Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing these datasets can aid in the development of machine learning algorithms, particularly for lesion identification, brain health quantification, and prognosis. These algorithms thrive on large amounts of information, but require diverse datasets to avoid overfitting to specific populations or acquisitions. While there are many large public MRI datasets, few of these include acute stroke. We describe clinical MRI using diffusion-weighted, fluid-attenuated and T1-weighted modalities for 1715 individuals admitted in the upstate of South Carolina, of whom 1461 have acute ischemic stroke. Demographic and impairment data are provided for 1106 of the stroke survivors from this cohort. Our validation demonstrates that machine learning can leverage the imaging data to predict stroke severity as measured by the NIH Stroke Scale/Score (NIHSS). We share not only the raw data, but also the scripts for replicating our findings. These tools can aid in education, and provide a benchmark for validating improved methods.

OBJECTIVE: In hospitalized patients, cigarette smoking is linked to increased readmission rates, emergency department visits, and overall mortality. Smoking cessation reduces these risks, but many patients who smoke are unsuccessful in quitting. Nicotine replacement therapy (NRT) is an effective tool that assists patients who smoke with quitting. This study evaluates NRT prescriptions during and after hospitalization at a large health system for patients who smoke.
METHODS: A retrospective cohort study was conducted to determine the number of patients who were prescribed NRT during an inpatient admission and at time of discharge from a network of nine hospitals across South Carolina between January 1, 2019 and January 1, 2023.
RESULTS: This study included 20,757 patients identified as actively smoking with at least one hospitalization during the study period. Of the cohort, 34.9% were prescribed at least one prescription for NRT during their admission to the hospital. Of the patients identified, 12.6% were prescribed NRT upon discharge from the hospital.
CONCLUSIONS: This study identified significantly low rates of NRT prescribed to smokers during hospitalization and at discharge. Although the management of chronic conditions is typically addressed in the outpatient setting, hospitalization may provide an opportunity for patients to initiate health behavior changes. The low rates of prescriptions for NRT present an opportunity to improve tobacco treatment during hospitalization and beyond.

UNASSIGNED: Intimate partner violence (IPV) is a significant public health issue, with a 25% lifetime prevalence. Screening for IPV in primary care is a recommended practice whose effectiveness is debated.
UNASSIGNED: To assess the effect of an electronic health record (EHR)-based multifactorial intervention screening on the detection of IPV risk in primary care practice.
UNASSIGNED: This cluster randomized clinical trial used a stepped-wedge design to assign 15 family medicine primary care clinics in the Medical University of South Carolina Health System in the Charleston region to 3 matched blocks from October 6, 2020, to March 31, 2023. All women aged 18 to 49 years who were seen in these clinics participated in this study.
UNASSIGNED: A noninterruptive EHR alert combined with confidential screening by computer questionnaire using the EHR platform followed by risk assessment and a decision support template.
UNASSIGNED: The main outcomes were the rate at which patients were screened for IPV across the clinics and the rate at which patients at risk for IPV were detected by screening procedures.
UNASSIGNED: The study clinics cared for 8895 unique patients (mean [SD] age, 34.6 [8.7] years; 1270 [14.3%] with Medicaid or Medicare and 7625 [85.7%] with private, military, or other insurance) over the study period eligible for the screening intervention. The intervention had significant effects on the overall rate of screening for IPV, increasing the rate of screening from 45.2% (10 268 of 22 730 patient visits) to 65.3% (22 303 of 34 157 patient visits) when the noninterruptive alert was active (relative risk, 1.46 [95% CI, 1.44-1.49]; P < .001). The confidential screening process was more effective than baseline nurse-led oral screening at identifying patients reporting past-year IPV (130 of 8895 patients [1.5%] vs 9 of 17 433 patients [0.1%]).
UNASSIGNED: The intervention was largely effective in increasing screening adherence and the positive detection rate of IPV in primary care. A highly private approach to screening for IPV in primary care may be necessary to achieve adequate detection rates while addressing potential safety issues of patients experiencing IPV.
UNASSIGNED: ClinicalTrials.gov Identifier: NCT06284148.

The Centers for Disease Control and Prevention (CDC) continues to promote the utilization of electronic health records (EHRs) to support population health management and reduce disparities. However, access to EHRs with capabilities to disaggregate data or generate digital dashboards is not always readily available in rural areas. With funding from CDC\'s DP-18-1815, the Division of Diabetes and Heart Disease Management (Division) at the South Carolina Department of Health and Environmental Control designed a quality improvement initiative to reduce health disparities for people with hypertension and high blood cholesterol in rural areas. With support from a nonprofit partner, the Division used qualitative evaluation methods to evaluate the extent to which practices were able to disaggregate data and report quality measures.

