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The scale and severity of the opioid epidemic call for innovative, multipronged solutions. Research and development is key to accelerate the discovery and evaluation of interventions that support pain and substance use disorder management. In parallel, the use and integration of blockchain technology within research networks holds the potential to address some of the unique challenges facing opioid research. This paper discusses the applications of blockchain technology and illustrates potential ways in which it could be applied to strengthen the validity of outcomes research on the opioid epidemic. We reviewed published and gray literature to identify useful applications of blockchain, specifically those that address the challenges faced by opioid research networks and programs. We then convened a panel of experts to discuss the strengths, limitations, and feasibility of each application. Blockchain has the potential to address some of the issues surrounding health data management, including data availability, data sharing and interoperability, and privacy and security. We identified five primary applications of blockchain to opioids: clinical trials and pharmaceutical research, incentivizing data donation and behavior change, secure exchange and management of e-prescriptions, supply chain management, and secondary use of clinical data for research and public health surveillance. The published literature was limited, leading us to rely on gray literature, which was also limited in its discussion of the technical aspects of implementation. The technical expert panel provided additional context and an assessment of feasibility that was lacking in the literature. Research on opioid use and misuse is challenging because of disparate data stored across different systems, data and system interoperability issues, and legal requirements. These areas must be navigated to make data accessible, timely, and useful to researchers. Blockchain technologies have the potential to act as a facilitator in this process, offering a more efficient, secure, and privacy-preserving solution for data exchange. Among the 5 primary applications, we found that clinical trial research, supply chain management, and secondary use of data had the most examples in practice and the potential effectiveness of blockchain. More discussions and studies should focus on addressing technical questions concerning scalability and tackling practical concerns such as cost, standards, and governance around the implementation of blockchain in health care. Policy concerns related to balancing the need for data accessibility that also protects patient privacy and autonomy in revoking consent should also be examined.

HIV has been reported to be cytotoxic in vitro and in lymph node infection models. Using a computational approach, we found that partial inhibition of transmissions of multiple virions per cell could lead to increased numbers of live infected cells. If the number of viral DNA copies remains above one after inhibition, then eliminating the surplus viral copies reduces cell death. Using a cell line, we observed increased numbers of live infected cells when infection was partially inhibited with the antiretroviral efavirenz or neutralizing antibody. We then used efavirenz at concentrations reported in lymph nodes to inhibit lymph node infection by partially resistant HIV mutants. We observed more live infected lymph node cells, but with fewer HIV DNA copies per cell, relative to no drug. Hence, counterintuitively, limited attenuation of HIV transmission per cell may increase live infected cell numbers in environments where the force of infection is high.

Objective: To use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows., Methods: To generate and refine models, we used (1) targeted literature reviews; (2) key informant interviews with 6 external PC CDS experts; (3) model refinement based on authors' experience; and (4) validation of the models by a 26-member steering committee., Results and Discussion: We identified 7 major issues that provide significant challenges and opportunities for healthcare systems, researchers, administrators, and health IT and app developers. Overcoming these challenges presents opportunities for new or modified policies, processes, procedures, technology, and expertise to: (1) Ensure patient-generated health data (PGHD), including patient-reported outcomes (PROs), are documented, reviewed, and managed by appropriately trained clinicians, between visits and after regular working hours. (2) Educate patients to use connected medical devices and handle technical issues. (3) Facilitate collection and incorporation of PGHD, PROs, patient preferences, and social determinants of health into existing electronic health records. (4) Troubleshoot erroneous data received from devices. (5) Develop dashboards to display longitudinal patient-reported data. (6) Provide reimbursement to support new models of care. (7) Support patient engagement with remote devices., Conclusion: Several new policies, processes, technologies, and expertise are required to ensure safe and effective implementation and use of PC CDS. As we gain more experience implementing and working with PC CDS, we should be able to begin realizing the long-term positive impact on patient health that the patient-centered movement in healthcare promises., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Patient-centered clinical decision support (PC CDS) includes digital health tools that support patients, caregivers, and care teams in healthcare decisions that incorporate patient-centered factors related to four components: knowledge, data, delivery, and use. This paper explores the current state of each factor and how each promotes patient-centeredness in healthcare. We conducted a literature review, reviewing 175 peer-reviewed and grey literature, and eighteen key informant interviews. Findings show a need for more research on how to incorporate patient input into the guideline selection and prioritization for PC CDS, development and implementation of PC CDS tools, technical challenges for capturing patient contributed data, and optimizing PC CDS across various settings to meet patient and caregiver needs. While progress is being made in each of the four components of PC CDS, critical gaps remain.

