Lessons Learned: Evaluation of Fracture Liaison Service Quality Improvement Efforts in a Large Academic Healthcare System.

BACKGROUND: The Fracture Liaison Service (FLS) care model, a care coordination program for patients experiencing a fragility fracture, is proven to improve management of patients with an osteoporotic fracture, but treatment initiation gaps persist. OBJECTIVE: We describe the evolution of a centralized FLS within a university-based healthcare system, including impact of adding clinical pharmacist consultation, and describe circumstances surrounding continued care gaps. DESIGN: Cohort analysis of osteoporosis medication initiation before FLS, after initial implementation, and after addition of pharmacist consultation. PATIENTS: Individuals aged 65 and older experiencing any fragility fracture between 7/1/16 and 3/31/22. INTERVENTION: A centralized team outreached eligible patients, ordered dual x-ray absorptiometry and laboratory tests as needed, and scheduled an osteoporosis-focused primary care appointment. Three years after FLS implementation, clinical pharmacist consultative review was added prior to the primary care visit. MAIN MEASURES: Initiation of osteoporosis pharmacologic therapy, completion of DXA, primary care follow-up rate, and description of circumstances where therapy was not initiated. KEY RESULTS: Of 1204 new fractures between 7/1/16 and 3/31/22, 315 patients were enrolled in one of two FLS phases, and 89 eligible historical controls were identified. Medication initiation rates went from 22/89 (25%) pre-FLS to 201/428 (47%) after-FLS phase 1 [POST1] (p<0.001) and to 106/187 (57%) after FLS phase 2 (POST2), when clinical pharmacist consultation was added (p=0.03 versus POST1). DXA was completed in 56/89 (67%) of pre-FLS patients, 364/428 (85%) POST1 patients (p<0.001 versus pre), and 163/187 (87%) POST2 (p< 0.001 versus PRE, p=0.59 versus POST1). Of 375 patients who did not initiate osteoporosis medication, more in the combined post-FLS cohorts attended a follow-up primary care appointment (233/308, 76% attended, versus pre-FLS 41/67, 61%, p=0.016). CONCLUSION: An FLS including centralized outreach and care coordination significantly improved patient follow-up, DXA, and medication initiation. Addition of de-centralized pharmacist consultation further improved medication initiation rates.

Patterns of red blood cell utilization: Harnessing electronic health records data from the Information Standard for Blood and Transplant (ISBT) 128 system within the Biologics Effectiveness and Safety (BEST) initiative.

BACKGROUND: Current hemovigilance methods generally rely on survey data or administrative claims data utilizing billing and revenue codes, each of which has limitations. We used electronic health records (EHR) linked to blood bank data to comprehensively characterize red blood cell (RBC) utilization patterns and trends in three healthcare systems participating in the U.S. Food and Drug Administration Center for Biologics Evaluation and Research Biologics Effectiveness and Safety (BEST) initiative. METHODS: We used Information Standard for Blood and Transplant (ISBT) 128 codes linked to EHR from three healthcare systems data sources to identify and quantify RBC-transfused individuals, RBC transfusion episodes, transfused RBC units, and processing methods per year during 2012-2018. RESULTS: There were 577,822 RBC units transfused among 112,705 patients comprising 345,373 transfusion episodes between 2012 and 2018. Utilization in terms of RBC units and patients increased slightly in one and decreased slightly in the other two healthcare facilities. About 90% of RBC-transfused patients had 1 (~46%) or 2-5 (~42%)transfusion episodes in 2018. Among the small proportion of patients with ≥12 transfusion episodes per year, approximately 60% of episodes included only one RBC unit. All facilities used leukocyte-reduced RBCs during the study period whereas irradiated RBC utilization patterns differed across facilities. DISCUSSION: ISBT 128 codes and EHRs were used to observe patterns of RBC transfusion and modification methods at the unit level and patient level in three healthcare systems participating in the BEST initiative. This study shows that the ISBT 128 coding system in an EHR environment provides a feasible source for hemovigilance activities.

