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Public health officials promoted COVID-19 vaccines to limit burdens placed on the U.S. healthcare system and end the pandemic. People in some closed religious communities refused to vaccinate and likely acquired temporary immunity through infection. This paper compares the death rates in Amish, Old Order Mennonites, and conservative Mennonite groups to a rate estimated for the U.S. population. Approximately two-thirds of the U.S. population was immunized against COVID-19, while few in the Amish/Mennonite community were. We find divergent patterns. Once vaccines became available, excess deaths declined in the general population and remained elevated among Amish and Mennonites. Vaccination campaigns must consider and value the cultural beliefs of closed religious communities to be effective. [ABSTRACT FROM AUTHOR]

The widespread adoption of science-based prevention requires local infrastructures for prevention service delivery. Communities That Care (CTC) is a tested prevention service delivery system that enables a local coalition of community stakeholders to use a science-based approach to prevention and improve the behavioral health of young people. This paper uses data from the Community Youth Development Study (CYDS), a community-randomized trial of CTC, to examine the extent to which better internal team functioning of CTC coalitions increases the community-wide adoption of science-based prevention within 12 communities, relative to 12 matched comparison communities. Specifically, this paper examines the potential of both a direct relationship between coalition functioning and the community-wide adoption of science-based prevention and a direct relationship between functioning and the coalition capacities that ultimately enable the adoption of science-based prevention. Findings indicate no evidence of a direct relationship between four dimensions of coalition functioning and the community-wide adoption of a science-based approach to prevention, but suggest a relationship between coalition functioning and coalition capacities (building new member skills and establishing external linkages with existing community organizations) that enable science-based prevention. [ABSTRACT FROM AUTHOR]

Objective: To measure how much of the postdischarge cost and utilization attributable to methicillin-resistant Staphylococcus aureus (MRSA) health care-associated infections (HAIs) occur within the US Department of Veterans Affairs (VA) system and how much occurs outside.Data Sources/study Setting: Health care encounters from 3 different settings and payment models: (1) within the VA; (2) outside the VA but paid for by the VA (purchased care); and (3) outside the VA and paid for by Medicare.Study Design: Historical cohort study using data from admissions to VA hospitals between 2007 and 2012.Methods: We assessed the impact of a positive MRSA test result on costs and utilization during the 365 days following discharge using inverse probability of treatment weights to balance covariates.Principal Findings: Among a cohort of 152,687 hospitalized Veterans, a positive MRSA test result was associated with an overall increase of 6.6 (95 percent CI: 5.7-7.5) inpatient days and $9,237 (95 percent CI: $8,211-$10,262) during the postdischarge period. VA inpatient admissions, Medicare reimbursements, and purchased care payments accounted for 60.6 percent, 22.5 percent, and 16.9 percent of these inpatient costs.Conclusions: While most of the excess postdischarge health care costs associated with MRSA HAIs occurred in the VA, non-VA costs make up an important subset of the overall burden. [ABSTRACT FROM AUTHOR]

Objective: To assess differences in risk (measured by expected costs associated with sociodemographic and clinical profiles) between Veterans receiving outpatient services through two community care (CC) programs: the Fee program ("Fee") and the Veterans Choice Program ("Choice").Data Sources/study Setting: Administrative data from VHA's Corporate Data Warehouse in fiscal years (FY) 2014-2015.Study Design: We compared the clinical characteristics of Veterans across three groups (Fee only, Choice only, and Fee & Choice). We classified Veterans into risk groups based on Nosos risk scores and examined the relationship between type of outpatient utilization and risk within each CC group. We also examined changes in utilization of VHA and CC in FY14-FY15. We used chi-square tests, t tests, and ANOVAs to identify significant differences between CC groups.Principal Findings: Of the 1,400,977 Veterans using CC in FY15, 91.4 percent were Fee-only users, 4.4 percent Choice-only users, and 4.2 percent Fee & Choice users. Mean concurrent risk scores were higher for Fee only and Fee & Choice (1.9, SD = 2.7; 1.8, SD = 2.2) compared to Choice-only users (1.0, SD = 1.2) (p < .0001). Most CC users were "dual users" of both VHA and CC in FY14-FY15.Conclusions: As care transitions from VHA to CC, VHA should consider how best to coordinate care with community providers to reduce duplication of efforts, improve handoffs, and achieve the best outcomes for Veterans. [ABSTRACT FROM AUTHOR]

