Healthcare systems collaborating to implement a shared decision-making tool in the electronic health record and build evidence on its adoption and use.

Introduction: Shared decision-making (SDM) is a method of care by which patients and clinicians work together to co-create a plan of care. Electronic health record (EHR) integration of SDM tools may increase adoption of SDM. We conducted a "lightweight" integration of a freely available electronic SDM tool, CV Prevention Choice, within the EHRs of three healthcare systems. Here, we report how the healthcare systems collaborated to achieve integration. Methods: This work was conducted as part of a stepped wedge randomized pragmatic trial. CV Prevention Choice was developed using guidelines for HTML5-based web applications. Healthcare systems integrated the tool in their EHR using documentation the study team developed and refined with lessons learned after each system integrated the electronic SDM tool into their EHR. CV Prevention Choice integration populates the tool with individual patient data locally without sending protected health information between the EHR and the web. Data abstraction and secure transfer systems were developed to manage data collection to assess tool implementation and effectiveness outcomes. Results: Time to integrate CV Prevention Choice in the EHR was 12.1 weeks for the first system, 10.4 weeks for the second, and 9.7 weeks for the third. One system required two 1-hour meetings with study team members and two healthcare systems required a single 1-hour meeting. Healthcare system information technology teams collaborated by sharing information and offering improvements to documentation. Challenges included tracking CV Prevention Choice use for reporting and capture of combination medications. Data abstraction required refinements to address differences in how each healthcare system captured data elements. Conclusion: Targeted documentation on tool features and resource mapping supported collaboration of IT teams across healthcare systems, enabling them to integrate a web-based SDM tool with little additional research team effort or oversight. Their collaboration helped overcome difficulties integrating the web application and address challenges to data harmonization for trial outcome analyses.

The design and development of an encounter tool to support shared decision making about preventing cardiovascular events.

Patients at high risk for cardiovascular disease (CVD) tend to receive less intensive preventive care. Clinical practice guidelines recommend shared decision making (SDM) to improve the quality of primary CVD prevention. There are tools for use during the clinical encounter that promote SDM, but, to our knowledge, there are no SDM encounter tools that support conversations about available lifestyle and pharmacological options that can lead to preventive care that is congruent with patient goals and CVD risk. Using the best available evidence and human-centered design (iterative design in the context of ultimate use with users), our team developed a SDM encounter tool, CV Prevention Choice. Each subsequent version during the iterative development process was evaluated in terms of content, usefulness, and usability by testing it in real preventive encounters. The final version of the tool includes a calculator that estimates the patient's risk of a major atherosclerotic CVD event in the next 10 years. Lifestyle and medication options are presented, alongside their pros, cons, costs, and other burdens. The risk reduction achieved by the selected prevention program is then displayed to support collaborative deliberation and decision making. A U.S. multicenter trial is estimating the effectiveness of CV Prevention Choice in achieving risk-concordant CV prevention while identifying the best strategies for increasing the adoption of the SDM encounter tool and its routine use in practice.

Increasing risk-concordant cardiovascular care in diverse health systems: a mixed methods pragmatic stepped wedge cluster randomized implementation trial of shared decision making (SDM4IP).

BACKGROUND: The primary prevention of cardiovascular (CV) events is often less intense in persons at higher CV risk and vice versa. Clinical practice guidelines recommend that clinicians and patients use shared decision making (SDM) to arrive at an effective and feasible prevention plan that is congruent with each person's CV risk and informed preferences. However, SDM does not routinely happen in practice. This study aims to integrate into routine care an SDM decision tool (CV PREVENTION CHOICE) at three diverse healthcare systems in the USA and study strategies that foster its adoption and routine use. METHODS: This is a mixed method, hybrid type III stepped wedge cluster randomized study to estimate (a) the effectiveness of implementation strategies on SDM uptake and utilization and (b) the extent to which SDM results in prevention plans that are risk-congruent. Formative evaluation methods, including clinician and stakeholder interviews and surveys, will identify factors likely to impact feasibility, acceptability, and adoption of CV PREVENTION CHOICE as well as normalization of CV PREVENTION CHOICE in routine care. Implementation facilitation will be used to tailor implementation strategies to local needs, and implementation strategies will be systematically adjusted and tracked for assessment and refinement. Electronic health record data will be used to assess implementation and effectiveness outcomes, including CV PREVENTION CHOICE reach, adoption, implementation, maintenance, and effectiveness (measured as risk-concordant care plans). A sample of video-recorded clinical encounters and patient surveys will be used to assess fidelity. The study employs three theoretical approaches: a determinant framework that calls attention to categories of factors that may foster or inhibit implementation outcomes (the Consolidated Framework for Implementation Research), an implementation theory that guides explanation or understanding of causal influences on implementation outcomes (Normalization Process Theory), and an evaluation framework (RE-AIM). DISCUSSION: By the project's end, we expect to have (a) identified the most effective implementation strategies to embed SDM in routine practice and (b) estimated the effectiveness of SDM to achieve feasible and risk-concordant CV prevention in primary care. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04450914 . Posted June 30, 2020 TRIAL STATUS: This study received ethics approval on April 17, 2020. The current trial protocol is version 2 (approved February 17, 2021). The first subject had not yet been enrolled at the time of submission.

A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation.

Population factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/or groups. Hence, availability of compiled data on abundance of DMET proteins in different populations can be useful for developing physiologically based pharmacokinetic (PBPK) models. The latter are routinely employed for prediction of PK profiles and drug interactions during drug development and in case of special populations, where clinical studies either are not feasible or have ethical concerns. Therefore, the main aim of this work was to develop a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors. The collation of literature reported data revealed high inter-laboratory variability in abundance of DMET proteins. We carried out unbiased meta-analysis to obtain weighted mean and percent coefficient of variation (%CV) values. The obtained %CV values were then integrated into a PBPK model to highlight the variability in drug PK in healthy adults, taking lamotrigine as a model drug. The validated PBPK model was extrapolated to predict PK of lamotrigine in paediatric and hepatic impaired populations. This study thus exemplifies importance of the DMET protein abundance database, and use of determined values of weighted mean and %CV after meta-analysis in PBPK modelling for the prediction of PK of drugs in healthy and special populations.

Cardiac allograft rejection as a complication of PD-1 checkpoint blockade for cancer immunotherapy: a case report.

INTRODUCTION: The increased availability of immunotherapeutic agents for the treatment of a wide array of cancer in the general oncology practice setting will reveal rare and unique toxicities. MATERIALS AND METHODS: The mechanism of cardiac allograft rejection in the context of PD-1 antibody therapy was explored in a patient with cutaneous squamous cell cancer complicating long-standing cardiac allograft. Immune cell infiltrate in the myocardium and peripheral blood lymphocyte repertoire were assessed using myocardial biopsy and temporal analysis of peripheral blood samples. The efficacy of high-intensity immunosuppression to reverse graft rejection was explored. RESULTS: Endomyocardial biopsy showed acute moderate diffuse cellular rejection with a predominant population of CD3+, CD8+ and CD4+ infiltrating lymphocytes; peripheral blood circulating lymphocytes showed a high frequency of proliferating and activated CD8+ T cells expressing PD-1 compared to a normal control. There was no difference in the activation and proliferation of CD4+ T cells compared to a normal control. Cardiac function improved following high-intensity immunosuppression and patient survived for up to 7 months after discontinuation of nivolumab. CONCLUSIONS: Immune checkpoint inhibitors should be avoided in allograft recipients but high-intensity immunosuppression is effective to salvage allograft rejection induced by these agents.