An Interactive Modeling Tool for Projecting the Health and Direct Medical Cost Impact of Changes in the Sexually Transmitted Diseases Prevention Program Budgets.

CONTEXT: Estimating the return on investment for public health services, tailored to the state level, is critical for demonstrating their value and making resource allocation decisions. However, many health departments have limited staff capacity and expertise to conduct economic analyses in-house. PROGRAM: We developed a user-friendly, interactive Excel-based spreadsheet model that health departments can use to estimate the impact of increases or decreases in sexually transmitted infection (STI) prevention funding on the incidence and direct medical costs of chlamydia, gonorrhea, syphilis, and STI-attributable HIV infections. Users tailor results to their jurisdictions by entering the size of their population served; the number of annual STI diagnoses; their prior annual funding amount; and their anticipated new funding amount. The interface was developed using human-centered design principles, including focus groups with 15 model users to collect feedback on an earlier model version and a usability study on the prototype with 6 model users to finalize the interface. IMPLEMENTATION: The STI Prevention Allocation Consequences Estimator ("SPACE Monkey 2.0") model will be publicly available as a free downloadable tool. EVALUATION: In the usability testing of the prototype, participants provided overall positive feedback. They appreciated the clear interpretations, outcomes expressed as direct medical costs, functionalities to interact with the output and copy charts into external applications, visualization designs, and accessible information about the model's assumptions and limitations. Participants provided positive responses to a 10-item usability evaluation survey regarding their experiences with the prototype. DISCUSSION: Modeling tools that synthesize literature-based estimates and are developed with human-centered design principles have the potential to make evidence-based estimates of budget changes widely accessible to health departments.

Variation in Patterns of Racial and Ethnic Disparities in Primary and Secondary Syphilis Diagnosis Rates Among Heterosexually Active Women by Region and Age Group in the United States.

BACKGROUND: Syphilis rates have increased substantially over the past decade. Women are an important population because of negative sequalae and adverse maternal outcomes including congenital syphilis. We assessed whether racial and ethnic disparities in primary and secondary (P&S) syphilis among heterosexually active women differ by region and age group. METHODS: We synthesized 4 national surveys to estimate numbers of heterosexually active women in the United States from 2014 to 2018 by region, race and ethnicity, and age group (18-24, 25-29, 30-44, and ≥45 years). We calculated annual P&S syphilis diagnosis rates, assessing disparities with rate differences and rate ratios comparing White, Hispanic, and Black heterosexually active women. RESULTS: Nationally, annual rates were 6.42 and 2.20 times as high among Black and Hispanic than among White heterosexually active women (10.99, 3.77, and 1.71 per 100,000, respectively). Younger women experienced a disproportionate burden of P&S syphilis and the highest disparities. Regionally, the Northeast had the highest Black-White and Hispanic-White disparities using a relative disparity measure (relative rate), and the West had the highest disparities using an absolute disparity measure (rate difference). CONCLUSIONS: To meet the racial and ethnic disparity goals of the Sexually Transmitted Infections National Strategic Plan, tailored local interventions that address the social and structural factors associated with disparities are needed for different age groups.

Racial and ethnic disparities in HIV diagnoses among heterosexually active persons in the United States nationally and by state, 2018.

BACKGROUND: Despite declining HIV infection rates, persistent racial and ethnic disparities remain. Appropriate calculations of diagnosis rates by HIV transmission category, race and ethnicity, and geography are needed to monitor progress towards reducing systematic disparities in health outcomes. We estimated the number of heterosexually active adults (HAAs) by sex and state to calculate appropriate HIV diagnosis rates and disparity measures within subnational regions. METHODS: The analysis included all HIV diagnoses attributed to heterosexual transmission in 2018 in the United States, in 50 states and the District of Columbia. Logistic regression models estimated the probability of past-year heterosexual activity among adults in three national health surveys, by sex, age group, race and ethnicity, education category, and marital status. Model-based probabilities were applied to estimated counts of HAAs by state, which were synthesized through meta-analysis. HIV diagnoses were overlaid to calculate racial- and ethnic-specific rates, rate differences (RDs), and rate ratios (RRs) among HAAs by sex and state. RESULTS: Nationally, HAA women have a two-fold higher HIV diagnosis rate than HAA men (rate per 100,000 HAAs, women: 6.57; men: 3.09). Compared to White non-Hispanic HAAs, Black HAAs have a 20-fold higher HIV diagnosis rate (RR, men: 21.28, women: 19.55; RD, men: 15.40, women: 31.78) and Hispanic HAAs have a 4-fold higher HIV diagnosis rate (RR, men: 4.68, RD, women: 4.15; RD, men: 2.79, RD, women: 5.39). Disparities were ubiquitous across regions, with >75% of states in each region having Black-to-White RR ≥10. CONCLUSION: The racial and ethnic disparities across regions suggests a system-wide failure particularly with respect to preventing HIV among Black and Hispanic women. Pervasive disparities emphasize the role for coordinated federal responses such as the current Ending the HIV Epidemic (EHE) initiative.

