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in category health policy

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

321: Analysis of Data Use Registers published by health data custodians in the UK
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Posted 26 May 2021

Analysis of Data Use Registers published by health data custodians in the UK
154 downloads medRxiv health policy

Nada Karrar, Shahriar Kabir Khan, Sinduja Manohar, Paola Quattroni, David Seymour, Susheel Varma

Transparency of how health and social care data is used by researchers is crucial to building public trust. We define 'data use registers' as a public record of data an organisation has shared with other individuals or organisations for the purpose of research, innovation and service evaluation, and are used by some data custodians across the United Kingdom to increase transparency of data use. They typically contain information about the type of data being shared, the purpose, date of approval and name of organisation or individual using (or receiving) the data. However, information published lacks standardisation across organisations. Registers do not yet have a consistent approach and are often incomplete, updated infrequently and not accessible to the public. In this paper, we present an empirical analysis of existing data use registers in the UK and investigate accessibility, content, format and frequency of updates across health data organisations. This analysis will inform future recommendations for a data use register standard that will be published by the UK Health Data Research Alliance.

322: Opioid Prescribing Mediating State Policy Intervention Effects on Drug Overdose Mortality
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Posted 16 May 2021

Opioid Prescribing Mediating State Policy Intervention Effects on Drug Overdose Mortality
154 downloads medRxiv health policy

Jacob James Rich, Robert Capodilupo

The Centers for Disease Control and Prevention reported 70 630 drug overdose deaths for 2019 in the United States, 70.5% of which were opioid-related. Preliminary estimates now warn that drug overdose deaths likely surpassed 86 000 during 2020. Despite a 57.4% decrease in opioid prescribing since a peak in 2012, the opioid death rate has increased 105.8% through 2019, as the share of those deaths involving fentanyl increased from 16.4% to 72.9%. This letter seeks to determine whether the opioid prescribing and mortality paradox is robust to accepted methods of causal policy analysis and if prescribing rates mediate the effects of policy interventions on overdose deaths. Using loge-loge ordinary least squares with three different specifications as sensitivity analyses for all 50 states and Washington, DC for the period 2001-2019, the elasticities from the regressions with all control variables report operational prescription drug monitoring programs (PDMPs) reduce prescribing rates 8.7%, while mandatory PDMPs increase death rates from opioids 16.6%, heroin and fentanyl 19.0%, cocaine 17.3% and all drugs 10.5%. There is also weak evidence that recreational marijuana laws reduce prescribing, increases in prescribing increase pain reliever deaths, pill mill laws increase cocaine deaths, and medical marijuana laws increase total overdose deaths, with demographic variables suggesting states with more male, less non-Hispanic white, and older citizens experience more overdoses. Weak mediation effects were observed for pain reliever, cocaine, and illicit opioid deaths, while broad reductions in prescribing have failed to reduce opioid overdoses.

323: 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
153 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.

324: Youth-oriented packaging and the demand for e-liquids: Evidence from data scraped from Amazon in the United Kingdom
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Posted 15 Mar 2021

Youth-oriented packaging and the demand for e-liquids: Evidence from data scraped from Amazon in the United Kingdom
152 downloads medRxiv health policy

Abdelaziz Lawani, Georgette Owusu-Amankwah, Anna-Liisa M Ihuhwa

To address the threat e-cigarettes poses to public health, especially among youths, the Food and Drug Administration (FDA) issued a policy in 2020 that regulates the sale and distribution of e-cigarettes with fruit and mint flavors. Such flavors are alleged to lure youth into smoking and can increase the likelihood for addiction to other drugs. However, this regulation does not address packaging that can have a similar effect on the demand for e-cigarettes products. Indeed, certain e-liquids use youth-oriented (kiddish, cartoonish, and colorful) packaging which are attractive to youth but may also induce a no-harm perception among e-liquids users. In this paper, we examine the impact of the youth-oriented packaging on e-liquid sales. Using data scraped from Amazon, the results of our analysis reveal that youth-oriented packaging increases the sale of e-liquids. In addition, the demand for e-liquids is inelastic and the percentage of propylene glycol (PG), the rating, and the sentiment in the online reviews left by previous buyers also influence the sale of e-liquids. This research suggests that besides fruit and mint flavors, the policy goal of reducing use among youth should also include packaging. The analysis finds that taxation policies to raise prices of e-liquids will not affect appreciably the demand for e-liquids. Policies for e-liquids control should focus on designing packaging that reduces the no- or low-risk perception.

325: 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
151 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.