BACKGROUND: Access to mental and physical healthcare in rural areas is challenging for Veterans and their families but essential for good health. Even though recent research has revealed some of the challenges rural Veterans face accessing healthcare, a complete understanding of the gap in access is still unclear.
METHODS: This qualitative study aimed to explore participants\' perceptions of healthcare access. Structured interviews were conducted with 124 Veterans and spouses of Veterans from rural qualifying counties in South Carolina and Florida.
RESULTS: The study\'s results revealed five main dimensions of access: geographic proximity, transportation, communication, cultural competence, and resources. Distance to service needed can negatively impact access for Veterans and their families in general, especially for those whose health is declining or who cannot drive because of their age. Lack of transportation, problems with transportation services, and lack of public transportation can lead to delays in care. Additionally, the lack of communication with the Veterans Affairs (VA) Health System and with the healthcare team, as well as inefficient communication among the healthcare team, lack of coordination of care between the VA health system and community providers, and the lack of cultural competence of healthcare providers and contracted personnel made access to services even more challenging.
CONCLUSIONS: Improving communication can help to develop a sense of trust between Veterans and the VA, and between Veterans and spouses with the healthcare team. It can also lead to increased patient satisfaction. Ensuring healthcare providers and contracted personnel are culturally competent to talk and treat Veterans can improve patient trust and adherence to treatment. Lastly, resource-related challenges included financial problems, lack of prompt access to appointments, lack of providers, limited access to local clinics and hospitals, limited local programs available, and reimbursement issues.

BACKGROUND: Children with medical complexity (CMC) comprise < 1% of the pediatric population, but account for nearly one-third of healthcare expenditures. Further, while CMC account for up to 80% of pediatric inpatient hospital costs, only 2% of Medicaid spending is attributed to home healthcare. As a result, the current health system heavily relies on family caregivers to fill existing care gaps. This study aimed to: (1) examine factors associated with hospital admissions among CMC and (2) contextualize the potential for home nursing care to improve outcomes among CMC and their families in South Carolina (SC).
METHODS: This mixed-methods study was conducted among CMC, their family caregivers, and physicians in SC. Electronic health records data from a primary care clinic within a large health system (7/1/2022-6/30/2023) was analyzed. Logistic regression examined factors associated with hospitalizations among CMC. In-depth interviews (N = 15) were conducted among physicians and caregivers of CMC statewide. Patient-level quantitative data is triangulated with conceptual findings from interviews.
RESULTS: Overall, 39.87% of CMC experienced ≥ 1 hospitalization in the past 12 months. CMC with higher hospitalization risk were dependent on respiratory or neurological/neuromuscular medical devices, not non-Hispanic White, and demonstrated higher healthcare utilization. Interview findings contextualized efforts to reduce hospitalizations, and suggested adaptations related to capacity and willingness to provide complex care for CMC and their families.
CONCLUSIONS: Findings may inform multi-level solutions for accessible, high-quality home nursing care among CMC and their families. Providers may learn from caregivers\' insight to emphasize family-centered care practices, acknowledging time and financial constraints while optimizing the quality of medical care provided in the home.

BACKGROUND: Birthing people in the United States face numerous challenges when accessing adequate prenatal care (PNC), with transportation being a significant obstacle. Nevertheless, previous studies that relied solely on the distance to the nearest provider cannot differentiate the effects of travel burden on provider selection and care utilization. These may exaggerate the degree of inequality in access and fail to capture perceived travel burden. This study investigated whether travel distances to the initially visited provider, to the predominant PNC provider, and perceived travel burden (measured by the travel disadvantage index (TDI)) are associated with PNC utilization.
METHODS: A retrospective cohort of people with live births were identified from South Carolina Medicaid claims files in 2015-2018. Travel distances were calculated using Google Maps. The estimated TDI was derived from local pilot survey data. PNC utilization was measured by PNC initiation and frequency. Repeated measure logistic regression test was utilized for categorical variables and one-way repeated measures ANOVA for continuous variables. Unadjusted and adjusted ordinal logistic regressions with repeated measure were utilized to examine the association of travel burdens with PNC usage.
RESULTS: For 25,801 pregnancies among those continuously enrolled in Medicaid, birthing people traveled an average of 24.9 and 24.2 miles to their initial and predominant provider, respectively, with an average TDI of -11.4 (SD, 8.5). Of these pregnancies, 60% initiated PNC in the first trimester, with an average of 8 total visits. Compared to the specialties of initial providers, predominant providers were more likely to be OBGYN-related specialists (81.6% vs. 87.9%, p < .001) and midwives (3.5% vs. 4.3%, p < .001). Multiple regression analysis revealed that every doubling of travel distance was associated with less likelihood to initiate timely PNC (OR: 0.95, p < .001) and a lower visit frequency (OR: 0.85, p < .001), and every doubling of TDI was associated with less likelihood to initiate timely PNC (OR: 0.94, p = .04).
CONCLUSIONS: Findings suggest that the association between travel burden and PNC utilization was statistically significant but of limited practical significance.

