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Background: The purpose of this study was to explore the factors influencing how individual Community Health Teams (CHTs) make decisions about what services to offer and how to allocate their resources., Methods: We conducted thirteen semi-structured interviews with all 13 CHTs program managers between January and March, 2021. We analyzed interviewees descriptions of their service offerings, resources allocation, and decision-making process to identify themes., Results: Four major themes emerged from the interview data as factors influencing community health team program managers' decision-making process: commitment to offering high-quality care coordination, Blueprint's stable and flexible structure, use of data in priority setting, and leveraging community partnerships and local resources., Conclusions: Community-based CHTs with flexible funding allowed programs to tailor service offerings in response to community needs. It is important for teams to have access to community-level data. Teams are cultivating and leveraging community partners to increase their care coordination capacity, which is focus of their work. CHTs are a model for leveraging community partnerships to increase service capacity and pubic engagement in health services for other states to replicate., (© 2023. The Author(s).)

Purpose: Identification and triage of severely injured patients to trauma centers is paramount to survival. Many patients are undertriaged in rural areas and do not receive proper care. The decision-making processes involved in triage are not well understood and should be assessed to improve the triage process and outcomes., Methods: Triage decision-making processes were explored through emergency medical services (EMS) practitioner focus groups and a discrete choice experiment (DCE). Attributes of trauma determined from focus groups and the literature included patient demography, injury mechanism, and trauma center distance. DCE data were analyzed using mixed logit models., Results: High-risk mechanism, decreased age, multiple comorbidities, and pregnancy were found to increase the preference for triage. Greater trauma center distance was found to decrease preference for triage, but practitioners were willing to trade off up to 2 h of travel time to transport a third-trimester pregnancy and 48 min of travel time to transport a 25-y-old than they would a 50-y-old with the same comorbidities, injuries, and stability., Conclusions: Our findings suggest that current forms of EMS protocols may not be appropriately tailored to support the mechanisms underlying practitioner decision making. Public health professionals and researchers should consider using DCEs to better understand EMS practitioner decision making and identify structures and incentives that may improve patient outcomes and optimally guide appropriate triage decisions., Highlights: Discrete choice experiments are an effective method to elicit prehospital practitioners' preferences around transport of the traumatized patient.Practitioner biases observed in EMS transport data are recovered in stated preference models incorporating individual preference heterogeneity.There is a discrepancy between the triage priorities recommended by protocol and those measured from prehospital practitioners' decisions-this may have implications in over- and undertriage rates and prehospital protocol design.

Background: National efforts to control US healthcare spending are potentially undermined by changes in patient characteristics, and in particular increases in rates of obesity and overweight. The objective of this study was to provide current estimates of the effect of obesity and overweight on healthcare spending overall, by service line and by payer using the National Institutes of Health classifications for BMI., Methods: We used a quasi-experimental design and analyzed the data using generalized linear models and two-part models to estimate obesity- and overweight-attributable spending. Data was drawn from the 2006 and 2016 Medical Expenditures Panel Survey. We identified individuals in the different BMI classes based on self-reported height and weight., Results: Total medical costs attributable to obesity rose to $126 billion per year by 2016, although the marginal cost of obesity declined for all obesity classes. The overall spending increase was due to an increase in obesity prevalence and a population shift to higher obesity classes. Obesity related spending between 2006 and 2016 was relatively constant due to decreases in inpatient spending, which were only partially offset by increases in outpatient spending., Conclusions: While total obesity related spending between 2006 and 2016 was relatively constant, by examining the effect of different obesity classes and overweight, it provides insight into spend for each level of obesity and overweight across service line and payer mix. Obesity class 2 and 3 were the main factors driving spending increases, suggesting that persons over BMI of 35 should be the focus for policies focused on controlling spending, such as prevention., (© 2022. The Author(s).)

