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Rxivist combines biology preprints from bioRxiv and medRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 161,200 papers from 673,214 authors.

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in category health policy

398 results found. For more information, click each entry to expand.

341: Who should get vaccinated first? An effective network information-driven priority vaccination strategy
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Posted 12 May 2021

Who should get vaccinated first? An effective network information-driven priority vaccination strategy
195 downloads medRxiv health policy

Dong Liu, Chi K. Tse, Rosa Ho Man Chan, Choujun Zhan

Approval of emergency use of the Novel Coronavirus Disease 2019 (COVID-19) vaccines in many countries has brought hope to ending the COVID-19 pandemic sooner. Considering the limited vaccine supply in the early stage of COVID-19 vaccination programs in most countries, a highly relevant question to ask is: who should get vaccinated first? In this article we propose a network information-driven vaccination strategy where a small number of people in a network (population) are categorized, according to a few key network properties, into priority groups. Using a network-based SEIR model for simulating the pandemic progression, the network information-driven vaccination strategy is compared with a random vaccination strategy. Results for both large-scale synthesized networks and real social networks have demonstrated that the network information-driven vaccination strategy can significantly reduce the cumulative number of infected individuals and lead to a more rapid containment of the pandemic. The results provide insight for policymakers in designing an effective early-stage vaccination plan.

342: How to quantify deaths averted derived from interrupted time-series analyses
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Posted 26 Mar 2021

How to quantify deaths averted derived from interrupted time-series analyses
193 downloads medRxiv health policy

Huan Jiang, Alexander Tran, Gerhard Gmel, Shannon Lange, Jakob Manthey, Robin Room, Pol Rovira, Mindaugas Stelemekas, Tadas Telksnys, Jurgen Rehm

Background Interrupted time series (ITS) are an important tool for determining whether alcohol control policies, as well as other policy interventions, are successful over and above secular trends or chance. Subsequent to estimating whether a policy has had an effect, quantifying the key outcomes, such as the number of prevented deaths, is of primary practical importance. The current paper compares the results of two different methodological approaches to quantify deaths averted using different two standard populations. Methods Time series methodologies were used to estimate the effect size in deaths averted of a substantial increase in excise taxation in Lithuania in 2017. We compare the impact of a) using ITS methodology vs. fitting the trend before the intervention to predict the following 12 months and comparing the predicted monthly estimates of deaths with the actual numbers; and b) adjusting the time series either using the World Health Organization standard or the age distribution of the Lithuania in the month before the intervention. The effect was estimated for by sex. Results The increase in excise taxation was associated with a substantial decrease in all-cause mortality in all models considered. ITS methodology and using the age-distribution of Lithuania were consistently associated with higher estimates of deaths averted. Although confidence and prediction intervals were highly overlapping, the point estimates differed substantially. The taxation increase was associated with 1,155 deaths averted in the year following the intervention (95% prediction interval: 729, 1,582), corresponding to 2.80% of all deaths in Lithuania in the respective year, for the model selected as best for planning policy interventions in Lithuania. Conclusions Fitting a time series model for the time until the intervention, and then comparing the predicted time points with the actual mortality, standardizing to country-specific weights, was chosen as the best way to derive practically relevant effect sizes.

343: Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing
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Posted 16 Sep 2021

Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing
193 downloads medRxiv health policy

Ibtihal Ferwana, Lav R. Varshney

Background Social capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking. Objective This study examines the relationship among public health behavior, vaccination, face masking, and physical distancing during COVID-19 pandemic and social capital indices in counties in the United States. Methods We used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate. Results We found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility. Conclusion Our results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits.

