Population Health Management最新文献

The Minority and Rural Coronavirus Insights Study (MRCIS) is an ongoing prospective cohort study examining health disparities associated with SARS-CoV-2 infection among medically underserved populations. This report describes procedures implemented to establish the MRCIS cohort and examines the factors associated with the molecular and serological assessment of SARS-CoV-2 infection status at participant enrollment. Participants were recruited from 5 geographically dispersed federally qualified health centers between November 2020 and April 2021. At baseline, participants completed a detailed demographic survey and biological samples were collected for testing. SARS-CoV-2 infection status was determined based on the combined molecular and serological test results. Chi-squared and logistic regression analyses were conducted to examine associations between sociodemographic factors, COVID-19 safety measures, existing comorbidities, and SARS-CoV-2 infection status. The final cohort included 3238 participants. The mean age of participants was 50.2 ± 15.8 years. Most participants identified as female (60.0%), heterosexual or straight (93.0%), White (47.6%), and Hispanic or Latino (49.1%). Approximately 26.1% of participants had at least one positive SARS-CoV-2 test result. The main effect model included age, sex, and race/ethnicity. Compared with adults ≥65 years, participants in all other age groups had ∼2 times increased odds of a positive SARS-CoV-2 test result. In addition, racial/ethnic minorities had ∼2 times increased odds of a positive SARS-CoV-2 infection status compared with non-Hispanic Whites. A unique cohort of a traditionally medically underserved minority population was established. Significant racial and ethnic disparities in SARS-CoV-2 infection status at baseline were discovered.

On March 1, 2018, the Massachusetts Medicaid and Children's Health Insurance Program (MassHealth) launched an ambitious accountable care organization (ACO) program that sought to integrate care across the physical, behavioral, functional, and social services continuum while holding ACOs accountable for cost and quality. The study objective was to describe changes in health care utilization among MassHealth members during the pre-ACO baseline (2015-2017) and post-implementation periods (2018 and 2019). Using MassHealth administrative data, the authors conducted a repeated cross-sectional study of MassHealth members enrolled in ACOs during 2015-2019. Rates of primary care visits, all-cause and primary-care sensitive emergency department (ED) visits, ED boarding, hospitalizations, acute unplanned admissions, and readmissions were reported during the baseline period (2015-2017) and year 1 (2018) and year 2 (2019). Primary care visit rates increased for adult members throughout the study period from a baseline mean of 7.2-9.2 per member per year (observed-to-expected [O:E]: 1.16) in 2019. Observed all-cause hospitalization rates fell below expected values with O:E ratios of 0.96 among adults and 0.79 among children in 2018, and 0.96 and 0.92 among adults and children, respectively, in 2019. All-cause ED visit rates increased slightly, and rates of pediatric asthma-related admissions, unplanned admissions for adults with ambulatory care sensitive conditions, and unplanned admissions and ED boarding for adults with substance use disorder and serious mental illness all declined for the study period. These findings are suggestive of utilization shifts to higher-value, lower-cost care under Massachusetts's innovative and comprehensive ACO model.

Clinical weight management programs face low participation. The authors assessed whether using electronic health record (EHR) data can identify variation in referral, consent, and engagement in a pediatric overweight and obesity (OW/OB) intervention. Using Epic EHR data collected between August 2020 and April 2021, sociodemographic and clinical diagnostic data (ie, International Classification of Disease [ICD] codes from visit and problem list [PL]) were analyzed to determine their association with referral, consent, and engagement in an OW/OB intervention. Bivariate analyses and multivariable logistic regression modeling were performed, with Bayesian inclusion criterion score used for model selection. Compared with the 581 eligible patients, referred patients were more likely to be boys (60% vs. 54%, respectively; P = 0.04) and have a higher %BMI_p95 (119% vs. 112%, respectively; P < 0.01); consented patients were more likely to have a higher %BMI_p95 (120% vs. 112%, respectively; P < 0.01) and speak Spanish (71% vs. 59%, respectively; P = 0.02); and engaged patients were more likely to have a higher %BMI_p95 (117% vs. 112%, respectively; P = 0.03) and speak Spanish (78% vs. 59%, respectively; P < 0.01). The regression model without either ICD codes or PL diagnoses was the best fit across all outcomes, which were associated with baseline %BMI_p95 and health clinic location. Neither visit nor PL diagnoses helped to identify variation in referral, consent, and engagement in a pediatric OW/OB intervention, and their role in understanding participation in such interventions remains unclear. However, additional efforts are needed to refer and engage younger girls with less extreme cases of OW/OB, and to support non-Hispanic families to consent.

