Learning Healthcare System Research Articles

Integrating N-of-1 Trials Into Learning Health Care Systems.

This Viewpoint explores how current ethical challenges of N-of-1 trials for serious neurological diseases could be addressed by integrating current approaches into learning healthcare systems.

Advancing District Nursing Care Through a Learning Healthcare System: A Viewpoint on Key Requirements.

The increasing complexity of healthcare needs driven by an ageing population places pressure on district nursing care. Many vulnerable older adults prefer to remain at home, requiring care coordinated with general practitioners and other professionals. This demand for integrated care is further challenged by a shortage of nursing professionals and the lack of standardised approaches to measure care quality. This article identifies the key requirements for implementing a learning healthcare system in district nursing care, using patient outcome data to foster continuous improvement and create a more adaptive, evidence-based, and patient-centred approach. This paper synthesises findings from multiple studies conducted as part of a PhD thesis, utilising a multi-method approach. These methods include examining patient outcomes in district nursing care and evaluating necessary cultural, organisational, and financial changes. Four key requirements were identified: (1) standardising patient outcome measures; (2) fostering a data-driven culture and strengthening professional autonomy; (3) enhancing organisational support and integrated care; and (4) adopting financing models that incentivise continuous learning and quality improvement. Implementing a learning healthcare system with patient outcome data in district nursing care requires a transformative shift. Standardising outcome measures, investing in information systems, and promoting continuous learning are crucial. Aligning financial incentives with patient outcomes, strengthening professional autonomy, and enhancing organisational support can make district nursing more responsive and capable of meeting complex needs. The described requirements are essential for advancing district nursing care through a more adaptive, evidence-based, and patient-centred approach.

The Age-Friendly Learning Healthcare System: Replicating electronic health record based documentation metrics for 4Ms care.

University of Utah Health (UUH) is an academic medical center that achieved "committed to care excellence" in age-friendly care in 2021 and has a long-standing culture of quality improvement central to a learning health system. University of California San Francisco (UCSF) developed electronic health record (EHR) documentation metrics for inpatient assessment of the 4Ms (What Matters, Medication, Mentation, and Mobility) based on the Institute for Healthcare Improvement's recommended care practice for an Age-Friendly Healthcare System. In partnership with UCSF, we replicated the assessment and action EHR metrics with local adaptations for each of the 4Ms at UUH. The UCSF team shared 4Ms documentation metrics and Structured Query Language code used to assess 4Ms care at UCSF. At UUH, this code was adapted for a different relational database management system and local clinical context. We assessed 4Ms care, individual M, and composite measures of all 4Ms, for all patients aged 65 and older admitted to UU Hospital between January 1, 2019 and December 31, 2021. We conducted a clinical validation of individual patient cases to confirm accuracy of 4Ms queries. In the 3-year study period, 16,489 qualifying patients, mean age 74.2, were admitted to UU Hospital in a total of 25,070 admissions with mean length of stay of 6.08 days. We were able to replicate 14 of the 16 EHR metrics of individual 4Ms developed at UCSF and five composite measures. For the composite measure addressing completeness of 4Ms care, 50% of patient encounters had all 4Ms administered during their encounter. Indicators of the completeness of 4Ms care can be measured using EHR data to validate implementation of the 4Ms at multiple academic medical centers. Key lessons to support future scaled-up assessments include the importance of adapting EHR measures to local activities and involving expert data analysts.

