Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

This cohort study analyzes quality incentives, requirements, and other measures in employment and payer contracts of primary care clinicians.

In the early 2000s, a Scottish Government Oral Health Action Plan identified the need for a national programme to improve child oral health and reduce inequalities. 'Childsmile' aimed to improve child oral health in Scotland, reduce inequalities in outcomes and access to dental services, and to shift the balance of care from treatment to prevention through targeted and universal components in dental practice, community and educational settings. This paper describes how an embedded, theory-based research and evaluation arm with multi-disciplinary input helps determine priorities and provides important strategic direction. Programme theory is articulated in dedicated, dynamic logic models, and evaluation themes are as follows: population-level data linkage; trials and economic evaluations; investigations drawing from behavioural and implementation science; evidence reviews and updates; and applications of systems science. There is also a growing knowledge sharing network internationally. Collaborative working from all stakeholders is necessary to maintain gains and to address areas that may not be working as well, and never more so with the major disruptions to the programme from the COVID-19 pandemic and response. Conclusions are that evaluation and research are synergistic with a complex, dynamic programme like Childsmile. The evidence obtained allows for appraisal of the relative strengths of component interventions and the reach and impact of Childsmile to feed into national policy.

BACKGROUND: The Providence Diabetes Collective Impact Initiative (DCII) was designed to address the clinical challenges of type 2 diabetes and the social determinants of health (SDoH) challenges that exacerbate disease impact. OBJECTIVE: We assessed the impact of the DCII, a multifaceted intervention approach to diabetes treatment that employed both clinical and SDoH strategies, on access to medical and social services. DESIGN: The evaluation employed a cohort design and used an adjusted difference-in-difference model to compare treatment and control groups. PARTICIPANTS: Our study population consisted of 1220 people (740 treatment, 480 control), aged 18-65 years old with a pre-existing type 2 diabetes diagnosis who visited one of the seven Providence clinics (three treatment and four control) in the tri-county area of Portland, Oregon, between August 2019 and November 2020. INTERVENTIONS: The DCII threaded together clinical approaches such as outreach, standardized protocols, and diabetes self-management education and SDoH strategies including social needs screening, referral to a community resource desk, and social needs support (e.g., transportation) to create a comprehensive, multi-sector intervention. MAIN MEASURES: Outcome measures included SDoH screens, diabetes education participation, HbA1c, blood pressure, and virtual and in-person primary care utilization, as well as inpatient and emergency department hospitalization. KEY RESULTS: Compared to patients at the control clinics, patients at DCII clinics saw an increase in diabetes education (15.5%, p<0.001), were modestly more likely to receive SDoH screening (4.4%, p<0.087), and had an increase in the average number of virtual primary care visits of 0.35 per member, per year (p<0.001). No differences in HbA1c, blood pressure, or hospitalization were observed. CONCLUSIONS: DCII participation was associated with improvements in diabetes education use, SDoH screening, and some measures of care utilization.

The objective of this study was to examine the impact of investments in community organizing made as part of a 10-year comprehensive community initiative focused on community power building in California. Data from multiple sources were used to examine the relationship between investments and one measure of civic engagement, voter turnout. Comparisons were made over time (2010-2019) and between intervention and propensity-weighted comparison sites. Analyses determined that investments by the funder were positively associated with turnout; this effect differed across elections and was largest in 2012. Broad investments to support community engagement, organizing, and base building had a positive impact on voting, an important indicator of civic engagement. In historically marginalized or underserved communities, investing in power building can yield benefits despite structural barriers that result in inequities. As restrictive electoral reforms grow across the country in the wake of the 2020 election, initiatives designed to build power may support proactively organizing against these changes or provide the infrastructure to understand and navigate them. Investing in community power building is a promising strategy for philanthropic organizations, organizers, and policy makers.

