Justin Blackburn
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The Economic Burden of Untreated Mental Illness in Indiana: Translating Evidence into Policy
Justin Blackburn, Ph.D., is an Associate Professor of Health Policy and Management at the Richard M. Fairbanks School of Public Health in Indianapolis. He is also the Health Policy Ph.D. Program Director and the Scientific Director Wellbeing Informed by Science and Evidence in Indiana (WISE Indiana), a research partnership between the Indiana Clinical and Translational Science Institute and the Indiana Family and Social Services Administration (FSSA). He earned an MPH in epidemiology from the University of Kentucky College of Public Health and a Ph.D. in epidemiology from the University of Alabama at Birmingham School of Public Health. He has published over 90 peer-reviewed articles, served on 27 dissertation research committees, and generated over $2 million in research funding.
Dr. Blackburn's research primarily involves leveraging large administrative data sets to evaluate public health policy and outcomes at the state, local, and national level. He is a frequent collaborator with state and local public health agencies, and has applied methodologically innovative approaches to evaluate important public health topics including dental health services and outcomes, long-term care policy and outcomes, Medicaid and CHIP coverage, and measuring health care quality. In a new study, Dr. Blackburn and his co-researchers, revealed the economic burden of untreated mental illness in Indiana, which results in $4.2 billion spent annually. Dr. Blackburn's use of data to inform health policies for the benefit of community members is another excellent example of how IUPUI's faculty members are TRANSLATING their RESEARCH INTO PRACTICE.
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Item The Economic Burden of Untreated Mental Illness in Indiana: Translating Evidence into Policy(Center for Translating Research Into Practice, IU Indianapolis, 2024-03-22) Blackburn, JustinWellbeing Informed by Science and Evidence in Indiana (WISE Indiana) is a partnership with the Indiana Clinical and Translational Sciences Institute’s Monon Collaborative and the Indiana Family and Social Services Administration (FSSA) to engage Indiana’s nationally-recognized academic experts to evaluate and inform Indiana practices, programs and policies. The WISE Indiana team determined that the value of untreated mental illness in Indiana is over $4 billion.Item Economic Burden Associated With Untreated Mental Illness in Indiana(American Medical Association, 2023) Taylor, Heather L.; Menachemi, Nir; Gilbert, Amy; Chaudhary, Jay; Blackburn, JustinImportance There is a paucity of systematically captured data on the costs incurred by society—individuals, families, and communities—from untreated mental illnesses in the US. However, these data are necessary for decision-making on actions and allocation of societal resources and should be considered by policymakers, clinicians, and employers. Objective To estimate the economic burden associated with untreated mental illness at the societal level. Design, Setting, and Participants This cross-sectional study used multiple data sources to tabulate the annual cost of untreated mental illness among residents (≥5 years old) in Indiana in 2019: the US National Survey on Drug Use and Health, the National Survey of Children’s Health, Indiana government sources, and Indiana Medicaid enrollment and claims data. Data analyses were conducted from January to May 2022. Main Outcomes and Measures Direct nonhealth care costs (eg, criminal justice system, homeless shelters), indirect costs (unemployment, workplace productivity losses due to absenteeism and presenteeism, all-cause mortality, suicide, caregiver direct health care, caregiver productivity losses, and missed primary education), and direct health care costs (disease-related health care expenditures). Results The study population consisted of 6 179 105 individuals (median [SD] age, 38.0 [0.2] years; 3 132 806 [50.7%] were women) of whom an estimated 429 407 (95% CI, 349 526-528 171) had untreated mental illness in 2019. The economic burden of untreated mental illness in Indiana was estimated to be $4.2 billion annually (range of uncertainty [RoU], $2.1 billion-$7.0 billion). The cost of untreated mental illness included $3.3 billion (RoU, $1.7 billion-$5.4 billion) in indirect costs, $708.5 million (RoU, $335 million-$1.2 billion) in direct health care costs, and $185.4 million (RoU, $29.9 million-$471.5 million) in nonhealth care costs. Conclusion and Relevance This cross-sectional study found that untreated mental illness may have significant financial consequences for society. These findings put into perspective the case for action and should be considered by policymakers, clinicians, and employers when allocating societal resources and funding. States can replicate this comprehensive framework as they prioritize key areas for action regarding mental health services and