Background: Medicare patients and other stakeholders often make health care decisions that have economic consequences. Research on economic variables that patients have identified as important is referred to as patient-centered outcomes research (PCOR) and can generate evidence that informs decision-making. Medicare fee-for-service (FFS) claims are widely used for research and are a potentially valuable resource for studying some economic variables, particularly when linked to other datasets., Objective: The aim of this study was to identify and assess the characteristics of federally funded administrative and survey data sources that can be linked to Medicare claims for conducting PCOR on some economic outcomes., Research Design: A targeted internet search was conducted to identify a list of relevant data sources. A technical panel and key informant interviews were used for guidance and feedback., Results: We identified 12 survey and 6 administrative sources of linked data for Medicare FFS beneficiaries. A majority provide longitudinal data and are updated annually. All linked sources provide some data on social determinants of health and health equity-related factors. Fifteen sources capture direct medical costs (beyond Medicare FFS payments); 5 capture indirect costs (eg, lost wages from absenteeism), and 7 capture direct nonmedical costs (eg, transportation)., Conclusions: Linking Medicare FFS claims data to other federally funded data sources can facilitate research on some economic outcomes for PCOR. However, few sources capture direct nonmedical or indirect costs. Expanding linkages to include additional data sources, and reducing barriers to existing data sources, remain important objectives for increasing high-quality, patient-centered economic research., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Importance: Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income., Objective: To provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity., Evidence Review: The Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback., Findings: The panel developed a conceptual framework to apply guiding principles across an algorithm's life cycle, centering health and health care equity for patients and communities as the goal, within the wider context of structural racism and discrimination. Multiple stakeholders can mitigate and prevent bias at each phase of the algorithm life cycle, including problem formulation (phase 1); data selection, assessment, and management (phase 2); algorithm development, training, and validation (phase 3); deployment and integration of algorithms in intended settings (phase 4); and algorithm monitoring, maintenance, updating, or deimplementation (phase 5). Five principles should guide these efforts: (1) promote health and health care equity during all phases of the health care algorithm life cycle; (2) ensure health care algorithms and their use are transparent and explainable; (3) authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness; (4) explicitly identify health care algorithmic fairness issues and trade-offs; and (5) establish accountability for equity and fairness in outcomes from health care algorithms., Conclusions and Relevance: Multiple stakeholders must partner to create systems, processes, regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. Reforms should implement guiding principles that support promotion of health and health care equity in all phases of the algorithm life cycle as well as transparency and explainability, authentic community engagement and ethical partnerships, explicit identification of fairness issues and trade-offs, and accountability for equity and fairness.

Background: Patient-centered clinical decision support (PC CDS) aims to assist with tailoring decisions to an individual patient's needs. Patient-generated health data (PGHD), including physiologic measurements captured frequently by automated devices, provide important information for PC CDS. The volume and availability of such PGHD is increasing, but how PGHD should be presented to clinicians to best aid decision-making is unclear., Objectives: Identify best practices in visualizations of physiologic PGHD, for designing a software application as a PC CDS tool., Methods: We performed a scoping review of studies of PGHD dashboards that involved clinician users in design or evaluations. We included only studies that used physiologic PGHD from single patients for usage in decision-making., Results: We screened 468 titles and abstracts, 63 full-text papers, and identified 15 articles to include in our review. Some research primarily sought user input on PGHD presentation; other studies garnered feedback only as a side effort for other objectives (e.g., integration with electronic health records [EHRs]). Development efforts were often in the domains of chronic diseases and collected a mix of physiologic parameters (e.g., blood pressure and heart rate) and activity data. Users' preferences were for data to be presented with statistical summaries and clinical interpretations, alongside other non-PGHD data. Recurrent themes indicated that users desire longitudinal data display, aggregation of multiple data types on the same screen, actionability, and customization. Speed, simplicity, and availability of data for other purposes (e.g., documentation) were key to dashboard adoption. Evaluations were favorable for visualizations using common graphing or table formats, although best practices for implementation have not yet been established., Conclusion: Although the literature identified common themes on data display, measures, and usability, more research is needed as PGHD usage grows. Ensuring that care is tailored to individual needs will be important in future development of clinical decision support., Competing Interests: A.B. is a stockholder in Elimu Informatics., (Thieme. All rights reserved.)

