at 18 months after enrollment. The key secondary outcomes are included as follows: the number of serum lithium level monitoring except for the first and final monitoring; exacerbation of the mood disorder during the study period, defined by hospitalization, increase in lithium dose, addition of antipsychotic drugs or mood stabilizers, or addition or increase of antidepressants; adherence defined by the proportion of days covered by lithium carbonate prescription during the study period.

RESULTS

A total of 111 patients were enrolled in this study. A total of 56 patients were assigned to the reminder group, and 55 patients were assigned to the usual care group. At the follow-up, 38 (69.1%) patients in the reminder group and 33 (60.0%) patients in the usual care group achieved the primary outcome (odds ratio 2.14, 95% CI 0.82-5.58, P=.12). The median number of serum lithium monitoring was 2 in the reminder group and 0 in the usual care group (rate ratio 3.62; 95% CI 2.47-5.29, P<.001). The exacerbation of mood disorders occurred in 17 (31.5%) patients in the reminder group and in 16 (34.8%) patients in the usual care group (odds ratio 0.97, 95% CI 0.42-2.28, P=.95).

CONCLUSIONS

We found insufficient evidence for an EHR-nested reminder to increase the achievement of therapeutic serum lithium concentrations. However, the number of monitoring increased with relatively simple and inexpensive intervention. The EHR-based reminders may be useful to improve quality of care for patients on lithium maintenance therapy, and they have potentials to be applied to other problems.

TRIAL REGISTRATION

University Hospital Medical Information Network Clinical Trials Registry UMIN000033633; https://tinyurl.com/5n7wtyav.

A Call to Improve Health by Achieving the Learning Health Care System

The learning health care system is an aspirational operational model for improving health care by learning from the care being delivered. The model, which has been endorsed by the National Academy of Medicine, aligns naturally with academic health systems, which have a mission to improve care for their communities through research and education. In this scholarly perspective, the authors define the learning health care system concept and its historical relationship to academic health systems; explore opportunities for and barriers to realizing the learning health care system; and propose actions to achieve the learning health care system at the local, regional, and national levels. The authors argue that the learning health care system model is essential to academic medicine's evolution and to achieving the foundational societal mission of academic health systems to advance health through research and education.

Contingency management to promote smoking cessation in people experiencing homelessness: Leveraging the electronic health record in a pilot, pragmatic randomized controlled trial

BACKGROUND

Cigarette smoking is disproportionately high among people experiencing homelessness (PEH). Contingency management (CM) is a strategy that has shown considerable efficacy for smoking cessation and has been used in short-term studies of smoking abstinence in PEH. We describe a pilot, pragmatic randomized controlled trial protocol, which leverages an electronic health record (EHR) infrastructure to assess the feasibility and acceptability of an extended CM intervention to improve long-term abstinence in PEH.

METHODS

We will conduct the study at three safety-net clinics in San Francisco among 90 adults experiencing homelessness who smoke cigarettes currently and have a desire to quit. We will encourage all participants to receive smoking cessation services that include behavioral counseling and pharmacotherapy through their clinics. We will randomly assign participants to an extended CM intervention group with escalating incentives contingent on abstinence or to a control group with fixed incentives for attending study visits. We will use the EHR to recruit participants, track receipt of counseling and pharmacotherapy during clinical care, and communicate with providers on participants' progress. CM participants will get escalating incentives for demonstration of carbon monoxide-verified abstinence over 6 months, with a total possible earnings of $475. Control participants will receive a fixed incentive of $5 for attending study visits, totaling $125. We will conduct the carbon-monoxide verified abstinence assessments-which will determine CM incentive amounts-daily during week 1, bi-weekly through week 4, weekly through week 13, and monthly through week 24. Measures of feasibility and acceptability, both quantitative and qualitative, will include assessments of screening and recruitment, adherence to study visits, engagement in smoking cessation clinical care, retention, and participant satisfaction. One of the primary clinical outcomes will be biochemically verified 7-day point prevalence abstinence at 6 months. We will measure secondary outcomes, which will include 7-day point prevalence abstinence at 2 weeks, 3 and 12 months.

