District of Columbia Department of Health

BackgroundLyme disease (LD) is the most common tick-borne illness in the United States (US). Incidence peaks in older adults, yet LD-associated healthcare costs are understudied in this population. This retrospective, observational study assessed LD-associated healthcare costs among US Medicare Fee-for-Service (FFS) beneficiaries aged ≥ 65 years.MethodsEligible LD cases were identified in Medicare FFS claims data (Medicare Parts A, B, and D) from Jan 2016–Jul 2023, had continuous eligibility for the assessment period, and had ≥ 1 outpatient or inpatient LD claim. Outpatient claims had an LD diagnosis code (A69.xx) with qualifying antibiotic treatment within 30 days. Inpatient claims had a primary LD diagnosis code or a secondary LD diagnosis code with a primary LD-linked condition. Cases were classified into subgroups (localized, disseminated, indeterminate) based on LD-associated diagnosis codes, outpatient and inpatient services, and antibiotics. Outcomes included LD-specific (medical) costs during individual LD episodes and all-cause (medical and pharmacy) costs at 6-month follow-up versus 6-month baseline. Comparisons used a paired t test for continuous measures, with significance noted at P< 0.001.ResultsAmong 121,941 identified LD cases, 53.0% were female, 93.4% were White, and the mean (standard deviation) age was 74.0 (6.0) years. Of these, 62.2% had localized LD, 21.3% had disseminated LD, and 16.6% had indeterminate LD. Mean LD-specific total (medical) costs were $1,513 overall and were highest for disseminated cases ($4,554) (Figure 1). Mean all-cause total costs at 6-month follow-up versus 6-month baseline were significantly higher for LD cases overall (Δ$4,378), localized LD cases (Δ$2,638), disseminated LD cases (Δ$9,888), and indeterminate LD cases (Δ$3,841) (Figure 2).ConclusionUS Medicare FFS beneficiaries with LD incurred substantial healthcare costs, especially those with disseminated disease. Strategies to prevent LD cases in older adults may decrease associated economic burden.DisclosuresHolly Yu, MSPH, Pfizer Inc.: Employee; may hold company shares and/or stocks. Peter Kardel, MA, ADVI Health LLC: Employee; may hold company shares and/or stocks. Heidi De Souza, MPH, ADVI Health LLC: Employee; may hold company shares and/or stocks. L. Hannah Gould, PhD, MS, MBA, Pfizer Inc.: Employee; may hold company shares and/or stocks.

The District of Columbia Department of Health (DC Health) has been a recipient of the Centers for Disease Control and Prevention's Colorectal Cancer Control Program funding since 2015. We present details on the partnership model established by DC Health to increase screening uptake among populations with low levels of colorectal cancer (CRC) screening. We examined the DC Health partnership model using a mixed-methods case study approach. DC Health's CRC screening program uses a socioecological framework approach, focusing on the individual, interpersonal, organization, and community levels, to work with partners to increase CRC screening by implementing evidence-based interventions. We present details on the role of each partner, their socioecological model of influence, and key responsibilities. The DC Health partnership supported implementation of evidence-based interventions and CRC screening in nine health systems that serve patient populations with high CRC risk factors and historically low CRC screening trends. CRC screening uptake among health system partners increased from 19% in 2015 to 53% by 2022, surpassing the average screening rate in DC's Federally Qualified Health Centers (47%). The DC Health experience illustrates how multi-level partnerships can contribute to increasing CRC screening.

