Instructions-Assignment SAHIE & HCUP UMBC (3)

Health Economics: ECON 467-01 (13351) & ECON 652-01(13431) Aug 27-Dec 8 Dept. of Economics, UMBC/Fall 2020 Step-by-step weekly Assignments to build up a paper Eight Individual Assignments each 4 points: Step1- Sep. 13-Data analyses of SAHIE Interactive Data Tool (4%) Step 2-Sep 27-Abstract: Formulate a public health economic research question using PICO elements and SAHIE data (4%) Step 3-Oct. 11-Send the First Draft of the paper to your reviewer (4%) Step 4-Oct. 25-Reviewer send constructive feedback to the authors (4%) Step 5-Nov. 8-Send the First Draft of the paper to the instructor (4%) Step 6-Nov. 29-Send Final Draft of the paper to the reviewer (4%) Step 7-Dec. 6-Reviewer send final constructive feedback to the authors (4%) Step 8-Dec. 13-Send the Final revised version of the Draft will be sent to the instructor (4%) 1

Instructions for Step1- Sep. 13-Data analyses of SAHIE Interactive Data Tool (4%) The Analyses in Health Disparities: Gaps in Access, Quality, and Affordability of Medical Care 1. These assignments' primary objective is to show the disparity in access to care and hospitalization utilization by different sociodemographic characteristics such as: by State, county, race, age, gender, income, etc. First, choose your key variables, and second, let SAHIE and HCUP create your tables and graphs to show disparities, and third, write a few paragraphs to explain your data analysis, findings. 2. Please choose similar regions and years to compare for both datasets SAHIE and HCUP. I-The Small Area Health Insurance Estimates ( SAHIE) shows the disparity in access to care by region, age, race, sex, income over the years (e.g., before and after the affordable care act, 2009 and 2017). Interactive Data Tool https://www.census.gov/data-tools/demo/sahie/#/ Data Tool : https://www.census.gov/programs-surveys/sahie/data/datasets.html II-Healthcare Cost and Utilization Project ( HCUP ), shows the disparity in healthcare utilization (hospitalization and length of stay in hospital) by regions , type of Insurance, age, sex, income , type of disease (e.g., Opioid) in two years between 2008 – 2017 (before and after ACA). HCUP Fast Stats - State Trends in Inpatient Stays by Payer https://www.hcup-us.ahrq.gov/faststats/StatePayerServlet? state1=MD&type1=PY00&combo1=s&state2=OH&type2=PY00&combo2=s&expansionInfoStat e=hide&dataTablesState=hide&definitionsState=hide&exportState=hide III-HCUP Fast Stats - Opioid-Related Hospital Use https :// www . hcup -us. ahrq .gov/ faststats / OpioidUseServlet ?radio- 3=on&location1=US&characteristic1=01&setting1=ED&location2=MD&characteristic2=01&setting2=I P& expansionInfoState =hide& dataTablesState =hide& definitionsState =hide& exportState =hide HCUP User Support (HCUP-US): www.hcup-us.ahrq.gov HCUPnet: https://hcupnet.ahrq.gov/#setup HCUP Statistical Briefs: www.hcup-us.ahrq.gov/reports/statbriefs/statbriefs.jsp Center on Budget and Policy Priorities . Chart Boo k: The Far-Reaching Benefits of the Affordable Care Act’s Medicaid Expansion, October 2, 2018 https://www.cbpp.org/research/health/chart-book-the-far-reaching-benefits-of-the-affordable-care-acts- medicaid 3. You need to submit your assignment on Bb in word document using SafeAssign Here are some sample questions to explore in your short essay. But you are not limited to explore only the following questions. a. Use SAHIE Interactive Data Tool to compare the number of insured/Uninsured in two States or two counties (e.g., Baltimore and Montgomery counties in Maryland) in the years 2006 and 2017. b. Download your table in an excel spreadsheet and make a nice table in the word document. c. In a brief essay (1-2 pages), please discuss what region had the highest uninsured rates than the other areas In 2006 and 2017? d. What county in your selected State has the highest rate of uninsured in 2006 and 2017? Check to see if this is related to their income level or age? e. Compare your tables with the charts from “ Center on Budget and Policy Priorities ” and discuss whether your selected states are one of the those with Medicaid Expansion or not. f. Write a one-page summary of your comparison by referring to the tables and graphs . Detailed information about Step1- Sep. 13-Data analyses of SAHIE Interactive Data Tool (4%) 2