344: Understanding Convergence Between Non-Hispanic Black and White COVID-19 Mortality: A County-Level Approach
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Posted 17 Mar 2021

Understanding Convergence Between Non-Hispanic Black and White COVID-19 Mortality: A County-Level Approach
193 downloads medRxiv health policy

Ralph Ignacio Lawton, Kevin Z Zheng, Daniel Zheng, Erich S Huang

Background: Non Hispanic Black populations have suffered greater per capita COVID19 mortality at more than 1.5 times that of White populations. Previous work has established that, over time, rates of Black and White mortality have converged; however, some studies suggest that regional shifts in COVID19 prevalence may play a role in the relative change between racial groups. The study objective was to investigate changes in Black and White COVID19 mortality over time and uncover potential mechanisms driving these changes. Methods and Findings: Using county level COVID-19 mortality data stratified by race, we investigate the trajectory of non Hispanic Black mortality, White mortality, and the Black/White per capita mortality ratio from June 2020 to January 2021. Over this period, in the counties studied, cumulative mortality rose by 56.7% and 82.8% for Black and White populations respectively, resulting in a decrease in mortality ratio of 0.369 (23.8%). These trends persisted even when a county-level fixed-effects model was used to estimate changes over time within counties (controlling for all time invariant county level characteristics and removing the effects of changes in regional distribution of COVID19). Next, we leverage county level variation over time in COVID19 prevalence to show that the declines in the Black/White mortality ratio can be explained by changes in COVID19 prevalence. Finally, we study heterogeneity in the time trend, finding that convergence occurs most significantly in younger populations, areas with less dense populations, and outside of the Northeast. Limitations include suppressed data in counties with fewer than 10 deaths in a racial category, and the use of provisional COVID19 death data that may be incomplete. Conclusions: The results of this study suggest that convergence in Black/White mortality is not driven by county level characteristics or changes in the regional dispersion of COVID19, but instead by changes within counties. Further, declines in the Black/White mortality ratio appear strongly linked to changes in COVID19 prevalence, rather than a time specific effect. Further studies on changes in exposure by race over time, or on the vulnerability of individuals who died at different points in the pandemic, may provide crucial insight on mechanisms and strategies to further reduce COVID19 mortality disparities.

345: Knowledge, attitude and practice towards antibiotic use and resistance among the veterinarians in Bangladesh
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Posted 08 Jun 2021

Knowledge, attitude and practice towards antibiotic use and resistance among the veterinarians in Bangladesh
191 downloads medRxiv health policy

Md Samun Sarker, Iftekhar Ahmed, Shariful Islam, Ruhena Begum, Ayesha Ahmed, Fatema Akter Mahua, Md. Ehsanul Kabir, Nure Alam Siddiky, Mohammed A. Samad

Background The emergence of antimicrobial resistance (AMR) is growing public health concern around the world. When a number of studies have emphasized the Knowledge, Attitude and Practice (KAP) regarding antibiotic use and resistance in humans, little attention has been paid to the veterinary sector. The aim of this study was to understand the KAP towards antibiotic use and resistance among the veterinarians in Bangladesh. Methods A cross-sectional online based questionnaire survey was conducted from August to September 2020 among the registered veterinary practitioners. A self-administered Google form questionnaire consists of 46 questions on knowledge, attitude and practice regarding antibiotic use and their resistance. Results A total of 208 registered veterinarians participated in this study. 85.1% of the participants were male and 55% of the participants had a Masters degree. Around 50% of the veterinarians were poultry practitioners. All respondents were familiar with antimicrobials. 91.35% of the participants knew that antibiotics can not cure viral infections while 97.6% believed that frequent antibiotic prescription rendered them less effective. Participants claimed that only they are eligible to prescribe drugs for the treatment of animals. Of the total participants, 87.02% believed that a local antimicrobial guideline would be more effective than an international one while around 80% disagreed with adding antibiotics with feed/water as a growth promoter in livestock. However, gaps in practices were highlighted, suggesting training deficiencies. Conclusion The study for the first time conducted in Bangladesh dictates the future interventions like courses, workshops, and seminars on antibiotic usage and resistance are needed to ameliorate the awareness and change the behavior of veterinarians with regards to the rational use of antibiotics while also considering individual motivations and justifications for using antibiotics.