Making Science Computable Using Evidence-Based Medicine on Fast Healthcare Interoperability Resources: Standards Development Project.

BACKGROUND: Evidence-based medicine (EBM) has the potential to improve health outcomes, but EBM has not been widely integrated into the systems used for research or clinical decision-making. There has not been a scalable and reusable computer-readable standard for distributing research results and synthesized evidence among creators, implementers, and the ultimate users of that evidence. Evidence that is more rapidly updated, synthesized, disseminated, and implemented would improve both the delivery of EBM and evidence-based health care policy. OBJECTIVE: This study aimed to introduce the EBM on Fast Healthcare Interoperability Resources (FHIR) project (EBMonFHIR), which is extending the methods and infrastructure of Health Level Seven (HL7) FHIR to provide an interoperability standard for the electronic exchange of health-related scientific knowledge. METHODS: As an ongoing process, the project creates and refines FHIR resources to represent evidence from clinical studies and syntheses of those studies and develops tools to assist with the creation and visualization of FHIR resources. RESULTS: The EBMonFHIR project created FHIR resources (ie, ArtifactAssessment, Citation, Evidence, EvidenceReport, and EvidenceVariable) for representing evidence. The COVID-19 Knowledge Accelerator (COKA) project, now Health Evidence Knowledge Accelerator (HEvKA), took this work further and created FHIR resources that express EvidenceReport, Citation, and ArtifactAssessment concepts. The group is (1) continually refining FHIR resources to support the representation of EBM; (2) developing controlled terminology related to EBM (ie, study design, statistic type, statistical model, and risk of bias); and (3) developing tools to facilitate the visualization and data entry of EBM information into FHIR resources, including human-readable interfaces and JSON viewers. CONCLUSIONS: EBMonFHIR resources in conjunction with other FHIR resources can support relaying EBM components in a manner that is interoperable and consumable by downstream tools and health information technology systems to support the users of evidence.

Dermatologic Research Potential of the Observational Health Data Sciences and Informatics (OHDSI) Network.

BACKGROUND: The Observational Health Data Sciences and Informatics (OHDSI) network enables access to billions of deidentified, standardized health records and built-in analytics software for observational health research, with numerous potential applications to dermatology. While the use of the OHDSI has increased steadily over the past several years, review of the literature reveals few studies utilizing OHDSI in dermatology. To our knowledge, the University of Colorado School of Medicine is unique in its use of OHDSI for dermatology big data research. SUMMARY: A PubMed search was conducted in August 2020, followed by a literature review, with 24 of the 72 screened articles selected for inclusion. In this review, we discuss the ways OHDSI has been used to compile and analyze data, improve prediction and estimation capabilities, and inform treatment guidelines across specialties. We also discuss the potential for OHDSI in dermatology - specifically, ways that it could reveal adherence to available guidelines, establish standardized protocols, and ensure health equity. Key Messages: OHDSI has demonstrated broad utility in medicine. Adoption of OHDSI by the field of dermatology would facilitate big data research, allow for examination of current prescribing and treatment patterns without clear best practice guidelines, improve the dermatologic knowledge base and, by extension, improve patient outcomes.

Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom.

BACKGROUND: A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity. METHODS: We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status. RESULTS: We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8-40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0-33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity. CONCLUSION: We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.

Efficient determination of equivalence for encrypted data.

Secure computation of equivalence has fundamental application in many different areas, including health-care. We study this problem in the context of matching an individual's identity to link medical records across systems under the socialist millionaires' problem: Two millionaires wish to determine if their fortunes are equal without disclosing their net worth (Boudot, et al. 2001). In Theorem 2, we show that when a "greater than" algorithm is carried out on a totally ordered set it is easy to achieve secure matching without additional rounds of communication. We present this efficient solution to assess equivalence using a set intersection algorithm designed for "greater than" computation and demonstrate its effectiveness on equivalence of arbitrary data values, as well as demonstrate how it meets regulatory criteria for risk of disclosure.