The DC Cohort is a longitudinal HIV cohort study of people with HIV receiving care at 14 clinical sites in Washington, DC, led by George Washington University. Data are routinely linked to the DC Department of Health (DC Health) HIV surveillance databases to increase data completeness and accuracy and to help identify people with HIV enrolled at multiple sites. The ATra Black Box (Black Box henceforth) is a novel privacy technology developed by Georgetown University, which is currently deployed in 40 public health jurisdictions. The Black Box provides a secure mechanism to link private health information across data systems. The Black Box was modified for the purposes of linking data from the DC Cohort to DC Health surveillance data and increasing the ease, feasibility, accuracy, and timeliness of future linkages. These modifications included providing deidentified data to George Washington University and developing analytic code to compare data between the DC Cohort and DC Health to report on data discrepancies. This paper reports on the results of the initial linkage using the Black Box. DC Cohort data on all consented participants from January 2011 through September 2022 were submitted to the Black Box. Simultaneously, all DC Health HIV surveillance data were also submitted to the Black Box. The data were matched using a predetermined algorithm, match-level scores were assigned, and matches were manually verified. The new Black Box graphical user interface allows users to check files for errors and easily track the Black Box processes and provides analytic plugins for running SAS code. A total of 9744 records of DC Cohort participants were submitted for matching to DC Health. Of these, 9060 participants (93.0%) matched to surveillance data and were validated through manual review. Match-level scores ranged from 20 to 100, and the validation found that scores of 61 and above were true matches. The SAS output files provided information on missing or conflicting data, including lab records, date of HIV diagnosis, and other key demographics. The linkage resulted in the addition of 48,970 CD4 T-lymphocyte counts, 33,413 viral load lab records, and 767 previously unrecognized deaths. Among the DC Cohort participants, 470 were enrolled at more than one site and 17 at more than two sites. The implementation of the Black Box for sharing DC Cohort and DC Health data resulted in better capture of HIV lab records, improved vital status information, and enhanced characterization of care patterns for people with HIV enrolled in the DC Cohort. Future linkages will include DC Health data on diagnoses of sexually transmitted infections, hepatitis, and tuberculosis.

Patient initiated transport refusal during Emergency Medical Service (EMS) opioid overdose encounters has become an endemic problem. This study aimed to quantify circumstantial and environmental factors which predict refusal of further care. In this cross-sectional analysis, a case definition for opioid overdose was applied retrospectively to EMS encounters. Selected cases had sociodemographic and situational/incident variables extracted using patient information and free text searches of case narratives. 50 unique binary variables were used to build a logistic model. Prehospital EMS overdose encounters in Washington, DC, USA, from July 2017 to July 2023. Of EMS encounters in the study timeframe, 14 587 cases were selected as opioid overdoses. Predicted probability for covariates was the outcome variable. Model performance was assessed using Stratified K-Fold Cross-Validation and scored with positive predictive value, sensitivity and F1. Prediction accuracy and McFadden's pseudo-R squared are also determined. The model achieved a predictive accuracy of 78% with a high positive predictive value (0.83) and moderate sensitivity (0.68). Bystander type influenced the refusal outcome, with decreased refusal probability associated with family (nondescript) (-28%) and parents (-16%), while presence of a girlfriend increased it (+28%). Negative situational factors like noted physical trauma (-62%), poor weather (-14%) and lack of housing (-14%) decreased refusal probability. Characteristics of the emergency response team, like a prior crew member encounter (+20%) or crew experience <1year (-36%), had a variable association with transport. Refusal of emergency transport for opioid overdose cases in Washington, DC, USA, has expanded by 43.8% since 2017. Several social, environmental and systematic factors can predict this refusal. Logistic regression models can be used to quantify broad categories of behavior in surveillance medical research.

Objective: To assess the impact of the coronavirus disease 2019 (COVID-19) pandemic on breastfeeding initiation (BFI) and duration among women enrolled in the Special Supplemental Nutrition Program for women, infants, and children (WIC) in Washington District of Columbia (DC). Materials and Methods: We used WIC program data from Washington DC to assess the pandemic's impact on BFI and duration among WIC recipients. t-Tests and unadjusted odds ratios compared breastfeeding outcomes before and during the pandemic. Multivariable logistic and linear regression models estimated the pandemic's impact on initiation and duration, respectively, while controlling for social determinants of health and other factors. Results: BFI was similar among women who gave birth before (61.4%) or during the pandemic (60.4%) (p = 0.359). However, the proportion of women who breastfed at 1 month decreased significantly from 56.1% (before pandemic) to 47.6% (during pandemic) (p < 0.0001). This pattern for duration continued at 3 and 6 months: 46.9% to 37.1% (p < 0.0001) at 3 months and 34.8% to 25.7% (p < 0.0001) at 6 months. On average, women who delivered during the pandemic breastfed 33.9 fewer days than those who delivered before (p < 0.0001). Conclusions: BFI among DC WIC recipients was similar for infants born before or during the pandemic, and determinants of initiation remained similar to previous reports (e.g., race/ethnicity, education). However, for women who initiated breastfeeding, average duration was significantly lower for infants born during the pandemic than before. Our findings suggest the importance of leveraging WIC and other breastfeeding supports to promote breastfeeding during pandemics and other emergencies.