The design, development, implementation, use, and evaluation of high-quality, patient-centered clinical decision support (PC CDS) is necessary if we are to achieve the quintuple aim in healthcare. We developed a PC CDS lifecycle framework to promote a common understanding and language for communication among researchers, patients, clinicians, and policymakers. The framework puts the patient, and/or their caregiver at the center and illustrates how they are involved in all the following stages: Computable Clinical Knowledge, Patient-specific Inference, Information Delivery, Clinical Decision, Patient Behaviors, Health Outcomes, Aggregate Data, and patient-centered outcomes research (PCOR) Evidence. Using this idealized framework reminds key stakeholders that developing, deploying, and evaluating PC-CDS is a complex, sociotechnical challenge that requires consideration of all 8 stages. In addition, we need to ensure that patients, their caregivers, and the clinicians caring for them are explicitly involved at each stage to help us achieve the quintuple aim., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Clinical decision support (CDS), which provides tools to assist clinical decision-making, can improve adherence to evidence-based practices, prevent medical errors, and support high-quality and patient-centered care delivery. Publicly available CDS that uses standards to express clinical logic (i.e., standards-based CDS) has the potential to reduce duplicative efforts of translating the same clinical evidence into CDS across multiple health care institutions. Yet development of such CDS is relatively new and its potential only partially explored., Objectives: This study aimed to describe lessons learned from a national initiative promoting publicly available, standards-based CDS resources, discuss challenges, and report suggestions for improvement., Methods: Findings were drawn from an evaluation of the Agency for Healthcare Research and Quality Patient-Centered Outcomes Research CDS Initiative, which aimed to advance evidence into practice through standards-based and publicly available CDS. Methods included literature and program material reviews, key informant interviews, and a web-based survey about a public repository of CDS artifacts and tools for authoring standards-based CDS., Results: The evaluation identified important lessons for developing and implementing standards-based CDS through publicly available repositories such as CDS Connect. Trust is a critical factor in uptake and can be bolstered through transparent information on underlying evidence, collaboration with experts, and feedback loops between users and developers to support continuous improvement. Additionally, while adoption of standards among electronic health record developers will make it easier to implement standards-based CDS, lower-resourced health systems will need extra support to ensure successful implementation and use. Finally, although we found the resources developed by the Initiative to offer valuable prototypes for the field, health systems desire more information about patient-centered, clinical, and cost-related outcomes to help them justify the investment required to implement standards-based, publicly available CDS., Conclusion: While the standards and technology to publicly share standards-based CDS have increased, broad dissemination and implementation remain challenging., Competing Interests: None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Patient use of mobile health applications is increasing. To promote patient-centered care, data from these apps must be integrated into clinician workflows within the electronic health record (EHR). Health Level 7 Fast Healthcare Interoperability Resources (FHIR) offers a standards-based application programming interface (API) that may support such integration., Objective: We aimed to use interoperability standards to integrate a patient mobile application (coronavirus 2019 [COVID-19] Tracker) with an EHR. The COVID-19 Tracker engages patients by sending introductory and reminder text messages, collecting vital signs and symptom data from COVID-19 patients, and providing actionable guidance if concerning issues are identified. This case report explored the use of FHIR APIs to integrate the app into EHR-enabled clinical workflows., Methods: The authors used notes from project meetings and from semistructured discussions among the application development team to track the design and implementation processes. Seven points of integration between the application and the EHR were identified, and approaches using FHIR to perform these integrations were delineated., Results: Although this clinical decision support integration project benefited from its standards-based approach, many challenges were encountered. These were due to (1) partial implementation of the FHIR standard in the EHR, particularly, components needed for patient engagement applications; (2) limited experience with the adoption of FHIR standards; and (3) gaps in the current FHIR standard. Alternative approaches, often not based on interoperability standards, were developed to overcome these limitations., Conclusion: Despite the challenges encountered due to the early