Characterizing treatment pathways at scale using the OHDSI network.

Observational research promises to complement experimental research by providing large, diverse populations that would be infeasible for an experiment. Observational research can test its own clinical hypotheses, and observational studies also can contribute to the design of experiments and inform the generalizability of experimental research. Understanding the diversity of populations and the variance in care is one component. In this study, the Observational Health Data Sciences and Informatics (OHDSI) collaboration created an international data network with 11 data sources from four countries, including electronic health records and administrative claims data on 250 million patients. All data were mapped to common data standards, patient privacy was maintained by using a distributed model, and results were aggregated centrally. Treatment pathways were elucidated for type 2 diabetes mellitus, hypertension, and depression. The pathways revealed that the world is moving toward more consistent therapy over time across diseases and across locations, but significant heterogeneity remains among sources, pointing to challenges in generalizing clinical trial results. Diabetes favored a single first-line medication, metformin, to a much greater extent than hypertension or depression. About 10% of diabetes and depression patients and almost 25% of hypertension patients followed a treatment pathway that was unique within the cohort. Aside from factors such as sample size and underlying population (academic medical center versus general population), electronic health records data and administrative claims data revealed similar results. Large-scale international observational research is feasible.

Implementation and Evaluation of a Novel Colorectal Cancer Decision Aid Using a Centralized Delivery Strategy.

BACKGROUND: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States; however, CRC screening reduces both incidence and mortality rates. Patient decision aids (DAs) are an evidence-based strategy to support patients making health-related decisions. CRC screening DAs can be unsuccessful due to provider preferences for colonoscopy and lack of effective DA implementation strategies within clinical settings. METHODS: A hybrid implementation-effectiveness study was conducted testing the feasibility of using an existing centralized preventive health screening outreach infrastructure to implement a novel CRC DA across a health care system. Participants included primary care patients at one of three study clinics. Implementation was assessed by determining whether patients remembered receiving the DA and were aware of CRC screening options. Effectiveness was measured by comparing overall screening rates between the control and intervention groups. RESULTS: Using a centralized delivery system was a feasible and efficient method for implementing DAs to a large academic health system. More than 90% of the intervention group remembered receiving the DA, and 80% found it helpful in their decision-making process. The DA was successful in improving CRC screening knowledge; however, overall CRC screening rates significantly decreased between the control and intervention periods (50.8% vs. 39.2%, respectively; p = 0.03). CONCLUSION: Centralized delivery is a feasible method for DA implementation. Although DAs increase knowledge, the true effectiveness of CRC DAs in clinical settings is unknown, as a result of the number in screening tests, diversity in DA format, and the variability in dissemination and implementation practices.

Perfectly Secure and Efficient Two-Party Electronic-Health-Record Linkage.

Patient health data are often found spread across various sources. However, precision medicine and personalized care requires access to the complete medical records. The first step towards this is to enable the linkage of health records spread across different sites. Existing record linkage solutions assume that data is centralized with no privacy/security concerns restricting sharing. However, that is often untrue. Therefore, we design and implement a portable method for privacy-preserving record linkage based on garbled circuits to accurately and securely match records. We also develop a novel approximate matching mechanism that significantly improves efficiency.

Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.