treatments.Item Age-Related Differences in Health-Related Quality of Life Among Western Canadian Nursing Home Residents(Oxford University Press, 2022) Shieu, Bianca; Schwartz, Todd; Hoben, Matthias; Toles, Mark; Beeber, Anna; Anderson, RuthNursing homes (NHs) typically focus on health-related quality of life (HRQoL) among residents aged 65 and over despite approximately 7% of NH residents are younger (aged 18-64). Research suggests that the needs of younger NH residents are not being met and they may have low HRQoL. However, differences in HRQoL of younger and older NH residents may not be apparent in studies that use HRQoL measures designed for research with older NH residents. We hypothesized that the younger residents would have lower HRQoL mean scores than the older (aged ≥ 65) residents using a HRQoL measure based on the HRQoL score derived from Resident Assessment Instrument – Minimum Data Set 2.0 items. The measure uses items that emphasize physical aspects of quality of life rather than social aspects. In a sample of 21,129 residents from 94 NHs in Western Canada, we performed descriptive analyses, t-test, chi-square test, and an adjusted propensity score (PS) analysis through retrospective cohort study from years 2016 to 2017. The HRQoL index score ranged from -.351 to .996 (Mean= 0.693, SD=0.265). In the PS model, the adjusted mean score for younger was higher than for older adults with a mean difference at 0.061 (95% CI 0.031, 0.091) (p<.001). Other domains such as mental health condition of quality of life must be examined in younger NH residents because it is a crucial factor influencing their daily lives, thereby we can explore a more complete set of HRQoL domains of them and redesign care for their unique needs.Item Measuring rurality in health services research: a scoping review(BMC, 2022-11-12) Danek, Robin; Blackburn, Justin; Greene, Marion; Mazurenko, Olena; Menachemi, NirPurpose: This study is a scoping review of the different methods used to measure rurality in the health services research (HSR) literature. Methods: We identified peer-reviewed empirical studies from 2010-2020 from seven leading HSR journals, including the Journal of Rural Health, that used any definition to measure rurality as a part of their analysis. From each study, we identified the geographic unit (e.g., county, zip code) and definition (e.g., Rural Urban Continuum Codes, Rural Urban Commuting Areas) used to classify categories of rurality. We analyzed whether geographic units and definitions used to classify rurality differed by focus area of studies, including costs, quality, and access to care. Lastly, we examined the number of rural categories used by authors to assess rural areas. Findings: In 103 included studies, five different geographic units and 11 definitions were used to measure rurality. The most common geographic units used to measure rurality were county (n = 59, 57%), which was used most frequently in studies examining cost (n = 12, 75%) and access (n = 33, 57.9%). Rural Urban Commuting Area codes were the most common definition used to measure rurality for studies examining access (n = 13, 22.8%) and quality (n = 10, 44%). The majority of included studies made rural versus urban comparisons (n = 82, 80%) as opposed to focusing on rural populations only (n = 21, 20%). Among studies that compared rural and urban populations, most studies used only one category to identify rural locations (n = 49 of 82 studies, 60%). Conclusion: Geographic units and definitions to determine rurality were used inconsistently within and across studies with an HSR focus. This finding may affect how health disparities by rural location are determined and thus how resources and federal funds are allocated. Future research should focus on developing a standardized system to determine under what circumstances researchers should use different geographic units and methods to determine rurality by HSR focus area.Item The impact of rural general hospital closures on communities-A systematic review of the literature(Wiley, 2023-11-20) Mills, Carol A.; Yeager, Valerie A.; Unroe, Kathleen T.; Holmes, Ann; Blackburn, Justin; Health Policy and Management, School of Public HealthPurpose: To compile the literature on the effects of rural hospital closures on the community and summarize the evidence, specifically the health and economic impacts, and identify gaps for future research. Methods: A systematic review of the relevant peer-reviewed literature, published from January 2005 through December 2021, included in the EMBASE, CINAHL, PubMed, EconLit, and Business Source Complete databases, as well as "gray" literature published during the same time period. A total of 21 articles were identified for inclusion. Findings: Over 90% of the included studies were published in the last 8 years, with nearly three-fourths published in the last 4 years. The most common outcomes studied were economic outcomes and employment (76%), emergent, and non-emergent transportation, which includes transport miles and travel time (42.8%), access to and supply of health care providers (38%), and quality of patient outcomes (19%). Eighty-nine percent of the studies that examined economic impacts found unfavorable results, including decreased income, population, and community economic growth, and increased poverty. Between 11 and 15.7 additional minutes were required to transport patients to the nearest emergency facility after closures. A lack of consistency in measures and definition of rurality challenges comparability across studies. Conclusions: The comprehensive impact of rural hospital closures on communities has not been well studied. Research shows predominantly negative economic outcomes as well as increased time and distance required to access health care services. Additional research and consistency in the outcome measures and definition of rurality is needed to characterize the downstream impact of rural hospital closures.Item Hospital Partnerships for Population Health: A Systematic Review of the Literature(Wolters Kluwer, 2021) Ellis Hilts, Katy; Yeager, Valerie A.; Gibson, P. Joseph; Halverson, Paul K.; Blackburn, Justin; Menachemi, Nir; Health Policy and Management, School of Public HealthThe U.S. healthcare system continues to experience high costs and suboptimal health outcomes that are largely influenced by social determinants of health. National policies such as the Affordable Care Act and value-based payment reforms incentivize healthcare systems to engage in strategies to improve population health. Healthcare systems are increasingly expanding or developing new partnerships with community-based organizations to support these efforts. We conducted a systematic review of peer-reviewed literature in the United States to identify examples of hospital-community partnerships; the main purposes or goals of partnerships; study designs used to assess partnerships; and potential outcomes (e.g., process- or health-related) associated with partnerships. Using robust keyword searches and a thorough reference review, we identified 37 articles published between January 2008 and December 2019 for inclusion. Most studies employed descriptive study designs (n = 21); health needs assessments were the most common partnership focus (n = 15); and community/social service (n = 21) and public health organizations (n = 15) were the most common partner types. Qualitative findings suggest hospital-community partnerships hold promise for breaking down silos, improving communication across sectors, and ensuring appropriate interventions for specific populations. Few studies in this review reported quantitative findings. In those that did, results were mixed, with the strongest support for improvements in measures of hospitalizations. This review provides an initial synthesis of hospital partnerships to address population health and presents valuable insights to hospital administrators, particularly those leading population health efforts.Item Practice and market factors associated with provider volume of health information exchange(Oxford University Press, 2021) Apathy, Nate C.; Vest, Joshua R.; Adler-Milstein, Julia; Blackburn, Justin; Dixon, Brian E.; Harle, Christopher A.; Health Policy and Management, School of Public HealthObjective: To assess the practice- and market-level factors associated with the amount of provider health information exchange (HIE) use. Materials and methods: Provider and practice-level data was drawn from the Meaningful Use Stage 2 Public Use Files from the Centers for Medicare and Medicaid Services, the Physician Compare National Downloadable File, and the Compendium of US Health Systems, among other sources. We analyzed the relationship between provider HIE use and practice and market factors using multivariable linear regression and compared primary care providers (PCPs) to non-PCPs. Provider volume of HIE use is measured as the percentage of referrals sent with electronic summaries of care (eSCR) reported by eligible providers attesting to the Meaningful Use electronic health record (EHR) incentive program in 2016. Results: Providers used HIE in 49% of referrals; PCPs used HIE in fewer referrals (43%) than non-PCPs (57%). Provider use of products from EHR vendors was negatively related to HIE use, while use of Athenahealth and Greenway Health products were positively related to HIE use. Providers treating, on average, older patients and greater proportions of patients with diabetes used HIE for more referrals. Health system membership, market concentration, and state HIE consent policy were unrelated to provider HIE use. Discussion: HIE use during referrals is low among office-based providers with the capability for exchange, especially PCPs. Practice-level factors were more commonly associated with greater levels of HIE use than market-level factors. Conclusion: This furthers the understanding that market forces, like competition, may be related to HIE adoption decisions but are less important for use once adoption has occurred.Item Decreasing deceased donor transplant rates among