Despite unprecedented progress in developing COVID-19 vaccines, global vaccination levels needed to reach herd immunity remain a distant target, while new variants keep emerging. Obtaining near universal vaccine uptake relies on understanding and addressing vaccine resistance. Simple questions about vaccine acceptance however ignore that the vaccines being offered vary across countries and even population subgroups, and differ in terms of efficacy and side effects. By using advanced discrete choice models estimated on stated choice data collected in 18 countries/territories across six continents, we show a substantial influence of vaccine characteristics. Uptake increases if more efficacious vaccines (95% vs 60%) are offered (mean across study areas = 3.9%, range of 0.6%-8.1%) or if vaccines offer at least 12 months of protection (mean across study areas = 2.4%, range of 0.2%-5.8%), while an increase in severe side effects (from 0.001% to 0.01%) leads to reduced uptake (mean = -1.3%, range of -0.2% to -3.9%). Additionally, a large share of individuals (mean = 55.2%, range of 28%-75.8%) would delay vaccination by 3 months to obtain a more efficacious (95% vs 60%) vaccine, where this increases further if the low efficacy vaccine has a higher risk (0.01% instead of 0.001%) of severe side effects (mean = 65.9%, range of 41.4%-86.5%). Our work highlights that careful consideration of which vaccines to offer can be beneficial. In support of this, we provide an interactive tool to predict uptake in a country as a function of the vaccines being deployed, and also depending on the levels of infectiousness and severity of circulating variants of COVID-19., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In the beginning of the COVID-19 US epidemic in March 2020, sweeping lockdowns and other aggressive measures were put in place and retained in many states until end of August of 2020; the ensuing economic downturn has led many to question the wisdom of the early COVID-19 policy measures in the US. This study's objective was to evaluate the cost and benefit of the US COVID-19-mitigating policy intervention during the first six month of the pandemic in terms of COVID-19 mortality potentially averted, versus mortality potentially attributable to the economic downturn. We conducted a synthesis-based retrospective cost-benefit analysis of the full complex of US federal, state, and local COVID-19-mitigating measures, including lockdowns and all other COVID-19-mitigating measures, against the counterfactual scenario involving no public health intervention. We derived parameter estimates from a rapid review and synthesis of recent epidemiologic studies and economic literature on regulation-attributable mortality. According to our estimates, the policy intervention saved 866,350-1,711,150 lives (4,886,214-9,650,886 quality-adjusted life-years), while mortality attributable to the economic downturn was 57,922-245,055 lives (2,093,811-8,858,444 life-years). We conclude that the number of lives saved by the spring-summer lockdowns and other COVID-19-mitigation was greater than the number of lives potentially lost due to the economic downturn. However, the net impact on quality-adjusted life expectancy is ambiguous., Competing Interests: The authors have declared that no competing interests exist.

Background: Reducing inappropriate referrals to specialists is a challenge for the healthcare system as it seeks to transition from volume to value-based healthcare. Given the projection of a severe shortage of rheumatologists in the near future, innovative strategies to decrease demand for rheumatology services may prove more fruitful than increasing the supply of rheumatologists. Efforts to increase appropriate utilization through reductions in capacity may have the unintended consequence of reducing appropriate care as well. This highlights the challenges in increasing the appropriate use of high cost services as the health system transitions to value based care. The objective of this study was to analyze factors affecting appropriateness of rheumatology services., Methods: This was a cross-sectional study of patients receiving Rheumatology services between November 2013 and October 2019. We used a proxy for "appropriateness": whether or not there was any follow-up care after the first appointment. Results from regression analysis and physicians' chart reviews were compared using an inter-rater reliability measure (kappa). Data was drawn from the EHR 2013-2019., Results: We found that inappropriate referrals increased 14.3% when a new rheumatologist was hired, which increased to 14.8% after wash-out period of 6 months; 15.7% after 12 months; 15.5% after 18 months and 16.7% after 18 months. Other factors influencing appropriateness of referrals included severity of disease, gender and insurance type, but not specialty of referring provider., Conclusions: Given the projection of a severe shortage of rheumatologists in the near future, innovative strategies to decrease demand for rheumatology services may prove more fruitful than increasing the supply of rheumatologists. Innovative strategies to decrease demand for rheumatology services may prove more fruitful than increasing the supply of rheumatologists. These findings may apply to other specialties as well. This study is relevant for health care systems that are implementing value-based payment models aimed at reducing inappropriate care., (© 2021. The Author(s).)

Background: Since the start of the global COVID-19 pandemic, countries have been mirroring each other's policies to mitigate the spread of the virus. Whether current measures alone will lead to behavioral change such as social distancing, washing hands, and wearing a facemask is not well understood. The objective of this study is to better understand individual variation in behavioral responses to COVID-19 by exploring the influence of beliefs, motivations and policy measures on public health behaviors. We do so by comparing The Netherlands and Flanders, the Dutch speaking part of Belgium., Methods and Findings: Our final sample included 2,637 respondents from The Netherlands and 1,678 from Flanders. The data was nationally representative along three dimensions: age, gender, and household income in both countries. Our key outcome variables of interest were beliefs about policy effectiveness; stated reasons for complying with public rules; and changes in behavior. For control variables, we included a number of measures of how severe the respondent believed Covid-19 to be and a number of negative side effects that the person may have experienced: loneliness, boredom, anxiety, and conflicts with friends and neighbors. Finally, we controlled for socio-demographic factors: age, gender, income (categorical), education (categorical) and the presence of Covid-19 risk factors (diabetes, high blood pressure, heart disease, asthma, allergies). The dependent variable for each of the estimation models is dichotomous, so we used Probit models to predict the probability of engaging in a given behavior. We found that motivations, beliefs about the effectiveness of measures, and pre-pandemic behavior play an important role. The Dutch were more likely to wash their hands than the Flemish (15.4%, p<0.01), visit family (15.5%, p < .01), run errands (12.0%, p<0.05) or go to large closed spaces such as a shopping mall (21.2%, p<0.01). The Dutch were significantly less likely to wear a mask (87.6%, p<0.01). We also found that beliefs about the virus, psychological effects of the virus, as well as pre-pandemic behavior play a role in adherence to recommendations., Conclusions: Our results suggest that policymakers should consider behavioral motivations specific to their country in their COVID-19 strategies. In addition, the belief that a policy is effective significantly increased the probability of the behavior, so policy measures should be accompanied by public health campaigns to increase adherence., Competing Interests: The authors have declared that no competing interests exist.