Objective: To examine the association between medical home enrollment and receipt of recommended care for Medicaid beneficiaries with multiple chronic conditions (MCC).Data Sources/study Setting: Secondary claims data from fiscal years 2008-2010. The sample included nonelderly Medicaid beneficiaries with at least two of eight target conditions (asthma, chronic obstructive pulmonary disease, diabetes, hypertension, hyperlipidemia, seizure disorder, major depressive disorder, and schizophrenia).Study Design: We used linear probability models with person- and year-level fixed effects to examine the association between patient-centered medical home (PCMH) enrollment and nine disease-specific quality-of-care metrics, controlling for selection bias and time-invariant differences between enrollees.Data Collection Methods: This study uses a dataset that links Medicaid claims with other administrative data sources.Principal Findings: Patient-centered medical home enrollment was associated with an increased likelihood of receiving eight recommended mental and physical health services, including A1C testing for persons with diabetes, lipid profiles for persons with diabetes and/or hyperlipidemia, and psychotherapy for persons with major depression and persons with schizophrenia. PCMH enrollment was associated with overuse of short-acting β-agonists among beneficiaries with asthma.Conclusions: The PCMH model can improve quality of care for patients with multiple chronic conditions. [ABSTRACT FROM AUTHOR]

Objective: The concept of shifting from volume (i.e., billing for as many patients and services as possible) to value (i.e., reducing costs while improving quality) has been a key underpinning of the development of accountable care organizations (ACOs), yet the cultural change necessary to make this shift has been previously unexplored.Data Sources/study Setting: Primary data collected through site visits to four private sector ACOs.Study Design: Cross-sectional, semi-structured interview study with analysis done at the ACO level to learn about ACO development.Data Collection: One hundred and forty-eight interviews recorded and transcribed verbatim followed by rigorous qualitative analysis using a grounded theory approach.Principal Findings: The importance of shifting organizational culture from volume to value was emphasized across sites and interviewees, particularly when defining an ACO; describing the shift in organizational focus to value; and discussing how to create value by emphasizing quality over volume. Value was viewed as more than cost-benefit, but rather encapsulated a paradigmatic cultural change in the way care is provided.Conclusions: We found that moving from volume to value is central to the culture change required of an ACO. Our findings can inform future efforts that aim to create a more effective value-based health care system. [ABSTRACT FROM AUTHOR]

Objective: To assess frequency, type, and extent of behavioral health (BH) nonquantitative treatment limits (NQTLs) before and after implementation of the Mental Health Parity and Addiction Equity Act of 2008 (MHPAEA).Data Sources: Secondary administrative data for Optum carve-out and carve-in plans.Study Design: Cross-tabulations and "two-part" regression models were estimated to assess associations of parity period with NQTLs.Data Collection/extraction Methods: Optum provided four proprietary BH databases, including 2008-2013 data for 40 carve-out and 385 carve-in employers from Optum's claims processing databases and 2010 data from interviews conducted by Optum's parity compliance team with 49 carve-out employers.Principal Findings: Preparity, carve-out plans required preauthorization for in-network inpatient/intermediate care; otherwise coverage was denied. Postparity, 73 percent would review later by request and half charged no penalty for late authorization. Outpatient visit authorization requirements virtually disappeared. For carve-out out-of-network inpatient/intermediate care, and for carve-ins, plans changed penalties to match medical service policies, but this did not necessarily lead to fewer requirements or lower penalties.Conclusion: After 2011, MHPAEA was associated with the transformation of BH care management, including much less restrictive preauthorization requirements, especially for in-network care provided by carve-out plans. [ABSTRACT FROM AUTHOR]

Objective: (1) To evaluate the operational efficiency of various sampling methods for patient exit interviews; (2) to discuss under what circumstances each method yields an unbiased sample; and (3) to propose a new, operationally efficient, and unbiased sampling method.Study Design: Literature review, mathematical derivation, and Monte Carlo simulations.Principal Findings: Our simulations show that in patient exit interviews it is most operationally efficient if the interviewer, after completing an interview, selects the next patient exiting the clinical consultation. We demonstrate mathematically that this method yields a biased sample: patients who spend a longer time with the clinician are overrepresented. This bias can be removed by selecting the next patient who enters, rather than exits, the consultation room. We show that this sampling method is operationally more efficient than alternative methods (systematic and simple random sampling) in most primary health care settings.Conclusion: Under the assumption that the order in which patients enter the consultation room is unrelated to the length of time spent with the clinician and the interviewer, selecting the next patient entering the consultation room tends to be the operationally most efficient unbiased sampling method for patient exit interviews. [ABSTRACT FROM AUTHOR]