Putting measurement-based care into action: a multi-method study of the benefits of integrating routine client feedback in coordinated specialty care programs for early psychosis

BackgroundMeasurement-based care (MBC) is an effective tool in the delivery of evidence-based practices (EBPs). MBC utilizes feedback loops to share information and drive changes throughout a learning healthcare system. Few studies have demonstrated this practice in team-based care for young people with early psychosis. This paper describes the development of a personalized feedback report derived from routine assessments that is shared with clients and clinicians as part of a MBC process.MethodsWe used a multi-method approach to evaluate the implementation of a personalized feedback report at 5 early psychosis coordinated specialty care programs (CSC). We compared clients enrolled in CSC who did and did not receive a feedback report over the first 6 months of treatment. The sample included 204 clients: 146 who did not receive the feedback report (treatment as usual, TAU) and were enrolled over 2 years, and 58 who received the feedback report. A subset of 67 clients completed measures at both intake and 6-month follow-up, including 42 who received the personalized feedback report and 25 who did not. We compared the two groups with regard to self-reported symptoms, likelihood of completing treatment, and perception of shared decision making. We conducted qualitative interviews with 5 clients and 5 clinicians to identify the benefits and challenges associated with the personalized feedback report.ResultsThe total sample showed significant improvements in shared decision-making and in their intent to complete the program. Post hoc analyses revealed significant increases in the personalized feedback group, and non-significant changes in the TAU group, although group-by-time interactions did not reach statistical significance. The feedback report group engaged in significantly more sessions of Supported Employment and Education (SEE), case management, and peer support, and fewer medication visits over the first 6 months of treatment. Both groups showed significant improvement in symptoms and functioning. Results from the qualitative analysis indicated that the experience of receiving the reports was valuable and validating for both patients and clinicians.ConclusionsA personalized feedback report was integrated into standard of care for early psychosis programs. This process may improve shared decision-making, strengthen the likelihood to stay in treatment, and increase treatment attendance in psychosocial interventions. We posit that this process facilitates recovery-oriented care, strengths-focused treatment planning, enhances intrinsic motivation, and strengthens the therapeutic alliance.

The Academic Community Early Psychosis Intervention Network: Toward building a novel learning health system across six US states

AbstractIntroductionCompared to usual care, specialty services for first‐episode psychosis (FES) have superior patient outcomes. The Early Psychosis Intervention Network (EPINET), comprised of eight U.S. regional clinical networks, aims to advance the quality of FES care within the ethos of learning healthcare systems (LHS). Among these, the Academic Community (AC) EPINET was established to provide FES care, collect common data elements, leverage informatics, foster a culture of continuous learning and quality improvement, and engage in practice‐based research.MethodsWe designed and implemented a novel LHS of university‐affiliated FES programs within a hub (academic leadership team) and spoke (FES clinics) model. A series of site implementation meetings engaged stakeholders, setting the stage for a culture that values data collection and shared learning. We built clinical workflows to collect common data elements at enrollment and at consecutive 6‐month intervals in parallel to an informatics workflow to deliver outcome visualizations and drive quality improvement efforts.ResultsAll six clinical sites successfully implemented data capture workflows and engaged in the process of designing the informatics platform. Upon developing the structure, processes, and initial culture of the LHS, a total of 614 patients enrolled in AC‐EPINET, with the most common primary diagnoses of schizophrenia (32.1%) and unspecified psychotic disorders (23.6%). Visualized outcomes were delivered to clinical teams who began to consider locally relevant quality improvement projects.ConclusionsAC‐EPINET is a novel LHS, with a simultaneous focus on science, informatics, incentives, and culture. The work of developing AC‐EPINET thus far has highlighted the need for future LHS’ to be mindful of the complexities of data security issues, develop more automated informatic workflows, resource quality assurance efforts, and attend to building the cultural infrastructure with the input of all stakeholders.

Abstract 4136975: Lipoprotein (a) Discovery Project: Assessing Patient and Professional Education Needs