346: Mask Interventions in K12 Schools Can Also Reduce Community Transmission in Fall 2021
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Posted 15 Sep 2021

Mask Interventions in K12 Schools Can Also Reduce Community Transmission in Fall 2021
191 downloads medRxiv health policy

Jessica A. Mele, Erik Rosenstrom, Julie Ivy, Maria Mayorga, Mehul D. Patel, Julie L Swann

The dominance of the COVID-19 Delta variant has renewed questions about the impact of K12 school policies, including the role of masks, on disease burden. A recent study showed masks and testing could reduce infections in students, but failed to address the impact on the community, while another showed masking is critical to slow disease spread in communities, but did not consider school openings under Delta. We project the impact of school-masking on the community, which can inform policy decisions, and support healthcare system planning. Our findings indicate that the implementation of masking policies in school settings can reduce additional infections post-school opening by 23-36% for fully-open schools, with an additional 11-13% reduction for hybrid schooling, depending on mask quality and fit. Masking policies and hybrid schooling can also reduce peak hospitalization need by 71% and result in the fewest additional deaths post-school opening. We show that given the current vaccination rates within the community, the best option for children and the general population is to employ consistent high-quality masking, and use social distancing where possible.

347: The relationship between new PCR positive cases and going out in public during the COVID-19 epidemic in Japan
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Posted 08 Mar 2021

The relationship between new PCR positive cases and going out in public during the COVID-19 epidemic in Japan
189 downloads medRxiv health policy

Hiromichi Takahashi, Iori Terada, Takuya Higuchi, Daisuke Takada, Jung-ho Shin, Susumu Kunisawa, Yuichi Imanaka

Suppression of the first wave of COVID-19 in Japan is assumedly attributable to people's increased risk perception by acquiring information from the government and media reports. In this study, going out in public amidst the spread of COVID-19 infections was investigated by examining new polymerase chain reaction (PCR) positive cases of COVID-19 and its relationship to four indicators of people going out in public (the people flow, the index of web searches for going outside, the number of times people browse restaurants, and the number of hotel guests), from the Regional Economic and Social Analysis System (V-RESAS). Two waves of COVID-19 infections were examined with cross-correlation analysis. In the first wave, all four indicators of going out reacted oppositely with the change in new PCR positive cases, showing a lag period of -1 to +6 weeks. In the second wave, the same relationship was only observed for the index of web searches for going outside. These results suggest that going out in public could not be described by new PCR positive cases alone in the second wave, even though they could explain people going out to some extent in the first wave.

348: Ideology, policy decision-making and environmental impact in the face of the Coronavirus pandemic in the US
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Posted 05 Sep 2021

Ideology, policy decision-making and environmental impact in the face of the Coronavirus pandemic in the US
189 downloads medRxiv health policy

Juan Prieto-Rodriguez, Rafael Salas, Douglas Noonan, Francisco Tomas Cabeza-Martinez, Javier Ramos-Gutierrez

Covid-19 pandemic was a challenge for the health systems of many countries. It altered people's way of life and shocked the world economy. In the United States, political ideology has clashed with the fight against the pandemic. President Trump's denial prevailed despite the warnings from the WHO and scientists who alerted of the seriousness of the situation. Despite this, some state governments did not remain passive in the absence of federal government measures, and passed laws restricting mobility (lockdowns). Consequently, the political polarity was accentuated. On the one hand, the defenders of more severe public health measures and, on the other, the advocates of individual rights and freedom above any other consideration. In this study, we analyze whether political partisanship and the political ideology has influenced the way Covid-19 was handled at the outbreak. Specifically, we analyze by using a Diff-in-Diff model, whether the ideology of each state, measure at three levels, affected the decrease in the NO2 levels observed after the pandemic outbreak in the US. We distinguish three alternative post-Covid periods and results show that the State ideology has a robust negative impact on the NO2 levels. There is an important difference between Democratic and Republican states, not just in the scope and following-up of the mobility and activity restrictions, but also in the speed they implemented them.

349: The Impact of the Affordable Care Act on Colorectal Cancer Incidence and Mortality: the case of Kaiser Permanente of Northern California
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Posted 27 Oct 2020

The Impact of the Affordable Care Act on Colorectal Cancer Incidence and Mortality: the case of Kaiser Permanente of Northern California
184 downloads medRxiv health policy

Catherine Lee, Elizabeth H. Eldridge, Mary E. Reed, Jeffrey K. Lee, Lawrence H Kushi, Donna Spiegelman