stages of FHIR development and adoption, FHIR standards provide a promising mechanism for overcoming longstanding barriers and facilitating the integration of patient engagement apps with EHRs. To accelerate the integration of apps into clinical workflows, additional components of the FHIR standard must be implemented within the EHR and other clinical systems. Continued expansion of available FHIR resources will help with tighter workflow integration., Competing Interests: A.B. owns stock in Elimu Informatics. Other authors do not have any competing interests to declare aside from the stated affiliation of each author with his/her employer., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers' (HCP) workflow are not well understood., Methods: Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre- and post-CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes., Results: In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%-36%) and 23% (95% CI: 21%-25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%-28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient's most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration., Conclusions: CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making., Competing Interests: Potential conflicts of interest. D. J. D. reports a grant to his institution for a clinical trial of new susceptibility test systems from bioMérieux, outside of the conduct of the study; payment for consulting on novel diagnostics from OpGen; and payment for consulting on antimicrobial resistance surveillance studies from JMI Laboratories. A. P. G. reports grants or contracts from the Agency for Healthcare Research and Quality (AHRQ), the CDC, and the National Institutes of Health (NIH), outside of the conduct of the study; payment for lecture from the North Carolina Health Association; and Human Factors and Ergonomics Society Executive Council. J. J. reports royalties from UpToDate. D. J. M. reports grant funding to support infection prevention and medical decision making research from the CDC, NIH, AHRQ, and the Veterans Affairs Health Services Research and Development Service, and reimbursement for travel related to meeting planning on speaking at meetings from the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. All other authors report no potential conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Importance: The Agency for Healthcare Research and Quality (AHRQ) Safety Program for Improving Antibiotic Use aimed to improve antibiotic prescribing in ambulatory care practices by engaging clinicians and staff to incorporate antibiotic stewardship into practice culture, communication, and decision-making. Little is known about implementation of antibiotic stewardship in ambulatory care practices., Objective: To examine changes in visits and antibiotic prescribing during the AHRQ Safety Program., Design, Setting, and Participants: This cohort study evaluated a quality improvement intervention in ambulatory care throughout the US in 389 ambulatory care practices from December 1, 2019, to November 30, 2020., Exposures: The AHRQ Safety Program used webinars, audio presentations, educational tools, and office hours to engage stewardship leaders and clinical staff to address attitudes and cultures that challenge judicious antibiotic prescribing and incorporate best practices for the management of common infections., Main Outcomes and Measures: The primary outcome of the Safety Program was antibiotic prescriptions per 100 acute respiratory infection (ARI) visits. Data on total visits and ARI visits were also collected. The number of visits and prescribing rates from baseline (September 1, 2019) to completion of the program (November 30, 2020) were compared., Results: Of 467 practices enrolled, 389 (83%) completed the Safety Program; of these, 292 (75%) submitted complete data with 6 590 485 visits to 5483 clinicians. Participants included 82 (28%) primary care practices, 103 (35%) urgent care practices, 34 (12%) federally supported practices, 39 (13%) pediatric urgent care practices, 21 (7%) pediatric-only practices, and 14 (5%) other practice types. Visits per practice per month decreased from a mean of 1624 (95% CI, 1317-1931) at baseline to a nadir of 906 (95% CI, 702-1111) early in the COVID-19 pandemic (April 2020), and were 1797 (95% CI, 1510-2084) at the end of the program. Total antibiotic prescribing decreased from 18.2% of visits at baseline to 9.5% at completion of the program (-8.7%; 95% CI, -9.9% to -7.6%). Acute respiratory infection visits per practice per month decreased from baseline (n = 321) to a nadir of 76 early in the pandemic (May 2020) and gradually increased through completion of the program (n = 239). Antibiotic prescribing for ARIs decreased from 39.2% at baseline to 24.7% at completion of the program (-14.5%; 95% CI, -16.8% to -12.2%)., Conclusions and Relevance: In this study of US ambulatory practices that participated in the AHRQ Safety Program, significant reductions in the rates of overall and ARI-related antibiotic prescribing were noted, despite normalization of clinic visits by completion of the program. The forthcoming AHRQ Safety Program content may have utility in ambulatory practices across the US.

