Effect of an Automated Patient Dashboard Using Active Choice and Peer Comparison Performance Feedback to Physicians on Statin Prescribing: The PRESCRIBE Cluster Randomized Clinical Trial

Use of an Online Palliative Care Clinical Curriculum to Train U.S. Hospital Staff: 2015-2019

Background: Most clinicians in the United States do not receive pre-professional education in pain and symptom management, communication skills, and caregiver support. The use of these skills by clinicians improves the quality of care for persons living with serious illness and enables the specialty-trained palliative care workforce to focus on patients whose needs are most complex. Objective: To review current trends in hospital use of the Center to Advance Palliative Care (CAPC) online clinical training curriculum. Description: Launched in 2015, CAPC clinical curriculum educates clinicians in the knowledge and skills necessary to improve care for patients with serious illness. CAPC currently offers 43 clinical courses and 4 Designations in recognition of successful completion of training by topic. Results: From January 15, 2015, to August 31, 2019, 26,535 clinicians working in hospitals completed 172,684 clinical courses. Registered nurses represented half of learners, and advanced practice providers were most likely to seek Designation. Physicians made up 22% of all learners; 85% of physician learners came from specialties beyond palliative care. Two of every five U.S. hospitals with more than 300 beds had at least one learner. In post-course evaluations, 84% reported that they will make practice changes as a result, and 70% reported that the content was new. Conclusions: The CAPC clinical curriculum is a widely used and valued method for education in clinical skills specific to the care of people living with serious illness. Findings suggest that an increasing number of hospital leaders recognize the importance of these skills in caring for patients with serious illness and support the necessary training.

Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial

Importance

Serious illness conversations (SICs) are structured conversations between clinicians and patients about prognosis, treatment goals, and end-of-life preferences. Interventions that increase the rate of SICs between oncology clinicians and patients may improve goal-concordant care and patient outcomes.

Objective

To determine the effect of a clinician-directed intervention integrating machine learning mortality predictions with behavioral nudges on motivating clinician-patient SICs.

Design, Setting, and Participants

This stepped-wedge cluster randomized clinical trial was conducted across 20 weeks (from June 17 to November 1, 2019) at 9 medical oncology clinics (8 subspecialty oncology and 1 general oncology clinics) within a large academic health system in Pennsylvania. Clinicians at the 2 smallest subspecialty clinics were grouped together, resulting in 8 clinic groups randomly assigned to the 4 intervention wedge periods. Included participants in the intention-to-treat analyses were 78 oncology clinicians who received SIC training and their patients (N = 14 607) who had an outpatient oncology encounter during the study period.

Interventions

(1) Weekly emails to oncology clinicians with SIC performance feedback and peer comparisons; (2) a list of up to 6 high-risk patients (≥10% predicted risk of 180-day mortality) scheduled for the next week, estimated using a validated machine learning algorithm; and (3) opt-out text message prompts to clinicians on the patient's appointment day to consider an SIC. Clinicians in the control group received usual care consisting of weekly emails with cumulative SIC performance.

Main Outcomes and Measures

Percentage of patient encounters with an SIC in the intervention group vs the usual care (control) group.

Results

The sample consisted of 78 clinicians and 14 607 patients. The mean (SD) age of patients was 61.9 (14.2) years, 53.7% were female, and 70.4% were White. For all encounters, SICs were conducted among 1.3% in the control group and 4.6% in the intervention group, a significant difference (adjusted difference in percentage points, 3.3; 95% CI, 2.3-4.5; P < .001). Among 4124 high-risk patient encounters, SICs were conducted among 3.6% in the control group and 15.2% in the intervention group, a significant difference (adjusted difference in percentage points, 11.6; 95% CI, 8.2-12.5; P < .001).

Conclusions and Relevance

In this stepped-wedge cluster randomized clinical trial, an intervention that delivered machine learning mortality predictions with behavioral nudges to oncology clinicians significantly increased the rate of SICs among all patients and among patients with high mortality risk who were targeted by the intervention. Behavioral nudges combined with machine learning mortality predictions can positively influence clinician behavior and may be applied more broadly to improve care near the end of life.

Trial Registration

ClinicalTrials.gov Identifier: NCT03984773.