Long COVID was originally identified through patient-reported experiences of prolonged symptoms. Many studies have begun to describe long COVID; however, this work typically focuses on medical records, instead of patient experiences, and lacks a comprehensive view of physical, mental, and social impacts. As part of our larger My COVID Diary (MCD) study, we captured patient experiences using a prospective and longitudinal patient-reported outcomes survey (PROMIS-10) and free-text narrative submissions. From this study population, we selected individuals who were still engaged in the MCD study and reporting poor health (PROMIS-10 scores < 3) at 6 months (n = 634). We used their PROMIS-10 and narrative data to describe and classify their long COVID experiences. Using Latent Class Analysis of the PROMIS-10 data, we identified four classifications of long COVID experiences: a few lingering issues (n = 107), significant physical symptoms (n = 113), ongoing mental and cognitive struggles (n = 235), and numerous compounding challenges (n = 179); each classification included a mix of physical, mental, and social health struggles with varying levels of impairment. The classifications were reinforced and further explained by patient narratives. These results provide a new understanding of the varying ways that long COVID presents to help identify and care for patients.

This study assesses the association between COVID-19 mRNA booster immunization compared with vaccination with the primary mRNA vaccination series alone and odds of hospitalization for COVID-19.

Background Research suggests the protection offered by COVID-19 vaccines might wane over time, prompting consideration of booster vaccinations. Data on which vaccines offer the most robust protection over time, and which patients are most vulnerable to attenuating protection, could help inform potential booster programmes. In this study, we used comprehensive hospitalisation data to estimate vaccine effectiveness over time. Methods In this case-control study, we used data from a large US health-care system to estimate vaccine effectiveness against severe SARS-CoV-2 infection and examined variation based on time since vaccination, vaccine type, and patients' demographic and clinical characteristics. We compared trends in attenuation of protection across vaccines and used a multivariable model to identify key factors associated with risk for severe breakthrough infection. Patients were considered to have severe COVID-19 if they were admitted to the hospital, had a final coded diagnosis of COVID-19 (according to International Classification of Diseases Tenth Revision code U07.1) or a positive nucleic acid amplification test for symptomatic SARS-CoV-2 during their hospitalisation, and were treated with remdesivir or dexamethasone during hospitalisation. Findings Between April 1, 2021, and Oct 26, 2021, we observed 9667 admissions for severe COVID-19 (ie, cases). Overall, 1293 (13.4%) of 9667 cases were fully vaccinated at the time of admission, compared with 22 308 (57.7%) of 38 668 controls, who were admitted to hospital for other reasons. The median time between vaccination and hospital admission among cases was 162 days (IQR 118-198). Overall vaccine effectiveness declined mostly over the course of the summer, from 94.5% (95% CI 91.4-96.5) in April, 2021 (pre-delta), to 84.0% (81.6-86.1) by October, 2021. Notably, vaccine effectiveness declined over time, from 94.0% (95% CI 92.8-95.0) at days 50-100 after vaccination to 80.4% (77.8-82.7) by days 200-250 after vaccination. After 250 days, vaccine effectiveness declines were even more notable. Among those who received the BNT162b2 (Pfizer-BioNTech) vaccine, vaccine effectiveness fell from an initial peak of 94.9% (93.2-96.2) to 74.1% (69.6-77.9) by days 200-250 after vaccination. Protection from the mRNA-1273 (Moderna) and Ad26.COV2 (Janssen) vaccines declined less over time, although the latter offered lower overall protection. Holding other factors constant, the risk of severe breakthrough infection was most strongly associated with age older than 80 years (adjusted odds ratio 1.76, 95% CI 1.43-2.15), vaccine type (Pfizer 1.39, 0.98-1.97; Janssen 14.53, 8.43-25.03; both relative to Moderna), time since vaccination (1.05, 1.03-1.07; per week after week 8 when protection peaks, technically), and comorbidities including organ transplantation (3.44, 95% CI 2.12-5.57), cancer (1.93, 1.60-2.33), and immunodeficiency (1.49, 1.13-1.96). Interpretation Vaccination remains highly effective against hospitalisation, but vaccine effectiveness declined after 200 days, particularly for older patients or those with specific comorbidities. Additional protection (eg, a booster vaccination) might be warranted for everyone, but especially for these populations. In addition to promoting general vaccine uptake, clinicians and policy makers should consider prioritising booster vaccinations in those most at risk of severe COVID-19. Copyright (C) 2022 Published by Elsevier Ltd. All rights reserved.

