Association of State Medicaid Income Eligibility Limits and Long-Term Survival After Cancer Diagnosis in the United States

PURPOSE: To examine the association between historic state Medicaid income eligibility limits and long-term survival among patients with cancer. METHODS: 1,449,144 adults age 18-64 years newly diagnosed with 19 common cancers between 2010 and 2013 were identified from the National Cancer Database. States' Medicaid income eligibility limits were categorized as ≤ 50%, 51%-137%, and ≥ 138% of federal poverty level (FPL). Survival time was measured from diagnosis date through December 31, 2017, for up to an 8-year follow-up. Multivariable Cox proportional hazards models with age as time scale were used to assess associations of eligibility limits and stage-specific survival, adjusting for the effects of sex, metropolitan statistical area, comorbidities, year of diagnosis, facility type and volume, and state. RESULTS: Among patients with newly diagnosed cancer age 18-64 years, patients living in states with lower Medicaid income eligibility limits had worse survival for most cancers in both early and late stages, compared with those living in states with Medicaid income eligibility limits ≥ 138% FPL. A dose-response relationship was observed for most cancers with lower income limits associated with worse survival (13 of 17 cancers evaluated for early-stage cancers, and 11 of 17 cancers evaluated for late-stage cancers, and leukemia and brain tumors with P-trend < .05). CONCLUSION: Lower Medicaid income eligibility limits were associated with worse long-term survival within stage; increasing Medicaid income eligibility may improve survival after cancer diagnosis.

Home Health Agency Ownership and Quality of Care Outcomes Among Medicare Beneficiaries

Medicare restructured home healthcare reimbursement from a cost-basis to a 60- day risk-based prospective payment system (PPS) in 2000 to implement the value-based payment model for home healthcare services. Currently home healthcare market in the U.S. is dominated by the presence of for-profit (FP) agencies instead of being primarily served by not-for-profit (NFP) agencies. Using data from the 2016-2018 OASIS for beneficiaries participated in the Medicare Current Beneficiary Survey (MCBS) (N=6,115), the current study examines whether home health agency ownership status is associated with length of stay (LOS) and discharge outcome Medicare home health care patients. Our first outcome variable is discharge status (modeled via ordered probit) with three categories: discharge to the community, inpatient hospital and other long-term care facilities. The second outcome variable is LOS and two dummy variables LOS ≤ 30 days and LOS ≥ 99 days were modeled via binary probit. The key independent variable was the ownership status of the agency (FP vs. NFP). Patient level covariates includes demographics (age, gender, race/ethnicity, marital status), comorbidity index, agency characteristics (metropolitan statistical area, hospital-based). Patients in FP agencies were 5.1% (p&lt;0.01) less likely to discharge to community, 15.3% (p&lt;0.001) less likely to have LOS ≤ 30 days but 7.5% (p&lt;0.001) more likely to have LOS ≥ 99 higher compared to patients from NFP agencies under the PPS. Our results have important implications for clinicians, patients and healthcare professionals to be cognizant about the influence of agency ownership on the delivery of healthcare services in home healthcare sector.

Percolation of temporal hierarchical mobility networks during COVID-19

Percolation theory is essential for understanding disease transmission patterns on the temporal mobility networks. However, the traditional approach of the percolation process can be inefficient when analysing a large-scale, dynamic network for an extended period. Not only is it time-consuming but it is also hard to identify the connected components. Recent studies demonstrate that spatial containers restrict mobility behaviour, described by a hierarchical topology of mobility networks. Here, we leverage crowd-sourced, large-scale human mobility data to construct temporal hierarchical networks composed of over 175 000 block groups in the USA. Each daily network contains mobility between block groups within a Metropolitan Statistical Area (MSA), and long-distance travels across the MSAs. We examine percolation on both levels and demonstrate the changes of network metrics and the connected components under the influence of COVID-19. The research reveals the presence of functional subunits even with high thresholds of mobility. Finally, we locate a set of recurrent critical links that divide components resulting in the separation of core MSAs. Our findings provide novel insights into understanding the dynamical community structure of mobility networks during disruptions and could contribute to more effective infectious disease control at multiple scales. This article is part of the theme issue ‘Data science approaches to infectious disease surveillance’.