COVID-19 vaccine uptake in the United States has proved challenging. A deeper characterization extending beyond demographics and political ideologies of those hesitating or resisting is needed to guide ongoing conversations. This study examined associations between US adults' vaccination intentions and mental health history, experience of the COVID-19 pandemic, and mental health outcomes. An online population-based cross-sectional survey was administered nationwide during January 4-7, 2021. Participants were questioned about past and current mental health, and completed the Patient Health Questionnaire 8 (PHQ-8), Generalized Anxiety Disorder 7-item (GAD-7), and Posttraumatic Diagnostic Scale (PDS)-5 (to capture symptoms of depression, anxiety, and traumatic stress, respectively). Experience of the pandemic included cumulative county-level COVID case and death rates, self-reported COVID-19 testing/exposure/diagnosis, and self-reported impact on routines, resources, and relationships. Of 936 respondents, 66% intended to be vaccinated, 14.7% responded "maybe," and 19.6% "no." Past diagnosis of obsessive compulsive disorder, less impact on routines or social supports, not having been screened or tested for COVID-19, not knowing someone who tested positive, and not self-isolating were associated with less intention to vaccinate. After controlling for demographic and pandemic experience factors, symptoms of traumatic stress, but not other mental health outcomes, were associated with less intention to vaccinate. The apparent contradiction between less negative impact of the pandemic and symptoms of traumatic stress being associated with less intention to be vaccinated indicates the complex nature of barriers to vaccine uptake. Results from this study contribute to the evidence base needed to improve ongoing and future communications about, and strategies to increase uptake of, vaccination.

The COVID-19 pandemic may widen the disparities in access to behavioral health (BH) services among groups that have been historically marginalized. However, the rapid expansion of telehealth presents an opportunity to reduce these disparities. The objective was to assess the impact of COVID-19 on BH visits, including in-person and telehealth, and BH treatments by different race and ethnicity groups. This was a retrospective, observational study using administrative claim data. Two cohorts were created: a before-COVID-19 group and a during-COVID-19 group. A difference-in-differences analysis was conducted to assess the access to BH-related visits between the 2 groups by different race and ethnicity groups. The study sample included 90,268 patients aged 18 to 64 years with repeated BH diagnoses in baseline periods and continuous medical and pharmacy enrollment. During the pandemic, BH telehealth visits surged, whereas the overall utilization of BH services, mental health medication, and counseling declined among all racial groups as the BH telehealth increase did not fully compensate for the reduction of in-person visits. Latino patients had a higher likelihood of using BH telehealth visits than White patients. However, Black patients had a lower likelihood of using substance use disorder (SUD) treatment than their White counterparts. Our results also suggested that care continuation and pre-established care-seeking behaviors are associated with increasing BH visits and treatments. As policy makers and payers are expanding offerings of telehealth visits, it is imperative to do so through a health equity lens and center the needs of groups that have been economically and socially marginalized to advance equitable adoption of telehealth.