This cohort study compares rates of COVID-19 between unvaccinated adults who did and did not previously test positive for SARS-CoV-2.

Behavioral health integration (BHI) changes the paradigm of primary care delivery by integrating behavioral healthcare into primary care. Thus, BHI likely alters the shared experiences of both patients and providers in an interrelated manner; however, their experiences are usually evaluated separately. The purpose of this study was to analyze these shared experiences together within patient-provider pairs in integrated clinics. First, patient interviews were conducted using semi-structured interview guides and transcripts were analyzed for major themes of patient experience. Next, providers named in patient interviews were interviewed around these same themes. Thematic analysis was performed on 18 transcripts (11 patients, 7 providers). Common themes included BHI experience, pain management, feeling heard by providers, and health care experiences. Areas of alignment included positive perception of BHI, an absence of long-term care, and a desire to share decision-making. Pain management was a persistent area of conflict, and the differing experiences were consistent with a change in the psychodynamic patient-provider model. This conflict highlights a gap in BHI and a need for provider education about psychodynamic relationship models.

Measuring patients’ care experience is necessary to understanding and improving health care quality and is a core component of patient-centered care. In this study, we test whether patient health care experiences differed between patients with and without health-related social needs, above and beyond demographic differences previously studied. This study relies on survey data from 2341 patients who visited 1 of 7 primary care clinics in Portland, Oregon, and surrounding communities during the latter half of 2018. Survey analysis reveal that patients with at least 1 health-related social need had greater odds of reporting staff not always answering questions, not getting all the care they need, not getting the information to manage care, not being treated with respect by their provider, and getting care being a hassle. The findings from this study suggest that patients with health-related social needs are not getting the holistic care they expect in their primary care clinics and find it a hassle to get care regardless of their demographic characteristics and insurance status. This study may help to inform how health care systems and clinics can best serve patients with health-related social needs.

Background: Hospital mortality rates among COVID-19 admissions fell as early surges waned, critical supply shortages were addressed, and new treatment options became available. However, new surges in late 2020 provide an opportunity to understand whether and how regional COVID-19 surges might overwhelm hospital systems in ways that impact the survivability of the disease among admitted patients. Methods: Electronic health records representing all COVID-19 inpatient admissions from 52 hospitals in the western US between May 2020 and February 2021 were analyzed. Multilevel logistic regression was used to assess the relationship between COVID-19 surges (defined as the percent of a hospital's total bed capacity occupied with COVID-19 patients) and in-hospital mortality among COVID-19 patients while adjusting for patient demographics, comorbidities, severity of illness at admission, and major treatment strategies. Participants included any patient admitted to a participating hospital with a lab-confirmed COVID-19 diagnosis between May 1, 2020 and February 28, 2021 (n=34,683 distinct admissions). Findings: Mortality rates for COVID-19 admissions went up when hospitals were filled with more COVID-19 patients. Holding constant the effects of patient characteristics, comorbidities, major treatments, and severity of illness at admission, a 5% increase in the proportion of hospital beds occupied by COVID-19 patients was associated with a 10% (OR=1.10, p<.001) increase in relative odds of dying during the inpatient stay. Interpretation: Results suggest that "surge effects" are a significant driver of hospital mortality, even in the absence of the critical supply shortages and uncertainty about treatment options that characterized the early pandemic. Results were not driven by "enriched" risk among admitted patients during surge periods. Rather, hospital systems overwhelmed with large volumes of COVID-19 patients may face barriers to optimal care delivery that result in a higher mortality rate among admitted patients. Preventing COVID-19 surges may help decrease not just the number of deaths, but the rate of deaths as well. Funding: The authors received no special funding for this study.Declaration of Interests: None to declare. Ethics Approval Statement: This study was approved by PSJH IRB with number: STUDY2021000078