BACKGROUND: Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and transformed into a common format and standard terminologies, and optimally linked to other data sources. The expertise and scalable solutions needed to transform data to conform to network requirements are beyond the scope of many health care organizations and there is a need for practical tools that lower the barriers of data contribution to clinical research networks. METHODS: We designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code, while retaining manual aspects of the process that requires knowledge of complex coding syntax. This approach provides the flexibility required for the ETL of heterogeneous data, variations in semantic expertise, and transparency of transformation logic that are essential to implement ETL conventions across clinical research sharing networks. Processing workflows are directed by the ETL specifications guideline, developed by ETL designers with extensive knowledge of the structure and semantics of health data (i.e., "health data domain experts") and target common data model. RESULTS: D-ETL was implemented to perform ETL operations that load data from various sources with different database schema structures into the Observational Medical Outcome Partnership (OMOP) common data model. The results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets. CONCLUSIONS: D-ETL supports a flexible and transparent process to transform and load health data into a target data model. This approach offers a solution that lowers technical barriers that prevent data partners from participating in research data networks, and therefore, promotes the advancement of comparative effectiveness research using secondary electronic health data.

Improving record linkage performance in the presence of missing linkage data.

INTRODUCTION: Existing record linkage methods do not handle missing linking field values in an efficient and effective manner. The objective of this study is to investigate three novel methods for improving the accuracy and efficiency of record linkage when record linkage fields have missing values. METHODS: By extending the Fellegi-Sunter scoring implementations available in the open-source Fine-grained Record Linkage (FRIL) software system we developed three novel methods to solve the missing data problem in record linkage, which we refer to as: Weight Redistribution, Distance Imputation, and Linkage Expansion. Weight Redistribution removes fields with missing data from the set of quasi-identifiers and redistributes the weight from the missing attribute based on relative proportions across the remaining available linkage fields. Distance Imputation imputes the distance between the missing data fields rather than imputing the missing data value. Linkage Expansion adds previously considered non-linkage fields to the linkage field set to compensate for the missing information in a linkage field. We tested the linkage methods using simulated data sets with varying field value corruption rates. RESULTS: The methods developed had sensitivity ranging from .895 to .992 and positive predictive values (PPV) ranging from .865 to 1 in data sets with low corruption rates. Increased corruption rates lead to decreased sensitivity for all methods. CONCLUSIONS: These new record linkage algorithms show promise in terms of accuracy and efficiency and may be valuable for combining large data sets at the patient level to support biomedical and clinical research.

Patient Perception and Impact of Home Test Kits on Health Care Utilization for Urinary Tract Infection.

Urinary tract infection (UTI) is a common reason for emergency department (ED) utilization that could potentially be treated by a primary care provider (PCP). This study assessed patient perceived value of a home UTI test kit plus educational materials and its impact on ED utilization for a UTI symptom episode. Women aged 18-75 years with Medicaid insurance and a history of 1-3 uncomplicated UTIs in the past year were prospectively identified and randomized to the intervention, intervention plus (intervention plus a patient portal message before its delivery), or standard of care group. A telephone survey was conducted 3-5 months after the mailing. Site of care for each UTI symptom episode was measured 12 months before and 6 months after the intervention. Test kit packages were mailed to 266 intervention individuals, and 150 responded to the telephone survey. Utilization outcomes were compared between a combined intervention group and a control group. Approximately one-third of the intervention patients experienced UTI symptoms within 5 months, and 73% used the test kit. Of those who experienced UTI symptoms, 58% contacted their PCP to seek care and 96% reported that the test kit was helpful. ED utilization was not significantly different in the intervention groups before and after the intervention, nor between the intervention and control groups postintervention. A home UTI test kit plus educational materials mailed to patients with a history of uncomplicated UTI was deemed helpful but did not have a measurable impact on ED utilization.

Linkability measures to assess the data characteristics for record linkage.