326: COVID-19 Vaccine Coverage Index: Identifying barriers to COVID-19 vaccine uptake across U.S. counties
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Posted 22 Jun 2021

COVID-19 Vaccine Coverage Index: Identifying barriers to COVID-19 vaccine uptake across U.S. counties
143 downloads medRxiv health policy

Anubhuti Mishra, Staci Sutermaster, Peter Smittenaar, Nicholas Stewart, Sema Sgaier

Importance: The United States is in a race against time to vaccinate its population to contain the COVID-19 pandemic. With limited resources, a proactive, targeted effort is needed to reach widespread community immunity. Objective: Identify county-level barriers to achieving rapid COVID-19 vaccine coverage and validate the index against vaccine rollout data. Design: Ecological study Setting: Population-based Participants: Longitudinal COVID-19 vaccination coverage data for 50 states and the District of Columbia and 3118 counties from January 12 through May 25, 2021. Exposure(s): The COVID-19 Vaccine Coverage index (CVAC) ranks states and counties on barriers to coverage through 28 indicators across 5 themes: historic undervaccination, sociodemographic barriers, resource-constrained health system, healthcare accessibility barriers, and irregular care-seeking behaviors. A score of 0 indicates the lowest level of concern, whereas a score of 1 indicates the highest level of concern. Main Outcome(s) and Measure(s): State-level vaccine administrations from January 12 through May 25, 2021, provided by the Centers for Disease Control and Prevention (CDC) and Our World In Data. County-level vaccine coverage as of May 25, 2021, provided by the CDC. Results: As of May 25, 2021, the CVAC strongly correlated with the percentage of population fully vaccinated against COVID-19 by county (r = -0.39, p=2.2x10-16) and state (r=-0.77, p=4.9x10-11). Low-concern states and counties have fully vaccinated 26.5% [t=6.8, p=1.7x10-7] and 26% (t=22.0, p=2.2x10-16) more people, respectively, compared to their high-concern counterparts. This vaccination gap is at its highest point since the start of vaccination and continues to grow. Higher concern on each of the five themes predicts a lower rate of vaccination at the county level (all p<.001). We identify five types of counties with distinct barrier profiles. Conclusions and Relevance: The CVAC measures underlying barriers to vaccination and is strongly associated with the speed of rollout. As the coverage gap between high- and low-concern regions continues to grow, the CVAC can inform a precision public health response targeted to underlying barriers.

327: 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
142 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.

328: 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
141 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.

329: 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
139 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.

330: Capturing Global, Predicting Local for Controlling Antimicrobial Resistance: a retrospective multivariable analysis
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Posted 27 May 2021

Capturing Global, Predicting Local for Controlling Antimicrobial Resistance: a retrospective multivariable analysis
138 downloads medRxiv health policy

Raghav Awasthi, Samprati Agrawal, Vaidehi Rakholia, Lovedeep Singh Dhingra, Aditya Nagori, Tavpritesh Sethi

Background: Antimicrobial resistance (AMR) is a complex multifactorial outcome of health, socio-economic and geopolitical factors. Therefore, tailored solutions for mitigation strategies could be more effective in dealing with this challenge. Knowledge-synthesis and actionable models learned upon large datasets are critical in order to diffuse the risk of entering into a post-antimicrobial era. Objective: This work is focused on learning Global determinants of AMR and predicting susceptibility of antibiotics at isolate level (Local) for WHO (world health organization) declared critically important pathogens Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii, Enterobacter cloacae, Staphylococcus aureus. Methods: In this study, we used longitudinal data (2004-2017) of AMR having 633820 isolates from 72 Middle and High-income countries. We integrated the Global burden of disease (GBD), Governance (WGI), and Finance data sets in order to find the unbiased and actionable determinants of AMR. We chose a Bayesian Decision Network (BDN) approach within the causal modeling framework to quantify determinants of AMR. Finally Integrating Bayesian networks with classical machine learning approaches lead to effective modeling of the level of AMR. Results: From MAR (Multiple Antibiotic Resistance) scores, we found that developing countries are at higher risk of AMR compared to developed countries, for all the critically important pathogens. Also, Principal Components Analysis(PCA) revealed that governance, finance, and disease burden variables have a strong association with AMR. We further quantified the impact of determinants in a probabilistic way and observed that heath system access and government effectiveness are strong actionable factors in reducing AMR, which was in turn confirmed by what-if analysis. Finally, our supervised machine learning models have shown decent performance, with the highest on Staphylococcus aureus. For Staphylococcus aureus, our model predicted susceptibility to Ceftaroline and Oxacillin with the highest AUROC, 0.94 and 0.89 respectively.