DISCUSSION

This trial will allow us to assess the feasibility and acceptability of a CM cessation intervention among PEH. The protocol's clinical setting and use of EHRs gives it significant potential for scalability. If found to be feasible, acceptable, and subsequently efficacious in a larger trial, the intervention could reduce tobacco-related health disparities by increasing long-term smoking abstinence among this vulnerable population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04982952. Registered on July 29, 2021.

Temporal Trends in Clinical Evidence of 5-Year Survival Within Electronic Health Records Among Patients With Early-Stage Colon Cancer Managed With Laparoscopy-Assisted Colectomy vs Open Colectomy

Importance

Temporal shifts in clinical knowledge and practice need to be adjusted for in treatment outcome assessment in clinical evidence.

Objective

To use electronic health record (EHR) data to (1) assess the temporal trends in treatment decisions and patient outcomes and (2) emulate a randomized clinical trial (RCT) using EHR data with proper adjustment for temporal trends.

Design, Setting, and Participants

The Clinical Outcomes of Surgical Therapy (COST) Study Group Trial assessing overall survival of patients with stages I to III early-stage colon cancer was chosen as the target trial. The RCT was emulated using EHR data of patients from a single health care system cohort who underwent colectomy for early-stage colon cancer from January 1, 2006, to December 31, 2017, and were followed up to January 1, 2020, from Mass General Brigham. Analyses were conducted from December 2, 2019, to January 24, 2022.

Exposures

Laparoscopy-assisted colectomy (LAC) vs open colectomy (OC).

Main Outcomes and Measures

The primary outcome was 5-year overall survival. To address confounding in the emulation, pretreatment variables were selected and adjusted. The temporal trends were adjusted by stratification of the calendar year when the colectomies were performed with cotraining across strata.

Results

A total of 943 patients met key RCT eligibility criteria in the EHR emulation cohort, including 518 undergoing LAC (median age, 63 [range, 20-95] years; 268 [52%] women; 121 [23%] with stage I, 165 [32%] with stage II, and 232 [45%] with stage III cancer; 32 [6%] with colon adhesion; 278 [54%] with right-sided colon cancer; 18 [3%] with left-sided colon cancer; and 222 [43%] with sigmoid colon cancer) and 425 undergoing OC (median age, 65 [range, 28-99] years; 223 [52%] women; 61 [14%] with stage I, 153 [36%] with stage II, and 211 [50%] with stage III cancer; 39 [9%] with colon adhesion; 202 [47%] with right-sided colon cancer; 39 [9%] with left-sided colon cancer; and 201 [47%] with sigmoid colon cancer). Tests for temporal trends in treatment assignment (χ2 = 60.3; P < .001) and overall survival (χ2 = 137.2; P < .001) were significant. The adjusted EHR emulation reached the same conclusion as the RCT: LAC is not inferior to OC in overall survival rate with risk difference at 5 years of -0.007 (95% CI, -0.070 to 0.057). The results were consistent for stratified analysis within each temporal period.

Conclusions and Relevance

These findings suggest that confounding bias from temporal trends should be considered when conducting clinical evidence studies with long time spans. Stratification of calendar time and cotraining of models is one solution. With proper adjustment, clinical evidence may supplement RCTs in the assessment of treatment outcome over time.

"Beyond MELD" - Emerging strategies and technologies for improving mortality prediction, organ allocation and outcomes in liver transplantation

In this review article, we discuss the model for end-stage liver disease (MELD) score and its dual purpose in general and transplant hepatology. As the landscape of liver disease and transplantation has evolved considerably since the advent of the MELD score, we summarise emerging concepts, methodologies, and technologies that may improve mortality prognostication in the future. Finally, we explore how these novel concepts and technologies may be incorporated into clinical practice.

Clinical Decision Support for Newborn Weight Loss: A Randomized Controlled Trial

BACKGROUND AND OBJECTIVE

The Newborn Weight Tool (NEWT) can inform newborn feeding decisions and might reduce health care utilization by preventing excess weight loss. Clinical decision support (CDS) displaying NEWT might facilitate its use. Our study's objective is to determine the effect of CDS displaying NEWT on feeding and health care utilization.