children (≤6 years) under the new kidney allocation system(Elsevier, 2018) Shelton, Brittany A.; Sawinski, Deirdre; Ray, Christopher; Reed, Rhiannon D.; MacLennan, Paul A.; Blackburn, Justin; Young, Carlton J.; Gray, Stephen; Yanik, Megan; Massie, Allan; Segev, Dorry L.; Locke, Jayme E.; Health Policy and Management, School of Public HealthThe Kidney Allocation System (KAS) was implemented in December 2014 with unknown impact on the pediatric waitlist. To understand the effect of KAS on pediatric registrants, deceased donor kidney transplant (DDKT) rate was assessed using interrupted time series analysis and time-to-event analysis. Two allocation eras were defined with an intermediary washout period: Era 1 (01/01/2013-09/01/2014), Era 2 (09/01/2014-03/01/2015), and Era 3(03/01/2015-03/01/2017). When using Cox proportional hazards, there was no significant association between allocation era and DDKT likelihood as compared to Era 1 (Era 3: aHR: 1.07, 95% CI: 0.97-1.18, P = .17). However, this was not consistent across all subgroups. Specifically, while highly sensitized pediatric registrants were consistently less likely to be transplanted than their less sensitized counterparts, this disparity was attenuated in Era 3 (Era 1 aHR: 0.04, 95%CI: 0.01-0.14, P < .001; Era 3 aHR: 0.33, 95% CI: 0.21-0.53, P < .001) whereas the youngest registrants aged 0-6 experienced a 21% decrease in DDKT likelihood in Era 3 as compared to Era 1 (aHR: 0.79, 95% CI: 0.64-0.98, P = .03). Thus, while overall DDKT likelihood remained stable with the introduction of KAS, registrants ≤ 6 years of age were disadvantaged, warranting further study to ensure equitable access to transplantation.Item Mood Disorder Episodes & Diagnosis in Different Settings: What Can We Learn?(Juniper, 2018) Sen, Bisakha; Blackburn, Justin; Morrisey, Michael A.; Kilgore, Meredith; Menachemi, Nir; Caldwell, Cathy; Becker, David; Health Policy and Management, School of Public HealthObjective: Over the past two decades in proportion of costs of mood disorders among children paid for by government insurance programs has increased substantially. The objective of this study is to gain a more in-depth understanding of patterns of mood disorder diagnosis (MDOD) among enrollees in the Alabama Children’s Health Insurance Program, ALL Kids. Method: A retrospective study using claims data from ALL Kids from 2008-2014 was conducted. The proportion of ‘initial’ MDOD incidents occurring in different care settings (inpatient/ED, physician’s office, outpatient), and the predictors of these incidents, were investigated. Patterns of repeated MDOD inpatient/ED incidents were examined. Results: Multinomial logistic regression results show black enrollees have higher relative risk ratios (RRR) of having a MDOD in inpatient/ED setting (RRR: 1.52, p< 0.01), as do Hispanics (RRR: 1.30, p< 0.01). Enrollees who receive the initial diagnosis in an inpatient/ED setting are at high risk of subsequent MDOD incidents in an inpatient setting/ED. There is no significant racial or ethnic difference in the subsequent number of inpatient/ED visits conditional on the location of the initial diagnosis. Conclusions: The pattern of repeated MDOD incidents in inpatient/ED settings may be indicative of acuity of conditions, lack of access to alternate sources of care for mood disorders, or poor adherence to treatment and inadequate home care. Enrollees who do have such an incident may be strong candidates for case management, potentially improving enrollee outcomes as well as reducing program costs by averting avoidable inpatient/ED MDOD incidents.Item Improving Communication in Nursing Homes Using Plan-Do-Study-Act Cycles of an SBAR Training Program(Sage, 2023) Kay, Samantha; Unroe, Kathleen T.; Lieb, Kristi M.; Kaehr, Ellen W.; Blackburn, Justin; Stump, Timothy E.; Evans, Russell; Klepfer, Sarah; Carnahan, Jennifer L.; Medicine, School of MedicineBackground: Incomplete communication between staff and providers may cause adverse outcomes for nursing home residents. The Situation-Background-Assessment-Recommendation (SBAR) tool is designed to improve communication around changes in condition (CIC). An adapted SBAR was developed for the Centers for Medicare and Medicaid Services demonstration project, OPTIMISTIC, to increase its use during a resident CIC and to improve documentation. Methods: Four Plan-Do-Study-Act (PDSA) cycles to develop and refine successive protocol implementation of the OPTIMISTIC SBAR were deployed in four Indiana nursing homes. Use of SBAR, documentation quality, and participant surveys were assessed pre- and post-intervention implementation. Results: OPTIMISTIC SBAR use and documentation quality improved in three of the four buildings. Participants reported improved collaboration between nurses and providers after SBAR intervention. Conclusion: Successive PDSA cycles implementing changes in an OPTIMISTIC SBAR protocol for resident CIC led to an increase in SBAR use, improved documentation, and better collaboration between nursing staff and providers.