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Introduction: Cardio-oncology focuses on diagnosing and preventing adverse cardiovascular outcomes in cancer patients. Interdisciplinary cardio-oncology services address the spectrum of prevention, detection, monitoring, and treatment of cancer patients at risk of cardio-toxicity and aim to improve the continuum of cardiac care for oncology patients. The goal of this study was to engage clinician and administrative stakeholders to assess multilevel needs, barriers, and expectations regarding cardio oncology services. Methods: We interviewed clinicians and administrators at an academic medical center using the Consolidated Framework for Implementation Research (CFIR) to understand multilevel determinants influencing cardio-oncology service implementation. We also conducted a web-based survey to assess the knowledge, attitude, and perceptions of cardio-oncology services held by local and regional clinicians who may refer cardio-oncology patients to the study site. Results: Multiple facilitators to cardio-oncology service implementation emerged. Interview participants believed cardio-oncology services could benefit patients and the organization by providing a competitive advantage. A majority (74%) of clinicians surveyed thought a cardio-oncology service would significantly improve cancer patients' prognoses. Implementation barriers discussed included costs and a siloed organizational structure that complicated cross-service collaboration. In the clinician survey, differences in the views toward cardio-oncology services held by cardiology versus oncology providers would need to be negotiated in future cardio-oncology service development. For example, while most providers accepted similar risk of cardio-toxicity when consenting patients for cancer therapy in a curative setting, cardiologists accepted significantly higher levels of risk than oncologists in an incurable setting: 75% of oncologists accepted 1-5% risk; 77% of cardiologists accepted =5% risk). Conclusions: Participants supported implementation and development of cardiooncology services. Respondents also noted multi-level barriers that could be addressed to maximize the potential for success. Engaging administrators and clinicians from cardiology and oncology disciplines in the future development of such services can help ensure maximal relevance and uptake. [ABSTRACT FROM AUTHOR]

Introduction: Texas Health Resources (THR), a large, nonprofit health care system based in the Dallas‐Fort Worth area, has collaborated with the University of Texas Southwestern Medical Center (UTSW) to develop and operate a unique, integrated approach for Learning Health System (LHS) workforce development. This training model centers on academic health system faculty members conducting later‐stage translational research within a partnering regional care delivery organization. Methods: The THR Clinical Scholars Program engages early career UTSW faculty members to conduct studies that are likely to have an impact on care delivery at the health system level. Interested candidates submit formal applications to the program. A joint committee comprised of senior research faculty from UTSW and THR clinical leadership reviews proposals with a focus on the shared LHS needs of both institutions—developing high quality research output that can be applied to enhance care delivery. A key prioritization criterion for funding is the degree to which the research addresses a question relevant to THR as a high‐volume network with multiple channels for consumers to access care. The program emphasis is on supporting embedded research initiatives using health system data to generate knowledge that will improve the quality and efficiency of care for the patient populations served by the participant organizations. Results: We discuss specific strategic and tactical components of the THR Clinical Scholars Program including an overview of the academic affiliation agreement between the collaborating organizations, criteria for successful program applications, data sharing, and funding. We also share project summaries from selected clinical scholars as examples of the LHS research done in the program to date. Conclusion: This experience report provides an implementation framework for other academic health systems interested in adopting similar LHS workforce training models with community partners. [ABSTRACT FROM AUTHOR]

Introduction: The exponential growth in health information technology (HIT) presents an immense opportunity for facilitating the data‐to‐knowledge‐to‐performance loop which supports learning health systems. This scoping review addresses the gap in knowledge around HIT implementation contextual factors such as organizational culture and provides a current state assessment. Methods: A search of 13 databases guided by Arskey and O'Malley's framework identified content on HIT implementations and organizational culture. The Consolidated Framework for Implementation Research (CFIR) was used to assess culture and to develop review criteria. Culture stress, culture effort, implementation climate, learning climate, readiness for implementation, leadership engagement, and available resources were the constructs examined. Rayyan and Qualtrics were used for screening and data extraction. Results: Fifty two studies included were mainly conducted in Academic Health Centers (n = 18, 35%) and at urban locations (n = 50, 96%). Interviews frequently used for data collection (n = 26, 50%) and guided by multiple frameworks (n = 34). Studies mostly focused on EHR implementations (n = 23, 44%) followed by clinical decision support (n = 9, 17%). About two‐thirds (n = 34, 65%) reflected culture stress theme and 62% (21 of 34) acknowledged it as a barrier. Culture effort identified in 27 studies and was a facilitator in most (78%, 21 of 27). Leadership engagement theme in majority studies (71%, n = 37), with 35% (n = 13) noting it as a facilitator. Eighty percent (42 studies) noted available resources, 12 of which identified this as barrier to successful implementation. Conclusions: It is vital to determine the culture and other CFIR inner setting constructs that are significant to HIT implementation as facilitators or barriers. This scoping review presents a limited number of empirical studies in this topic highlighting the need for additional research to quantify the effects of culture. This will help build evidence and best practices that facilitate HIT implementations and hence serve as a platform to support robust learning health systems. [ABSTRACT FROM AUTHOR]

