A. All Hilltop Institute (UMBC) Works
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Item Mother-Child Closeness and Adolescent Structural Neural Networks: A Prospective Longitudinal Study of Low-Income Families(Oxford University Press, 2024-11-08) Hong, Sunghyun H.; Hardi, Felicia A.; Tillem, Scott; Goetschius, Leigh Gayle; Brooks-Gunn, Jeanne; McLoyd, Vonnie; Lopez-Duran, Nestor L.; Mitchell, Colter; Hyde, Luke W.; Monk, Christopher S.Mother-child closeness, a mutually trusting and affectionate bond, is an important factor in shaping positive youth development. However, little is known about the neural pathways through which mother-child closeness are related to brain organization. Utilizing a longitudinal sample primarily from low-income families (N=181; 76% African American youth and 54% female), this study investigated the associations between mother-child closeness at ages 9 and 15 and structural connectivity organization (network integration, robustness, and segregation) at age 15. The assessment of mother-child closeness included perspectives from both mother and child. The results revealed that greater mother-child closeness is linked with increased global efficiency and transitivity, but not modularity. Specifically, both the mother’s and child’s report of closeness at age 15 predicted network metrics but report at age 9 did not. Our findings suggest that mother-child closeness is associated with neural white matter organization, as adolescents who experienced greater mother-child closeness displayed topological properties indicative of more integrated and robust structural networks.Item Study protocol: a mixed-methods study of the implementation of doula care to address racial health equity in six state Medicaid programs(Springer Nature, 2024-08-08) Jarlenski, Marian; Kennedy, Susan; Johnson, Annaliese; Hale, Caroline; D’Angelo, Zoe; Nedhari, Aza; Coffee, Gerria; Chappell-McPhail, Molly; Green, Kiddada; Méndez, Dara D.; Goetschius, Leigh G.; Gareau, Sarah; Ashford, Kristin; Barnes, Andrew J.; Ahrens, Katherine A.; Zivin, Kara; Mosley, Elizabeth; Tang, Lu; Writing Committee for Medicaid Outcomes Distributed Research NetworkRacial inequities in severe maternal morbidity (SMM) and mortality constitute a public health crisis in the United States. Doula care, defined as care from birth workers who provide culturally appropriate, non-clinical support during pregnancy and postpartum, has been proposed as an intervention to help disrupt obstetric racism as a driver of adverse pregnancy outcomes in Black and other birthing persons of colour. Many state Medicaid programs are implementing doula programs to address the continued increase in SMM and mortality. Medicaid programs are poised to play a major role in addressing the needs of these populations with the goal of closing the racial gaps in SMM and mortality. This study will investigate the most effective ways that Medicaid programs can implement doula care to improve racial health equity.Item Predicting Hospitalization with the Hilltop Institute Analytics Research Team(UMBC Center for Social Science Research, 2024-02-12) Anson, Ian; Goetschius, Leigh; Han, Fei; Henderson, Morgan; Kim, Jean; Anson,Ian; Mallinson,Christine; Filomeno,Felipe; Kim,Jean; Moreland,D’Juan; Barnes,Amy; Ralston,MyriamOn today’s episode we hear from Dr. Leigh Goetschius, Data Scientist Advanced, Dr. Fei Han, Principal Data Scientist and Affiliate Assistant Professor in the UMBC Department of Computer Science and Electrical Engineering, and Dr. Morgan Henderson, Principal Data Scientist and Affiliate Assistant Professor in the UMBC Department of Economics. Together, these researchers form the UMBC Hilltop Institute Analytics Research team. Our conversation focuses on their work in creating predictive models in the field of healthcare.Item Nursing Home Characteristics and Resident Quality of Care Outcomes: A Scoping Review of Recent Empirical Research(LSE Press, 2024-05-01) Millar, Roberto J.; Diehl, Christin; Blake, Elizabeth; Fakeye, Oludolapo; Kusmaul, NancyContext: Nursing facilities are an essential part of the long-term care continuum, providing a setting where older adults and persons with disabilities receive critical services and supports. Despite extensive research linking facility characteristics to resident outcomes, the facility and resident factors under investigation vary in the context of a diverse industry landscape and poor understanding of key quality of care outcomes.Objectives: This scoping review focused on identifying key concepts, summarising existing findings, and identifying gaps in research linking nursing facility characteristics and resident outcomes.Methods: Guided by PRISMA-ScR guidelines, this scoping review focused on empirical, English-language research published in five databases between 2005 and 2022. The research studies meeting specified inclusion criteria were subjected to thematic analysis for the extraction of key concepts and synthesis of findings.Findings: The 91 research studies in the final analytic sample conceptualised facility-level characteristics and resident outcomes using six and nine broad domains, respectively. The subcategories making up these discrete domains varied widely across studies. While evidence of linkages between facility environments and resident outcomes varied, there was general support that higher staffing capacity and home-like environments with support for autonomy and social integration were linked to better functional outcomes and higher overall subjective well-being of residents.Implications: It is imperative to understand how facility-level characteristics