BackgroundThe Patient Protection and Affordable Care Act (ACA) eliminated cost sharing for preventive services, including colorectal cancer (CRC) screening for individuals aged 50 to 75 with private health insurance. The present study is the first to examine the impact of the no-cost CRC screening due to the ACA on CRC incidence and mortality. MethodsWe modeled trends in CRC incidence and CRC-related mortality in an open cohort of 2,113,283 Kaiser Permanente Northern California (KPNC) members aged 50 years and older between 2003 and 2016 using an interrupted time series design. Individual-level data were analyzed at the month-level. Analyses were adjusted for age, race/ethnicity and sex. As a sensitivity analysis, we considered a controlled approach, with a comparison group of KPNC members covered by health plans with pre-ACA zero cost-sharing for CRC screening. ResultsA total of 178,582,512 person-months were used in the analysis of CRC incidence, of which 48% occurred in the period before the ACA was passed into law (1/1/2003-3/31/2010) and 52% after (4/1/2010-12/31/2016). In primary analyses, the model for CRC incidence indicated a drop in the trend coinciding with the passage of the ACA (change in level incidence rate ratio, IRR: 0.83, 95% CI: 0.77-0.90, p-value < 0.0001), followed by a decrease in trend (change in slope IRR: 0.97/year, 95% CI: 0.93-1.00, p-value = 0.05). Results for CRC-related mortality were similar. Our controlled results indicate that free screening due to the ACA was associated with greater improvements in CRC outcomes among members previously covered by health plans with out-of-pocket costs for screening, compared to health plans with zero cost sharing for screening before the ACA went into effect. ConclusionsWe found that free CRC screening due to the ACA was associated with a decrease in age-, race/ethnicity- and sex-adjusted CRC incidence and CRC-related mortality, after accounting for contemporaneous competing interventions. Furthermore, these findings were robust to the addition of a comparison group with zero cost sharing both pre- and post-ACA.

350: Inequalities and policy gaps in maternal health among Empowered Action Group (EAG) States in India: Evidence from Demographic Health Survey
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Posted 15 Jan 2021

Inequalities and policy gaps in maternal health among Empowered Action Group (EAG) States in India: Evidence from Demographic Health Survey
180 downloads medRxiv health policy

Manzoor Ahmad Malik, Saddaf Naaz Akhtar

Health inequality in maternal health is one of the serious challenges currently faced by public health experts. Maternal mortality in Empowered Action Group (EAG) states is highest and so are the health inequalities prevalent. We have made a comprehensive attempt to understand maternal health inequality and the risk factors concerning the EAG states in India, using recent data of Demography Health Survey of India (2015-16). Bi-variate, multivariate logistic regression, and concentration indices were used. The study has measured the four outcome variables of maternal health namely antenatal care of at least 4 visits, institutional delivery, contraceptive use, and unmet need. The study revealed that better maternal health is heavily concentrated among the richer households, while the negative concentration index of unmet need clearly reflected the greater demand for higher unmet need among the poor households in the EAG states of India. Challenges of inequalities still persist at large in maternal health, but to achieve better health these inequalities must be reduced. Since inequality mainly affects the poor households due to a lower level of income. Therefore, specific measures must be taken from a demand-side perspective in order to enhance their income and reduce the disparities in the EAG states of India.

351: Study on horizon-scanning with a focus on the development of AI-based medical products: citation network analysis
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Posted 01 Mar 2021

Study on horizon-scanning with a focus on the development of AI-based medical products: citation network analysis
178 downloads medRxiv health policy

