BACKGROUND: Pre-exposure prophylaxis (PrEP) is a highly effective pharmaceutical intervention that prevents HIV infection, but PrEP uptake across the US has been slow among men who have sex with men (MSM), especially among Black/African American (B/AA) and Hispanic /Latino (H/L) MSM. This study investigates the acceptability and essential components of a peer-driven intervention (PDI) for promoting PrEP uptake among MSM, with a specific focus on B/AA and H/L communities. METHODS: We conducted 28 semi-structured, qualitative interviews with MSM in southern New England to explore the components of a PDI, including attitudes, content, and effective communication methods. A purposive sampling strategy was used to recruit diverse participants who reflect the communities with the highest burden of HIV infection. RESULTS: Of 28 study participants, the median age was 28 years (interquartile range [IQR]: 25, 35). The sample comprised B/AA (39%, n = 11) and H/L (50%, n = 14) individuals. Notably, nearly half of the participants (46%) were current PrEP users. We found that many participants were in favor of using a PDI approach for promoting PrEP. Additionally, several participants showed interest in becoming peer educators themselves. They emphasized the need for strong communication skills to effectively teach others about PrEP. Moreover, participants noted that peer education should cover key topics like how PrEP works, how effective it is, and any possible side effects. CONCLUSIONS: Our study shows that effective PDIs, facilitated by well-trained peers knowledgeable about PrEP, could enhance PrEP uptake among MSM, addressing health disparities and potentially reducing HIV transmission in B/AA and H/L communities.

BACKGROUND: The syndemic nature of gonococcal infections and HIV provides an opportunity to develop a synergistic intervention tool that could address the need for adequate treatment for gonorrhea, screen for HIV infections, and offer pre-exposure prophylaxis (PrEP) for persons who meet the criteria. By leveraging information available on electronic health records, a clinical decision support (CDS) system tool could fulfill this need and improve adherence to Centers for Disease Control and Prevention (CDC) treatment and screening guidelines for gonorrhea, HIV, and PrEP. OBJECTIVE: The goal of this study was to translate portions of CDC treatment guidelines for gonorrhea and relevant portions of HIV screening and prescribing PrEP that stem from a diagnosis of gonorrhea as an electronic health record-based CDS intervention. We also assessed whether this CDS solution worked in real-world clinic. METHODS: We developed 4 tools for this CDS intervention: a form for capturing sexual history information (SmartForm), rule-based alerts (best practice advisory), an enhanced sexually transmitted infection (STI) order set (SmartSet), and a documentation template (SmartText). A mixed methods pre-post design was used to measure the feasibility, use, and usability of the CDS solution. The study period was 12 weeks with a baseline patient sample of 12 weeks immediately prior to the intervention period for comparison. While the entire clinic had access to the CDS solution, we focused on a subset of clinicians who frequently engage in the screening and treatment of STIs within the clinical site under the name "X-Clinic." We measured the use of the CDS solution within the population of patients who had either a confirmed gonococcal infection or an STI-related chief complaint. We conducted 4 midpoint surveys and 3 key informant interviews to quantify perception and impact of the CDS solution and solicit suggestions for potential future enhancements. The findings from qualitative data were determined using a combination of explorative and comparative analysis. Statistical analysis was conducted to compare the differences between patient populations in the baseline and intervention periods. RESULTS: Within the X-Clinic, the CDS alerted clinicians (as a best practice advisory) in one-tenth (348/3451, 10.08%) of clinical encounters. These 348 encounters represented 300 patients; SmartForms were opened for half of these patients (157/300, 52.33%) and was completed for most for them (147/300, 89.81%). STI test orders (SmartSet) were initiated by clinical providers in half of those patients (162/300, 54%). HIV screening was performed during about half of those patient encounters (191/348, 54.89%). CONCLUSIONS: We successfully built and implemented multiple CDC treatment and screening guidelines into a single cohesive CDS solution. The CDS solution was integrated into the clinical workflow and had a high rate of use.

BACKGROUND: Syphilis in Florida increased 49% from 2016-2020. Moreover, many serological tests for syphilis (STS) do not indicate current infection. Traditionally, syphilis surveillance systems used reactor grids, a method for prioritizing STS for investigation based on age, non-treponemal titer, and/or sex. In 2022, Florida's STD surveillance system implemented an automated method for processing electronically reported STS (eSTS), expanding upon the reactor grid, using an individual's current STS (treponemal and non-treponemal), treatment history, and historical STS results aiming for more efficiently processing eSTS. We compared the new method of processing eSTS results against the reactor grid and determined potential value in time/cost savings of this change. METHODS: All eSTS (n = 4,144) from 1/2/2023-1/8/2023 were compared by how the logic-based method processed test results vs. how the reactor grid processed test results. Each method was compared using measurements of accuracy (e.g., sensitivity/specificity). Time and cost savings in eSTS processing were estimated. RESULTS: Using the surveillance case definition as reference, the accuracy of the logic-based method for processing eSTS was nearly double (82.3% vs. 43.6%), had greater specificity (79.0% vs. 33.0%), and increased positive predictive value (47.5% vs. 22.0%) when compared to the reactor grid method. Sensitivity (99.5% vs. 98.6%) and negative predictive value (99.9% vs. 99.2%) remained similar. The logic-based method is estimated to save 7,783 hours annually (~$185,000). CONCLUSIONS: Processing eSTS based on current and historical STS results is significantly more accurate than using a reactor grid. Moreover, these improvements save time and resources that can be better allocated to other program prevention activities.