OBJECTIVES: Accurate record linkage (RL) enables consolidation and de-duplication of data from disparate datasets, resulting in more comprehensive and complete patient data. However, conducting RL with low quality or unfit data can waste institutional resources on poor linkage results. We aim to evaluate data linkability to enhance the effectiveness of record linkage. MATERIALS AND METHODS: We describe a systematic approach using data fitness ("linkability") measures, defined as metrics that characterize the availability, discriminatory power, and distribution of potential variables for RL. We used the isolation forest algorithm to detect abnormal linkability values from 188 sites in Indiana and Colorado, and manually reviewed the data to understand the cause of anomalies. RESULT: We calculated 10 linkability metrics for 11 potential linkage variables (LVs) across 188 sites for a total of 20 680 linkability metrics. Potential LVs such as first name, last name, date of birth, and sex have low missing data rates, while Social Security Number vary widely in completeness among all sites. We investigated anomalous linkability values to identify the cause of many records having identical values in certain LVs, issues with placeholder values disguising data missingness, and orphan records. DISCUSSION: The fitness of a variable for RL is determined by its availability and its discriminatory power to uniquely identify individuals. These results highlight the need for awareness of placeholder values, which inform the selection of variables and methods to optimize RL performance. CONCLUSION: Evaluating linkability measures using the isolation forest algorithm to highlight anomalous findings can help identify fitness-for-use issues that must be addressed before initiating the RL process to ensure high-quality linkage outcomes.

Improving Maternal Health Care Quality and Outcomes: Evaluation of a Pregnancy Medical Home.

Current maternal care recommendations in the United States focus on monitoring fetal development, management of pregnancy complications, and screening for behavioral health concerns. Often missing from these recommendations is support for patients experiencing socioeconomic or behavioral health challenges during pregnancy. A Pregnancy Medical Home (PMH) is a multidisciplinary maternal health care team with nurse navigators serving as patient advocates to improve the quality of care a patient receives and health outcomes for both mother and infant. Using bivariate comparisons between PMH patients and reference groups, as well as interviews with project team members and PMH graduates, this evaluation assessed the impact of a PMH at an academic medical university on patient care and birth outcomes. This PMH increased depression screenings during pregnancy and increased referrals to behavioral health care. This evaluation did not find improvements in maternal or infant birth outcomes. Interviews found notable successes and areas for program enhancement.

Prescribing Patterns of Dupilumab for Atopic Dermatitis in Adults: Retrospective, Observational Cohort Study.

BACKGROUND: Atopic dermatitis (AD) is a common inflammatory disease caused by a type 2 T helper cell-mediated immune response to environmental antigens. Approximately 1 in 5 patients with AD presents with moderate to severe disease, and treatments approved by the Food and Drug Administration include emollients, topical glucocorticoids, and calcineurin inhibitors. Dupilumab, a fully human monoclonal antibody, improves AD via inhibition of interleukin-4 and interleukin-13. OBJECTIVE: Our aim was to characterize the prescribing patterns of dupilumab for AD in adults at a large university-affiliated health system. METHODS: A retrospective, observational cohort study was conducted using electronic data from the Observational Health Data Sciences and Informatics database, assessing data from the University of Colorado Medical Campus and its affiliates. The outcome measured was the prevalence of dupilumab prescribed for adults with AD (n=6421), between March 28, 2013, and March 28, 2021. We assessed whether the characteristics of patients who received dupilumab were different from those who did not. Each patient characteristic was assessed using a univariate logistic regression with the binary outcome of receiving or not receiving dupilumab. RESULTS: We found a population prevalence of 5.6% (6421/114,476) for AD. In our cohort, Black patients with AD were more than twice as likely to have received dupilumab compared to White patients (odds ratio 2.352, 95% CI 1.58-3.39). Patients with a diagnosis of atopic neurodermatitis were approximately twice as likely to have received dupilumab compared to those with other diagnostic variants of AD (odds ratio 1.87, 95% CI 1.01-3.22). CONCLUSIONS: Our results demonstrate that both patient racial characteristics and specific AD diagnoses were associated with variations in dupilumab prescription patterns.

A Transgender Health Information Resource: Participatory Design Study.