Industry payments and physicians prescriptions: Effect of a payment restriction policy.

The pharmaceutical industry spends billions of dollars every year for marketing its products to US health care providers. This study investigates the association between industry marketing payments and physicians' prescription in New York and Massachusetts, and examines the effect of the Massachusetts payment restriction policy on this association in comparison with the New York State that has no payment restriction policy. Three panel data models (fixed effects regression (FE), first difference regression (FD), and first difference with lagged independent variable (LFD)) were used to establish the association accounting for unobserved confounders and reverse causality. The main indicator is the total amount of industry payments for meals, drug samples, consulting fees, etc. (excluding research funding, and ownership). Dependent variables are a) yearly days' supply of Medicare Part D prescriptions, b) yearly costs of prescribed prescriptions. Secular time trends, as well as differences between the two states were controlled in all models. All three panel models showed significant positive association between industry payments and physician prescriptions. Particularly, these models show that in the base year (2014), a 1% increase in the annual industry payments was associated with (0.01%-0.04%) increase in days' supply of medication, and (0.01%-0.05%) increase in prescription costs for NYS providers. Moreover, FE and FD models show that compared to NYS physicians, the association of industry payments with days' supply and costs of Medicare Part D prescriptions was (0.01%-0.02%) smaller for MA physicians. Because of the smaller sample size and lower power, the LFD model did not detect a significant difference between the NYS and MA providers. The findings of this study provide additional evidence that industry payments are associated with increases in the volume and cost of Medicare prescriptions. Moreover, these findings provide preliminary evidence that payment restriction policies negatively moderate this association, which calls for further research.

A Rapid Review of the Impact of Systems-Level Policies and Interventions on Population-Level Outcomes Related to the Opioid Epidemic, United States and Canada, 2014-2018.

OBJECTIVES: In the United States, rising rates of overdose deaths and recent outbreaks of hepatitis C virus and HIV infection are associated with injection drug use. We updated a 2014 review of systems-level opioid policy interventions by focusing on evidence published during 2014-2018 and new and expanded opioid policies. METHODS: We searched the MEDLINE database, consistent with the 2014 review. We included articles that provided original empirical evidence on the effects of systems-level interventions on opioid use, overdose, or death; were from the United States or Canada; had a clear comparison group; and were published from January 1, 2014, through July 19, 2018. Two raters screened articles and extracted full-text data for qualitative synthesis of consistent or contradictory findings across studies. Given the rapidly evolving field, the review was supplemented with a search of additional articles through November 17, 2019, to assess consistency of more recent findings. RESULTS: The keyword search yielded 535 studies, 66 of which met inclusion criteria. The most studied interventions were prescription drug monitoring programs (PDMPs) (59.1%), and the least studied interventions were clinical guideline changes (7.6%). The most common outcome was opioid use (77.3%). Few articles evaluated combination interventions (18.2%). Study findings included the following: PDMP effectiveness depends on policy design, with robust PDMPs needed for impact; health insurer and pharmacy benefit management strategies, pill-mill laws, pain clinic regulations, and patient/health care provider educational interventions reduced inappropriate prescribing; and marijuana laws led to a decrease in adverse opioid-related outcomes. Naloxone distribution programs were understudied, and evidence of their effectiveness was mixed. In the evidence published after our search's 4-year window, findings on opioid guidelines and education were consistent and findings for other policies differed. CONCLUSIONS: Although robust PDMPs and marijuana laws are promising, they do not target all outcomes, and multipronged interventions are needed. Future research should address marijuana laws, harm-reduction interventions, health insurer policies, patient/health care provider education, and the effects of simultaneous interventions on opioid-related outcomes.