This paper presents a deep-learning-based method to detect recreational vessels. The method takes advantage of existing underwater acoustic measurements from an Estuarine Soundscape Observatory Network based in the estuaries of South Carolina (SC), USA. The detection method is a two-step searching method, called Deep Scanning (DS), which includes a time-domain energy analysis and a frequency-domain spectrum analysis. In the time domain, acoustic signals with higher energy, measured by sound pressure level (SPL), are labeled for the potential existence of moving vessels. In the frequency domain, the labeled acoustic signals are examined against a predefined training dataset using a neural network. This research builds training data using diverse vessel sound features obtained from real measurements, with a duration between 5.0 seconds and 7.5 seconds and a frequency between 800 Hz to 10,000 Hz. The proposed method was then evaluated using all acoustic data in the years 2017, 2018, and 2021, respectively; a total of approximately 171,262 2-minute.wav files at three deployed locations in May River, SC. The DS detections were compared to human-observed detections for each audio file and results showed the method was able to classify the existence of vessels, with an average accuracy of around 99.0%.

UNASSIGNED: Undetectable = Untransmittable (U = U) means that people with HIV who achieve and maintain an undetectable viral load have effectively zero risk of sexually transmitting the virus to others. However, research on how U = U is perceived by older adults living with HIV (OAH) is currently lacking. This study explored U = U views among OAH. From October 2019 to February 2020, we conducted open-ended interviews with 24 OAH recruited at an HIV clinic in South Carolina. Interviews were audio-recorded and transcribed. We employed thematic analysis in this study. Three themes emerged from the analysis: (a) Conflicting beliefs in U = U; (b) Use condoms regardless; and (c) Fear of HIV reinfection. Despite strong scientific evidence supporting U = U, some OAH do not believe in U = U. This lack of belief could deprive OAH of the benefits U = U offers. Therefore, it is vital to educate OAH about U = U to enhance their understanding and belief in U = U.

OBJECTIVE: Unnecessary cesarean delivery increases the risk of complications for birthing people and infants.
BACKGROUND: Examining the intersectionality of rural and racial disparities in low-risk cesarean delivery is necessary to improve equity in quality obstetrics care.
OBJECTIVE: To evaluate rural and racial/ethnic differences in Nulliparous, Term, Singleton, Vertex (NTSV) and primary cesarean delivery rates before and during the COVID-19 pandemic in South Carolina.
METHODS: This retrospective cohort study used birth certificates linked to all-payer hospital discharge data for South Carolina childbirths from 2018 to 2021. Multilevel logistic regressions examined differences in cesarean outcomes by rural/urban hospital location and race/ethnicity of birthing people during pre-pandemic (January 2018-February 2020) and peri-pandemic periods (March 2020-December 2021), adjusting for maternal, infant, and hospital characteristics among two low-risk pregnancy cohorts: 1) Nulliparous, Term, Singleton, Vertex (NTSV, n = 65,974) and 2) those without prior cesarean (primary, n = 167,928).
RESULTS: Black vs. White disparities remained for NTSV cesarean in adjusted models (urban pre-pandemic aOR = 1.34, 95 %CI 1.23-1.46) but were not significantly different for primary cesarean, apart from rural settings peri-pandemic (aOR = 0.87, 95 %CI 0.79-0.96). Hispanic individuals had higher adjusted odds of NTSV cesarean only for rural settings pre-pandemic (aOR = 1.28, 95 %CI 1.05-1.56), but this disparity was not significant during the pandemic (aOR = 1.13, 95 %CI 0.93-1.37).
CONCLUSIONS: Observed rural and racial/ethnic disparities in cesarean delivery outcomes were present before and during the COVID-19 pandemic. Strategies effective in reducing racial disparities in primary cesarean may be useful in also reducing Black vs. White NTSV cesarean disparities.