Introduction: It is estimated that 1 in 5 Americans have high lipoprotein (a) [Lp(a)] levels. High levels of Lp(a) are an independent, predominantly inherited, and causal risk factor for atherosclerotic cardiovascular disease (ASCVD). More investigation is needed to better understand the gaps in both professional and patient education on Lp(a) and its associated risk with ASCVD. Goals: The American Heart Association (AHA) is implementing a national 3-year initiative called the Lp(a) Discovery Project to understand system-level practice patterns for patients screened for high Lp(a) and develop models for national education. We aim to gauge an understanding of healthcare professional (HCP) and patient awareness, perceptions, knowledge, and behaviors of Lp(a) to develop a comprehensive educational approach that ultimately encourages patient-provider shared decision-making. Methods: To assess patient education needs, an online survey was conducted from October 11 to November 6, 2023, by Harris Insights&Analytics LLC with a nationally representative sample of 3,006 U.S. adults 18 years+. To assess professional education needs, the AHA engaged 10 champions from diverse health systems with established Lp(a) screening processes and workflows to participate in a Learning Healthcare System model to share best practices, inform on models for Lp(a) screening, and provide input on professional education topics. Results: The patient survey revealed that 34% of adults do not perceive high Lp(a) to pose an increased risk of heart attack, peripheral artery disease or stroke. If told that high Lp(a) does increase this risk, 63% are motivated to have their Lp(a) level checked and 88% would be motivated to reduce their risk for these conditions if they had high Lp(a). Ultimately, HCP recommendation was the most significant driver in getting screened among those who had their Lp(a) measured (61%). AHA-led champion interviews revealed that primary and specialty care HCPs need education on the importance of Lp(a) testing and cascade screening for family members as well as care considerations for patients with high Lp(a). Conclusion: Given that patients are most likely to be screened for Lp(a) if their HCP recommends it, we will focus on 1) educating patients and HCPs on the connection between Lp(a) and risk for cardiovascular disease and stroke and 2) providing HCPs with guidance on care considerations for those with high Lp(a) including cascade screening.

Abstract 4136995: Veterans Affairs (VA) Lipid Optimization Reimagined Quality Improvement Program (VALOR-QI) in Veterans with Atherosclerotic Cardiovascular Disease (ASCVD) at the San Juan VA

ASCVD is the principal cause of morbidity and mortality for Veterans in the VA Healthcare System. San Juan VA is one of 50 VA sites participating in a national quality improvement initiative called the VALOR QI: VA Lipid Optimization Reimagined Quality Improvement Project. Is a collaborative project between the U.S. Department of Veterans Affairs (VA) and the American Heart Association (AHA) with the goal of positively impacting Veterans’ cardiovascular (CV) health. VA sites work with an AHA QI consultant to develop and deploy a local quality improvement plan to help overcome site specific barriers preventing Veterans from achieving optimal cholesterol levels. The program’s objectives include improving clinical pathways and processes to impact ASCVD management through a Learning Healthcare System model of quality improvement designed to improve the management of dyslipidemia among those with high-risk ASCVD. The hypothesis is that patients who are part of the VALOR QI program will be more successful in reaching LDL-C target. This will help to reduce the risk of ASCVD and mortality for the patients, promoting better management of lipid levels through medications, diet and regular monitoring. As part of the methodology, the patients are enrolled to the program using the criteria of Veterans > 18 years of age with diagnosis of ASCVD and LDL-C > 70 mg/dl or non-HDL > 100 mg/dl. The Healthcare Coach has a full track of their lipid medications, assists the patients with refills, provides educational materials, follows up with their clinical appointments, and emphasizes the importance of having a good compliance with therapy, appointments and diets to maintain the target of LDL-C. Once the patient starts with a new lipid medication, they are followed in 3 months with labs. After reaching the target the patient is followed up closely in 6 months with labs to prevent relapse. The VALOR QI Program started at VA San Juan in June 2023 and, as of May 30, 2024, had directly engaged 282 Hispanic patients. 111 (39.4%) achieved target LDL-C; 268 (95%) have any statin use; 117 (41.5%) are on any non-statin lipid-lowering therapy (LLT); 116 (41%) are on statin plus LLT; 25 (8.9%) are on PCSK9, and 133 (47.2%) received educational materials. In conclusion, this initiative led to target LDL levels in 39% of patients which represents a significant population. As this program is further implemented in our institution, we expect improvement in patient outcomes and prognosis.