Takuya Takata, Hajime Sasaki, Hiroko Yamano, Masashi Honma, Mayumi Shikano

ObjectivesHorizon-scanning for innovative technologies that might be applied to medical products and require new assessment approaches/regulations will help to prepare regulators, allowing earlier access to the product for patients and an improved benefit/risk ratio. In this study, we focused on the field of AI-based medical image analysis as a retrospective example of medical devices, where many products have recently been developed and applied. We proposed and validated horizon-scanning using citation network analysis and text mining for bibliographic information analysis. Methods and analysisResearch papers for citation network analysis which contain "convolutional*" OR "machine-learning" OR "deep-learning" were obtained from Science Citation Index Expanded (SCI-expanded) in the Web of Science (WoS). The citation network among those papers was converted into an unweighted network with papers as nodes and citation relationships as links. The network was then divided into clusters using the topological clustering method and the characteristics of each cluster were confirmed by extracting a summary of frequently cited academic papers, and the characteristic keywords, in the cluster. ResultsWe classified 119,553 publications obtained from SCI and grouped them into 36 clusters. Hence, it was possible to understand the academic landscape of AI applications. The key articles on AI-based medical image analysis were included in one or two clusters, suggesting that clusters specific to the technology were appropriately formed. Based on the average publication year of the constituent papers of each cluster, we tracked recent research trends. It was also suggested that significant research progress would be detected as a quick increase in constituent papers and the number of citations of hub papers in the cluster. ConclusionWe validated that citation network analysis applies to the horizon-scanning of innovative medical devices and demonstrated that AI-based electrocardiograms and electroencephalograms can lead to the development of innovative products. Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LICitation network analysis can provide an academic landscape in the investigated research field, based on the citation relationship of research papers and objective information, such as characteristic keywords and publication year. C_LIO_LIIt might be possible to detect possible significant research progress and the emergence of new research areas through analysis every several months. C_LIO_LIIt is important to confirm the opinions of experts in this area when evaluating the results of the analysis. C_LIO_LIInformation on patents and clinical trials for this analysis is currently unavailable. C_LI

352: Construction and application of a revised satisfaction index model for Chinese urban and rural residents basic medical insurance
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Posted 25 May 2020

Construction and application of a revised satisfaction index model for Chinese urban and rural residents basic medical insurance
178 downloads medRxiv health policy

Wenwei Cheng, Jin Cheng, Xiaofang Liu, Yanyan Wu, Weichu Sun, Xiaofang Yan, Liai Peng, Xiaoli Liu, Qi Wang, Mingming Luo, Tingting Sha, Jingcheng Shi, Fang Yang

Background: Quality is the most important factor of satisfaction However, the existing URRBMI index model lacks the decomposition of the connotation of perceived quality and cannot provide a reference for quality improvement and satisfaction promotion. Objective: This study aims to construct a Satisfaction Index Model for Chinese Urban and Rural Residents Basic Medical Insurance (SIM-URRBMI) with accurate and detailed measurement of perceived quality and give a feasible and scientific suggestion for URRBMI or insurance for other countries in the world. Methods: Based on the theoretical framework of The American Customer Satisfaction Index (ACSI), the connotation of perceived quality was refined by literature review and expert consultation to form a pool of alternative measurement variables.A three-stage randomized stratified cluster sampling was adopted to select the main decision makers for pupils' URRBMI in 8 primary schools from Changsha City. Both Classic Test Theory (CTT) and Item Response Theory (IRT) were used for selection of the measurement variables. The model's reliability and validity were tested using partial least square (PLS) related methods. Results: A total of 1909 respondents who had insurance for their children were investigated with the initial questionnaire. The revised SIM-URRBMI consists of 11 latent variables and 28 measurement variables with good reliability and validity. Among the three explanatory variables of public satisfaction, perceived quality had the largest total effect (0.737). The variable with greatest effect among the five first-order latent variables on perceived quality was quality of the medical insurance policy (0.472). Conclusions: The revised SIM-URRBMI consists of 11 latent variables and 28 measurement variables with good reliability and validity. It provides accurate assessment of perceived quality, which will greatly help performance improvement. Perceived quality is crucial to public satisfaction, especially, the most important aspects are policies regarding medical insurance reimbursement (basic coverage scope, coinsurance, deductible).

353: Evaluation of Clinical Threshold Policies for Cataract Surgery and the Regional Variation in Rates of Surgery
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Posted 26 Mar 2021

Evaluation of Clinical Threshold Policies for Cataract Surgery and the Regional Variation in Rates of Surgery
173 downloads medRxiv health policy