Objective: We conducted a horizon scan to (1) identify challenges in patient-centered clinical decision support (PC CDS) and (2) identify future directions for PC CDS., Materials and Methods: We engaged a technical expert panel, conducted a scoping literature review, and interviewed key informants. We qualitatively analyzed literature and interview transcripts, mapping findings to the 4 phases for translating evidence into PC CDS interventions (Prioritizing, Authoring, Implementing, and Measuring) and to external factors., Results: We identified 12 challenges for PC CDS development. Lack of patient input was identified as a critical challenge. The key informants noted that patient input is critical to prioritizing topics for PC CDS and to ensuring that CDS aligns with patients' routine behaviors. Lack of patient-centered terminology standards was viewed as a challenge in authoring PC CDS. We found a dearth of CDS studies that measured clinical outcomes, creating significant gaps in our understanding of PC CDS' impact. Across all phases of CDS development, there is a lack of patient and provider trust and limited attention to patients' and providers' concerns., Discussion: These challenges suggest opportunities for advancing PC CDS. There are opportunities to develop industry-wide practices and standards to increase transparency, standardize terminologies, and incorporate patient input. There is also opportunity to engage patients throughout the PC CDS research process to ensure that outcome measures are relevant to their needs., Conclusion: Addressing these challenges and embracing these opportunities will help realize the promise of PC CDS-placing patients at the center of the healthcare system., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Patient Centered Outcomes Research (PCOR) and health care delivery system transformation require investments in development of tools and techniques for rapid dissemination of clinical and operational best practices. This paper explores the current technology landscape for patient-centered clinical decision support (PC CDS) and what is needed to make it more shareable, standards-based, and publicly available with the goal of improving patient care and clinical outcomes. The landscape assessment used three sources of information: (1) a 22-member technical expert panel; (2) a literature review of peer-reviewed and grey literature; and (3) key informant interviews with PC CDS stakeholders. We identified ten salient technical considerations that span all phases of PC CDS development; our findings suggest there has been significant progress in the development and implementation of PC CDS but challenges remain.