Suicidality among clients in a network of coordinated specialty care (CSC) programs for first-episode psychosis: Rates, changes in rates, and their predictors

BackgroundPeople experiencing their first episode of psychosis have high risk of suicide, and programs specializing in early psychosis have not always achieved reduced risk. The present study analyzes patterns of suicide ideation, self-harm, and suicide attempts within the Connection Learning Healthcare System of 23 early psychosis programs in Pennsylvania and Maryland that follow the Coordinated Specialty Care treatment model. MethodPeople with first episode psychosis (n = 1101) were assessed at admission and every six months using a standardized battery that included self-reported past-month ideation and clinician-reported past-six-month ideation, self-harm, and suicide attempts. ResultsAt admission, there were 28 % rates of self-reported past-month suicide ideation and 52 % rates clinician-reported past-six-month suicide ideation, 23 % rate of clinician-reported self-harm, and 15 % rate of attempts. After the first six months of treatment there were significantly lower rates of clinician-reported suicidality (with reductions of at least 77 %), and after the first year of treatment there was significantly lower self-reported ideation (with approximately 54 % reporting lower past-month ideation). Changes were not accounted for by differential early discharge. A range of psychosocial variables predicted within- and between-subject variability in suicidality. Social and role functioning, depressive symptom severity, and a sense of recovery were significant within-subject predictors of all four measures of suicidality. ConclusionsCompared to admission, we observed substantially lower rates of suicidality within the first year of treatment for clients with first episode psychosis in Coordinated Specialty Care. Reductions were predicted by some of the variables targeted by the treatment model.

1579P The Dutch national adolescent and young adult (AYA) cancer care network, a data driven learning healthcare system

1579P The Dutch national adolescent and young adult (AYA) cancer care network, a data driven learning healthcare system

Exploring the barriers, facilitators and needs to use patient outcomes in district nursing care: A multi-method qualitative study.

To provide an in-depth insight into the barriers, facilitators and needs of district nurses and nurse assistants on using patient outcomes in district nursing care. As healthcare demands grow, particularly in district nursing, there is a significant need to understand how to systematically measure and improve patient outcomes in this setting. Further investigation is needed to identify the barriers and facilitators for effective implementation. A multi-method qualitative study. Open-ended questions of a survey study (N = 132) were supplemented with in-depth online focus group interviews involving district nurses and nurse assistants (N = 26) in the Netherlands. Data were analysed using thematic analysis. Different barriers, facilitators and needs were identified and compiled into 16 preconditions for using outcomes in district nursing care. These preconditions were summarised into six overarching themes: follow the steps of a learning healthcare system; provide patient-centred care; promote the professional's autonomy, attitude, knowledge and skills; enhance shared responsibility and collaborations within and outside organisational boundaries; prioritise and invest in the use of outcomes; and boost the unity and appreciation for district nursing care. The preconditions identified in this study are crucial for nurses, care providers, policymakers and payers in implementing the use of patient outcomes in district nursing practice. Further exploration of appropriate strategies is necessary for a successful implementation. This study represents a significant step towards implementing the use of patient outcomes in district nursing care. While most research has focused on hospitals and general practitioner settings, this study focuses on the needs for district nursing care. By identifying 16 key preconditions across themes such as patient-centred care, professional autonomy and unity, the findings offer valuable guidance for integrating a learning healthcare system that prioritises the measurement and continuous improvement of patient outcomes in district nursing. Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines. No patient or public contribution.

Data Quality-Driven Improvement in Health Care: Systematic Literature Review.