Rapid antiretroviral therapy initiation (R-ART) for treatment of HIV has been recommended since 2017, however it has not been adopted widely across the US. The study purpose was to understand facilitators and barriers to R-ART implementation in the U.S. This was a qualitative design involving semi-structured interviews. The study sample was comprised of the medical leadership of nine US HIV clinics that were early implementers of R-ART. In-depth, semi-structured interviews were performed. The Consolidated Framework for Implementation Research (CFIR) was used to guide thematic analysis. We identified three main content areas: strong scientific rationale for R-ART, buy-in from multiple key stakeholders, and the condensed timeline of R-ART. The CFIR construct of Evidence Strength and Quality was cited as an important factor in R-ART implementation. Buy-in from key stakeholders and immediate access to medications ensured the success of R-ART implementation. Patient acceptance of the condensed timeline for ART initiation was facilitated when presented in a patient-centered manner, including empathetic communication and addressing other patient needs concurrently. The condensed timeline of R-ART presented logistical challenges and opportunities for the development of intense patient-provider relationships. Results from the analysis showed that R-ART implementation should address the following: 1) logistical planning to implement HIV treatment with a condensed timeline 2) patients' mixed reactions to a new HIV diagnosis and 3) the high cost of HIV medications.

From 2015 to 2020, the THRIVE project supported 7 US health departments to improve HIV prevention services for Black or African American (Black) and Hispanic or Latino gay, bisexual, and other men who have sex with men (GBM) and transgender women (TGW). We described services provided in the THRIVE PrEP continuum. Using Poisson regression models, we estimated associations between race or ethnicity and age and PrEP screening, linkage, and prescription. We examined associations between colocation of services and PrEP linkage and prescription for 2 sites. THRIVE served 12,972 GBM without HIV; 37% of PrEP-eligible GBM were prescribed PrEP. THRIVE served 1185 TGW without HIV; 45% of PrEP-eligible TGW were prescribed PrEP. Black and Hispanic or Latino GBM were 29% (RR = 0.71, 95% CI: 0.66-0.77) and 19% (RR = 0.81, 95% CI: 0.75-0.87) less likely, respectively, to be prescribed PrEP than White GBM. GBM aged 18-24 years and 55 years or older were 19% (RR = 0.81, 95% CI: 0.75-0.87) and 22% (RR = 0.78, 95% CI: 0.67-0.9) less likely, respectively, to be prescribed PrEP compared with those aged 35-44 years. Colocated services were associated with a 54% (RR = 1.54, 95% CI: 1.44-1.64) and a 31% (RR = 1.31, 95% CI: 1.19-1.43) greater likelihood of PrEP linkage and prescription, respectively, compared with services at different locations. THRIVE provided PrEP to higher proportions of PrEP-eligible persons than current national estimates; however, PrEP use disparities persist. Colocation of services may be a useful component of jurisdictional strategies to increase PrEP coverage.

Abstract BackgroundThe 2022 mpox outbreak infected over 30,000 people in the United States. Infections were commonly associated with sexual contact between men. Interventions included vaccination and reductions in sexual partnerships. We estimated the averted infections attributable to each intervention using mathematical modeling.MethodsWe fit a dynamic network transmission model to mpox cases reported by the District of Columbia through January 2023. We incorporated vaccine administration data and reported reductions in sexual partnerships among gay, bisexual, or other men who have sex with men (MSM). Model output consisted of predicted cases over time with or without vaccination and/or behavior change.ResultsWe estimated initial case reductions were due to behavior change. Vaccination alone averted 64% [IQR:57%-72%] and behavior change alone averted 21% [IQR:11%-29%] of cases. Vaccination and behavior change together averted 80% [IQR:74%-85%] of cases. In the absence of vaccination, behavior change reduced cumulative cases but also prolonged the outbreak.ConclusionsInitial case declines were likely caused by behavior change, but vaccination averted more cases overall. Overall, this indicates that encouraging individuals to protect themselves was vital in the early outbreak, but that combination with a robust vaccination program was ultimately required for control.