BACKGROUND: Despite the abundance of health information on the internet for people who identify as transgender and gender diverse (TGD), much of the content used is found on social media channels, requiring individuals to vet the information for relevance and quality. OBJECTIVE: We developed a prototype transgender health information resource (TGHIR) delivered via a mobile app to provide credible health and wellness information for people who are TGD. METHODS: We partnered with the TGD community and used a participatory design approach that included focus groups and co-design sessions to identify users' needs and priorities. We used the Agile software development methodology to build the prototype. A medical librarian and physicians with expertise in transgender health curated a set of 97 information resources that constituted the foundational content of the prototype. To evaluate the prototype TGHIR app, we assessed the app with test users, using a single item from the System Usability Scale to assess feature usability, cognitive walk-throughs, and the user version of the Mobile Application Rating Scale to evaluate the app's objective and subjective quality. RESULTS: A total of 13 people who identified as TGD or TGD allies rated their satisfaction with 9 of 10 (90%) app features as good to excellent, and 1 (10%) of the features-the ability to filter to narrow TGHIR resources-was rated as okay. The overall quality score on the user version of the Mobile Application Rating Scale was 4.25 out of 5 after 4 weeks of use, indicating a good-quality mobile app. The information subscore received the highest rating, at 4.75 out of 5. CONCLUSIONS: Community partnership and participatory design were effective in the development of the TGHIR app, resulting in an information resource app with satisfactory features and overall high-quality ratings. Test users felt that the TGHIR app would be helpful for people who are TGD and their care partners.

Co-design of the Transgender Health Information Resource: Web-Based Participatory Design.

BACKGROUND: There is an urgent and unmet need for accessible and credible health information within the transgender and gender-diverse (TGD) community. Currently, TGD individuals often seek and must find relevant resources by vetting social media posts. A resource that provides accessible and credible health-related resources and content via a mobile phone app may have a positive impact on and support the TGD population. OBJECTIVE: COVID-19 stay-at-home orders forced a shift in the methods used in participatory design. In this paper, we aimed to describe the web-based participatory methods used to develop the Transgender Health Information Resource. We also described and characterized the web-based engagement that occurred during a single session of the overall design process. METHODS: We planned and conducted web-based design sessions to replace the proposed in-person sessions. We used web-based collaborative tools, including Zoom (Zoom Video Communications), Mural (Mural), REDCap (Research Electronic Data Capture; Vanderbilt University), and Justinmind (Justinmind), to engage the participants in the design process. Zoom was used as an integrated platform for design activities. Mural was used to perform exercises, such as free listing, brainstorming, and grouping. REDCap allowed us to collect survey responses. Justinmind was used to create prototypes that were shared and discussed via Zoom. Recruitment was led by one of our community partners, One Colorado, who used private Facebook groups in which web-based flyers were dispersed. The design process took place in several workshops over a period of 10 months. We described and characterized engagement during a single design session by tracking the number of influential interactions among participants. We defined an influential interaction as communication, either verbal or web-based content manipulation, that advanced the design process. RESULTS: We presented data from a single design session that lasted 1 hour and 48 minutes and included 4 participants. During the session, there were 301 influential interactions, consisting of 79 verbal comments and 222 web-based content manipulations. CONCLUSIONS: Web-based participatory design can elicit input and decisions from participants to develop a health information resource, such as a mobile app user interface. Overall, participants were highly engaged. This approach maintained the benefits and fidelity of traditional in-person design sessions, mitigated deficits, and exploited the previously unconsidered benefits of web-based methods, such as enhancing the ability to participate for those who live far from academic institutions. The web-based approach to participatory design was an efficient and feasible methodological design approach.

Playing in the clinical decision support sandbox: tools and training for all.