The promise of real-world evidence and the learning health care system primarily depends on access to high-quality data. Despite widespread awareness of the prevalence and potential impacts of poor data quality (DQ), best practices for its assessment and improvement are unknown. This review aims to investigate how existing research studies define, assess, and improve the quality of structured real-world health care data. A systematic literature search of studies in the English language was implemented in the Embase and PubMed databases to select studies that specifically aimed to measure and improve the quality of structured real-world data within any clinical setting. The time frame for the analysis was from January 1945 to June 2023. We standardized DQ concepts according to the Data Management Association (DAMA) DQ framework to enable comparison between studies. After screening and filtering by 2 independent authors, we identified 39 relevant articles reporting DQ improvement initiatives. The studies were characterized by considerable heterogeneity in settings and approaches to DQ assessment and improvement. Affiliated institutions were from 18 different countries and 18 different health domains. DQ assessment methods were largely manual and targeted completeness and 1 other DQ dimension. Use of DQ frameworks was limited to the Weiskopf and Weng (3/6, 50%) or Kahn harmonized model (3/6, 50%). Use of standardized methodologies to design and implement quality improvement was lacking, but mainly included plan-do-study-act (PDSA) or define-measure-analyze-improve-control (DMAIC) cycles. Most studies reported DQ improvements using multiple interventions, which included either DQ reporting and personalized feedback (24/39, 61%), IT-related solutions (21/39, 54%), training (17/39, 44%), improvements in workflows (5/39, 13%), or data cleaning (3/39, 8%). Most studies reported improvements in DQ through a combination of these interventions. Statistical methods were used to determine significance of treatment effect (22/39, 56% times), but only 1 study implemented a randomized controlled study design. Variability in study designs, approaches to delivering interventions, and reporting DQ changes hindered a robust meta-analysis of treatment effects. There is an urgent need for standardized guidelines in DQ improvement research to enable comparison and effective synthesis of lessons learned. Frameworks such as PDSA learning cycles and the DAMA DQ framework can facilitate this unmet need. In addition, DQ improvement studies can also benefit from prioritizing root cause analysis of DQ issues to ensure the most appropriate intervention is implemented, thereby ensuring long-term, sustainable improvement. Despite the rise in DQ improvement studies in the last decade, significant heterogeneity in methodologies and reporting remains a challenge. Adopting standardized frameworks for DQ assessment, analysis, and improvement can enhance the effectiveness, comparability, and generalizability of DQ improvement initiatives.

A human centered design approach to define and measure documentation quality using an EHR virtual simulation.

Electronic health record (EHR) documentation serves multiple functions, including recording patient health status, enabling interprofessional communication, supporting billing, and providing data to support the quality infrastructure of a Learning Healthcare System. There is no definition and standardized method to assess documentation quality in EHRs. Using a human-centered design (HCD) approach, we define and describe a method to measure documentation quality. Documentation quality was defined as timely, accurate, user-centered, and efficient. Measurement of quality used a virtual simulated standardized patient visit via an EHR vendor platform. By observing and recording documentation efforts, nurse practitioners (NPs) (N = 12) documented the delivery of an Age-Friendly Health System (AFHS) 4Ms (what Matters, Medication, Mentation, and Mobility) clinic visit using a standardized case. Results for timely documentation indicated considerable variability in completion times of documenting the 4Ms. Accuracy varied, as there were many types of episodes of erroneous documentation and extra time in seconds in documenting the 4Ms. The type and frequency of erroneous documentation efforts were related to navigation burden when navigating to different documentation tabs. The evaluated system demonstrated poor usability, with most participants scoring between 60 and 70 on the System Usability Scale (SUS). Efficiency, measured as click burden (the number of clicks used to navigate through a software system), revealed significant variability in the number of clicks required, with the NPs averaging approximately 13 clicks above the minimum requirement. The HCD methodology used in this study to assess the documentation quality proved feasible and provided valuable information on the quality of documentation. By assessing the quality of documentation, the gathered data can be leveraged to enhance documentation, optimize user experience, and elevate the quality of data within a Learning Healthcare System.

Comparison of the Response to an Electronic Versus a Traditional Informed Consent Procedure in Terms of Clinical Patient Characteristics: Observational Study.