Implementation of a Behavioral Economics Electronic Health Record (BE-EHR) Module to Reduce Overtreatment of Diabetes in Older Adults

BACKGROUND

Intensive glycemic control is of unclear benefit and carries increased risk for older adults with diabetes. The American Geriatrics Society's (AGS) Choosing Wisely (CW) guideline promotes less aggressive glycemic targets and reduction in pharmacologic therapy for older adults with type II diabetes. Meanwhile, behavioral economic (BE) approaches offer promise in influencing hard-to-change behavior, and previous studies have shown the benefits of using electronic health record (EHR) technology to encourage guideline adherence.

OBJECTIVE

This study aimed to develop and pilot test an intervention that leverages BE with EHR technology to promote appropriate diabetes management in older adults.

DESIGN

A pilot study within the New York University Langone Health (NYULH) EHR and Epic system to deliver BE-inspired nudges at five NYULH clinics at varying time points from July 12, 2018, through October 31, 2019.

PARTICIPANTS

Clinicians across five practices in the NYULH system whose patients were older adults (age 76 and older) with type II diabetes.

INTERVENTIONS

A BE-EHR module comprising six nudges was developed through a series of design workshops, interviews, user-testing sessions, and clinic visits. BE principles utilized in the nudges include framing, social norming, accountable justification, defaults, affirmation, and gamification.

MAIN MEASURES

Patient-level CW compliance.

KEY RESULTS

CW compliance increased 5.1% from a 16-week interval at baseline to a 16-week interval post intervention. From February 14 to June 5, 2018 (prior to the first nudge launch in Vanguard clinics), CW compliance for 1278 patients was mean (95% CI)-16.1% (14.1%, 18.1%). From July 3 to October 22, 2019 (after BE-EHR module launch at all five clinics), CW compliance for 680 patients was 21.2% (18.1%, 24.3%).

CONCLUSIONS

The BE-EHR module shows promise for promoting the AGS CW guideline and improving diabetes management in older adults. A randomized controlled trial will commence to test the effectiveness of the intervention across 66 NYULH clinics.

NIH TRIAL REGISTRY NUMBER

NCT03409523.

Effect of Passive Choice and Active Choice Interventions in the Electronic Health Record to Cardiologists on Statin Prescribing: A Cluster Randomized Clinical Trial

Importance

Statin therapy is underused for many patients who could benefit.

Objective

To evaluate the effect of passive choice and active choice interventions in the electronic health record (EHR) to promote guideline-directed statin therapy.

Design, Setting, and Participants

Three-arm randomized clinical trial with a 6-month preintervention period and 6-month intervention. Randomization conducted at the cardiologist level at 16 cardiology practices in Pennsylvania and New Jersey. The study included 82 cardiologists and 11 693 patients. Data were analyzed between May 8, 2019, and January 9, 2020.

Interventions

In passive choice, cardiologists had to manually access an alert embedded in the EHR to select options to initiate or increase statin therapy. In active choice, an interruptive EHR alert prompted the cardiologist to accept or decline guideline-directed statin therapy. Cardiologists in the control group were informed of the trial but received no other interventions.

Main Outcomes and Measures

Primary outcome was statin therapy at optimal dose based on clinical guidelines. Secondary outcome was statin therapy at any dose.

Results

The sample comprised 11 693 patients with a mean (SD) age of 63.8 (9.1) years; 58% were male (n = 6749 of 11 693), 66% were White (n = 7683 of 11 693), and 24% were Black (n = 2824 of 11 693). The mean (SD) 10-year atherosclerotic cardiovascular disease (ASCVD) risk score was 15.4 (10.0); 68% had an ASVCD clinical diagnosis. Baseline statin prescribing rates at the optimal dose were 40.3% in the control arm, 39.1% in the passive choice arm, and 41.2% in the active choice arm. In adjusted analyses, the change in statin prescribing rates at optimal dose over time was not significantly different from control for passive choice (adjusted difference in percentage points, 0.2; 95% CI, -2.9 to 2.8; P = .86) or active choice (adjusted difference in percentage points, 2.4; 95% CI, -0.6 to 5.0; P = .08). In adjusted analyses of the subset of patients with clinical ASCVD, the active choice intervention resulted in a significant increase in statin prescribing at optimal dose relative to control (adjusted difference in percentage points, 3.8; 95% CI, 1.0-6.4; P = .008). No other subset analyses were significant. There were no significant changes in statin prescribing at any dose for either intervention.