Supporting healthcare decision-making that is patient-centered and evidence-based requires investments in the development of tools and techniques for dissemination of patient-centered outcomes research findings via methods such as clinical decision support (CDS). This article explores the technical landscape for patient-centered CDS (PC CDS) and the gaps in making PC CDS more shareable, standards-based, and publicly available, with the goal of improving patient care and clinical outcomes. This landscape assessment used: (1) a technical expert panel; (2) a literature review; and (3) interviews with 18 CDS stakeholders. We identified 7 salient technical considerations that span 5 phases of PC CDS development. While progress has been made in the technical landscape, the field must advance standards for translating clinical guidelines into PC CDS, the standardization of CDS insertion points into the clinical workflow, and processes to capture, standardize, and integrate patient-generated health data., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

To evaluate changes in Clostridioides difficile incidence rates for Maryland hospitals that participated in the Statewide Prevention and Reduction of C. difficile (SPARC) collaborative. Pre-post, difference-in-difference analysis of non-randomised intervention using four quarters of preintervention and six quarters of postintervention National Healthcare Safety Network data for SPARC hospitals (April 2017 to March 2020) and 10 quarters for control hospitals (October 2017 to March 2020). Mixed-effects negative binomial models were used to assess changes over time. Process evaluation using hospital intervention implementation plans, assessments and interviews with staff at eight SPARC hospitals. Maryland, USA. All Maryland acute care hospitals; 12 intervention and 36 control hospitals. Participation in SPARC, a public health-academic collaborative made available to Maryland hospitals, with staggered enrolment between June 2018 and August 2019. Hospitals with higher C. difficile rates were recruited via email and phone. SPARC included assessments, feedback reports and ongoing technical assistance. Primary outcomes were C. difficile incidence rate measured as the quarterly number of C. difficile infections per 10 000 patient-days (outcome measure) and SPARC intervention hospitals' experiences participating in the collaborative (process measures). SPARC invited 13 hospitals to participate in the intervention, with 92% (n=12) participating. The 36 hospitals that did not participate served as control hospitals. SPARC hospitals were associated with 45% greater C. difficile reduction as compared with control hospitals (incidence rate ratio=0.55, 95% CI 0.35 to 0.88, p=0.012). Key SPARC activities, including access to trusted external experts, technical assistance, multidisciplinary collaboration, an accountability structure, peer-to-peer learning opportunities and educational resources, were associated with hospitals reporting positive experiences with SPARC. SPARC intervention hospitals experienced 45% greater reduction in C. difficile rates than control hospitals. A public health-academic collaborative might help reduce C. difficile and other hospital-acquired infections in individual hospitals and at state or regional levels., Competing Interests: Competing interests: SC reports consulting fees from Basilea and Theravance for work on external infection adjudication committees. KC reports investigator-initiated study funds from Merck & Co and served as a speaker for GenMark Diagnostics. LLM reports research funds from Clorox., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: Antibiotic overuse in long-term care (LTC) is common, prompting calls for antibiotic stewardship programs (ASPs) designed for specific use in these settings. The optimal approach to establish robust, sustainable ASPs in LTC facilities is unknown., Objectives: To determine if the Agency for Healthcare Research and Quality (AHRQ) Safety Program for Improving Antibiotic Use, an educational initiative to establish ASPs focusing on patient safety, is associated with reductions in antibiotic use in LTC settings., Design, Setting, and Participants: This quality improvement study including 439 LTC facilities in the US assessed antibiotic therapy data following a pragmatic quality-improvement program, which was implemented to assist facilities in establishing ASPs and with antibiotic decision-making. Training was conducted between December 2018 and November 2019. Data were analyzed from January 2019 to December 2019., Interventions: Fifteen webinars occurred over 12 months (December 2018 to November 2019), accompanied by additional tools, activities, posters, and pocket cards. All clinical staff were encouraged to participate., Main Outcomes and Measures: The primary outcome was antibiotic starts per 1000 resident-days. Secondary outcomes included days of antibiotic therapy (DOT) per 1000 resident-days, the number of urine cultures per 1000 resident-days, and Clostridioides difficile laboratory-identified events per 10 000 resident-days. All outcomes compared data from the baseline (January-February 2019) to the completion of the program (November-December 2019). Generalized linear mixed models with random intercepts at the site level assessed changes over time., Results: Of a total 523 eligible LTC facilities, 439 (83.9%) completed the safety program. The mean difference for antibiotic starts from baseline to study completion per 1000 resident-days was -0.41 (95% CI, -0.76 to -0.07; P = .02), with fluoroquinolones showing the greatest decrease at -0.21 starts per 1000 resident-days (95% CI, -0.35 to -0.08; P = .002). The mean difference for antibiotic DOT per 1000 resident-days was not significant (-3.05; 95% CI, -6.34 to 0.23; P = .07). Reductions in antibiotic starts and use were greater in facilities with greater program engagement (as measured by webinar attendance). While antibiotic starts and DOT in these facilities decreased by 1.12 per 1000 resident-days (95% CI, -1.75 to -0.49; P < .001) and 9.97 per 1000 resident-days (95% CI, -15.4 to -4.6; P < .001), respectively, no significant reductions occurred in low engagement facilities. Urine cultures per 1000 resident-days decreased by 0.38 (95% CI, -0.61 to -0.15; P = .001). There was no significant change in facility-onset C difficile laboratory-identified events., Conclusions and Relevance: Participation in the AHRQ safety program was associated with the development of ASPs that actively engaged clinical staff in the decision-making processes around antibiotic prescriptions in participating LTC facilities. The reduction in antibiotic DOT and starts, which was more pronounced in more engaged facilities, indicates that implementation of this multifaceted program may support successful ASPs in LTC settings.

The scale and severity of the opioid epidemic call for innovative, multipronged solutions. Research and development is key to accelerate the discovery and evaluation of interventions that support pain and substance use disorder management. In parallel, the use and integration of blockchain technology within research networks holds the potential to address some of the unique challenges facing opioid research. This paper discusses the applications of blockchain technology and illustrates potential ways in which it could be applied to strengthen the validity of outcomes research on the opioid epidemic. We reviewed published and gray literature to identify useful applications of blockchain, specifically those that address the challenges faced by opioid research networks and programs. We then convened a panel of experts to discuss the strengths, limitations, and feasibility of each application. Blockchain has the potential to address some of the issues surrounding health data management, including data availability, data sharing and interoperability, and privacy and security. We identified five primary applications of blockchain to opioids: clinical trials and pharmaceutical research, incentivizing data donation and behavior change, secure exchange and management of e-prescriptions, supply chain management, and secondary use of clinical data for research and public health surveillance. The published literature was limited, leading us to rely on gray literature, which was also limited in its discussion of the technical aspects of implementation. The technical expert panel provided additional context and an assessment of feasibility that was lacking in the literature. Research on opioid use and misuse is challenging because of disparate data stored across different systems, data and system interoperability issues, and legal requirements. These areas must be navigated to make data accessible, timely, and useful to researchers. Blockchain technologies have the potential to act as a facilitator in this process, offering a more efficient, secure, and privacy-preserving solution for data exchange. Among the 5 primary applications, we found that clinical trial research, supply chain management, and secondary use of data had the most examples in practice and the potential effectiveness of blockchain. More discussions and studies should focus on addressing technical questions concerning scalability and tackling practical concerns such as cost, standards, and governance around the implementation of blockchain in health care. Policy concerns related to balancing the need for data accessibility that also protects patient privacy and autonomy in revoking consent should also be examined., (©Aldren Gonzales, Scott R Smith, Prashila Dullabh, Lauren Hovey, Krysta Heaney-Huls, Meagan Robichaud, Roger Boodoo. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 27.08.2021.)