331: School start times and academic achievement - a systematic review on grades and test scores
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Posted 20 May 2021

School start times and academic achievement - a systematic review on grades and test scores
138 downloads medRxiv health policy

Anna M Biller, Karin Meissner, Eva C Winnebeck, Giulia Zerbini

School start times have been at the centre of many scientific and political debates given the accumulating evidence that bell times are generally too early, and thus lead to an epidemic of sleep restriction in the student population. Recent media attention has conveyed the message that later school starts not only improve sleep but also result in better academic achievement. Several studies have been recently published on this topic requiring a comprehensive review of the results to clarify the relationship between later school start times and academic achievement to inform the general public and policy makers. To this end, we conducted a systematic review of the current literature on school starting times and academic achievement in middle and high school students, considering grades and standardised test scores as achievement measures. We followed the PRISMA guidelines for searching, including, and reporting relevant literature and identified 21 studies for detailed analysis. Evidence quality of included studies was assessed with a pre-defined risk of bias assessment using modified items from the GRADE scheme and ROBINS-I tool. About half of the reviewed studies reported no (positive or negative) effect of delaying school times on grades and test scores, while the other half reported either mixed or positive results. Given the strong heterogeneity of included studies, we grouped them according to various characteristics, such as academic outcomes, dose of delay, evidence quality, or study design to identify potential hidden effects. Despite this, we could not identify any generalisable effect beyond single studies as to whether delaying school times has clear beneficial effects on academic performance. Given that grades and scores determine future career trajectories and predict future success, the question whether school start times contribute to academic achievement is of great interest for the general public and needs to be further clarified. Mechanistically, it is very likely that improved sleep leads to or mediates improved cognitive performance and learning, but definitive conclusions on whether this also translates into better grades and scores across all students requires better evidence at this stage. Importantly, this does not preclude other positive outcomes of later start times such as improved sleep (quality), motivation or learning but draws attention on current gaps and shortcomings. To this end, we also highlight critical methodological aspects and provide suggestions to increase the evidence-level and to guide the direction of research in future studies.

332: 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?
137 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.

333: 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
134 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.

334: 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
134 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.

335: 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
133 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.

336: 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
132 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.

337: 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
131 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

338: Determinants of disease prevalence and antibiotic consumption for children under five in Nepal: analysis and modelling of demographic health survey data from 2006 to 2016
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Posted 10 Jul 2020

Determinants of disease prevalence and antibiotic consumption for children under five in Nepal: analysis and modelling of demographic health survey data from 2006 to 2016
129 downloads medRxiv health policy

Charlotte Zheng, Abilasha Karkey, Tianyi Wang, Gerald Makuka, H. Rogier van Doorn, Sonia Lewycka

Abstract Objectives Our aim was to examine the geographic, socio-economic and behavioural factors associated with disease and antibiotic consumption in Nepal from 2006 to 2016; as well as explore healthcare seeking patterns and the source of antibiotics. Methods Cross-sectional data on children under five in households from Nepal was extracted from the 2006, 2011 and 2016 Demographic Health Surveys (DHS). Univariate and multivariate analyses were carried out to assess the association of disease prevalence and antibiotic use with age, sex, ecological zone, urban/rural location, wealth index, maternal smoking, use of clean fuel, sanitation, nutrition, access to healthcare and vaccinations. Results Prevalence of fever, acute respiratory infection (ARI) and diarrhoea decreased from 2006 to 2016, while the proportion using antibiotics increased. Wealth, use of clean fuel, improved toilet sanitation, nutrition and access to healthcare were associated with reduced rates of disease. Those in the highest wealth index are starting to use less antibiotics and antibiotic consumption in rural areas has surpassed urban regions over time. Health-seeking from the private sector has overtaken government facilities since 2006 with source of antibiotics mainly originating from pharmacies and private hospitals. Adherence to WHO recommended antibiotics has reduced over time. Conclusions With rising wealth, there has been decline in disease prevalence but increase in antibiotic use with greater access to unregulated sources. Understanding antibiotic use and identifying associated behavioural and socio-economic factors could help to inform methods in reducing inappropriate antibiotic use whilst ensuring access to those who need them.

339: Extraordinary attention, ordinary neglect: the high cost of disaster preparedness and response
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Posted 28 Oct 2020

Extraordinary attention, ordinary neglect: the high cost of disaster preparedness and response
128 downloads medRxiv health policy

Robert A. Hahn

BackgroundFunds allocated to disaster preparedness and response in the U.S. have grown rapidly in recent decades. This analysis examines the ratio of cost per outcome of public health events classified as disasters and those not classified as disasters, e.g., smoking-related morbidity and mortality. MethodsMortality is taken as an outcome metric; the validity of this measure is assessed by examination of ratios of tangible and intangible costs of disaster and non-disaster outcomes to mortality from two conditions, using available data. The relative allocation of CDC funding to disaster and non-disaster events is assumed to conservatively represent the U.S. overall relative funding allocation. ResultsNon-disaster deaths are 2,500 more likely than disaster deaths; we allocate 370 times more funding per disaster death than we do per non-disaster death. ConclusionThe rationality of this implicit decision be reconsidered.

340: 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
120 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.

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