Labor and Delivery Unit Closures in Rural Georgia from 2012–2016 and the Impact on Black Women: A Mixed-Methods Investigation

Background. Obstetric provider coverage in rural Georgia has worsened, with nine rural labor and delivery units (LDUs) closing outside the Atlanta Metropolitan Statistical Area from 2012–2016. Georgia consistently has one of the highest maternal mortality rates in the nation and faces increased adverse health consequences from this decline in obstetric care.Objective. This study explores what factors may be associated with rural hospital LDU closures in Georgia from 2012–2016.Methods. This study describes differences between rural Georgia hospitals based on LDU closure status through a quantitative analysis of 2011 baseline regional, hospital, and patient data, and a qualitative analysis of newspaper articles addressing the closures.Results. LDUs that closed had higher proportions of Black female residents in their Primary Care Service Areas (PCSAs), of Black birthing patients, and of patients with Medicaid, self-pay or other government insurance; lower LDU birth volume; more women giving birth within their PCSA of residence; fewer obstetricians and obstetric provider equivalents per LDU; and fewer average annual births per obstetric provider. Qualitative results indicate financial distress primarily contributed to closures, but also suggest that low birth volume and obstetric provider shortage impacted closures.Conclusions for Practice. Rural LDU closure in Georgia has a disproportionate impact on Black and low-income women and may be prevented through funding maternity healthcare and addressing provider shortages.

2. Space Time Trends of Community Onset Staphylococcus aureus Infections in Children Living in Southeastern United States: 2002-2016

Background Staphylococcus aureus (S. aureus) remains a serious cause of infections in the United States and worldwide. Methicillin susceptible S. aureus (MSSA) is the cause of half of all health care–associated staphylococcal infections, and Methicillin Resistant S. aureus (MRSA) is the leading cause of community onset skin and soft tissue infections in the US. This study looks at a 15-year trend of community onset (CO)-MRSA and MSSA infections and determines ‘best’ to ‘worst’ infection trends. We identified distinct groups of CO-MRSA and MSSA infection rate trajectories by grouping census tracts of the 20 county Atlanta Metropolitan Statistical Area (MSA) between 2002 to 2016 with similar temporal trajectories. Methods This is a retrospective study from 2002-2016, using electronic health records of children living in Atlanta, Georgia with S. aureus infections and relevant US census data (at the census tract level). A group based trajectory model was applied to generate community onset S. aureus trajectory infection groups (low, high, very high) by census tract and were mapped using ArcGIS. Results Three CO-MSSA infection groups (low, high, very high) and two CO-MRSA infection groups (low, high) were detected among 909 census tracts in the 20 counties. We found ~74% of all the census tracts with S.aureus occurrence during this time period belonged to low infection rate groups for both MRSA and MSSA, with a higher proportion occurring in the less densely populated counties. Census tracts in DeKalb County, one of Atlanta’s most densely populated areas, had the highest proportion of the worst infection trend patterns (CO-MRSA high or very high, CO-MSSA high or very high). Trends of Community-Onset MRSA and MSSA Infection Rates Based on Group-based Trajectory Models Spatial patterns for CO-MRSA and CO-MSSA Trajectory Trends in the Atlanta Metropolitan Area Between 2002 to 2016 Conclusion Trends of S. aureus infection patterns, stratified by antibiotic resistance over geographic areas and time, identify communities with higher risks for MRSA infection compared to MSSA infection. Further investigation of the determinants of the trajectory groupings and the geographic outliers identified by this study may be a way to target prevention strategies aimed to prevent S. aureus infections. Disclosures All Authors: No reported disclosures

Trade-offs in the relationship between competition and audit quality

Purpose Fears over public accounting becoming increasingly concentrated have inspired several attempts to study the relationship between competition and audit quality. These studies have yielded conflicting results without a clear reason as to why. This paper aims to propose a new approach and empirically demonstrate a non-monotonic association between competition and audit quality. Design/methodology/approach Using metropolitan statistical area level data from the USA over the period of 2000–2014, the author shows that the effect that changes in the competition will have on audit quality depends upon the current competitive state of the market. Findings Audit quality is at its highest level when competition is neither too high nor too low. In addition, the point of inflection at which competition turns from being helpful to harmful is influenced by the saturation of the Big 4 auditors in the market. Practical implications These findings can help explain the mixed results of the literature and provide insight into the role that regulators can play in modulating competition. Originality/value This is the first paper to document a non-monotonic relationship between competition and audit quality. By introducing and exploring the validity of a non-monotonic component in the audit quality equation, the authors can better determine, which competitive structures generate desired levels of audit quality.