METHODS

At an hospital involved in NEWT development, we randomly assigned 2682 healthy infants born ≥36 weeks gestation in 2018-2019 either to CDS displaying NEWT with an electronic flag if most recent weight was ≥75th weight loss centile or to a control of usual care with NEWT accessed at clinician discretion. Our primary outcome was feeding type concordant with weight loss, defined as exclusive breastfeeding for those not flagged, exclusive breastfeeding or supplementation for those flagged once, and supplementation for those flagged more than once. Secondary outcomes included inpatient and outpatient utilization in the first 30 days. We used χ2 and Student's t tests to compare intervention infants with control and to compare trial infants with those born in 2017.

RESULTS

Feeding was concordant with for 1854 (74.5%) trial infants and did not differ between randomized groups (P = .65); concordant feeding was higher for all trial infants than for infants born in 2017 (64.4%; P < .0005). Readmission occurred for 51 (3.8%) CDS infants and 45 (3.4%) control infants (P = .56). Among the 60% of trial infants with outpatient records available, there were 3.5 ± 1.7 visits with no differences between randomized groups (P = .10).

CONCLUSIONS

At an hospital involved in NEWT development, CDS displaying NEWT did not alter either feeding or health care utilization compared with discretionary NEWT access.

Effectiveness of an Analytics-Based Intervention for Reducing Sleep Interruption in Hospitalized Patients: A Randomized Clinical Trial

IMPORTANCE

Sleep has major consequences for physical and emotional well-being. Hospitalized patients experience frequent iatrogenic sleep interruptions and there is evidence that such interruptions can be safely reduced.

OBJECTIVE

To determine whether a clinical decision support tool, powered by real-time patient data and a trained prediction algorithm, can help physicians identify clinically stable patients and safely discontinue their overnight vital sign checks.

DESIGN, SETTING, AND PARTICIPANTS

A randomized clinical trial, with inpatient encounters randomized 1:1 to intervention vs usual care, was conducted from March 11 to November 24, 2019. Participants included physicians serving on the primary team of 1699 patients on the general medical service (not in the intensive care unit) of a tertiary care academic medical center.

INTERVENTIONS

A clinical decision support notification informed the physician if the patient had a high likelihood of nighttime vital signs within the reference ranges based on a logistic regression model that used real-time patient data as input. The notification provided the physician an opportunity to discontinue measure of nighttime vital signs, dismiss the notification for 1 hour, or dismiss the notification for that day.

MAIN OUTCOMES AND MEASURES

The primary outcome was delirium, as determined by bedside nurse assessment of Nursing Delirium Screening Scale scores, a standardized delirium screening tool (delirium diagnosed with score ≥2). Secondary outcomes included mean nighttime vital sign checks. Potential harms included intensive care unit transfers and code blue alarms. All analyses were conducted on the basis of intention-to-treat.

RESULTS

A total of 1930 inpatient encounters in 1699 patients (intervention encounters: 566 of 966 [59%] men; mean [SD] age, 53 [15] years) were randomized. In the intervention vs control arm, there was a significant decrease in the mean (SD) number of nighttime vital sign checks (0.97 [0.95] vs 1.41 [0.86]; P < .001) with no increase in intensive care unit transfers (49 [5%] vs 47 [5%]; P = .92) or code blue alarms (2 [0.2%] vs 9 [0.9%]; P = .07). The incidence of delirium was not significantly reduced (108 [11%] vs 123 [13%]; P = .32).

CONCLUSIONS AND RELEVANCE

While this randomized clinical trial found no difference between groups in the primary outcome, delirium incidence, the secondary findings indicate that a real-time prediction algorithm embedded within a clinical decision support tool in the electronic health record can help physicians identify clinically stable patients who can forgo routine vital sign checks, safely giving them greater opportunity to sleep. Other aspects of hospital care that depend on clinical stability, such as level of care or cardiac monitoring, may be amenable to a similar intervention.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04046458.