We combined field-based data with mathematical modeling to estimate the effectiveness of smartphone-enabled COVID-19 exposure notification in Pennsylvania, USA. We estimated that digital notifications potentially averted 7-69 cases/1,000 notifications during November 8, 2020-January 2, 2021. Greater use and increased compliance could increase the effectiveness of digital notifications.

BACKGROUND: Chlamydia and gonorrhea cases continue to rise in Illinois, increasing by 16.4% and 70.9% in 2019, respectively, compared with 2015. Providers are required to report both chlamydia and gonorrhea, as mandated by public health laws. Manual reporting remains a huge burden; 90%-93% of cases were reported to Illinois Department of Public Health (IDPH) via electronic laboratory reporting (ELR), and the remaining were reported through web-based data entry platforms, faxes, and phone calls. However, cases reported via ELRs only contain information available to a laboratory facility and do not contain additional data needed for public health. Such data are typically found in an electronic health record (EHR). Electronic case reports (eCRs) were developed and automated the generation of case reports from EHRs to be reported to public health agencies. OBJECTIVE: Prior studies consolidated trigger criteria for eCRs, and compared with manual reporting, found it to be more complete. The goal of this project is to pilot standards-based eCR for chlamydia and gonorrhea. We evaluated the throughput, completeness, and timeliness of eCR compared to ELR, as well as the implementation experience at a large health center-controlled network in Illinois. METHODS: For this study, we selected 8 clinics located on the north, west, and south sides of Chicago to implement the eCRs; these cases were reported to IDPH. The study period was 52 days. The centralized EHR used by these clinics leveraged 2 of the 3 case detection scenarios, which were previously defined as the trigger, to generate an eCR. These messages were successfully transmitted via Health Level 7 electronic initial case report standard. Upon receipt by IDPH, these eCRs were parsed and housed in a staging database. RESULTS: During the study period, 183 eCRs representing 135 unique patients were received by IDPH. eCR reported 95% (n=113 cases) of all the chlamydia cases and 97% (n=70 cases) of all the gonorrhea cases reported from the participating clinical sites. eCR found an additional 14 (19%) cases of gonorrhea that were not reported via ELR. However, ELR reported an additional 6 cases of chlamydia and 2 cases of gonorrhea, which were not reported via eCR. ELR reported 100% of chlamydia cases but only 81% of gonorrhea cases. While key elements such as patient and provider names were complete in both eCR and ELR, eCR was found to report additional clinical data, including history of present illness, reason for visit, symptoms, diagnosis, and medications. CONCLUSIONS: eCR successfully identified and created automated reports for chlamydia and gonorrhea cases in the implementing clinics in Illinois. eCR demonstrated a more complete case report and represents a promising future of reducing provider burden for reporting cases while achieving greater semantic interoperability between health care systems and public health.

BACKGROUND: Clinicians increasingly serve youths from societal/cultural backgrounds different from their own. This raises questions about how to interpret what such youths report. Rescorla et al. (2019, European Child & Adolescent Psychiatry, 28, 1107) found that much more variance in 72,493 parents' ratings of their offspring's mental health problems was accounted for by individual differences than by societal or cultural differences. Although parents' reports are essential for clinical assessment of their offspring, they reflect parents' perceptions of the offspring. Consequently, clinical assessment also requires self-reports from the offspring themselves. To test effects of individual differences, society, and culture on youths' self-ratings of their problems and strengths, we analyzed Youth Self-Report (YSR) scores for 39,849 11-17 year olds in 38 societies. METHODS: Indigenous researchers obtained YSR self-ratings from population samples of youths in 38 societies representing 10 culture cluster identified in the Global Leadership and Organizational Behavioral Effectiveness study. Hierarchical linear modeling of scores on 17 problem scales and one strengths scale estimated the percent of variance accounted for by individual differences (including measurement error), society, and culture cluster. ANOVAs tested age and gender effects. RESULTS: Averaged across the 17 problem scales, individual differences accounted for 92.5% of variance, societal differences 6.0%, and cultural differences 1.5%. For strengths, individual differences accounted for 83.4% of variance, societal differences 10.1%, and cultural differences 6.5%. Age and gender had very small effects. CONCLUSIONS: Like parents' ratings, youths' self-ratings of problems were affected much more by individual differences than societal/cultural differences. Most variance in self-rated strengths also reflected individual differences, but societal/cultural effects were larger than for problems, suggesting greater influence of social desirability. The clinical significance of individual differences in youths' self-reports should thus not be minimized by societal/cultural differences, which-while important-can be taken into account with appropriate norms, as can gender and age differences.