Conclusions and Relevance

The passive choice and active choice interventions did not change statin prescribing. In the subgroup of patients with clinical ASCVD, the active choice intervention led to a small increase in statin prescribing at the optimal dose, which could inform the design or targeting of future interventions.

Trial Registration

ClinicalTrials.gov Identifier: NCT03271931.

Social norms interventions to change clinical behaviour in health workers: a systematic review and meta-analysis

Background

A social norms intervention seeks to change the clinical behaviour of a target health worker by exposing them to the values, beliefs, attitudes or behaviours of a reference group or person. These low-cost interventions can be used to encourage health workers to follow recommended professional practice.

Objective

To summarise evidence on whether or not social norms interventions are effective in encouraging health worker behaviour change, and to identify the most effective social norms interventions.

Design

A systematic review and meta-analysis of randomised controlled trials.

Data sources

The following databases were searched on 24 July 2018: Ovid MEDLINE (1946 to week 2 July 2018), EMBASE (1974 to 3 July 2018), Cumulative Index to Nursing and Allied Health Literature (1937 to July 2018), British Nursing Index (2008 to July 2018), ISI Web of Science (1900 to present), PsycINFO (1806 to week 3 July 2018) and Cochrane trials (up to July 2018).

Participants

Health workers took part in the study.

Interventions

Behaviour change interventions based on social norms.

Outcome measures

Health worker clinical behaviour, for example prescribing (primary outcome), and patient health outcomes, for example blood test results (secondary), converted into a standardised mean difference.

Methods

Titles and abstracts were reviewed against the inclusion criteria to exclude any that were clearly ineligible. Two reviewers independently screened the remaining full texts to identify relevant papers. Two reviewers extracted data independently, coded for behaviour change techniques and assessed quality using the Cochrane risk-of-bias tool. We performed a meta-analysis and presented forest plots, stratified by behaviour change technique. Sources of variation were explored using metaregression and network meta-analysis.

Results

A total of 4428 abstracts were screened, 477 full texts were screened and findings were based on 106 studies. Most studies were in primary care or hospitals, targeting prescribing, ordering of tests and communication with patients. The interventions included social comparison (in which information is given on how peers behave) and credible source (which refers to communication from a well-respected person in support of the behaviour). Combined data suggested that interventions that included social norms components were associated with an improvement in health worker behaviour of 0.08 standardised mean differences (95% confidence interval 0.07 to 0.10 standardised mean differences) (n = 100 comparisons), and an improvement in patient outcomes of 0.17 standardised mean differences (95% confidence interval 0.14 to 0.20) (n = 14), on average. Heterogeneity was high, with an overall I 2 of 85.4% (primary) and 91.5% (secondary). Network meta-analysis suggested that three types of social norms intervention were most effective, on average, compared with control: credible source (0.30 standardised mean differences, 95% confidence interval 0.13 to 0.47); social comparison combined with social reward (0.39 standardised mean differences, 95% confidence interval 0.15 to 0.64); and social comparison combined with prompts and cues (0.33 standardised mean differences, 95% confidence interval 0.22 to 0.44).

Limitations

The large number of studies prevented us from requesting additional information from authors. The trials varied in design, context and setting, and we combined different types of outcome to provide an overall summary of evidence, resulting in a very heterogeneous review.

Conclusions

Social norms interventions are an effective method of changing clinical behaviour in a variety of health service contexts. Although the overall result was modest and very variable, there is the potential for social norms interventions to be scaled up to target the behaviour of a large population of health workers and resulting patient outcomes.

Future work

Development of optimised credible source and social comparison behaviour change interventions, including qualitative research on acceptability and feasibility.

Study registration

This study is registered as PROSPERO CRD42016045718.

Funding

This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 41. See the NIHR Journals Library website for further project information.

Implementing nudges for suicide prevention in real-world environments: project INSPIRE study protocol

Background

Suicide is a global health issue. There are a number of evidence-based practices for suicide screening, assessment, and intervention that are not routinely deployed in usual care settings. The goal of this study is to develop and test implementation strategies to facilitate evidence-based suicide screening, assessment, and intervention in two settings where individuals at risk for suicide are especially likely to present: primary care and specialty mental health care. We will leverage methods from behavioral economics, which involves understanding the many factors that influence human decision making, to inform strategy development.