influence resident outcomes, and this scoping review provides insight into these complex relationships. A better understanding of this area is key to improving policies and regulatory oversight, as well as more broadly inform data driven decision-making.Item 2024 Nancy Kusmaul, Social Work, Receives “Outstanding Individual In Academia” Award From The Congressional Research Institute For Social Work And Policy(2024-04-26) Duque, Catalina Sofia Dansberger; Demond, MarlaynaUMBC's Nancy Kusmaul, associate professor of social work, a scholar and advocate for the rights of older adults and professional caregivers, received the “Outstanding Individual in Academia” award from the Congressional Research Institute for Social Work and Policy in March 2024 at a ceremony on Capitol Hill. Kusmaul’s work is informed by her 10 years of experience as a social worker and over a decade of novel scholarship.Item New U.S. News rankings honor UMBC strengths in teaching, innovation, and inclusion(UMBC News, 2020-09-14) McCaffrey, Kait; Winnick, DinahItem CARE COMPARE STAR RATINGS AND FAMILY SATISFACTION IN MARYLAND NURSING FACILITIES(Oxford University Press, 2023-12-21) Millar, Roberto; Diehl, Christin; Kusmaul, Nancy; Stockwell, IanNursing facilities provide critical services and supports to individuals with long-term care needs. The quality of care in nursing facilities varies depending on facility structural characteristics. Moreover, the measurement and perceptions of what constitutes quality of care varies across stakeholders. We used publicly available data to examine the association between family satisfaction with care and the Centers for Medicare & Medicaid Services’(CMS’s) Care Compare five-star quality ratings in the context of facility characteristics. Facility-level data of family satisfaction with care were merged with CMS’s five-star star ratings of 220 Maryland nursing facilities in 2021. Using univariate and bivariate statistics, we explored differences in family ratings and five-star ratings across facility ownership (for-profit vs. non-profit), geographic location (urban vs. rural), and average resident occupancy (1-60, 61-120, and 121+). Relationships were examined across overall ratings, as well as across subdomain of the two quality rating frameworks (e.g., staffing, autonomy, health inspections). Family members of residents in non-profit, rural, and low-occupancy facilities rated facilities higher. Non-profit and low-occupancy facilities were statistically more likely to be rated four or five stars, while no significant association was observed across geographic location. The association between subdomain-specific family satisfaction and star ratings varied across facilities of different structures. Findings emphasize the need for comprehensive quality of care frameworks that consider views of quality across stakeholders and types of facilities. A clear understanding of nursing facility structure and quality of care is critical to advance data-driven decision making.Item Designing Optimal Recommended Budgeting Thresholds for a Medicaid Program(AJMC, 2022-07-14) Henderson, Morgan; Stockwell, IanObjectives: To develop and test a methodology for optimally setting automatic auditing thresholds to minimize administrative costs without encouraging overall budget growth in a state Medicaid program. Study Design: Two-stage optimization using administrative Maryland Medicaid plan-of-service data from fiscal year (FY) 2019. Methods: In the first stage, we use an unsupervised machine learning method to regroup acuity levels so that plans of service with similar spending profiles are grouped together. Then, using these regroupings, we employ numerical optimization to estimate the recommended budget levels that could minimize the number of audits across those groupings. We simulate the effects of this proposed methodology on FY 2019 plans of service and compare the resulting number of simulated audits with actual experience. Results: Using optimal regrouping and numerical optimization, this method could reduce the number of audits by 10.4% to 36.7% relative to the status quo, depending on the search space parameters. This reduction is a result of resetting recommended budget levels across acuity groupings, with no anticipated increase in the total recommended budget amount across plans of service. These reductions are driven, in general, by an increase in recommended budget level for acuity groupings with low variance in plan-of-service spending and a reduction in recommended budget level for acuity groupings with high variance in plan-of-service spending. Conclusions: Using machine learning and optimization methods, it is possible to design recommended budget thresholds that could lead to significant reductions in administrative burden without encouraging overall cost growth.Item Relationship between Event Prevalence Rate and Gini Coefficient of Predictive Model(Canadian Center of Science and Education, 2022-02) Han, Fei; Stockwell, IanPredictive models are currently used for early intervention to help identify patients with a high risk of adverse events. Assessing the accuracy of such models is a crucial part of the development process. To measure the predictive performance of a scoring model, quantitative indices such as the K-S statistic and C-statistic are used. This paper discusses the relationship between Gini coefficients and event prevalence rates. The main contribution of the paper is the theoretical proof of the relationship between the Gini coefficient and event prevalence rate.Item Impact of the Patient-Centered Medical Home on Consistently High-Cost Patients(AJMC, 