Background: High quality serious illness communication requires good understanding of patients' values and beliefs for their treatment at end of life. Natural Language Processing (NLP) offers a reliable and scalable method for measuring and analyzing value- and belief-related features of conversations in the natural clinical setting. We use a validated NLP corpus and a series of statistical analyses to capture and explain conversation features that characterize the complex domain of moral values and beliefs. The objective of this study was to examine the frequency, distribution and clustering of morality lexicon expressed by patients during palliative care consultation using the Moral Foundations NLP Dictionary., Methods: We used text data from 231 audio-recorded and transcribed inpatient PC consultations and data from baseline and follow-up patient questionnaires at two large academic medical centers in the United States. With these data, we identified different moral expressions in patients using text mining techniques. We used latent class analysis to explore if there were qualitatively different underlying patterns in the PC patient population. We used Poisson regressions to analyze if individual patient characteristics, EOL preferences, religion and spiritual beliefs were associated with use of moral terminology., Results: We found two latent classes: a class in which patients did not use many expressions of morality in their PC consultations and one in which patients did. Age, race (white), education, spiritual needs, and whether a patient was affiliated with Christianity or another religion were all associated with membership of the first class. Gender, financial security and preference for longevity-focused over comfort focused treatment near EOL did not affect class membership., Conclusions: This study is among the first to use text data from a real-world situation to extract information regarding individual foundations of morality. It is the first to test empirically if individual moral expressions are associated with individual characteristics, attitudes and emotions.

Given the role of human behavior in the spread of disease, it is vital to understand what drives people to engage in or refrain from health-related behaviors during a pandemic. This paper examines factors associated with the adoption of self-protective health behaviors, such as social distancing and mask wearing, at the start of the Covid-19 pandemic in the USA. These behaviors not only reduce an individual's own risk of infection but also limit the spread of disease to others. Despite these dual benefits, universal adoption of these behaviors is not assured. We focus on the role of socioeconomic differences in explaining behavior, relying on data collected in April 2020 during the early stages of the Covid-19 pandemic. The data include information on income, gender and race along with unique variables relevant to the current pandemic, such as work arrangements and housing quality. We find that higher income is associated with larger changes in self-protective behaviors. These gradients are partially explained by the fact that people with less income are more likely to report circumstances that make adopting self-protective behaviors more difficult, such as an inability to tele-work. Both in the USA and elsewhere, policies that assume universal compliance with self-protective measures-or that otherwise do not account for socioeconomic differences in the costs of doing so-are unlikely to be effective or sustainable., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© The Author(s) 2021.)

Objectives: There is an incomplete understanding of the host humoral immune response to severe acute respiratory syndrome (SARS)-coronavirus (CoV)-2, which underlies COVID-19, during acute infection. Host factors such as age and sex as well as the kinetics and functionality of antibody responses are important factors to consider as vaccine development proceeds. The receptor-binding domain of the CoV spike (RBD-S) protein mediates host cell binding and infection and is a major target for vaccine design to elicit neutralising antibodies., Methods: We assessed serum anti-SARS-CoV-2 RBD-S IgG, IgM and IgA antibodies by a two-step ELISA and neutralising antibodies in a cross-sectional study of hospitalised COVID-19 patients of varying disease severities. Anti-RBD-S IgG levels were also determined in asymptomatic seropositives., Results: We found equivalent levels of anti-RBD-S antibodies in male and female patients and no age-related deficiencies even out to 93 years of age. The anti-RBD-S response was evident as little as 6 days after onset of symptoms and for at least 5 weeks after symptom onset. Anti-RBD-S IgG, IgM and IgA responses were simultaneously induced within 10 days after onset, with anti-RBD-S IgG sustained over a 5-week period. Anti-RBD-S antibodies strongly correlated with neutralising activity. Lastly, anti-RBD-S IgG responses were higher in symptomatic COVID-19 patients during acute infection compared with asymptomatic seropositive donors., Conclusion: Our results suggest that anti-RBD-S IgG reflect functional immune responses to SARS-CoV-2, but do not completely explain age- and sex-related disparities in COVID-19 fatalities., Competing Interests: The authors declare no conflict of interest., (© 2020 The Authors. Clinical & Translational Immunology published by John Wiley & Sons Australia, Ltd on behalf of Australian and New Zealand Society for Immunology, Inc.)