Methods

We will identify key mechanisms that limit implementation of evidence-based suicide screening, assessment, and intervention practices in primary care and specialty mental health through contextual inquiry involving behavioral health and primary care clinicians. Second, we will use contextual inquiry results to systematically design a menu of behavioral economics-informed implementation strategies that cut across settings, in collaboration with an advisory board composed of key stakeholders (i.e., behavioral economists, clinicians, implementation scientists, and suicide prevention experts). Finally, we will conduct rapid-cycle trials to test and refine the menu of implementation strategies. Primary outcomes include clinician-reported feasibility and acceptability of the implementation strategies.

Discussion

Findings will elucidate ways to address common and unique barriers to evidence-based suicide screening, assessment, and intervention practices in primary care and specialty mental health care. Results will yield refined, pragmatically tested strategies that can inform larger confirmatory trials to combat the growing public health crisis of suicide.

Professionalism Revealed: Rethinking Quality Improvement in the Wake of a Pandemic

The pace of health care quality improvement in the United States has been slow. After 2 decades of efforts relying largely on quality measurement and performance-linked payment incentives, we need new ideas and new conversations. As revealed by health care workers’ response to the Covid-19 pandemic, professionalism in health care may be an underused resource. Reframing quality improvement around the linchpin of care delivery — physician agency — could provide much-needed direction by elucidating strategies that address problems of information or motivation when professionals act as agents on their patients’ behalf. These strategies need not rely on measures. Physicians’ collective ability to observe and learn can be better tapped and their intrinsic motivation better supported. This article discusses the inherent limitations of measure-focused approaches, provides a framework for conceiving a next generation of initiatives that aim to improve care by more productively leveraging professionalism, and offers specific directions for policy and practice.

Barriers to hypertension and diabetes management in primary health care in Argentina: qualitative research based on a behavioral economics approach

Despite efforts to improve detection and treatment of adults with hypertension and diabetes in Argentina, many public healthcare system users remain undiagnosed or face barriers in managing these diseases. The purpose of this study is to identify health system, provider, and user-related factors that may hinder detection and treatment of hypertension and diabetes using a traditional and behavioral economics approach. We did qualitative research using in-depth semistructured interviews and focus groups with healthcare providers and adult users of Public Primary Care Clinics. Health system barriers included inadequate care accessibility; poor integration between primary care clinics and local hospitals; lack of resources; and gender bias and neglect of adult chronic disease. Healthcare provider-related barriers were inadequate training; lack of availability or reluctance to adopt Clinical Practice Guidelines; and lack of counseling prioritization. From a behavioral economics perspective, bottlenecks were related to inertia and a status quo, overconfidence, and optimism biases. User-related barriers for treatment adherence included lack of accurate information; resistance to adopt lifelong treatment; affordability; and medical advice mistrust. From a behavioral economics perspective, the most significant bottlenecks were overconfidence and optimism, limited attention, and present biases. Based on these findings, new interventions that aim to improve prevention and control of chronic conditions can be proposed. The study provides empirical evidence regarding the barriers and bottlenecks in managing chronic conditions in primary healthcare settings. Results may contribute to the design of behavioral interventions targeted towards healthcare provision for the affected population.

The effectiveness of behavioral economics-informed interventions on physician behavioral change: A systematic literature review

OBJECTIVE

Interventions informed by behavioral economics have the potential to change behaviors governed by underlying cognitive biases. This has been explored extensively for various use in healthcare including changing patient behavior and, more recently, physician behavior. We aimed to systematically review the literature on the use and effectiveness of behavioral economics-informed interventions in changing physician behavior.

METHOD

We searched Medline, Cochrane Library, EBM Reviews, PsychINFO, EconLit, Business Source Complete and Web of Science for peer-reviewed studies published in English that examined the effectiveness of behavioral economics-informed interventions on physician behavioral change. We included studies of physicians in all care settings and specialties and all types of objectively measured behavioral outcomes. The reporting quality of included studies was appraised using the Effective Public Health Practice Project tool.

RESULTS

We screened 6,439 studies and included 17 studies that met our criteria, involving at least 9,834 physicians. The majority of studies were conducted in the United States, published between 2014 and 2018, and were in the patient safety and quality domain. Reporting quality of included studies included strong (n = 7), moderate (n = 6) and weak (n = 4). Changing default settings and providing social reference points were the most widely studied interventions, with these studies consistently demonstrating their effectiveness in changing physician behavior despite differences in implementation methods among studies. Prescribing behavior was most frequently targeted in included studies, with consistent effectiveness of studied interventions.

