Tag / healthcare

by Sydney Lash

IT Strategization for Streamlining Lung Cancer Registry Processes In NC

Problem Statement

Lung cancer is one of the most significant chronic disease burdens in North Carolina, both in terms of incidence and mortality. According to CDC data from 2023, the state experienced 34.9 deaths per 100,000 residents from lung cancer and 58.4 new cases per 100,000 residents, both higher than the national averages.(1)These elevated rates place lung cancer among the most pressing cancer-related public health challenges in North Carolina.

Disparities are evident among racial and ethnic minorities across timeliness of diagnosis, treatment access, and five-year survival rates. (2) Risk factors also contribute to North Carolina’s elevated burden; adult smoking prevalence alongside of youth e-cigarette use are both higher than the national average.(3)

These statistics underscore the urgency of strengthening surveillance systems to provide timely, representative data that can inform prevention, screening, and equitable treatment strategies for lung cancer in North Carolina.

Current State of Surveillance

The North Carolina Central Cancer Registry (NCCCR) is the state’s legally mandated system for tracking cancer incidence, treatment, and outcomes. As part of the CDC’s National Program of Cancer Registries (NPCR) and the North American Association of Central Cancer Registries (NAACCR), it provides a comprehensive record of cancer cases across hospitals, clinics, and laboratories. NCCCR data are essential for understanding cancer trends, guiding public health policy, and supporting national cancer control efforts.

Despite its strengths, the NCCCR faces several limitations that reduce its effectiveness in addressing urgent public health concerns, such as lung cancer. Timeliness, integration, and equity monitoring are the main challenges. The registry data is often delayed up to 2 years behind real-world diagnoses, NCCCR is often not linked to behavioral data, and equity-based variables may be incomplete.

For a condition such as lung cancer, these limitations hinder North Carolina’s ability to respond quickly and equitably. Modernizing NCCCR to improve timeliness and representativeness is therefore critical to reducing the state’s disproportionate lung cancer burden.

Modernization Strategy

To address these gaps, North Carolina should modernize its cancer surveillance system by aligning the NCCCR with CSTE Objective 2.1: “Improve traditional surveillance systems to provide timely and representative chronic disease insights.” (4) The goal is to reduce reporting lag, strengthen representativeness, and create actionable insights for prevention and treatment of lung cancer.

A unique opportunity exists through the Cancer Identification and Precision Oncology Center (CIPOC) at UNC-Chapel Hill, which was recently awarded ARPA-H funding to aggregate and analyze cancer data from diverse sources—including electronic health records, pathology and radiology images, claims, and geographic information utilizing large language models.(5) CIPOC is designed to support real-time cancer case identification and equitable care delivery. Integrating NCCCR modernization with CIPOC’s infrastructure would allow the registry to improve timeliness, enhance data linkage, and support equity-focused initiatives

By grounding modernization in CSTE’s national strategy while leveraging CIPOC’s cutting-edge infrastructure, North Carolina can create a best-practice model for other states. This integrated approach would demonstrate how traditional registries and advanced AI-enabled systems can work together to provide high-quality data while leveraging the improved efficiency that AI brings.

Summary

North Carolina faces an urgent burden from lung cancer, with incidence and mortality rates above the national average and significant disparities across racial and geographic groups.

Modernizing the NCCCR to improve timeliness, completeness, and representativeness is critical to addressing this challenge. By aligning with CSTE Objective 2.1 and leveraging the AI-enabled infrastructure of CIPOC, the state can reduce delays in reporting, link surveillance data to risk factors and screening uptake, and generate equity-focused insights for targeted interventions.

This integrated approach demonstrates how traditional registries can evolve into rapid, representative systems and provides a best-practice model that other states and chronic conditions can adopt.

The model has clear implications beyond lung cancer. The same framework can be applied to other cancers, as well as non-cancer conditions like COPD or cardiovascular disease. Importantly, the CIPOC project’s use of retrieval-augmented generation and advanced prompting strategies to extract and synthesize multi-modal data provides an adaptable toolkit for modern surveillance. By applying the most effective AI methods refined within CIPOC, North Carolina can not only strengthen its lung cancer registry but also inform future AI applications in healthcare surveillance more broadly. This positions the state as a leader in operationalizing CSTE’s strategic plan while demonstrating how cutting-edge AI methods can scale across diseases and conditions.

by Sydney Lash

Race, Place, and Quality

A Look at Hypertension Management Among Black Women in North Carolina

This semester, in my Social Epidemiology course, we had to propose a study related to our course content. I chose to explore how race, place, and healthcare quality intersect to shape outcomes for Black women living with hypertension.