Jack Lisle, Naadir Ansari, Mohamad Jabir

ObjectivesPrevious work has suggested wide variation in policies for cataract surgery across different Commissioning Groups, but did not evaluate the potential impact of that variation on access. This study characterises the variation in rates of cataract surgery across England, reviews threshold policies against NICE guidance, and explores whether stringency of policy has a significant effect on access, to determine whether threshold policies are contributing to unequal access to surgery. It examines the effect of social deprivation and the impact of prior approval processes, where these are in place. MethodsInformation on number of surgeries undertaken and threshold policy were provided from 127 Clinical Commissioning Groups ("CCGs") through Freedom of Information request. The results were grouped by threshold stringency and analysed on an age group-corrected basis. ANOVA testing was performed to assess effect of policy stringency on regional rates of cataract surgery. ResultsIn the population over 60 years old, rates of cataract surgery vary across CCGs, from 1,980 to 6,427 per 100,000 population with a standard deviation (784.76) of 22% of the mean value, 3,598. There is variability in threshold policies for cataract surgery between CCGs: 33 had no policy, 45 utilised NICE-compliant policies, accessible on the basis of Quality of Life ("QoL") impact, and 39 required that Visual Acuity ("VA") threshold be exceeded, against current NICE guidance. Increasing restrictiveness of policy is associated with decreasing rates of cataract surgery (p<0.01) and accounts for 18% of the total variation seen. Variation in deprivation across CCGs contributes to 11% of the total deviation (p<0.01). There is little evidential basis to many policies, with 40% of policies not citing any supporting evidence. Prior approval processes represent 7.3% of total cataract activity but are not significantly associated with a reduced rate of cataract surgery (p=0.56). ConclusionOver two-thirds of CCGs continue to use threshold-based policies for access to cataract surgery, with increasing stringency of policy associated with decreasing cataract activity. A third of CCGs control access solely on the basis of visual acuity requirements, despite NICE guidance to the contrary. There is a need for consistency in policy across CCGs, and introduction of validated quality of life impact assessment tool to reduce variability of access.

354: The COVID-19 pandemic shifted the Veterans Affairs System toward being a payer and virtual care provider: is it sustainable?
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Posted 01 Jun 2021

The COVID-19 pandemic shifted the Veterans Affairs System toward being a payer and virtual care provider: is it sustainable?
171 downloads medRxiv health policy

Liam Rose, Linda Diem Tran, Steven M Asch, Anita Vashi

Objective: To examine how VA shifted care delivery methods one year into the pandemic. Study Setting: All encounters paid or provided by VA between January 1, 2019 and February 27, 2021. Study Design: We aggregated all VA paid or provided encounters and classified them into community (non-VA) acute and non-acute visits, VA acute and non-acute visits, and VA virtual visits. We then compared the number of encounters by week over time to pre-pandemic levels. Data Extraction Methods: Aggregation of administrative VA claims and health records. Principal Findings: VA has experienced a dramatic and persistent shift to providing virtual care and purchasing care from non-VA providers. Before the pandemic, a majority (63%) of VA care was provided in-person at a VA facility. One year into the pandemic, in-person care at VA's constituted just 33% of all visits. Most of the difference made up by large expansions of virtual care; total VA provided visits (in person and virtual) declined (4.9 million to 4.2 million) while total visits of all types declined only 3.5%. Community provided visits exceeded prepandemic levels (2.3 million to 2.9 million, +26%). Conclusion: Unlike private health care, VA has resumed in-person care slowly at its own facilities, and more rapidly in purchased care with different financial incentives a likely driver. The very large expansion of virtual care nearly made up the difference. With a widespread physical presence across the U.S., this has important implications for access to care and future allocation of medical personnel, facilities, and resources.

355: A reinforcement learning model to inform optimal decision paths for HIV elimination
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Posted 14 Jul 2021

A reinforcement learning model to inform optimal decision paths for HIV elimination
169 downloads medRxiv health policy

