Background: The emergency department is a critical juncture in the trajectory of care of patients with serious, life-limiting illness. Implementation of a clinical decision support (CDS) tool automates identification of older adults who may benefit from palliative care instead of relying upon providers to identify such patients, thus improving quality of care by assisting providers with adhering to guidelines. The Primary Palliative Care for Emergency Medicine (PRIM-ER) study aims to optimize the use of the electronic health record by creating a CDS tool to identify high risk patients most likely to benefit from primary palliative care and provide point-of-care clinical recommendations. Methods: A clinical decision support tool entitled Emergency Department Supportive Care Clinical Decision Support (Support-ED) was developed as part of an institutionally-sponsored value based medicine initiative at the Ronald O. Perelman Department of Emergency Medicine at NYU Langone Health. A multidisciplinary approach was used to develop Support-ED including: a scoping review of ED palliative care screening tools; launch of a workgroup to identify patient screening criteria and appropriate referral services; initial design and usability testing via the standard System Usability Scale questionnaire, education of the ED workforce on the Support-ED background, purpose and use, and; creation of a dashboard for monitoring and feedback. Results: The scoping review identified the Palliative Care and Rapid Emergency Screening (P-CaRES) survey as a validated instrument in which to adapt and apply for the creation of the CDS tool. The multidisciplinary workshops identified two primary objectives of the CDS: to identify patients with indicators of serious life limiting illness, and to assist with referrals to services such as palliative care or social work. Additionally, the iterative design process yielded three specific patient scenarios that trigger a clinical alert to fire, including: 1) when an advance care planning document was present, 2) when a patient had a previous disposition to hospice, and 3) when historical and/or current clinical data points identify a serious life-limiting illness without an advance care planning document present. Monitoring and feedback indicated a need for several modifications to improve CDS functionality. Conclusions: CDS can be an effective tool in the implementation of primary palliative care quality improvement best practices. Health systems should thoughtfully consider tailoring their CDSs in order to adapt to their unique workflows and environments. The findings of this research can assist health systems in effectively integrating a primary palliative care CDS system seamlessly into their processes of care. Trial registration: ClinicalTrials.gov Identifier: NCT03424109. Registered 6 February 2018, Grant Number: AT009844–01.

Introduction Emergency departments (ED) care for society’s most vulnerable older adults who present with exacerbations of chronic disease at the end of life, yet the clinical paradigm focuses on treatment of acute pathologies. Palliative care interventions in the ED capture high-risk patients at a time of crisis and can dramatically improve patient-centred outcomes. This study aims to implement and evaluate Primary Palliative Care for Emergency Medicine (PRIM-ER) on ED disposition, healthcare utilisation and survival in older adults with serious illness. Methods and analysis This is the protocol for a pragmatic, cluster-randomised stepped wedge trial to test the effectiveness of PRIM-ER in 35 EDs across the USA. The intervention includes four core components: (1) evidence-based, multidisciplinary primary palliative care education; (2) simulation-based workshops; (3) clinical decision support; and (4) audit and feedback. The study is divided into two phases: a pilot phase, to ensure feasibility in two sites, and an implementation and evaluation phase, where we implement the intervention and test the effectiveness in 33 EDs over 2 years. Using Centers for Medicare and Medicaid Services (CMS) data, we will assess the primary outcomes in approximately 300 000 patients: ED disposition to an acute care setting, healthcare utilisation in the 6 months following the ED visit and survival following the index ED visit. Analysis will also determine the site, provider and patient-level characteristics that are associated with variation in impact of PRIM-ER. Ethics and dissemination Institutional Review Board approval was obtained at New York University School of Medicine to evaluate the CMS data. Oversight will also be provided by the National Institutes of Health, an Independent Monitoring Committee and a Clinical Informatics Advisory Board. Trial results will be submitted for publication in a peer-reviewed journal. Trial registration number NCT03424109; Pre-results

Embedded pragmatic clinical trials (ePCTs) play a vital role in addressing current population health problems, and their use of electronic health record (EHR) systems promises efficiencies that will increase the speed and volume of relevant and generalizable research. However, as the number of ePCTs using EHR-derived data grows, so does the risk that research will become more vulnerable to biases due to differences in data capture and access to care for different subsets of the population, thereby propagating inequities in health and the healthcare system. We identify 3 challenges—incomplete and variable capture of data on social determinants of health, lack of representation of vulnerable populations that do not access or receive treatment, and data loss due to variable use of technology—that exacerbate bias when working with EHR data and offer recommendations and examples of ways to actively mitigate bias.

Primary care practices often engage in quality improvement (QI) in order to stay current and meet quality benchmarks, but the extent to which turnover affects practices’ QI ability is not well described. The authors examined qualitative data from practice staff and external facilitators participating in a large-scale QI initiative to understand the relationship between turnover and QI efforts. The examination found turnover can limit practices’ ability to engage in QI activities in various ways. When a staff member leaves, remaining staff often absorb additional responsibilities, and QI momentum slows as new staff are trained or existing staff are reengaged. Turnover alters staff dynamics and can create barriers to constructive working relationships and team building. When key practice members leave, they can take with them institutional memory about QI purpose, processes, and long-term vision. Understanding how turnover affects QI may help practices, and those helping them with QI, manage the disruptive effects of turnover.

Practice facilitation is a promising practice transformation strategy, but further examination of its effectiveness in improving adoption of guidelines for multiple cardiovascular disease risk factors is needed. The objective of the study is to determine whether practice facilitation is effective in increasing the proportion of patients meeting the Million Hearts ABCS outcomes: (A) aspirin when indicated, (B) blood pressure control, (C) cholesterol management, and (S) smoking screening and cessation intervention. The study used a stepped-wedge cluster RCT design with 4 intervention waves. Data were extracted for 13 quarters between January 1, 2015 and March 31, 2018, which encompassed the control, intervention, and follow-up periods for all waves, and analyzed in 2019. A total of 257 small independent primary care practices in New York City were randomized into 1 of 4 waves. The intervention consisted of practice facilitators conducting at least 13 practice visits over 1 year, focused on capacity building and implementing system and workflow changes to meet cardiovascular disease care guidelines. The main outcomes were the Million Hearts' ABCS measures. Two additional measures were created: (1) proportion of tobacco users who received a cessation intervention (smokers counseled) and (2) a composite measure that assessed the proportion of patients meeting treatment targets for A, B, and C (ABC composite). The S measure improved when comparing follow-up with the control period (incidence rate ratio=1.152, 95% CI=1.072, 1.238, p<0.001) and when comparing follow-up with intervention (incidence rate ratio=1.060, 95% CI=1.013, 1.109, p=0.007). Smokers counseled improved when comparing the intervention period with control (incidence rate ratio=1.121, 95% CI=1.037, 1.211, p=0.002). Increasing the impact of practice facilitation programs that target multiple risk factors may require a longer, more intense intervention and greater attention to external policy and practice context. This study is registered at www.clinicaltrials.gov NCT02646488.