CONCLUSION

Changing default settings and providing social reference points were the most frequently studied and consistently effective interventions in changing physician behavior towards guideline-concordant practices. Additional theory-informed research is needed to better understand the mechanisms underlying the effectiveness of these interventions to guide implementation.

Strategies to Improve Participation of Older Adults in Cancer Research

Cancer is a disease associated with aging. As the US population ages, the number of older adults with cancer is projected to dramatically increase. Despite this, older adults remain vastly underrepresented in research that sets the standards for cancer treatments and, consequently, clinicians struggle with how to interpret data from clinical trials and apply them to older adults in practice. A combination of system, clinician, and patient barriers bar opportunities for trial participation for many older patients, and strategies are needed to address these barriers at multiple fronts, five of which are offered here. This review highlights the need to (1) broaden eligibility criteria, (2) measure relevant end points, (3) expand standard trial designs, (4) increase resources (e.g., institutional support, interdisciplinary care, and telehealth), and (5) develop targeted interventions (e.g., behavioral interventions to promote patient enrollment). Implementing these solutions requires a substantial investment in engaging and collaborating with community-based practices, where the majority of older patients with cancer receive their care. Multifaceted strategies are needed to ensure that older patients with cancer, across diverse healthcare settings, receive the highest-quality, evidence-based care.

Impact of a State Opioid Prescribing Limit and Electronic Medical Record Alert on Opioid Prescriptions: a Difference-in-Differences Analysis

BACKGROUND

Prescribing limits are one policy strategy to reduce short-term opioid prescribing, but there is limited evidence of their impact.

OBJECTIVE

Evaluate implementation of a state prescribing limit law and health system electronic medical record (EMR) alert on characteristics of new opioid prescriptions, refill rates, and clinical encounters.

DESIGN

Difference-in-differences study comparing new opioid prescriptions from ambulatory practices in New Jersey (NJ) to controls in Pennsylvania (PA) from 1 year prior to the implementation of a NJ state prescribing limit (May 2016-May 2017) to 10 months after (May 2017-March 2018).

PARTICIPANTS

Adults with new opioid prescriptions in an academic health system with practices in PA and NJ.

INTERVENTIONS

State 5-day opioid prescribing limit plus health system and health system EMR alert.

MAIN MEASURES

Changes in morphine milligram equivalents (MME) and tablet quantity per prescription, refills, and encounters, adjusted for patient and prescriber characteristics.

KEY RESULTS

There were a total of 678 new prescriptions in NJ and 4638 in PA. Prior to the intervention, median MME/prescription was 225 mg in NJ and 150 mg in PA, and median quantity was 30 tablets in both. After implementation, median MME/prescription was 150 mg in both states, and median quantity was 20 in NJ and 30 in PA. In the adjusted model, there was a greater decrease in mean MME and tablet quantity in NJ relative to PA after implementation of the policy plus alert (- 82.99 MME/prescription, 95% CI - 148.15 to - 17.84 and - 10.41 tabs/prescription, 95% CI - 19.70 to - 1.13). There were no significant differences in rates of refills or encounters at 30 days based on exposure to the interventions.

CONCLUSIONS

Implementation of a prescribing limit and EMR alert was associated with an approximately 22% greater decrease in opioid dose per new prescription in NJ compared with controls in PA. The combination of prescribing limits and alerts may be an effective strategy to influence prescriber behavior.

Using Behavioral Economics and Technology to Improve Outcomes in Cardio-Oncology

Patients with cancer are often at elevated risk for cardiovascular disease due to overlapping risk factors and cardiotoxic anticancer treatments. Their cancer diagnoses may be the predominant focus of clinical care, with less of an emphasis on concurrent cardiovascular risk management. Widely adopted technology platforms, including electronic health records and mobile devices, can be leveraged to improve the cardiovascular outcomes of these patients. These technologies alone may be insufficient to change behavior and may have greater impact if combined with behavior change strategies. Behavioral economics is a scientific field that uses insights from economics and psychology to help explain why individuals are often predictably irrational. Combining insights from behavioral economics with these scalable technology platforms can positively impact medical decision-making and sustained healthy behaviors. This review focuses on the principles of behavioral economics and how "nudges" and scalable technology can be used to positively impact clinician and patient behaviors.