Why This Study?

Black women in the U.S. face unique and layered health challenges due to the intersecting effects of racism and sexism. The weathering hypothesis, developed by Geronimus et al., suggests that chronic exposure to social, economic, and racial stressors accelerates health deterioration—particularly among Black women.1,2

Despite advances in treatment, disparities in chronic disease outcomes persist. Black women, especially in rural areas, remain more likely to experience uncontrolled hypertension. This raises critical questions about how structural barriers, such as geographic isolation and limited access to high-quality care, interact with in-clinic factors, such as provider bias.

Layered forms of marginalization interact to shape Black women’s health experiences

My Research Question

Among Black women receiving care at Federally Qualified Health Centers (FQHCs) in North Carolina, how does the impact of geographic proximity on hypertension management differ between urban and rural communities?

My hypothesis: Geographic proximity will have a smaller impact on hypertension management among Black women in rural communities compared to those in urban areas due to compounded marginalization and systemic barriers.

Background Context

  • Rural communities tend to have a higher chronic disease burden.3
  • High-burden ZIP Code Tabulation Areas (ZCTAs) had nearly double the proportion of Black residents compared to low-burden ZCTAs.3
  • On average, people in high-burden areas live 8.7 miles from the nearest FQHC, compared to 4.6 miles in low-burden areas.3
  • Clinical quality gaps persist: Non-Hispanic Black individuals are 12% less likely to have adequately controlled blood pressure, even after adjusting for socioeconomic and healthcare access factors.11,12

A map showing FQHC distribution across North Carolina and a gradient scale representing rurality by RUCA score.

Proposed Study Design

  • Design: Cross-sectional observational study
  • Population: Black women aged 18+ with a diagnosis of hypertension and at least two FQHC visits between Jan 2023 – Dec 2024
  • Data Source: EHR data from FQHCs across North Carolina
  • Exposure: Proximity to FQHC, measured by distance from home ZIP to clinic
  • Comparison Groups: Urban vs. rural residence (based on RUCA score)
  • Outcome: Blood pressure control (e.g., SBP <140 mmHg)
  • Covariates: Socioeconomic status, insurance, comorbidities, clinic characteristics

A directed acyclic graph illustrating the conceptual model of how structural and clinical factors interact to influence hypertension management.

Final Thoughts

Developing this proposal deepened my understanding of how place, identity, and systemic inequity play a role in measurable health outcomes. Mapping these disparities is only the beginning. As researchers, we must also imagine ways to redesign care systems that serve Black women and their intersectional identities more equitably.

References

  1. Geronimus AT, Hicken M, Keene D, Bound J. “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. Am J Public Health. 2006;96(5):826-833. doi:10.2105/AJPH.2004.060749
  2. Chinn JJ, Martin IK, Redmond N. Health Equity Among Black Women in the United States. J Womens Health (Larchmt). 2021;30(2):212-219. doi:10.1089/jwh.2020.8868
  3. Benavidez GA, Zahnd WE, Hung P, Eberth JM. Chronic Disease Prevalence in the US: Sociodemographic and Geographic Variations by Zip Code Tabulation Area. Prev Chronic Dis 2024;21:230267. DOI: http://dx.doi.org/10.5888/pcd21.230267.
  4. Ndugga N, Hill L, Artiga S. Key data on health and health care by race and ethnicity. KFF. Published June 11, 2024. Accessed November 14, 2024. https://www.kff.org/key-data-on-health-and-health-care-by-race-and-ethnicity/?entry=health-status-and-outcomes-chronic-disease-and-cancer
  5. Agency for Healthcare Research and Quality. 2023 National Healthcare Quality and Disparities Report Appendixes. AHRQ Pub. No. 23(24)-0091-EF. December 2023.
  6. Ochieng N, Biniek JF, Cubanski J, Neuman T. Disparities in health measures by race and ethnicity among beneficiaries in Medicare Advantage: A review of the literature. KFF. Published December 13, 2023. Accessed October 15, 2024. https://www.kff.org/medicare/report/disparities-in-health-measures-by-race-and-ethnicity-among-beneficiaries-in-medicare-advantage-a-review-of-the-literature/
  7. Jha AK, Zaslavsky AM, Orav EJ, Epstein AM, Ayanian JZ. Quality of ambulatory care for privately insured and Medicare Advantage enrollees in the United States. Health Aff (Millwood).
  8. Tong M, Hill L, Artiga S. Racial disparities in cancer outcomes, screening, and treatment. KFF. Published February 3, 2022. Accessed November 14, 2024. https://www.kff.org/racial-equity-and-health-policy/issue-brief/racial-disparities-in-cancer-outcomes-screening-and-treatment/
  9. Alsheik N, Blount L, Qiong Q, et al. Outcomes by race in breast cancer screening with digital breast tomosynthesis versus digital mammography. J Am Coll Radiol. 2021;18(7):906-918. doi:10.1016/j.jacr.2020.12.033
  10. Miller-Kleinhenz JM, Collin LJ, Seidel R, Oyesanmi O. Racial disparities in diagnostic delay among women with breast cancer. J Am Coll Radiol. 2021;18(10):1384-1393. doi:10.1016/j.jacr.2021.06.019
  11. Abrahamowicz AA, Ebinger J, Whelton SP, Commodore-Mensah Y, Yang E. Racial and Ethnic Disparities in Hypertension: Barriers and Opportunities to Improve Blood Pressure Control. Curr Cardiol Rep. 2023;25(1):17-27. doi:10.1007/s11886-022-01826-x
  12. Crim MT, Yoon SS, Ortiz E, et al. National surveillance definitions for hypertension prevalence and control among adults. Circ Cardiovasc Qual Outcomes. 2012;5(3):343-351. doi:10.1161/CIRCOUTCOMES.111.963439
by Sydney Lash