The Analyses in Health Disparities: Gaps in Access, Quality, and Affordability of Medical Care A sample of work from my ex-student: Sean Fleming Disparities in Health Insurance Coverage: Maryland and Virginia, 2006-2017 Objective : To show the disparity in access to healthcare between Maryland and Virginia in 2006 and 2017. In 2006, 15.6% of Maryland's population was uninsured, which was very close to Virginia with 15.5%. By 2017, after the Affordable Care Act (ACA), both states experienced decreases in the percent of uninsured populations. Still, there was a more considerable drop observed in Maryland. The percent of uninsured Maryland residents fell by more than half over this period to 7.0% in 2017. In contrast, the percent of uninsured Virginia residents shrank to 10.2% in 2017. Health Insurance Coverage by Race In 2006, 10.7% of Marylanders and 11.7% of Virginians of the White non-Hispanic race were uninsured. By 2017, 4.3% of Marylanders and 7.6% of Virginians of the White non-Hispanic race were uninsured. In 2006, 19.2% of Marylanders and 19.3% of Virginians of Black non-Hispanic race were uninsured. By 2017, 6.8% of Marylanders and 11.6% of Virginians of Black non-Hispanic race were uninsured. This clearly shows that the percentage of Black non-Hispanic without insurance in Virginia is becoming more extensive than in Maryland (11.6% vs. 6.8%). In 2006, 37.8% of Marylanders and 37.3% of Virginians of Hispanic origin were uninsured. By 2017, 20.4% of Marylanders and 23.5% of Virginians of Hispanic origin were uninsured. 4

Step 2-Sep 27-Abstract: Formulate a public health economic research question using PICO elements and SAHIE data (4%) Please check the resources for "How to Formulate your Research Question in Public Health?" https://umbc.box.com/s/ojsku4i9i1e5bc64xdyo0oz6hxf71k3f https://umbc.app.box.com/file/658215500561?s=2bvaa2p2jy2b995cx5b0skz32i16oyhd According to the Guides for Authors of the "Journal of Health Economics", "A concise and factual abstract is required. The abstract should state the purpose of the research, the principal results, and major conclusions briefly. An abstract is often presented separately from the article, so it must be able to stand alone. For this reason, References should be avoided, but if essential, then cite the author(s) and year(s). Also, non-standard or uncommon abbreviations should be avoided, but if essential, they must be defined at their first mention in the abstract itself." Available at: https://www.elsevier.com/wps/find/journaldescription.cws_home/505560?generatepdf=true Example for step 2: Opioid-related Hospitalizations and Emergency Department Visits among American by Sociodemographic Characteristics, during 2007 and 2018 Abstract Background : The opioid epidemic in the United States receives significant attention at both the Federal and State levels. Twenty-three million American adults suffer from addiction. In 2015, over 33,000 Americans died from an overdose of opioids, and that increased to 64,000 in 2016 and 72,000 deaths in 2017. The national rate of opioid-related inpatient stays and emergency department (ED) visits increased by 64.1% and 99.4%, respectively, between 2005 and 2014. From 2011 to 2017, the opioid epidemic cost is estimated to exceed $1 trillion and is projected to be increased to an additional $500 billion by 2020 (Addiction Center, 2019). Objective : The study explores the regional and Sociodemographic differences that explain the variation of opioid-related inpatient stays, ED visits and overdose death between 2007 and 2018. Methods: We used the Secondary data analysis from Small Area Health Insurance Estimates (SAHIE) and Healthcare Cost and Utilization Project (HCUP) database from 2007 to 2018. The target outcomes are geographic rates of opioid-related hospitalizations, ED rates of opioid use, and overdose death by sociodemographic characteristics, the region of the State, and health insurance coverage status. Results: The state-level rates of opioid-related inpatients stays are highest in New York, District of Columbia, Maryland, Massachusetts, Rhode Island, West Virginia, and Connecticut compared to the other states. However, those states with the highest rate of Opioid use are not necessarily having the highest quality of hospitalization and mortality. In all six states, males' ratio to females' inpatient rates is higher than in the other states. It seems that the quality of male to female inpatient rates are higher in these six states with generous Medicaid policy, and Medicaid is driving the gender differences in inpatient rate in Opioids (e.g., comparing with Colorado). Policy Implications: Rates of opioid-related hospitalizations, EDs, and death are varied geographically, by states, gender, age, and type of insurance. More research is needed to examine factors that impact regional variation and what influences the concurrent use of opioids by sociodemographic characteristics. Word Count: 327 5