Reducing cardiovascular risk among people living with HIV: Rationale and design of the INcreasing Statin Prescribing in HIV Behavioral Economics REsearch (INSPIRE) randomized controlled trial

Cardiovascular disease (CVD) is a major cause of morbidity among people living with HIV (PLWH). Statins can safely and effectively reduce CVD risk in PLWH, but evidence-based statin therapy is under-prescribed in PLWH. Developed using an implementation science framework, INcreasing Statin Prescribing in HIV Behavioral Economics REsearch (INSPIRE) is a stepped-wedge cluster randomized trial that addresses organization-, clinician- and patient-level barriers to statin uptake in Los Angeles community health clinics serving racially and ethnically diverse PLWH. After assessing knowledge about statins and barriers to clinician prescribing and patient uptake, we will design, implement and measure the effectiveness of (1) educational interventions targeting leadership, clinicians, and patients, followed by (2) behavioral economics-informed clinician feedback on statin uptake. In addition, we will assess implementation outcomes, including changes in clinician acceptability of statin prescribing for PLWH, clinician acceptability of the education and feedback interventions, and cost of implementation.

Impact of the KidneyWise toolkit on chronic kidney disease referral practices in Ontario primary care: a prospective evaluation

OBJECTIVES

Chronic kidney disease (CKD) is common; therefore, coordination of care between primary care and nephrology is important. Ontario Renal Network's KidneyWise toolkit was developed to provide guidance on the detection and management of people with CKD in primary care (www.kidneywise.ca). The aim of this study was to evaluate the impact of the April 2015 KidneyWise toolkit release on the characteristics of primary care referrals to nephrology.

DESIGN AND SETTING

The study was a prospective pre-post design conducted at two nephrology sites (community site: Trillium Health Partners in Mississauga, Ontario, Canada, and academic site: St Joseph's Healthcare in Hamilton, Ontario, Canada). Referrals were compared during the 3-month time period immediately prior to, and during a 3-month period 1 year after, the toolkit release.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was the change in proportion of referrals for CKD that met the KidneyWise criteria. Additional secondary referral and quality of care outcomes were also evaluated. Multivariable logistic regression was used to evaluate preselected variables for their independent association with referrals that met the KidneyWise criteria.

RESULTS

The proportion of referrals for CKD among people who met the KidneyWise referral criteria did not significantly change from pre-KidneyWise to post-KidneyWise implementation (44.7% vs 45.8%, respectively, adjusted OR 1.16, 95% CI 0.85 to 1.59, p=0.36). The proportion of referrals for CKD that provided a urine albumin-creatinine ratio significantly increased post-KidneyWise (25.8% vs 43.8%, adjusted OR 1.45, 95% CI 1.06 to 1.97, p=0.02). The significant independent predictors of meeting the KidneyWise referral criteria were academic site, increased age and use of the KidneyWise referral form.

CONCLUSIONS

We did not observe any change in the proportion of appropriate referrals for CKD at two large nephrology centres 1 year after implementation of the KidneyWise toolkit.

Neurological Dashboards and Consultation Turnaround Time at an Academic Medical Center

BACKGROUND

Neurologists perform a significant amount of consultative work. Aggregative electronic health record (EHR) dashboards may help to reduce consultation turnaround time (TAT) which may reflect time spent interfacing with the EHR.

OBJECTIVES

This study was aimed to measure the difference in TAT before and after the implementation of a neurological dashboard.

METHODS

We retrospectively studied a neurological dashboard in a read-only, web-based, clinical data review platform at an academic medical center that was separate from our institutional EHR. Using our EHR, we identified all distinct initial neurological consultations at our institution that were completed in the 5 months before, 5 months after, and 12 months after the dashboard go-live in December 2017. Using log data, we determined total dashboard users, unique page hits, patient-chart accesses, and user departments at 5 months after go-live. We calculated TAT as the difference in time between the placement of the consultation order and completion of the consultation note in the EHR.

RESULTS

By April 30th in 2018, we identified 269 unique users, 684 dashboard page hits (median hits/user 1.0, interquartile range [IQR] = 1.0), and 510 unique patient-chart accesses. In 5 months before the go-live, 1,434 neurology consultations were completed with a median TAT of 2.0 hours (IQR = 2.5) which was significantly longer than during 5 months after the go-live, with 1,672 neurology consultations completed with a median TAT of 1.8 hours (IQR = 2.2; p = 0.001). Over the following 7 months, 2,160 consultations were completed and median TAT remained unchanged at 1.8 hours (IQR = 2.5).