State-level Medicaid expansion under the Affordable Care Act (ACA) led to significant gains in insurance coverage, yet take-up remains low among many high-need populations. Researchers conducted a randomized controlled trial to study the impact of improved communication and low-cost behaviorally informed “nudges” on Medicaid take-up. The low-cost interventions significantly increased enrollment. The effects were larger among a population that had already expressed interest in obtaining coverage, but more persistent among those low-income individuals who were already enrolled in other state assistance programs

Results Summary Download Summary Español (pdf) Audio Recording (mp3) Results Summary What was the research about? Behavioral health integration, or BHI, is when clinics manage both physical and mental health care in the same place. The goal of BHI is to improve the coordination of services to better meet patients’ needs. In this study, the research team wanted to learn if BHI improved patients’ experiences of care. The team looked at clinics that were using BHI and scored them on staff training, how well staff work together, and other aspects of BHI. Then the team looked at whether clinics with higher scores had better Patient-reported experiences of care Patient-reported experiences of being judged, or stigma, in a healthcare setting Quality of care The team also looked at whether patients who felt stigma were less likely to get their healthcare needs met. What were the results? The study didn’t find a relationship between clinics’ scores on BHI and patients’ experiences of care or of stigma. In addition, overall scores on BHI didn’t relate to clinics’ quality of care. But the study found that Patients receiving care from clinics that had higher scores for training staff on BHI had fewer unnecessary emergency room visits. Clinics with higher scores for how well staff worked together did a better job of monitoring patients who took medicine for six months or longer. Clinics with higher scores for integrating their financial systems for physical and mental health services did a better job of following up with patients and monitoring those who took medicine for six months or longer. Also, patients who experienced stigma were more likely to report that they didn’t get their healthcare needs met. Who was in the study? The study included 2,524 adult patients receiving care at 1 of 12 clinics in Oregon. Of these, 88 percent were white. The average age was 53, and 68 percent were women. In addition, 52 percent of patients had a mental health condition. All patients lived in Oregon and had a commercial, Medicaid, or Medicare Advantage insurance plan. What did the research team do? Staff at each clinic completed a survey. The survey asked about ways the clinic integrated physical and mental health care, including training and overall cooperation in managing the two kinds of services. Patients completed a survey about their healthcare experiences during the study’s first year and again one year later. The survey asked how quickly patients got care, if the care was hassle free, and whether people felt stigma when they went to the clinic. To assess the quality of care that patients received, the research team looked at health records for 20,279 patients at the clinics. Then the research team looked at the relationship between clinics’ scores for BHI and patients’ experiences. A patient advisory team gave input on the study. What were the limits of the study? All clinics in the study used BHI. Results may differ if the research team had been able to compare clinics that were using BHI with those that weren’t. Future research could compare patient experiences of care at clinics using BHI with clinics not using BHI. How can people use the results? Healthcare clinics can use these results when planning ways to help patients improve their mental and physical health. Professional AbstractProfessional AbstractObjective To observe the effects of behavioral health integration (BHI) efforts on patient experience, perceived stigma, and claims-based quality of care Study Design Design Elements Description Design Cluster nonrandomized longitudinal observational study Population Survey: 2,524 patients in 12 clinics in Oregon Claims data: 20,729 patients seen in 1 of 12 clinics in the past 21 months Interventions/ Comparators Level of integration of behavioral and physical health care in primary care clinics Outcomes Patient experience and perceived stigma, claims-based quality of care Timeframe Up to 2-year follow-up for study outcomes In this prospective cluster nonrandomized longitudinal observational study, the research team examined whether there was an association between the integration of behavioral and physical health care in primary care clinics and three outcomes: patient experience, claims-based quality of care, and perceived stigma. The team also examined the relationship between stigma and patient experience and the impact of integration on this relationship. The research team collected data in 12 primary care and safety net clinics. All clinics are part of Oregon’s Medicaid Accountable Care Organizations and were integrating physical and behavioral health care as part of a statewide policy initiative. Clinic staff completed a clinic audit tool that measured five BHI domains: integrated care staffing and training, data sharing between mental and physical health providers, workflow and collaboration, integrated financial arrangements, and overall BHI integration. In the first and second year of the project, 2,524 adult patients receiving care at the clinics completed patient experience surveys. Of these, 88% were white, and the average age was 53. In addition, 68% were female, and 52% of respondents reported at least one behavioral health diagnosis. All patients were Oregon residents enrolled in a commercial, Medicaid, or Medicare Advantage insurance plan. The research team used a survey to assess perceived stigma and four domains of the patient experience: all care needs met, timely access to care, hassle-free care, and provider-to-provider communication. The team measured quality of care using five items from Oregon’s All Payer All Claims data set. Data were from 20,279 patients receiving care at one of the 12 clinics over a 21-month period. A patient advisory team assisted in study design and survey development. Results BHI scores were not associated with improved patient experience or reduced perceived stigma over time. Stigma was strongly associated with poor patient experience outcomes, but integration did not change this. The research team also found no associations between overall BHI scores and any of the five quality of care indicators. However, three BHI domains were positively associated with quality of care indicators. Clinics with better integrated care training had a lower rate of avoidable emergency department visits (p<0.05); clinics with integrated workflows had better monitoring of patients on persistent medications (p<0.05); and integrated financing was associated with better patient follow-up within seven days of a mental health discharge (p<0.05) and better monitoring of patients on persistent medications (p<0.05). Limitations The research team measured the degree to which elements of structural integration were associated with patient outcomes, but the study cannot offer evidence of a causal relationship. The measure of clinic integration may not have been optimal for determining association. Other measures of integration may have yielded different results. Survey response rates were low; which may have affected results. Conclusions and Relevance At two-year follow-up, integrated care was not associated with patients’ quality of care or perceived stigma. Future Research Needs Future research could measure BHI differently or incorporate research designs better suited to test a causal relationship. Researchers could also explore further whether reducing stigma in clinical settings may improve the patient experience and enable BHI programs to have a stronger impact.