2023-12-04) Fakeye, Oludolapo A.; Hsu, Yea-Jen; Weiner, Jonathan P.; Marsteller, Jill A.Objective: To evaluate the effect of a statewide multipayer patient-centered medical home (PCMH) demonstration on patients consistently within the highest ranks of health services expenditure across Maryland. Study Design: Post hoc longitudinal analyses of administrative data on privately insured patients of medical homes that participated in the Maryland Multi-Payer PCMH Program (MMPP), matched for comparison to medical homes in a single-payer PCMH program and to non-PCMH practices. Methods: Consistently high-cost patients (CHPs) were defined as being in the top statewide quintile of payer expenditure over a 2-year baseline period. Using population-averaged generalized linear regression models, we evaluated the odds of CHPs remaining in the highest-cost quintile during the 2-year MMPP implementation period and assessed changes in their utilization patterns. Results: Six percent of included patients were CHPs and accounted for one-third of total expenditure. For CHPs in multipayer PCMHs, estimated odds of remaining in this status after 2 years were lower by 34% (adjusted OR [AOR], 0.66; 95% CI, 0.41-0.90; P = .03) relative to CHPs in non-PCMH practices and higher by 41% (AOR, 1.41; 95% CI, 1.08-1.75; P = .004) compared with CHPs in single-payer PCMHs. Relative to CHPs in non-PCMH practices, CHPs in multipayer PCMHs had inpatient admissions decline by 40% (incidence rate ratio [IRR], 0.60; 95% CI, 0.36-1.00; P = .049) and visits to the attributed primary care provider increase by 21% (IRR, 1.21; 95% CI, 1.05-1.39; P = .01). Conclusions: Relative to routine primary care, the PCMH model significantly reduces the probability that CHPs remain in this expensive category and enhances continuity of care.Item A Facility-Level Analysis of Nursing Home Compare Five Star Rating and Maryland’s Family Satisfaction with Care Survey Get access Arrow(Oxford University Press, 2023-12-18) Kusmaul, Nancy; Millar, Roberto J; Diehl, Christin; Stockwell, IanBackground and Objectives: Nursing facilities care for individuals with cognitive and/or physical disabilities. Poor quality is associated with greater disease and mortality. Quality comprises many factors and different stakeholders value different factors. This study aimed to compare two care quality frameworks, one based on observable factors and one on family satisfaction. Research Design and Methods: We merged publicly available 2021 Maryland nursing facility data. The Maryland Health Care Commission surveys long-term care residents’ family satisfaction across seven domains. CMS’ five-star ratings aggregate inspections, staffing, and quality measures. We used univariate and bivariate statistics to compare the frameworks. Results: The dataset included 220 facilities and 4,610 survey respondents. The average facility rating was 7.70/10 and overall 77% of respondents would recommend the facility. Eighty-six percent of respondents from 5-star facilities, 79% from 4-star facilities, and 76% from 3-star facilities would recommend the facility compared to 65% from 1-star facilities (p < 0.001, p < 0.01 and p < 0.05, respectively). Four or 5-star facilities received significantly higher ratings (8.33, p < 0.001; 7.75, p < 0.05, respectively) than 1-star facilities (7.07). Discussion and Implications: Our results corroborated earlier findings of strong associations between CMS ratings and satisfaction at the extremes of the five-star system. These associations are inconsistent across family-reported domains. This suggests overlap between the frameworks. CMS ratings address care quality; family satisfaction measures quality of life and care quality. High satisfaction is associated with high care quality and quality of life; lower satisfaction is associated with lower care quality.Item Hilltop Researchers Awarded NSF Grant to Study Hospital Pricing Behavior(The Hilltop Institute, 2022-08-01) The Hilltop InstituteItem Transparency In Coverage: A New Tool For Promoting Provider Gender Equity?(Health Affairs, 2023-08-30) Henderson, Morgan; Mouslim, MorganeItem How New Data On Hospital “Discounted Cash Prices” Might Lead To Patient Savings(Health Affairs, 2021-11-08) Mouslim, Morgane; Henderson, MorganIn a new HealthAffairs blog post, Hilltop researchers Morgane Mouslim, DVM, ScM, and Morgan Henderson, PhD, describe their continued work on hospital price transparency. Mouslim and Henderson have been investigating hospital price transparency and the effects of the January 2021 Centers for Medicare & Medicaid Services (CMS) final rule that requires hospitals to publish the prices of their services.Item The Price You Pay: Hospitals are posting procedure costs online, but consumers say price tags can still be hard to find(InvestigateTV, 2023-08-07) Molina, Daniela; DePompa, Rachel; Romans, PaytonItem One Year Later, Where Are The 'Transparency In Coverage' Compliance Studies?(Health Affairs, 2023-09-19) Henderson, Morgan; Mouslim, MorganeItem HCA doctors say its cost-cutting is endangering Appalachian patients — a warning for the whole U.S. health care system(STAT, 2023-11-30) Bannow, TaraItem Data Transparency(Incremental Healthcare, 2022-01-24) Terhayden, Nick vanItem Vascular Screening and Amputation in Diabetic Medicaid Participants in Maryland(The Hilltop Institute, 2023) Holmes, Katherine; Zylstra, Brittney; Idala, DavidItem The Utility of Data from Long-Term Care Assessments for Reducing Repeated Hospital Encounters among Medicare-Medicaid Dually Eligible Beneficiaries(2023) Fakeye, Oludolapo; Rana, Prashant; Han, Fei; Henderson, Morgan; Stockwell, Ian