Introduction: Digital exposure notification (EN) approaches may offer considerable advantages over traditional contact tracing in speed, scale, efficacy, and confidentiality in pandemic control. We applied the science of learning health systems to test the effect of framing and digital means, email vs Short Message Service (SMS), on EN adoption among patients of an academic health center. Methods: We tested three communication approaches of the Apple and Google EN system in a rapid learning cycle involving 15 000 patients pseudorandomly assigned to three groups. The patients in the first group received a 284‐word email that presented EN as a tool that can help slow the spread. The patients in the second group received a 32‐word SMS that described EN as a new tool to help slow the spread (SlowTheSpreadSMS). Patients in the third group received a 47‐word SMS that depicted the system as a new digital tool that can empower them to protect their family and friends (EmpowerSMS). A brief four‐question anonymous survey of adoption was included in a reminder message sent 2 days after the initial outreach. Results: One hundred and sixty people responded to the survey within 1 week: 2.33% from EmpowerSMS, 0.97% from SlowTheSpreadSMS, and 0.53% from emails; 29 (41.43%), 24 (41.38%), and 11 (34.38%) reported having adopted EN from each group, respectively. Patient reported barriers to adoption included iOS version incompatibility, privacy concerns, and low trust of government agencies or companies like Apple and Google. Patients recommended that healthcare systems play an active role in disseminating information about this tool. Patients also recommended advertising on social media and providing reassurance about privacy. Conclusions: The EmpowerSMS resulted in relatively more survey responses. Both SMS groups had slightly higher, but not statistically significant EN adoption rates compared to email. Findings from the pilot not only informed operational decision‐making in our health system but also contributed to EN rollout planning in our State. [ABSTRACT FROM AUTHOR]

Introduction: Academic health centers are poised to improve health through their clinical, education, and research missions. However, these missions often operate in silos. The authors explored stakeholder perspectives at diverse institutions to understand challenges and identify alignment strategies. Methods: Authors used an exploratory qualitative design and thematic analysis approach with data obtained from electronic surveys sent to participants at five U.S. academic health centers (2017‐18), with four different types of medical school/health system partnerships. Participants included educators, researchers, system leaders, administrators, clinical providers, resident/fellow physicians, and students. Investigators coded data using constant comparative analysis, met regularly to reconcile uncertainties, and collapsed/combined categories. Results: Of 175 participants invited, 113 completed the survey (65%). Three results categories were identified. First, five higher‐order themes emerged related to aligning missions, including (a) shared vision and strategies, (b) alignment of strategy with community needs, (c) tension of economic drivers, (d) coproduction of knowledge, and (e) unifying set of concepts spanning all missions. Second, strategies for each mission were identified, including education (new competencies, instructional methods, recruitment), research (shifting agenda, developing partnerships, operations), and clinical operations (delivery models, focus on patient factors/needs, value‐based care, well‐being). Lastly, strategies for integrating each dyadic mission pair, including research‐education, clinical operations education, and research‐clinical operations, were identified. Conclusions: Academic health centers are at a crossroads in regard to identity and alignment across the tripartite missions. The study's results provide pragmatic strategies to advance the tripartite missions and lead necessary change for improved patient health. [ABSTRACT FROM AUTHOR]

Introduction: A learning health system (LHS) must improve care in ways that are meaningful to patients, integrating patient‐centered outcomes (PCOs) into core infrastructure. PCOs are common following cancer treatment, such as urinary incontinence (UI) following prostatectomy. However, PCOs are not systematically recorded because they can only be described by the patient, are subjective and captured as unstructured text in the electronic health record (EHR). Therefore, PCOs pose significant challenges for phenotyping patients. Here, we present a natural language processing (NLP) approach for phenotyping patients with UI to classify their disease into severity subtypes, which can increase opportunities to provide precision‐based therapy and promote a value‐based delivery system. Methods: Patients undergoing prostate cancer treatment from 2008 to 2018 were identified at an academic medical center. Using a hybrid NLP pipeline that combines rule‐based and deep learning methodologies, we classified positive UI cases as mild, moderate, and severe by mining clinical notes. Results: The rule‐based model accurately classified UI into disease severity categories (accuracy: 0.86), which outperformed the deep learning model (accuracy: 0.73). In the deep learning model, the recall rates for mild and moderate group were higher than the precision rate (0.78 and 0.79, respectively). A hybrid model that combined both methods did not improve the accuracy of the rule‐based model but did outperform the deep learning model (accuracy: 0.75). Conclusion: Phenotyping patients based on indication and severity of PCOs is essential to advance a patient centered LHS. EHRs contain valuable information on PCOs and by using NLP methods, it is feasible to accurately and efficiently phenotype PCO severity. Phenotyping must extend beyond the identification of disease to provide classification of disease severity that can be used to guide treatment and inform shared decision‐making. Our methods demonstrate a path to a patient centered LHS that could advance precision medicine. [ABSTRACT FROM AUTHOR]

Introduction Academic health centers are reorganizing in response to dramatic changes in the health-care environment. To improve value, they and other health systems must become a learning health system, specifically one that has the capacity to understand performance across the continuum of care and use that information to achieve continuous improvements in efficiency and effectiveness. While learning health system concepts have been well described, the practical steps to create such a system are not well defined. Establishing the necessary infrastructure is particularly challenging at academic health centers due to their tripartite missions and complex organizational structures. Methods Using an evidence-based framework, this article describes a series of organizational-level interventions implemented at an academic health center to create the structures and processes to support the functions of a learning health system. Results Following implementation of changes from 2008 to 2013, system-level performance improved in multiple domains: patient satisfaction, population health screenings, improvement education, and patient engagement. Conclusions This experience can be applied to health systems that wrestle with making system-level change when existing cultures, structures, and processes vary. Using an evidence -based framework is useful when developing the structures and processes that support the functions of a learning health system. [ABSTRACT FROM AUTHOR]