Background: Perceived patient demand for antibiotics drives unnecessary antibiotic prescribing in outpatient settings, but little is known about how clinicians experience this demand or how this perceived demand shapes their decision-making., Objective: To identify how clinicians perceive patient demand for antibiotics and the way these perceptions stimulate unnecessary prescribing., Methods: Qualitative study using semi-structured interviews with clinicians in outpatient settings who prescribe antibiotics. Interviews were analyzed using conventional and directed content analysis., Results: Interviews were conducted with 25 clinicians from nine practices across three states. Patient demand was the most common reason respondents provided for why they prescribed non-indicated antibiotics. Three related factors motivated clinically unnecessary antibiotic use in the face of perceived patient demand: (i) clinicians want their patients to regard clinical visits as valuable and believe that an antibiotic prescription demonstrates value; (ii) clinicians want to avoid negative repercussions of denying antibiotics, including reduced income, damage to their reputation, emotional exhaustion, and degraded relationships with patients; (iii) clinicians believed that certain patients are impossible to satisfy without an antibiotic prescription and felt that efforts to refuse antibiotics to such patients wastes time and invites the aforementioned negative repercussions. Clinicians in urgent care settings were especially likely to describe being motivated by these factors., Conclusion: Interventions to improve antibiotic use in the outpatient setting must address clinicians' concerns about providing value for their patients, fear of negative repercussions from denying antibiotics, and the approach to inconvincible patients., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Interest in application programming interfaces (APIs) is increasing as key stakeholders look for technical solutions to interoperability challenges. We explored three thematic areas to assess the current state of API use for data access and exchange in health care: (1) API use cases and standards; (2) challenges and facilitators for read and write capabilities; and (3) outlook for development of write capabilities., Methods: We employed four methods: (1) literature review; (2) expert interviews with 13 API stakeholders; (3) review of electronic health record (EHR) app galleries; and (4) a technical expert panel. We used an eight-dimension sociotechnical model to organize our findings., Results: The API ecosystem is complicated and cuts across five of the eight sociotechnical model dimensions: (1) app marketplaces support a range of use cases, the majority of which target providers' needs, with far fewer supporting patient access to data; (2) current focus on read APIs with limited use of write APIs; (3) where standards are used, they are largely Fast Healthcare Interoperability Resources (FHIR); (4) FHIR-based APIs support exchange of electronic health information within the common clinical data set; and (5) validating external data and data sources for clinical decision making creates challenges to provider workflows., Conclusion: While the use of APIs in health care is increasing rapidly, it is still in the pilot stages. We identified five key issues with implications for the continued advancement of API use: (1) a robust normative FHIR standard; (2) expansion of the common clinical data set to other data elements; (3) enhanced support for write implementation; (4) data provenance rules; and (5) data governance rules. Thus, while APIs are being touted as a solution to interoperability challenges, they remain an emerging technology that is only one piece of a multipronged approach to data access and use., Competing Interests: A.W. reports grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. D.F.S. reports grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. P.D. and N.R. report grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. K.H-H. reports grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. L.H. reports grants from the Office of the National Coordinator of Health Information Technology during the conduct of the study., (Georg Thieme Verlag KG Stuttgart · New York.)

Interest in application programming interfaces (APIs) as a means to increase health data access and exchange among patients, health care providers, and payers has become an important area for development. In an effort to better understand the various contexts in which APIs can be applied, we explored different use cases. While APIs and our collective understanding of the best ways to implement and use them continue to develop, in the coming years the use of proprietary and standards-based APIs could be key to the sustainability of applied clinical informatics research, as well as associated improvements in patient engagement, clinical decision making, efficiency, quality and safety of the healthcare delivery system.