Specific causes of mortality among various types of health care professionals (HCPs), including those characterized by age, gender, and race, have not been well described. The National Occupational Mortality Surveillance data for deaths in 26 US states in 1999, 2003-2004, and 2007-2014 were queried to address this question. Proportionate mortality ratios (PMRs) were calculated to compare specific causes of mortality among HCPs compared with those among the general population. HCPs were less likely to die from heart disease (PMR 93, 95% confidence intervals [CI] 92-94), alcoholism (PMR 62, 95% CI 57-68), drugs (PMR 80, 95% CI 70-90), and more likely to die from cerebrovascular disease (PMR 105, 95% CI 104-107) and diabetes (PMR 107, 95% CI 105-109). HCPs aged 18-64 years were more likely to die by suicide (PMR 104, 95% CI 101-107), whereas those aged 65-90 years were less likely to die by suicide (PMR 84, 95% CI 77-91), with physicians (PMR 251, 95% CI 229-275) and other HCPs having high PMR for suicide. Among all HCPs, suicide PMR was similarly increased, whereas heart disease PMRs are similarly decreased among Black compared with those among White HCPs and those among male compared with those among female HCPs. HCPs as a group and specific types of HCPs demonstrate causes of mortality that differ in important ways from the general population. Race and gender-based trends in PMRs for key causes of mortality among HCPs suggest that employment in a health care field may not alter race and gender disparities noted among the general population.

Employers may evaluate employee claims data for various reasons, including assessment of medical insurance and wellness plan efficacy, monitoring employee health trends, and identifying focus areas for wellness measures. The objective of this scoping review (ScR) is to describe the available literature reporting the use, applications, and outcomes of employee health claims data by self-insured employers. The ScR was conducted in a stepwise manner using an established framework: identifying the research question, identifying and selecting relevant studies, charting the data, and collating and reporting results. Literature searches were conducted in PubMed and Embase. Studies of self-insured employee populations that were conducted by the employer/s through May 2022 were identified using predefined criteria. Forty-one studies were included. The majority (90%) were cohort study designs; most employers (51%) were in industries such as aluminum production and health insurance providers. Twenty-four (59%) studies supplemented claims data with other sources such as human resource data to evaluate programs and/or health outcomes. A range of exposures (eg, chronic conditions, wellness program participation) and outcomes (eg, rates or costs of conditions, program effectiveness) were considered. Among the 25 studies that reported on patient confidentiality and privacy, 68% indicated institutional review board approval and 48% reported use of deidentified data. Many self-insured employers have used employee health claims data to gain insights into their employees' needs and health care utilization. These data can be used to identify potential improvements for wellness and other targeted programs to improve employee health and decrease absenteeism.

The adoption of e-consults, a form of formal, asynchronous provider-to-provider communication in which specialty medical advice is sought, has been proven to reduce unnecessary specialty consultations, build provider relationships, and reduce fragmentation of care. While the utilization of e-consults is generally a well-accepted alternative method of incorporating specialist expertise into a patient's plan of care and adoption has become common, the implementation of this disruptive care delivery modality can be challenging. This article seeks to describe the process and operational outcomes of e-consult adoption in an integrated health system with a focus on the benefits in the context of value-based care. Implications of e-consult adoption on referral volumes, wait times, and cancellation rates at the service line level are investigated. E-consult adoption and completion metrics, including utilization, completed versus rejected, turn-around times, and projected cost savings, are also discussed.

The goal of health equity is for all people to have opportunities and resources for optimal health outcomes regardless of their social identities, residence in marginalized communities, and/or experience with oppressive systems. Social determinants of health (SDOH)-the conditions in which we are born, grow, live, work, and age-are inextricably tied to health equity. Advancing health equity thus requires reliable measures of SDOH. In the United States, comprehensive individual-level data on SDOH are difficult to collect, may be inaccurate, and do not capture all dimensions of inequitable outcomes. Individual area-based indicators are widely available, but difficult to use in practice. Numerous area-level composite indices are available to describe SDOH, but there is no consensus on which indices are most appropriate to use. This article presents an analytic taxonomy of currently available SDOH composite indices and compares their components and predictive ability, providing insights into gaps and areas for further research.