Lessons Learned from a National Hospital Antibiotic Stewardship Implementation Project.

BACKGROUND: The goal of antibiotic stewardship programs (ASPs) is to ensure that patients receive effective therapy while minimizing adverse events. To overcome barriers commonly faced in implementing successful ASPs, the Agency for Healthcare Research and Quality (AHRQ) established a multifaceted, nationwide Safety Program for Improving Antibiotic Use in 2018. This report summarizes the lessons learned from the implementation of this initiative based on structured interviews of personnel from participating sites. METHODS: At the completion of the one-year initiative, semistructured exit interviews were conducted with site leaders at 151 of the 402 hospitals that participated. These interviews consisted of open-ended questions about the perceived effectiveness of components of the Safety Program. Qualitative analyses incorporated both deductive coding themes (based on existing literature) and an iteratively developed inductive coding framework (based on salient themes that emerged from a subset of interviews). RESULTS: Several components of the Safety Program were identified as effective in expanding local stewardship activities, including techniques and strategies to implement sustainable ASPs, access to Implementation Advisors to keep sites engaged, provision of local benchmarked antibiotic use data to compare to similar hospitals, and Safety Program materials such as the antibiotic time-out tool to integrate stewardship techniques into daily work flows. The biggest challenges to greater effectiveness were suboptimal frontline staff engagement and difficulty changing antibiotic prescribing culture. Some approaches used to overcome these barriers (peer-to-peer communication and education through team huddles, identifying physician champions, informal rounds to enhance collegiality and buy-in, and engagement of hospital leadership) were identified. CONCLUSION: Lessons learned from the Safety Program can be applied by other teams looking to promote an effective ASP at their hospital or system. The themes that emerged in this study likely also have relevance across a wide range of large-scale quality improvement initiatives.

Patient-Centered Clinical Decision Support-Where Are We and Where to Next?

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.

Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care.

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.

Medicare Data Linkages for Conducting Patient-Centered Outcomes Research on Economic Outcomes.

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.

Implementation and evaluation of an electronic health record-integrated app for postpartum monitoring of hypertensive disorders of pregnancy using patient-contributed data collection.

Remote monitoring of women experiencing hypertensive disorders of pregnancy (HDP) can provide timely life-saving data, particularly if these data are integrated into existing patient and clinical workflows. This pilot intervention of a smartphone application (app) for postpartum monitoring of hypertensive disorders integrates patient-contributed data into electronic health records (EHRs) to support monitoring and clinical decision-making. Results from the evaluation of the pilot highlight the resources needed when implementing the app, challenges for integrating an app into the EHR, and the usability and utility of the HDP monitoring app for patient and clinician users. The implementation team's key observations included the importance of a local clinical champion, more robust patient involvement and support for the remote patient monitoring program, an impetus for EHR developers to adopt data integration standards, and a need to expand the capabilities of the standards to support interventions using patient-contributed data.

Visualization of Patient-Generated Health Data: A Scoping Review of Dashboard Designs.

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.

Lessons Learned from a National Initiative Promoting Publicly Available Standards-Based Clinical Decision Support.

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.

A lifecycle framework illustrates eight stages necessary for realizing the benefits of patient-centered clinical decision support.

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.

Federal Data for Conducting Patient-centered Outcomes Research on Economic Outcomes.

BACKGROUND: Patients are increasingly interested in data on the economic burdens and impacts of health care choices; caregivers, employers, and payers are also interested in these costs. Although there have been various federal investments into patient-centered outcomes research (PCOR), an assessment of the coverage and gaps in federally funded data for PCOR economic evaluations has not been produced to date. OBJECTIVES: To classify relevant categories of PCOR economic costs, to assess current federally funded data for coverage of these categories, and to identify gaps for future research and collection. RESEARCH DESIGN: A targeted internet search was conducted to identify a list of relevant outcomes and data sources. The study team assessed data sources for coverage of economic outcomes. A technical panel and key informant interviews were used for evaluation and feedback. RESULTS: Four types of formal health care sector costs, 3 types of informal health care sector costs, and 10 types of non-health care sector costs were identified as relevant for PCOR economic evaluations. Twenty-nine federally funded data sources were identified. Most contained elements on formal costs. Data on informal costs (eg, transportation) were less common, and non-health care sector costs (eg, productivity) were the least common. Most data sources were annual, cross-sectional, nationally representative individual-level surveys. CONCLUSIONS: The existing federal data infrastructure captures many areas of the economic burden of health and health care, but gaps remain. Research from multiple data sources and potential future integrations may offset gaps in individual data sources. Linkages are promising strategies for future research on patient-centered economic outcomes.