Ideas for Reviewers to provide constructive feedback to the author! Reviewers need to use track change to provide constructive feedback for the authors! Below please find a sample of reviewers' comments to a submitted paper to the World Health & Population. Thank you for agreeing to review the attached manuscript. Some background on the journal: World Health and Population ( WHP ) provides a forum for researchers and policymakers worldwide to publish original research, reviews, and commentaries on health- and population-related topics. WHP encourages the conduct and dissemination of applied research and policy analysis from diverse international settings. It is the goal of WHP to explore ideas, share best practices, and enable excellence in healthcare worldwide through publishing contributions by researchers, policymakers, and practitioners from these settings. Submissions of particular interest include evaluations of health and population interventions, which allow researchers, policymakers, and practitioners to gain insights further to promote the health and welfare of served populations. Our preferred length for research papers is approximately 3,500 words (12-15 typewritten, double-spaced pages) inclusive of 4 figures and 4 tables . Submissions must include an abstract of 150 words or less. Pages should be numbered consecutively throughout. Manuscript Title: …… Reviewer: ……………. Date: ___ ............. Reviewer's Recommendation for Editors (Please bold/underline your recommendation) Accept as is with minor editing, Accept with minor revisions. Revise/Resubmit Reject ________________________________________________________________________ Reviewer's comments for editors ONLY 7

Publication Priority (Please bold/underline your recommendation) Please rate the publication priority from 1 (routine) to 5 (fast track): 1 2 3 4 5 Routine Fast Track ______________________________________________________________ Rating (Please bold/underline your recommendation) Please rate the paper from 1 (poor) to 5 (superior) on the following measures: Overall Quality 1 2 3 4 5 Originality 1 2 3 4 5 Data 1 2 3 4 5 N/A Analysis/Methods 1 2 3 4 5 N/A Conclusions 1 2 3 4 5 Balance 1 2 3 4 5 Writing 1 2 3 4 5 Policy Relevance 1 2 3 4 5 ________________________________________________________________________ Reviewer's comments for author(s) I would like to thank the author for their submission. I agree with the author that there is a strong need to strengthen XXXXX care services in Country X and improved organization in itself would go a long way to improving patient care. However, there were some difficulties with the paper in a number of aspects which led to the recommendation to reject it for publication in this journal: The paper does not have clearly designated sections or flow, so it is difficult to understand how the statements fit together to form a cohesive paper. It was not clear what the final recommendations were in terms of: new policy, new organization, new referral pathways, make-up of the XXXXX team It was not possible to determine a clear call to action for the reader based on these recommendations I have a working knowledge of XXXXX care and organization in Country X and around Sao Paulo and the working of the SUS system yet I found the article difficult to interpret. I believe the general international audience of this journal will struggle to understand and apply the message. Unfortunately, in its current format, I do not feel the paper is understandable or relevant to this journal's broad international audience. I have used track change in the attached file to provide more constructive feedback for the author. I hope the authors persevere and revise the document and submit it again to a more appropriate journal. There is a considerable need for advocacy for improved organization of XXXXX care services in Country X . 8