Although policy often emphasizes health care expansions to improve population health, neighborhood characteristics may also influence outcomes. Documenting the association between neighborhood features and health poses several empirical challenges, including the potential for bias from relying on self-reported outcomes, selection bias from using health care data, and contextual limitations due to a methodological focus on one element of neighborhood attributes. In this exploratory analysis, we introduce rich data linking individual clinical health outcomes from a low-income community sample with primary data on a variety of neighborhood characteristics, and investigate the relationships between multiple aspects of neighborhoods and health. We find that neighborhoods have widely varying combinations of attributes and that residents of areas with lower socioeconomic deprivation, greater grocery store availability, and more active living characteristics were in better health than individuals living outside of these areas. Although this analysis does not establish causal pathways, it provides a foundation for future analyses to examine how neighborhoods interact with health policy and health care access to improve population health.

Background:Efforts to improve outcomes for the 10% of patients using two thirds of health care expenditures increasingly include addressing social determinants. Empiric evidence is needed to identify the highest impact nonmedical drivers of medical complexity and cost.Objectives:This study examines whether complex, highest cost patients have different patterns of critical life adversity than those with better health and lower utilization.Research Design:Using a validated algorithm we constructed a complexity/cost risk patient profile. We developed and fielded a life experience survey (Supplemental Digital Content 1, http://links.lww.com/MLR/B920) to a representative sample, then examined how the prevalence of specific adversities varied between complex, high-cost individuals, and others.Subjects:Surveys were sent to 9176 adult Medicaid members in Portland, Oregon.Measures:Our primary variable was high medical complexity health cost risk; an alternative specification combined health cost risk and actual utilization/cost. Our survey instrument measured exposure to early and later-life adversities.Results:Compared with healthy individuals in our population, medically complex individuals had significantly higher rates of adversity. The greatest risk of medical complexity and cost was associated with substance use [odds ratio (OR), 4.1], homelessness (OR, 3.0), childhood maltreatment (OR, 2.8), and incarceration (OR 2.4). Those with the highest prior year acute care utilization and cost had the highest rates of these same factors: substance use (62.5%), homelessness (61.7%), childhood maltreatment (55.5%), and incarceration (52.1%).Conclusion:Clinical and policy strategies that mitigate high-impact social drivers of poor outcomes are likely critical for improving both health and costs for complex, high-needs patients.