Objectives: Introduce the CDS-Sandbox, a cloud-based virtual machine created to facilitate Clinical Decision Support (CDS) developers and implementers in the use of FHIR- and CQL-based open-source tools and technologies for building and testing CDS artifacts. Materials and Methods: The CDS-Sandbox includes components that enable workflows for authoring and testing CDS artifacts. Two workshops at the 2020 and 2021 AMIA Annual Symposia were conducted to demonstrate the use of the open-source CDS tools. Results: The CDS-Sandbox successfully integrated the use of open-source CDS tools. Both workshops were well attended. Participants demonstrated use and understanding of the workshop materials and provided positive feedback after the workshops. Discussion: The CDS-Sandbox and publicly available tutorial materials facilitated an understanding of the leading-edge open-source CDS infrastructure components. Conclusion: The CDS-Sandbox supports integrated use of the key CDS open-source tools that may be used to introduce CDS concepts and practice to the clinical informatics community.

Patient and researcher stakeholder preferences for use of electronic health record data: a qualitative study to guide the design and development of a platform to honor patient preferences.

OBJECTIVE: This qualitative study aimed to understand patient and researcher perspectives regarding consent and data-sharing preferences for research and a patient-centered system to manage consent and data-sharing preferences. MATERIALS AND METHODS: We conducted focus groups with patient and researcher participants recruited from three academic health centers via snowball sampling. Discussions focused on perspectives on the use of electronic health record (EHR) data for research. Themes were identified through consensus coding, starting from an exploratory framework. RESULTS: We held two focus groups with patients (n = 12 patients) and two with researchers (n = 8 researchers). We identified two patient themes (1-2), one theme common to patients and researchers (3), and two researcher themes (4-5). Themes included (1) motivations for sharing EHR data, (2) perspectives on the importance of data-sharing transparency, (3) individual control of personal EHR data sharing, (4) how EHR data benefits research, and (5) challenges researchers face using EHR data. DISCUSSION: Patients expressed a tension between the benefits of their data being used in studies to benefit themselves/others and avoiding risk by limiting data access. Patients resolved this tension by acknowledging they would often share their data but wanted greater transparency on its use. Researchers expressed concern about incorporating bias into datasets if patients opted out. CONCLUSIONS: A research consent and data-sharing platform must consider two competing goals: empowering patients to have more control over their data and maintaining the integrity of secondary data sources. Health systems and researchers should increase trust-building efforts with patients to engender trust in data access and use.

Community Engagement in Research and Design of a Transgender Health Information Resource.

BACKGROUND: Access to credible and relevant health care information is an unmet need for the transgender and gender-diverse (TGD) community. This paper describes the community engagement methods and resulting community priorities as part of a codesign process for the development of a Transgender Health Information Resource (TGHIR) application. METHODS: A lesbian, gay, bisexual, transgender, and queer advocacy organization and an academic health sciences team partnered to establish a community advisory board (CAB) of TGD individuals, parents of TGD individuals, and clinicians with expertise in transgender health to inform the project. The analytic-deliberative model and group facilitation strategies based on Liberating Structures guided procedures. Affinity grouping was used to synthesize insights from CAB meeting notes regarding roles and perspectives on the design of the TGHIR application. We used the Patient Engagement in Research Scale (PEIRS) to evaluate CAB members' experience with the project. RESULTS: The CAB emphasized the importance of designing the application with and for the TGD community, including prioritizing intersectionality and diversity. CAB engagement processes benefited from setting clear expectations, staying focused on goals, synchronous and asynchronous work, and appreciating CAB member expertise. TGHIR application scope and priorities included a single source to access relevant, credible health information, the ability to use the app discreetly, and preserving privacy (i.e., safe use). An out-of-scope CAB need was the ability to identify both culturally and clinically competent TGD health care providers. PEIRS results showed CAB members experienced moderate to high levels of meaningful engagement (M[standard deviation] = 84.7[12] out of 100). CONCLUSION: A CAB model was useful for informing TGHIR application priority features. In-person and virtual methods were useful for engagement. The CAB continues to be engaged in application development, dissemination, and evaluation. The TGHIR application may complement, but will not replace, the need for both culturally and clinically competent health care for TGD people.