Addressing Healthcare Disparities in North Carolina

Through my Healthcare Data Visualization course I, alongside two other classmates, were tasked with creating a dashboard using a data set and platform of our choice. Using data from the 2018 Health Professional Shortage Area (HPSA) dataset provided by the U.S. Department of Health & Human Services, our analysis reveals critical insights into the challenges and opportunities for improving healthcare access statewide.

Key Findings from the Analysis

  1. Healthcare Shortages Are Severe in Underserved Areas
    The average provider-to-population ratio in HPSA-designated areas is 2.11 clinicians per 10,000 residents, significantly below the recommended 6.67 clinicians. This stark disparity highlights the strain on underserved communities, especially in rural regions.
  2. Poverty Rates Compound Access Issues
    North Carolina’s poverty rate—measured as residents below 200% of the federal poverty line—is 27%, slightly above the national average of 26.9%. This economic disadvantage exacerbates barriers to healthcare, disproportionately affecting rural counties.
  3. Medically Underserved Areas (MUAs) Require Immediate Attention
    MUA scores, which account for clinician ratios, infant mortality, poverty levels, and the percentage of elderly populations, show an alarming average of 51.76 across NC—well below the national threshold of 62. Henderson and Transylvania counties, with MUA scores of 0, represent the most critically underserved areas in the state.
  4. Rural Hospitals Closures and Policy Impacts
    Historical trends show peaks in shortages in 2002 and 2015-2018, correlating with changes in HPSA methodology and rural hospital closures. These events further stress the importance of sustained policy interventions.
  5. Prioritization of Resources by HPSA Scores
    The HPSA scoring system, used by the National Health Service Corps (NHSC), prioritizes counties for clinician assignments. Mecklenburg County has the highest HPSA score due to its large population, indicating where current resources are concentrated. However, smaller rural counties with lower scores risk being overlooked despite their critical needs.

Access to quality healthcare is a fundamental need, yet many counties across North Carolina face significant shortages in healthcare providers, particularly in rural and economically disadvantaged areas. Our findings underscore the urgent need for targeted interventions. Allocating resources to counties with the highest ratios of underserved populations, addressing the economic and geographic barriers to care, and replicating successful policies in declining shortage areas can help mitigate these disparities. For policymakers, healthcare providers, and community leaders, this analysis serves as a roadmap for reducing inequities and ensuring better access to healthcare for all North Carolinians.