CONCLUSION

At a large academic institution, we found a significant decrease in inpatient consult TAT 5 and 12 months after the implementation of a neurological dashboard. Further study is necessary to investigate the cognitive and operational effects of aggregative dashboards in neurology and to optimize their use.

Association of an Active Choice Intervention in the Electronic Health Record Directed to Medical Assistants With Clinician Ordering and Patient Completion of Breast and Colorectal Cancer Screening Tests

IMPORTANCE

Early cancer detection can lead to improved outcomes, but cancer screening tests are often underused.

OBJECTIVE

To evaluate the association of an active choice intervention in the electronic health record directed to medical assistants with changes in clinician ordering and patient completion of breast and colorectal cancer screening tests.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective quality improvement study was conducted among 69 916 patients eligible for breast or colorectal cancer screening at 25 primary care practices at the University of Pennsylvania Health System between September 1, 2014, and August 31, 2017. Data analysis was conducted from January 21 to July 8, 2019.

INTERVENTIONS

From 2016 to 2017, 3 primary care practices at the University of Pennsylvania Health System implemented an active choice intervention in the electronic health record that prompted medical assistants to inform patients about cancer screening during check-in and template orders for clinicians to review during the visit.

MAIN OUTCOMES AND MEASURES

The primary outcome was clinician ordering of cancer screening tests. The secondary outcome was patient completion of cancer screening tests within 1 year of the primary care visit.

RESULTS

The sample eligible for breast cancer screening comprised 26 269 women with a mean (SD) age of 60.4 (6.9) years; 15 873 (60.4%) were white and 7715 (29.4%) were black. The sample eligible for colorectal cancer screening comprised 43 647 patients with a mean (SD) age of 59.4 (7.5) years; 24 416 (55.9%) were women, 19 231 (44.1%) were men, 29 029 (66.5%) were white, and 9589 (22.0%) were black. For breast cancer screening, the intervention was associated with a significant increase in clinician ordering of tests (22.2 percentage points; 95% CI, 17.2-27.6 percentage points; P < .001) but no change in patient completion (0.1 percentage points; 95% CI, -4.0 to 4.3 percentage points; P = .45). For colorectal cancer screening, the intervention was associated with a significant increase in clinician ordering of tests (13.7 percentage points; 95% CI, 8.0-18.9 percentage points; P < .001) but no change in patient completion (1.0 percentage points; 95% CI, -3.2 to 4.6 percentage points; P = .36).

CONCLUSIONS AND RELEVANCE

An active choice intervention in the electronic health record directed to medical assistants was associated with a significant increase in clinician ordering of breast and colorectal cancer screening tests. However, it was not associated with a significant change in patient completion of either cancer screening test during a 1-year follow-up.

An Audit and Feedback Intervention to Improve Internal Medicine Residents' Performance on Ambulatory Quality Measures: A Randomized Controlled Trial

Audit and feedback is an effective method to improve attending physician performance. However, there are limited data on how audit and feedback impacts care provided by resident physicians. The authors conducted a 3-arm randomized clinical trial among internal medicine resident physicians to examine the impact of an audit and feedback intervention on ambulatory quality measures (AQMs). Residents in all 3 groups received an email containing the contact information of a population health coordinator and a list of AQMs (control). In addition, the Practice Target group received individual AQM data compared to the target AQM goals for all primary care practices. The Peer Comparison group received information on individual AQM data compared to the average performance of residents in the same postgraduate year. Residents in each intervention group received updated information 6 months later. Ten AQMs related to diabetes care, hypertension management, lipid control, and cancer screening, as well as a composite quality score, were examined at baseline, 6 months, and 13 months. At 13 months follow-up, the Practice Target group had statistically significant improvement in cervical cancer screening rate (77% vs. 65.3%), colorectal cancer screening rate (72.5% vs. 64.6%), and composite quality score (71.7% vs 65.4%) compared to baseline. Providing internal medicine residents with individual AQMs data compared to target goal for the practice led to statistically significant improvement in cancer screening rates and the composite quality score. Audit and feedback may be a relatively simple yet effective tool to improve population health in the resident clinic setting.