Electronic informed consent (eIC) is increasingly used in clinical research due to several benefits including increased enrollment and improved efficiency. Within a learning health care system, a pilot was conducted with an eIC for linking data from electronic health records with national registries, general practitioners, and other hospitals. We evaluated the eIC pilot by comparing the response to the eIC with the former traditional paper-based informed consent (IC). We assessed whether the use of eIC resulted in a different study population by comparing the clinical patient characteristics between the response categories of the eIC and former face-to-face IC procedure. All patients with increased cardiovascular risk visiting the University Medical Center Utrecht, the Netherlands, were eligible for the learning health care system. From November 2021 to August 2022, an eIC was piloted at the cardiology outpatient clinic. Prior to the pilot, a traditional face-to-face paper-based IC approach was used. Responses (ie, consent, no consent, or nonresponse) were assessed and compared between the eIC and face-to-face IC cohorts. Clinical characteristics of consenting and nonresponding patients were compared between and within the eIC and the face-to-face cohorts using multivariable regression analyses. A total of 2254 patients were included in the face-to-face IC cohort and 885 patients in the eIC cohort. Full consent was more often obtained in the eIC than in the face-to-face cohort (415/885, 46.9% vs 876/2254, 38.9%, respectively). Apart from lower mean hemoglobin in the full consent group of the eIC cohort (8.5 vs 8.8; P=.0021), the characteristics of the full consenting patients did not differ between the eIC and face-to-face IC cohorts. In the eIC cohort, only age differed between the full consent and the nonresponse group (median 60 vs 56; P=.0002, respectively), whereas in the face-to-face IC cohort, the full consent group seemed healthier (ie, higher hemoglobin, lower glycated hemoglobin [HbA1c], lower C-reactive protein levels) than the nonresponse group. More patients provided full consent using an eIC. In addition, the study population remained broadly similar. The face-to-face IC approach seemed to result in a healthier study population (ie, full consenting patients) than the patients without IC, while in the eIC cohort, the characteristics between consent groups were comparable. Thus, an eIC may lead to a better representation of the target population, increasing the generalizability of results.

Improving access to buprenorphine for rural veterans in a learning health care system.

To describe a learning health care system research process designed to increase buprenorphine prescribing for the treatment of opioid use disorder (OUD) in rural primary care settings within U.S. Department of Veterans Affairs (VA) treatment facilities. Using national administrative data from the VA Corporate Data Warehouse, we identified six rural VA health care systems that had improved their rate of buprenorphine prescribing within primary care from 2015 to 2020 (positive deviants). We conducted qualitative interviews with leaders, clinicians, and staff involved in buprenorphine prescribing within primary care from these sites to inform the design of an implementation strategy. Qualitative interviews to inform implementation strategy development. Interviews were audio-recorded, transcribed verbatim, and coded by a primary coder and secondary reviewer. Analysis utilized a mixed inductive/deductive approach. To develop an implementation strategy, we matched clinical needs identified within interviews with resources and strategies participants had utilized to address these needs in their own sites. Interview participants (n = 30) identified key clinical needs and strategies for implementing buprenorphine in rural, primary care settings. Common suggestions included the need for clinical mentorship or a consult service, buprenorphine training, and educational resources. Building upon interview findings and in partnership with a clinical team, we developed an implementation strategy composed of an engaging case-based training, an audit and feedback process, and educational resources (e.g., Buprenorphine Frequently Asked Questions, Rural Care Model Infographic). We describe a learning health care system research process that leveraged national administrative data, health care provider interviews, and clinical partnership to develop an implementation strategy to encourage buprenorphine prescribing in rural primary care settings.