Research on behavioral health integration (BHI) often explores outcomes for quality and cost, but less is known about impacts of integration work on key patient experience outcomes. A mixed-methods longitudinal study of BHI was conducted in 12 primary care clinics in Oregon to assess how adoption of key integration practices including integrated staffing models, integrated care trainings for providers, and integrated data sharing impacted a set of patient experience outcomes selected and prioritized by an advisory panel of active patients. Results showed that adopting key aspects of integration was not associated with improved patient experience outcomes over time. Patient interviews highlighted several potential reasons why, including an overemphasis by health systems on the structural aspects of integration versus the experiential components and potential concerns among patients about stigma and discrimination in the primary care settings where integration is focused.

We examine the effect of a value-based insurance design (VBID) program implemented at a large public employer in the state of Oregon. The program substantially increased cost-sharing for several healthcare services likely to be of low value for most patients: diagnostic services (e.g., imaging services) and surgeries (e.g., spinal surgeries for pain). Using a difference-in-differences design coupled with granular, administrative health insurance claims data over the period 2008-2012, we estimate the change in low-value service use among beneficiaries before and after program implementation relative to a comparison group not exposed to the VBID. Our findings suggest that the VBID significantly reduced the use of targeted services, with an implied elasticity of demand of -0.22. We find no evidence that the VBID led to substitution to non-targeted services or increased overall healthcare costs. However, we also observe no evidence that the program led to cost-savings.

In 2012, Oregon embarked on an ambitious plan to redesign financing and care delivery for Medicaid. Oregon's Coordinated Care Organizations (CCOs) are the first statewide effort to use accountable care principles to pay for Medicaid benefits. We surveyed 8,864 Medicaid-eligible participants approximately 1 year before and 12 months after CCO implementation to assess the impact of CCOs on member-reported outcomes. We compared changes in outcomes over time between Medicaid CCO members, Medicaid fee-for-service (FFS) members, and those who were uninsured. After 1 year, Medicaid beneficiaries enrolled in CCOs reported better access to care, better quality care, and better connections to primary care than Medicaid FFS or uninsured persons. We did not find early evidence of improvements in preventive care and screenings or in ED utilization. Although these are early indicators, results suggest that Oregon's delivery system transformation is having a positive impact on patient experience outcomes.

Following the Patient Protection and Affordable Care Act, Medicaid eligibility in the United States expanded to include low-income adults. One key challenge for organizations and providers serving the Medicaid population was predicting if and how this change would alter the composition of enrollees. This study characterized demographics, socioeconomic challenges, and health of the expansion and non-expansion Medicaid populations in a metropolitan area in Oregon using a survey and Medicaid claims. Results showed that the expansion population has more men and non-English speakers than the non-expansion population. They also have greater education and employment, but face similar socioeconomic challenges including struggling to meet basic needs and housing instability. This study also found comparable self-reported physical and mental health, but lower prevalence of physical or mental health diagnoses and several ambulatory care reactive conditions including hypertension, obesity, and type 2 diabetes. The authors concluded that expansion and non-expansion populations differ in sex, language, education, employment, and health, but they face similar socioeconomic challenges. This information is useful for organizations coordinating and providing care to Medicaid members so they can understand the needs of the population and set appropriate population health management strategies.