Sources:

https://data.hrsa.gov/tools/shortage-area/hpsa-find

https://www.bls.gov/opub/reports/working-poor/2020/#:~:text=In%202020%2C%2037.2%20million%20people%2C%20or%2011.4,notes%20section%20for%20examples%20of%20poverty%20levels.)

https://healthycommunitiesnc.org/

ciceroinstitute.org/research/north-carolina-physician-shortage-facts/

by Sydney Lash

Exploring Primary Care Ratios in North Carolina Counties

In an effort to improve my data analysis skills within the field of Public Health, I am currently working on an analysis of healthcare access across three different counties in North Carolina. This initial analysis focuses on the ratio of primary care physicians to residents, a crucial aspect of understanding healthcare resource availability. The counties under scrutiny include Mecklenburg County, Anson County, and Stanly County, chosen deliberately from different tiers defined by the North Carolina Department of Commerce (County Distress Rankings (Tiers) | NC Commerce). Mecklenburg sits in Tier 3, offering a contrast to Cumberland County in Tier 1 and Guilford County in Tier 2. These tiers, determined by factors like unemployment rates, median household income, growth percentage, and property tax base per capita, set the stage for a nuanced examination of healthcare disparities. Tier three indicates the highest standing and tier one indicates the lowest.

Number of Primary Care Physicians Across Three North Carolina Counties

The graph above illustrates the count of active Primary Care Physicians, utilizing data sourced from the Vital Statistics and Health dataset provided by the North Carolina Department of Health and Human Services. Acknowledging substantial variations in county sizes, as highlighted in the second graph, I opted to shift the focus toward examining the ratio of primary care physicians to residents. This choice offers a more equitable comparison, considering the difference in population size of the counties of interest. By emphasizing ratios over raw numbers, we gain a more nuanced understanding of healthcare accessibility in relation to the population size of each county.

Population Trends Across Three NC Counties

As per the Healthy North Carolina 2030 goals set by the North Carolina Institute of Medicine, the optimal physician-to-population ratio stands at 1:1500. In the visual representation below, I’ve charted the actual physician-to-population ratios for the three examined counties. Accompanying this chart is a reference line, showcasing the target ratio proposed by the North Carolina Institute of Medicine.

Physician to Population Ratio Across Three NC Counties

Analyzing the data across Mecklenburg, Guilford, and Cumberland counties, a notable trend emerges. Mecklenburg and Guilford counties consistently surpass the ideal physician-to-population ratio. This aligns with expectations, considering their urban profiles, higher income potential, and developmental status, making them attractive destinations for physicians.

In contrast, Cumberland County experiences dips below the optimal ratio in specific years, notably in 2011, 2017, 2018, 2019, and 2022. This pattern corresponds with Cumberland’s relatively rural character, where a scattering of towns and cities, led by Fayetteville, constitutes the majority of the population.

As the nation grapples with a primary care shortage, rural counties like Cumberland bear the brunt of the impact. Implementing technologies such as telemedicine and expanding the role of Nurse Practitioners and Physician Associates can serve as crucial measures to address healthcare disparities in these rural communities.

Recognizing the enduring significance of primary care physicians in public health, these professionals play a vital role in disease prevention and detection through routine check-ups. Moreover, they provide essential health education to patients and effectively manage chronic diseases. As we navigate the complexities of healthcare access, it becomes increasingly evident that sustaining a robust primary care infrastructure is indispensable for promoting the health of our communities.

Goals and Outcomes

Synthesizing Data with Context from Valid Sources: To enhance the depth of my analysis, I factored in the county tier rankings along with the physician ratio guidelines outlined by the North Carolina Institute of Medicine’s Healthy North Carolina 2030 initiative. This additional layer of information contributes valuable context to the examination, offering insights into the broader healthcare goals and standards set for the state.

Integrating Multiple Data Sources: I integrated data from both the North Carolina Department of Health and Human Services and the US Census to formulate a comprehensive physician-to-population ratio. This step allowed for a more robust and nuanced analysis, providing a clearer picture of the healthcare landscape across the selected counties.

Creating Clear Visualizations

Questioning Data Validity: Examining the graphs of primary care physician counts across the three counties, I noticed a common pattern with a peak around 2015 or 2016. To ensure accuracy, I attempted to cross-verify this data using other sources reporting primary care physician numbers in North Carolina by county. Despite my efforts, I couldn’t find additional information or an explanation for the observed peak. However, I proceeded with the analysis, trusting the North Carolina Department of Health and Human Services as the most reliable source for this data.

Dataset source: https://linc.osbm.nc.gov/

County Population source: https://www.census.gov/

North Carolina Healthy People 2030 Primary Care Goals: https://nciom.org/wp-content/uploads/2020/01/Primary-Care-Workforce.pdf