Privacy Enhanced Authentication for Online Learning Healthcare Systems

Privacy Enhanced Authentication for Online Learning Healthcare Systems

Cause of death coding in asthma

BackgroundWhile clinical coding is intended to be an objective and standardized practice, it is important to recognize that it is not entirely the case. The clinical and bureaucratic practices from event of death to a case being entered into a research dataset are important context for analysing and interpreting this data. Variation in practices can influence the accuracy of the final coded record in two different stages: the reporting of the death certificate, and the International Classification of Diseases (Version 10; ICD-10) coding of that certificate.MethodsThis study investigated 91,022 deaths recorded in the Scottish Asthma Learning Healthcare System dataset between 2000 and 2017. Asthma-related deaths were identified by the presence of any of ICD-10 codes J45 or J46, in any position. These codes were categorized either as relating to asthma attacks specifically (status asthmatic; J46) or generally to asthma diagnosis (J45).ResultsWe found that one in every 200 deaths in this were coded as being asthma related. Less than 1% of asthma-related mortality records used both J45 and J46 ICD-10 codes as causes. Infection (predominantly pneumonia) was more commonly reported as a contributing cause of death when J45 was the primary coded cause, compared to J46, which specifically denotes asthma attacks.ConclusionFurther inspection of patient history can be essential to validate deaths recorded as caused by asthma, and to identify potentially mis-recorded non-asthma deaths, particularly in those with complex comorbidities.

Dashboards to Support Implementation of the Quebec Alzheimer Plan: Evaluation Study With Regional and Professional Considerations.

Health organizations face the critical task of executing and overseeing comprehensive health care. To address the challenges associated with this task, evidence-based dashboards have emerged as valuable tools. Since 2016, the regional health organizations of Quebec, Canada, have been responsible for ensuring implementation of the Quebec Alzheimer Plan (QAP), a provincial plan that aims to reinforce the capacity of primary care services to detect, diagnose, and treat persons with dementia. Despite the provincial scope of the QAP, the diverse material and human resources across regions introduce variability in the interest, utility, and specific needs associated with these dashboards. The aim of this study was to assess the interest and utility of dashboards to support the QAP implementation, as well as to determine the needs for improving these aspects according to the perspectives of various types of professionals involved across regions. An evaluative study using qualitative methods was conducted within a collaborative research approach involving different stakeholders, including the ministerial advisor and the four project managers responsible for supporting the implementation of the QAP, as well as researchers/scientific advisors. To support these organizations, we developed tailored, 2-page paper dashboards, detailing quantitative data on the prevalence of dementia, the use of health services by persons with dementia, and achievements and challenges of the QAP implementation in each organization's jurisdiction. We then conducted 23 focus groups with the managers and leading clinicians involved in the implementation of the QAP of each regional health organization. Real-time notes were taken using a structured observation grid. Content analysis was conducted according to different regions (organizations with university mandates or nearby organizations, labeled "university/peripheral"; organizations for which only part of the territory is in rural areas, labeled "mixed"; and organizations in remote or isolated areas, labeled "remote/isolated") and according to different types of participants (managers, leading clinicians, and other participants). Participants from organizations in all regions expressed interest in these dashboards and found them useful in several ways. However, they highlighted the need for indicators on orphan patients and other health care providers. Differences between regions were observed, particularly in the interest in continuity of care in university/peripheral regions and the need for diagnostic tools adapted to the culture in remote/isolated regions. These dashboards support the implementation of an Alzheimer Plan and contribute to the emergence of a learning health care system culture. This project allows each region to increase its monitoring capacity for the implementation of the QAP and facilitates reflection among individuals locally carrying out the implementation. The perspectives expressed will guide the preparation of the next iteration of the dashboards.

Creating pragmatic, rapid-cycle, evidence-based innovation: The Kaiser Permanente Northern California Delivery Science and Applied Research (DARE) program.