Integrating a Patient Engagement App into an Electronic Health Record-Enabled Workflow Using Interoperability Standards.

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.

Assessment of Changes in Visits and Antibiotic Prescribing During the Agency for Healthcare Research and Quality Safety Program for Improving Antibiotic Use and the COVID-19 Pandemic.

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.

The Technology Landscape of Patient-Centered Clinical Decision Support - Where Are We and What Is Needed?

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.

Challenges and opportunities for advancing patient-centered clinical decision support: findings from a horizon scan.

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 technical landscape for patient-centered CDS: progress, gaps, and challenges.

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.

Implementation of an Antibiotic Stewardship Program in Long-term Care Facilities Across the US.

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.

Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals.

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.

Impact of Statewide Prevention and Reduction of Clostridioides difficile (SPARC), a Maryland public health-academic collaborative: an evaluation of a quality improvement intervention.

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.

Potential Uses of Blockchain Technology for Outcomes Research on Opioids.

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.

Association of a Safety Program for Improving Antibiotic Use With Antibiotic Use and Hospital-Onset Clostridioides difficile Infection Rates Among US Hospitals.

Importance: Regulatory agencies and professional organizations recommend antibiotic stewardship programs (ASPs) in US hospitals. The optimal approach to establish robust, sustainable ASPs across diverse hospitals is unknown. Objective: To assess whether the Agency for Healthcare Research and Quality Safety Program for Improving Antibiotic Use is associated with reductions in antibiotic use across US hospitals. Design, Setting, and Participants: A pragmatic quality improvement program was conducted and evaluated over a 1-year period in US hospitals. A total of 437 hospitals were enrolled. The study was conducted from December 1, 2017, to November 30, 2018. Data analysis was performed from March 1 to October 31, 2019. Interventions: The Safety Program assisted hospitals with establishing ASPs and worked with frontline clinicians to improve their antibiotic decision-making. All clinical staff (eg, clinicians, pharmacists, and nurses) were encouraged to participate. Seventeen webinars occurred over 12 months, accompanied by additional durable educational content. Topics focused on establishing ASPs, the science of safety, improving teamwork and communication, and best practices for the diagnosis and management of infectious processes. Main Outcomes and Measures: The primary outcome was overall antibiotic use (days of antibiotic therapy [DOT] per 1000 patient days [PD]) comparing the beginning (January-February 2018) and end (November-December 2018) of the Safety Program. Data analysis occurred using linear mixed models with random hospital unit effects. Antibiotic use from 614 hospitals in the Premier Healthcare Database from the same period was analyzed to evaluate contemporary US antibiotic trends. Quarterly hospital-onset Clostridioides difficile laboratory-identified events per 10 000 PD were a secondary outcome. Results: Of the 437 hospitals enrolled, 402 (92%) remained in the program until its completion, including 28 (7%) academic medical centers, 122 (30%) midlevel teaching hospitals, 167 (42%) community hospitals, and 85 (21%) critical access hospitals. Adherence to key components of ASPs (ie, interventions before and after prescription of antibiotics, availability of local antibiotic guidelines, ASP leads with dedicated salary support, and quarterly reporting of antibiotic use) improved from 8% to 74% over the 1-year period (P < .01). Antibiotic use decreased by 30.3 DOT per 1000 PD (95% CI, -52.6 to -8.0 DOT; P = .008). Similar changes in antibiotic use were not observed in the Premier Healthcare Database. The incidence rate of hospital-onset C difficile laboratory-identified events decreased by 19.5% (95% CI, -33.5% to -2.4%; P = .03). Conclusions and Relevance: The Agency for Healthcare Research and Quality Safety Program appeared to enable diverse hospitals to establish ASPs and teach frontline clinicians to self-steward their antibiotic use. Safety Program content is publicly available.

Engaging patients and stakeholders in preresearch: findings from the Pipeline to Proposal Awards Initiative.

Aim: The Patient-Centered Outcomes Research Institute Pipeline to Proposal (P2P) Awards Initiative funded 177 awardees to engage patients and stakeholder partners in preresearch. Based on P2P, we described engagement strategies; outcomes; facilitators; and challenges to inform research funders and stakeholders participating in preresearch. Materials & methods: We used a qualitative approach based on content analysis of program data and interviews with P2P awardees and partners. Results: Awardees developed partnership infrastructure by recruiting patients and stakeholders, establishing clear roles, and providing training. Building trust was key to engaging patients and stakeholders in preresearch. Awardees reported partners were more likely to engage in PCOR in the future. Conclusion: P2P awardees increased capacity of patient and stakeholder partnerships to conduct PCOR.