Seyedeh Nazanin khatami, Chaitra Gopalappa

The 'Ending the HIV Epidemic (EHE)' national plan aims to reduce annual HIV incidence in the United States from 38,000 in 2015 to 9,300 by 2025 and 3,300 by 2030. Diagnosis and treatment are two most effective interventions, and thus, identifying corresponding optimal combinations of testing and retention-in-care rates would help inform implementation of relevant programs. Considering the dynamic and stochastic complexity of the disease and the time dynamics of decision-making, solving for optimal combinations using commonly used methods of parametric optimization or exhaustive evaluation of pre-selected options are infeasible. Reinforcement learning (RL), an artificial intelligence method, is ideal; however, training RL algorithms and ensuring convergence to optimality are computationally challenging for large-scale stochastic problems. We evaluate its feasibility in the context of the EHE goal. We trained an RL algorithm to identify a 'sequence' of combinations of HIV-testing and retention-in-care rates at 5-year intervals over 2015-2070, which optimally leads towards HIV elimination. We defined optimality as a sequence that maximizes quality-adjusted-life-years lived and minimizes HIV-testing and care-and-treatment costs. We show that solving for testing and retention-in-care rates through appropriate reformulation using proxy decision-metrics overcomes the computational challenges of RL. We used a stochastic agent-based simulation to train the RL algorithm. As there is variability in support-programs needed to address barriers to care-access, we evaluated the sensitivity of optimal decisions to three cost-functions. The model suggests to scale-up retention-in-care programs to achieve and maintain high annual retention-rates while initiating with a high testing-frequency but relaxing it over a 10-year period as incidence decreases. Results were mainly robust to the uncertainty in costs. However, testing and retention-in-care alone did not achieve the 2030 EHE targets, suggesting the need for additional interventions. The results from the model demonstrated convergence. RL is suitable for evaluating phased public health decisions for infectious disease control.

356: Tobacco control policies and smoking cessation treatment utilization: a moderated mediation analysis
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Posted 20 Oct 2020

Tobacco control policies and smoking cessation treatment utilization: a moderated mediation analysis
166 downloads medRxiv health policy

Johannes Thrul, Kira E. Riehm, Joanna E. Cohen, G. Caleb Alexander, Jon S. Vernick, Ramin Mojtabai

BackgroundTobacco policies, including clean indoor air laws and cigarette taxes, increase smoking cessation in part by stimulating the use of cessation treatments. We explored whether the mediating effect of such treatments varies across socio-demographic groups. MethodsWe used data from 62,165 U.S. adult participants in the 2003 and 2010/11 Current Population Survey-Tobacco Use Supplement (CPS-TUS) who reported smoking cigarettes during the past year. Building on prior structural equation models used to quantify the degree to which smoking cessation treatments (prescription medications, nicotine replacement therapy, counselling/support groups, quitlines, and internet resources) mediated the association between clean indoor air laws, cigarette excise taxes, and recent smoking cessation, we added selected moderators to each model to investigate whether mediation effects varied by sex, race/ethnicity, education, income, and health insurance status. ResultsFor clean indoor air laws, the mediating effect of prescription medication and nicotine replacement therapies varied significantly between racial/ethnic, age, and education groups in 2003. However, none of these moderation effects remained significant in 2010/11. For cigarette excise taxes in 2010/2011, the mediating effect of counseling was stronger in older adults; whereas, the mediating effect of prescription medications tended to be stronger in younger adults. No other moderator reached statistical significance. Smoking cessation treatments did not mediate the effect of taxes on smoking cessation in 2003 and were not included in these analyses. ConclusionsSociodemographic differences in how smoking cessation treatment use mediates between clean indoor air laws and smoking cessation have decreased from 2003 to 2010/11. In most cases, policies appear to stimulate smoking cessation treatment use similarly across varied sociodemographic groups.

357: What do we know about violence against women in pandemic times? Insights based on search trends
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Posted 29 May 2021

What do we know about violence against women in pandemic times? Insights based on search trends
165 downloads medRxiv health policy

Rafaela Ferreira Guatimosim, Ana Luiza Silva Teles, Fabiano Franca Loureiro, Antonio Geraldo da Silva, Debora Marques de Miranda, Leandro Fernandes Malloy-Diniz

Abstract: Purpose: This short communication aims to assess the situation of domestic violence against women in Brazil during social isolation due to the COVID-19 pandemic. Methods: We extracted data from Google Trends showing the magnitude of searches on the topics domestic violence and complaint and then compared with the data of the complaint reports of the Brazilian Forum for Public Safety (FBSP). Results: Searches on Google containing those terms have increased while the complaints reports against domestic violence have decreased. Conclusion: The growth of searches about domestic violence and domestic violence complaints indicates the possibility of a real rise in this type of violence in Brazil.