Ongoing crises in the quality, affordability, sustainability, value, and equity of U.S. healthcare call for rapid, massive-scale innovations across multiple specialties. Physician groups and healthcare organizations commit significant monetary and personnel investments for innovation and improvement efforts, but most lack over-arching systems theory-supported conceptual frameworks for efficiently coordinating the timely, large-volume idea generation, refinement, prioritization, evidence development, implementation, and re-evaluation strategies needed for rapid-cycle improvements in health care delivery, outcomes, and value. This article describes one large-scale, generalizable model: The Permanente Medical Group's (TPMG) Delivery Science and Applied Research (DARE) program within Kaiser Permanente Northern California. This organization-level initiative was designed to: (1) elicit clinical innovation and quality concerns across clinical specialties; (2) prioritize these questions for next-step evaluations; (3) create dedicated analytic, research, and clinical expertise to rapidly study the questions generated; (4) develop communities of clinician-researchers, embedded within their specialties' clinical operations, who gather ideas for evaluation, generate evidence, and facilitate implementation of research results (a.k.a. evidence-based innovators); and (5) broadly disseminate findings, to connect results with potential next-step implementation. The DARE program and its components rapidly led to more than 200 recently completed or ongoing projects, informed care changes, influenced national guidelines, developed communities of evidence-based clinician innovators in 15 specialties, and empowered new paths for career diversity and physician wellness. Key factors in the DARE program's success include explicitly defining high-impact ideas; engaging researchers with analysts experienced with large clinical data systems; developing several research funding mechanisms scaled to project size; prioritizing rapid and efficient project completion; supporting clinician-investigators embedded within their specialties; and structured organization-wide dissemination of findings for informing potential implementation. High-volume, evidence-based innovation programs can be important, scale-able, reproducible models for different settings for increasing quality, affordability, sustainability, value, and equity in healthcare and furthering the difficult-to-achieve concept of developing sustainable learning healthcare systems.

Transforming into a Learning Health System: A Quality Improvement Initiative.

The Institute of Medicine introduced the Learning Healthcare System concept in 2006. The system emphasizes quality, safety, and value to improve patient outcomes. The Bellevue Clinic and Surgical Center is an ambulatory surgical center that embraces continuous quality improvement to provide exceptional patient-centered care to the pediatric surgical population. We used statistical process control charts to study the hospital's electronic health record data. Over the past 7 years, we have focused on the following areas: efficiency (surgical block time use), effectiveness (providing adequate analgesia after transitioning to an opioid-sparing protocol), efficacy (creating a pediatric enhanced recovery program), equity (evaluating for racial disparities in surgical readmission rates), and finally, environmental safety (tracking and reducing our facility's greenhouse gas emissions from inhaled anesthetics). We have seen improvement in urology surgery efficiency, resulting in a 37% increase in monthly surgical volume, continued adaptation to our opioid-sparing protocol to further reduce postanesthesia care unit opioid administration for tonsillectomy and adenoidectomy cases, successful implementation of an enhanced recovery program, continued work to ensure equitable healthcare for our patients, and more than 85% reduction in our facility's greenhouse gas emissions from inhaled anesthetics. The Bellevue Clinic and Surgical Center facility is a living example of a learning health system, which has evolved over the years through continued patient-centered QI work. Our areas of emphasis, including efficiency, effectiveness, efficacy, equity, and environmental safety, will continue to impact the community we serve positively.

Evolving assessment pathways for precision oncology medicines to improve patient access: a tumor-agnostic lens.

Genomic and molecular alterations are increasingly important in cancer diagnosis, and scientific advances are opening new treatment avenues. Precision oncology (PO) uses a patient's genomic profile to determine optimal treatment, promising fewer side effects and higher success rates. Within PO, tumor-agnostic (TA) therapies target genomic alterations irrespective of tumor location. However, traditional value frameworks and approval pathways pose challenges which may limit patient access to PO therapies. This study describes challenges in assessing PO and TA medicines, explores possible solutions, and provides actionable recommendations to facilitate an iterative life-cycle assessment of these medicines. After reviewing the published literature, we obtained insights from key stakeholders and European experts across a range of disciplines, through individual interviews and an industry workshop. The research was guided and refined by an international expert committee through 2 sounding board meetings. The current challenges faced by PO and TA medicines are multiple and can be demonstrated through real-world examples of the current barriers and opportunities. A life-cycle approach to assessment should be taken, including key actions at the early stages of evidence generation, regulatory and reimbursement stage, as well as payment and adoption solutions that make use of the evolving evidence base. Working toward these solutions to maximize PO medicine value is a shared responsibility and stands to benefit all stakeholders. Our call to action is to expand access to comprehensive genomic testing, foster a learning health care system, enable fast and equitable access to cost-effective treatments, and ultimately improve health outcomes.