16. Maine Adopted and Implemented Implemented expansion on 1/10/2019 17. Maryland Adopted and Implemented Implemented expansion on 1/1/2014 18. Massachusetts Adopted and Implemented Implemented expansion on 1/1/2014 19. Michigan Adopted and Implemented Implemented expansion on 4/1/2014 20. Minnesota Adopted and Implemented Implemented expansion on 1/1/2014 21. Missouri Adopted but Not Implemented 22. Montana Adopted and Implemented Implemented expansion on 1/1/2016 23. Nebraska Adopted but Not Implemented 24. Nevada Adopted and Implemented Implemented expansion on 1/1/2014 25. New HampshireAdopted and Implemented Implemented expansion on 8/15/2014 26. New Jersey Adopted and Implemented Implemented expansion on 1/1/2014 27. New Mexico Adopted and Implemented Implemented expansion on 1/1/2014 28. New York Adopted and Implemented Implemented expansion on 1/1/2014 29. North Dakota Adopted and Implemented Implemented expansion on 1/1/2014 30. Ohio Adopted and Implemented Implemented expansion on 1/1/2014 31. Oklahoma Adopted but Not Implemented 32. Oregon Adopted and Implemented Implemented expansion on 1/1/2014 33. Pennsylvania Adopted and Implemented Implemented expansion on 1/1/2015 34. Rhode Island Adopted and Implemented Implemented expansion on 1/1/2014 35. Utah Adopted and Implemented Implemented expansion on 1/1/2020 36. Vermont Adopted and Implemented Implemented expansion on 1/1/2014 37. Virginia Adopted and Implemented Expansion coverage implemented 1/1/2019 38. Washington Adopted and Implemented Implemented expansion on 1/1/2014 39. West Virginia Adopted and Implemented Implemented expansion on 1/1/2014 https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid- under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId %22:%22Location%22,%22sort%22:%22asc%22%7D https://www.kff.org/medicaid/issue-brief/status-of-state-medicaid-expansion-decisions- interactive-map/ 10

Example of PICOST for Medicaid expansion! Title: Does the ACA Medicaid expansion decrease the Opioid-Related Hospital Use? Research Question : Have enrollees living in DE and CT experienced a consistent level of access to medical care and decrease level of the Opioid-Related Hospital Use by race, age, and income before and after the Medicaid expansion? Key Words : Medicaid expansion, disparity, quality care, health access, SAHIE, HCUP P1: Primary target population :? million in CT and DE between the age 50-64 receive health coverage through Medicaid. I: Medicaid expansion C : non-elderly adult in states without Medicaid expansion Outcomes: number of days in hospital or …. Settings: Inpatient hospitalization Timing (T): time for comparing the outcomes before and after the expansion of the Medicaid program ACA (2006-2017-present) Two sample studies using SAHIE data Mark Borgschulte and Jacob Vogler (2020). Did the ACA Medicaid expansion save lives? Journal of Health Economics . Volume 72, July 2020, 102333 https://www.sciencedirect.com/science/article/abs/pii/S0167629619306228 Lizhong Peng, Xiaohui Guo, and Chad D. Meyerhoefer (2019). The effects of Medicaid expansion on labor market outcomes: Evidence from border counties First published: 20 December 2019 https://doi.org/10.1002/hec.3976 https://onlinelibrary.wiley.com/doi/10.1002/hec.3976 https://www.sciencedirect.com/science/article/abs/pii/S0167629619306228 11