Background: The COVID-19 pandemic forced many health systems to proactively reduce care delivery to prepare for an expected surge in hospitalizations. There have been concerns that care deferral may have negative health effects, but it is hoped that telemedicine can provide a viable alternative., Objective: This study aimed to understand what type of health care services were being deferred during the COVID-19 pandemic lockdown, the role played by telemedicine to fill in care gaps, and changes in attitudes toward telemedicine., Methods: We conducted a cross-sectional analysis of survey responses from 1694 primary care patients in a mid-sized northeastern city. Our main outcomes were use of telemedicine and reports of care deferral during the shutdown., Results: Deferred care was widespread-48% (n=812) of respondents deferred care-but it was largely for preventive services, particularly dental and primary care, and did not cause concerns about negative health effects. In total, 30.2% (n=242) of those who delayed care were concerned about health effects, with needs centered around orthopedics and surgery. Telemedicine was viewed more positively than prior to the pandemic; it was seen as a viable option to deliver deferred care, particularly by respondents who were over 65 years of age, female, and college educated. Mental health services stood out for having high levels of deferred care., Conclusions: Temporary health system shutdowns will give rise to deferred care. However, much of the deferrals will be for preventive services. The effect of this on patient health can be moderated by prioritizing surgical and orthopedic services and delivering other services through telemedicine. Having telemedicine as an option is particularly crucial for mental health services., (©Adam Atherly, Eline Van Den Broek-Altenburg, Victoria Hart, Kelsey Gleason, Jan Carney. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2020.)

Background: Models of preferences in health services research (HSR) and Health Economics are often defined by readily available information, such as that captured in claims data and electronic health records. Yet many important questions about patient choices cannot be easily studied because of a lack of critical data elements. The objective of this review is to outline the advantages of using stated preferences (SP) data in health services research, and to outline how these methods can be used to evaluate choices that have not yet been offered or studied., Main Body: This article focuses on the application of DCE's to relevant policy and health system delivery questions currently relevant, particularly in the United States. DCE's may be helpful to collect data from patient or consumer data that we currently do not have. The article provides examples of research questions that have been answered using SP data collected with a DCE. It outlines how to construct a DCE and how to analyze the data. It also discusses the methodological challenges and emphasizes important considerations regarding the design and estimation methods. SP data can be adopted in situations where we would like to have consumer choice data, but we currently do not. These are often hypothetical situations to analyze the decision-making process of individuals. With SP data it is possible to analyze trade-offs patients make when choosing between treatment options where these hard to measure attributes are important., Conclusion: This paper emphasizes that a carefully designed DCE and appropriate estimation methods can open up a new world of data regarding trade-offs patients and providers in healthcare are willing to make. It updates previous "how to" guide for DCE's for health services researchers and health economists who are not familiar with these methods or have been unwilling to use them and updates previous description of these methods with timely examples.

This paper estimates the magnitude of switching costs in the Medicare Advantage program. Consumers are generally assumed to pick plans that provide the combination of benefits and premiums that maximize their individual utility. However, the plan choice literature has generally omitted prior choices from choice models. The analysis is based on five years of the Medicare Current Beneficiary Survey, a nationally representative longitudinal dataset. The MCBS data were combined with data on Medicare Advantage Part C plan benefits and premiums. Individual choices are modeled as a function of individual characteristics, plan characteristics and prior year plan choices using a mixed logit model. We found relatively high rates of switching between plans within insurer (20%), although less switching between insurers. Prior year plan choices were highly significant at both the contract and plan level. Premium was negative and significant. Loyalty (contract and plan), premium and plan structure were found to be heterogeneous in preferences. We found a statistically significant willingness to pay for a lower prescription drug deductible and lower copays. Switching costs were higher for sicker individuals. Switching costs between plans offered by the same insurer are far lower than switching costs between insurers; beneficiaries will switch plans if an alternative is perceived as $233 a month better than the current choice and switch insurers if the alternative is perceived as $944 better than the current plan/contract, on average. Premium elasticities would be 34% greater in magnitude if prior choices were irrelevant. We provide evidence that the state dependence is structural rather than spurious.