World’s biggest retailer launches Walmart Plus and customers have their say

Purpose The Covid crisis led to a huge worldwide shift in consumer behavior. In response, Walmart’s revised business strategy promoted their online delivery service known as Walmart Plus. This study aims to critique the potential of this new venture via a customer value analysis. Design/methodology/approach Using the customer value funnel, Walmart’s market environment, organizational factors, customer perceptions and business performance are examined. An exploratory survey collected data from South Florida residents on awareness and interest in Walmart Plus. Findings The changing marketplace forced Walmart to quickly adapt to online buyers and emphasize the value of their retail and grocery products. Walmart Plus is an alternative to Amazon Prime and can assist the company gain market share in regional grocery markets. Research limitations/implications This work is largely conceptual and presents a case study featuring a limited sample in one metropolitan statistical area. While the findings are insightful, it may not be representative of the US market. Practical implications Corporate executives and entrepreneurs must respond to changing market conditions and rethink their business models to deliver superior customer value. This requires introducing innovative services and digital initiatives to compete successfully. The paper concludes with recommendations for management and questions for consideration. Originality/value Walmart is the dominant American retailer and a global leader. While there has been considerable research on this retail giant, there has been limited analysis of their digital initiatives such as Walmart Plus.

SPATIAL ANALYSIS: PENDEKATAN METROPOLITAN STATISTICAL AREA UNTUK PERENCANAAN PEMBANGUNAN MANUSIA DI PROVINSI JAWA TENGAH

Pembangunan manusia menjadi salah satu fokus utama pemerintah dalam Rencana Pembangunan Jangka Menengah Nasional (RPJMN) 2020-2024. Hal tersebut tertuang pada agenda ketiga dari tujuh agenda pembangunan, yaitu “Meningkatkan Sumber Daya Manusia yang Berkualitas dan Berdaya Saing”. Tingkat pembangunan manusia pada suatu wilayah dapat tercermin melalui Indeks Pembangunan Manusia (IPM). Pada tahun 2020, IPM Provinsi Jawa Tengah bernilai 71,87. Meski sudah termasuk pada kategori tinggi (70-80), namun IPM Provinsi Jawa Tengah tersebut masih termasuk ke rentang bawah yang lebih mendekati kategori sedang (<70). Jika dibandingkan dengan provinsi lain, IPM Provinsi Jawa Tengah hanya menempati posisi ke-13 diantara 34 provinsi lainnya. Oleh karena itu, pada penelitian ini, pendekatan analisis deskriptif, analisis spasial, dan Metropolitan Statistical Area (MSA) akan digunakan untuk menentukan wilayah prioritas pembangunan manusia di Provinsi Jawa Tengah. Hasil analisis deskriptif menunjukkan bahwa wilayah kiri atau timur Provinsi Jawa Tengah memiliki persebaran nilai IPM yang cenderung lebih rendah. Perencanaan pembangunan manusia di Provinsi Jawa Tengah sebaiknya difokuskan pada ketiga MSA yang terbentuk, yaitu MSA Tegal, MSA Pekalongan, dan MSA Purworejo.

Impact of External Environmental Dimensions on Financial Performance of Major Teaching Hospitals in the U.S.

Teaching hospitals have a unique mission to not only deliver graduate medical education but to also provide both inpatient and ambulatory care and to conduct clinical medical research; therefore, they are under constant financial pressure, and it is important to explore what types of external environmental components affect their financial performance. This study examined if there is an association between the short-term and long-term financial performance of major teaching hospitals in the United States and the external environmental dimensions, as measured by the Resource-Dependence Theory. Data for 226 major teaching hospitals spanning 46 states were analyzed. The dependent variable for short-term financial performance was days cash on hand, and dependent variable for long-term financial performance was return on assets, both an average of most recently available 4-year data (2014–2017). Utilizing linear regression model, results showed significance between outpatient revenue and days cash on hand as well as significant relationship between population of the metropolitan statistical area, unemployment rate of the metropolitan statistical area, and teaching hospital’s return on assets. Additionally, system membership, type of ownership/control, and teaching intensity also showed significant association with return on assets. By comprehensively examining all major teaching hospitals in the U.S. and analyzing the association between their short-term and long-term financial performance and external environmental dimensions, based upon Resource-Dependence Theory, we found that by offering diverse outpatient services and novel delivery options, administrators of teaching hospitals may be able to increase organizational liquidity.

The more, the better? Forecasting gains from high-frequency housing prices in a Markov-switching dynamic factor model

This paper extracts housing boom-bust cycle signals from metropolitan statistical area (MSA)-level housing prices using a Markov-switching dynamic factor model. To mitigate the estimation bias, it utilizes high-frequency housing prices that follow the methodology of the monthly Case–Shiller house price indices. The housing bust phases specified from weekly and daily housing prices precede those based on monthly prices by approximately 2 years. MSAs with top signal-to-noise ratios offer greater marginal contributions to improvements in forecasting housing cycles than MSAs with bottom ratios for all frequencies. The results highlight the importance of indicator quality and provide evidence against “The more, the better” since incorporating more MSA-level housing prices into housing factors does not guarantee more satisfactory housing cycle forecasts.