358: Economic Impact Payment, Human Mobility and the COVID-19 Mitigation in the United States
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Posted 19 May 2021

Economic Impact Payment, Human Mobility and the COVID-19 Mitigation in the United States
164 downloads medRxiv health policy

Ruohao Zhang

This paper studies the relationship between the individual's income and COVID-19 mitigation effort contribution. The paper suggests that in addition to the government mandatory policies, the income compensation policy is an alternative government instrument that helps increase the individual and social aggregate COVID-19 mitigation effort. I empirically test the effect of the income compensation policy by utilizing the United States economic impact payment (EIP) in April 2020 as a quasi-natural experiment, and use the cellphone GPS measured human mobility data as the outcome indicator of the COVID-19 mitigation effort. I find that by receiving EIP, individuals on average significantly increase median home dwell time by 3%-5% (about 26-45 minutes). This paper highlights an unintended effect of EIP: in addition to providing economic assistance, EIP also helps mitigate the COVID-19 virus transmission.

359: The effect of smaller classes on infection-related school absence: Evidence from the Project STAR randomized controlled trial
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Posted 18 May 2021

The effect of smaller classes on infection-related school absence: Evidence from the Project STAR randomized controlled trial
163 downloads medRxiv health policy

Paul T von Hippel

In an effort to reduce viral transmission, many schools are planning to reduce class size if they have not reduced it already. Yet the effect of class size on transmission is unknown. To determine whether smaller classes reduce school absence, especially when community disease prevalence is high, we merge data from the Project STAR randomized class size trial with influenza and pneumonia data from the 122 Cities Mortality Reporting System on deaths from pneumonia and influenza. Project STAR was a block-randomized trial that followed 10,816 Tennessee schoolchildren from kindergarten in 1985-86 through third grade in 1988-89. Children were assigned at random to small classes (13 to 17 students), regular-sized classes (22 to 26 students), and regular-sized class with a teachers aide. Mixed effects regression showed that small classes reduced absence, but not necessarily by reducing infection. In particular, small classes reduced absence by 0.43 days/year (95% CI -0.06 to -0.80, p<0.05), but had no significant interaction with pneumonia and influenza mortality (95% CI -0.27 to +0.30, p>0.90). Small classes, by themselves, may not suffice to reduce the spread of viruses.

360: How to incentivise doctor attendance in Bangladesh: a latent class analysis of a discrete choice experiment
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Posted 22 Mar 2021

How to incentivise doctor attendance in Bangladesh: a latent class analysis of a discrete choice experiment
163 downloads medRxiv health policy

Blake Angell, Mushtaq Khan, Mir Raihanul Islam, Kate Mandeville, Nahitun Naher, Eleanor Hutchinson, Martin McKee, Syed Masud Ahmed, Dina Balabanova

Objective: To elicit preferences of doctors over interventions to address doctor absenteeism in rural facilities in Bangladesh, a pervasive form of corruption across the country. Methods: We conducted a discrete choice experiment with 308 doctors across four tertiary hospitals in Dhaka, Bangladesh. Four attributes of rural postings were included based on a literature review, qualitative research and a consensus-building workshop with policymakers and key health-system stakeholders: relationship with the community, security measures, attendance-based policies, and incentive payments. Respondent choices were analysed with mixed multinomial logistic and latent class models and were used to simulate the likely uptake of jobs under different policy packages. Results: All attributes significantly impacted doctor choices (p<0.01). Doctors strongly preferred jobs at rural facilities where there was a supportive relationship with the community ({beta}=0.93), considered good attendance in education and training (0.77) or promotion decisions (0.67), with functional security (0.67) and higher incentive payments (0.5 per 10% increase of base salary). Jobs with disciplinary action for poor attendance were disliked by respondents (-.63). Latent class analysis identified three groups of doctors that differed in their uptake of jobs. Scenario modelling identified intervention packages that differentially impacted doctor behaviour and combinations that could feasibly improve doctor attendance. Conclusion: Bangladeshi doctors have strong but varied preferences over interventions to overcome absenteeism. Some were unresponsive to intervention but a substantial number appear amenable to change. Designing policy packages that consider these differences and target particular doctors could begin to generate sustainable solutions to doctor absenteeism in rural Bangladesh.

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