Background: There is accelerating interest in measuring and reporting the quality of care delivered by health care providers and organizations, but methods for defining the patient panels for which they are held accountable are not well defined.Objectives: To examine the potential impact of using alternative algorithms to define accountable patient populations for performance assessment.Research Design: We used administrative data regarding Community Health Center (CHC) visits in simulations of performance assessment for breast, cervical, and colorectal cancer screening.Participants: Fifteen CHC sites in the northeastern US.Measures: We used three different algorithms to define patient populations eligible for measurement of cancer screening rates and simulated center-level performance rates based on these alternative population definitions.Results: Focusing on breast cancer screening, the percentage of women aged 51-75 eligible for this measure across CHCs, if using the most stringent algorithm (requiring a visit in the assessment year plus at least one visit in the 2 years prior), ranged from 28% to 60%. Analogous ranges for cervical and colorectal cancer screening were 18-59% and 26-62%, respectively. Simulated performance data from the centers demonstrate that variations in eligible patient populations across health centers could lead to the appearance of large differences in health center performance or differences in expected rankings of CHCs when no such differences exist. For instance, when holding performance among similar populations constant, but varying the proportion of populations seen across different health centers, simulated health center adherence to screening guidelines varied by over 15% even though actual adherence for similar populations did not differ.Conclusions: Quality measurement systems, such as those being used in pay-for-performance and public reporting programs, must consider the definitions used to identify sample populations and how such populations might differ across providers, clinical practice groups, and provider systems. [ABSTRACT FROM AUTHOR]

Background: Although multiple co-occurring chronic illnesses within the same individual are increasingly common, few studies have examined the challenges of multimorbidity from the patient perspective.Objective: The aim of this study is to examine the self-management learning needs and willingness to see non-physician providers of patients with multimorbidity compared to patients with single chronic illnesses.Design: This research is designed as a cross-sectional survey.Participants: Based upon ICD-9 codes, patients from a single VHA healthcare system were stratified into multimorbidity clusters or groups with a single chronic illness from the corresponding cluster. Nonproportional sampling was used to randomly select 720 patients.Measurements: Demographic characteristics, functional status, number of contacts with healthcare providers, components of primary care, self-management learning needs, and willingness to see nonphysician providers.Results: Four hundred twenty-two patients returned surveys. A higher percentage of multimorbidity patients compared to single morbidity patients were "definitely" willing to learn all 22 self-management skills, of these only 2 were not significant. Compared to patients with single morbidity, a significantly higher percentage of patients with multimorbidity also reported that they were "definitely" willing to see 6 of 11 non-physician healthcare providers.Conclusions: Self-management learning needs of multimorbidity patients are extensive, and their preferences are consistent with team-based primary care. Alternative methods of providing support and chronic illness care may be needed to meet the needs of these complex patients. [ABSTRACT FROM AUTHOR]

Background: Language barriers in medical care are a large and growing problem in the United States. Most research has focused on how language barriers affect patients. Less is known of the physician perspective and the efforts they are making to overcome these barriers.Objective: To learn about current approaches to communicating with limited English-proficient (LEP) patients and the associated financial and nonfinancial constraints that private practice physicians and managers perceive in providing these services.Design: Computer-assisted telephone focus groups with open-ended discussion guide.Setting: Small private practices in geographic areas that have experienced recent dramatic increases in LEP populations.Participants: Primary care physicians, specialists, and practice managers.Approach: Focus group transcripts were systematically coded using grounded theory analysis. The research team then identified common themes that arose across the groups.Results: Citing the cost, inaccessibility, and inconvenience of using professional interpreters, physicians commonly used family and friends as interpreters. Few recalled any actual experience with professional interpreters or were well-informed about the cost of their services. Physicians and office managers voiced uniform concern about how language barriers impede quality and safety of patient care and increased malpractice risk.Conclusions: Health care providers in private practice recognize the importance of overcoming language barriers. However, perceived barriers to implementing cost-effective strategies to these barriers are high. Physicians in private practice would benefit from information about how to best overcome language barriers in their practices efficiently and affordably. [ABSTRACT FROM AUTHOR]

Background: The gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the "eight Americas," to explore the causes of the disparities that can inform specific public health intervention policies and programs.Methods and Findings: The eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15-44 y) and middle-aged (45-59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations.Conclusions: Disparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries. [ABSTRACT FROM AUTHOR]