Background: Social determinants of health (SDH) are increasingly seen as important to understanding patient health and identifying appropriate interventions to improve health outcomes in what is a complex interplay between health system-, community-, and individual-level factors., Objective: The objective of the paper was to investigate the development of electronic health record (EHR) software products that allow health care providers to identify and address patients' SDH in health care settings., Methods: We conducted interviews with six EHR vendors with large market shares in both ambulatory and inpatient settings. We conducted thematic analysis of the interviews to (1) identify their motivations to develop such software products, (2) describe their products and uses, and (3) identify facilitators and challenges to collection and use of SDH data-through their products or otherwise-either at the point of care or in population health interventions., Results: Our findings indicate that vendor systems and their functionalities are influenced by client demand and initiative, federal initiatives, and the vendors' strategic vision about opportunities in the health care system. Among the small sample of vendors with large market shares, SDH is a new area for growth, and the vendors range in the number and sophistication of their SDH-related products. To enable better data analytics, population health management, and interoperability of SDH data, vendors recognized the need for more standardization of SDH performance measures across various federal and state programs, better mapping of SDH measures to multiple types of codes, and development of more codes for all SDH measures of interest., Conclusions: Vendors indicate they are actively developing products to facilitate the collection and use of SDH data for their clients and are seeking solutions to data standardization and interoperability challenges through internal product decisions and collaboration with policymakers. Due to a lack of policy standards around SDH data, product-specific decisions may end up being de facto policies given the market shares of particular vendors. However, commercial vendors appear ready to collaboratively discuss policy solutions such as standards or guidelines with each other, health care systems, and government agencies in order to further promote integration of SDH data into the standard of care for all health systems., (©Maysoun Freij, Prashila Dullabh, Sarah Lewis, Scott R Smith, Lauren Hovey, Rina Dhopeshwarkar. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 07.06.2019.)

Objective: To characterize nationwide variation and factors associated with clinical laboratories': (1) capabilities to send structured test results electronically to ordering practitioners' EHR systems; and (2) their levels of exchange activity, as measured by whether they sent more than three-quarters of their test results as structured data to ordering practitioners' EHR systems., Materials and Methods: A national survey of all independent and hospital laboratories was conducted in 2013. Using an analytic weighted sample of 9382 clinical laboratories, a series of logistic regression analyses were conducted to identify organizational and area characteristics associated with clinical laboratories' exchange capability and activity., Results: Hospital-based clinical laboratories (71%) and larger clinical laboratories (80%) had significantly higher levels of capability compared to independent (58%) and smaller laboratories (48%), respectively; though all had similar levels of exchange activity, with 30% of clinical laboratories sending 75% or more of their test results electronically. In multivariate analyses, hospital and the largest laboratories had 1.87 and 4.40 higher odds, respectively, of possessing the capability to send results electronically compared to independent laboratories (p<0.001). Laboratories located in areas with a higher share of potential exchange partners had a small but significantly greater capability to send results electronically and higher levels of exchange activity(p<0.05)., Conclusion: Clinical laboratories' capability to exchange varied by size and type; however, all clinical laboratories had relatively low levels of exchange activity. The role of exchange partners potentially played a small but significant role in driving exchange capability and activity., (Published by Elsevier B.V.)

There is widespread consensus that Health Information Exchange, the electronic sharing of patients' health information between delivery settings, is critical to improving the quality and efficiency of patient care. The United States has had limited success in establishing broad-based HIE. To address these issues, the federal government funded the State Health Information Exchange Cooperative Agreement Program. An in-depth qualitative study was conducted, consisting of site visits and semi-structured discussions with 105 respondents in 5 states to understand early HIE implementation experiences. Results show the last two years have seen unprecedented growth in HIE infrastructure. Key factors such as maturity of HIE at baseline and healthcare market characteristics have shaped governance models and technical infrastructures. Early focus on stakeholder value proposition and sustainability planning is critical for long-term success. States continue to face numerous challenges in converting stakeholder support into financial commitment and real-time exchange of health information. We discuss the key issues states faced in attempting to realize broad-based HIE and offer insights that may assist other states.

In 2007 the Assistant Secretary for Planning and Evaluation (ASPE) contracted with the National Opinion Research Center (NORC) to conduct an evaluation of a Personal Health Record (PHR) pilot offered to CMS Fee-for-Service (FFS) beneficiaries. The intent of the evaluation is to: 1) determine the usability/utility components of PHRs; 2) identify standard features and best practices in the development and deployment; and 3) analyze the key consumer issues and perceptions related to PHR use.

In 2006 CMS and AHRQ funded the National Resource Center for Health IT (NRC) to evaluate the findings from the 5 CMS ePrescribing (eRx) pilots. During this evaluation, the NRC identified research areas from: 1) questions left unanswered by the pilot contractors, 2) gaps in knowledge identified by the evaluation team and, 3) areas requiring additional industry experience. The research areas encompass standards, implementation considerations and outcomes such as ADEs, pharmacy workflow and physician adoption.