BACKGROUND: Optimizing STD reporting to state public health authorities is important to reduce incidence and manage outbreaks of STDs. Electronic lab reporting (ELR) is the standard through which local clinics report STDs to state public health authority. Electronic case reporting (eCR) is an alternative approach which automates transmission of case reports to public health jurisdictions using electronic health record (EHR) data. METHODS: Working with three Community Health Centers (CHCs) in Oregon between February 3, 2020 and May 15, 2020, we piloted an automated electronic case reporting (eCR) approach for gonorrhea (GC) and chlamydia (CT) from these clinics to the Oregon Health Authority. We compared the eCR approach to the existing ELR approach to determine completeness of case reporting for GC/CT. RESULTS: A total of 365 eCRs from 206 unique patients were generated. Among 154 instances where the case detection logic was satisfied for chlamydia, 37% (54 instances) were based on the presence of a diagnosis and 63% (97 instances) were based on laboratory data. Among 232 instances where logic was satisfied for gonorrhea, 44% (102 instances) reflected a diagnosis and 56% (130 instances) reflected laboratory results. Data completeness was uniformly equal or higher for eCRs vs. ELRs. CONCLUSIONS: The eCR approach was successful in identifying chlamydia and gonorrhea cases and provided a more complete set of information to assist public health authorities when compared with ELRs. eCR has the potential to automate and relieve staff burden on an important reporting requirement for clinical providers.

BACKGROUND: In the absence of a vaccine or pharmacological treatment, prevention and control of Guinea worm disease is dependent on timely identification and containment of cases to interrupt transmission. The Chad Guinea Worm Eradication Program (CGWEP) surveillance system detects and monitors Guinea worm disease in both humans and animals. Although Guinea worm cases in humans has declined, the discovery of canine infections in dogs in Chad has posed a significant challenge to eradication efforts. A foundational information system that supports the surveillance activities with modern data management practices is needed to support continued program efficacy. METHODS: We sought to assess the current CGWEP surveillance and information system to identify gaps and redundancies and propose system improvements. We reviewed documentation, consulted with subject matter experts and stakeholders, inventoried datasets to map data elements and information flow, and mapped data management processes. We used the Information Value Cycle (IVC) and Data-Information System-Context (DISC) frameworks to help understand the information generated and identify gaps. RESULTS: Findings from this study identified areas for improvement, including the need for consolidation of forms that capture the same demographic variables, which could be accomplished with an electronic data capture system. Further, the mental models (conceptual frameworks) IVC and DISC highlighted the need for more detailed, standardized workflows specifically related to information management. CONCLUSIONS: Based on these findings, we proposed a four-phased roadmap for centralizing data systems and transitioning to an electronic data capture system. These included: development of a data governance plan, transition to electronic data entry and centralized data storage, transition to a relational database, and cloud-based integration. The method and outcome of this assessment could be used by other neglected tropical disease programs looking to transition to modern electronic data capture systems.

BACKGROUND: Public health reporting is the cornerstone of public health practices that inform prevention and control strategies. There is a need to leverage advances made in the past to implement an architecture that facilitates the timely and complete public health reporting of relevant case-related information that has previously not easily been available to the public health community. Electronic laboratory reporting (ELR) is a reliable method for reporting cases to public health authorities but contains very limited data. In an earlier pilot study, we designed the Public Health Automated Case Event Reporting (PACER) platform, which leverages existing ELR infrastructure as the trigger for creating an electronic case report. PACER is a FHIR (Fast Health Interoperability Resources)-based system that queries the electronic health record from where the laboratory test was requested to extract expanded additional information about a case. OBJECTIVE: This study aims to analyze the pilot implementation of a modified PACER system for electronic case reporting and describe how this FHIR-based, open-source, and interoperable system allows health systems to conduct public health reporting while maintaining the appropriate governance of the clinical data. METHODS: ELR to a simulated public health department was used as the trigger for a FHIR-based query. Predetermined queries were translated into Clinical Quality Language logics. Within the PACER environment, these Clinical Quality Language logical statements were managed and evaluated against the providers' FHIR servers. These predetermined logics were filtered, and only data relevant to that episode of the condition were extracted and sent to simulated public health agencies as an electronic case report. Design and testing were conducted at the Georgia Tech Research Institute, and the pilot was deployed at the Medical University of South Carolina. We evaluated this architecture by examining the completeness of additional information in the electronic case report, such as patient demographics, medications, symptoms, and diagnoses. This additional information is crucial for understanding disease epidemiology, but existing electronic case reporting and ELR architectures do not report them. Therefore, we used the completeness of these data fields as the metrics for enriching electronic case reports. RESULTS: During the 8-week study period, we identified 117 positive test results for chlamydia. PACER successfully created an electronic case report for all 117 patients. PACER extracted demographics, medications, symptoms, and diagnoses from 99.1% (116/117), 72.6% (85/117), 70.9% (83/117), and 65% (76/117) of the cases, respectively. CONCLUSIONS: PACER deployed in conjunction with electronic laboratory reports can enhance public health case reporting with additional relevant data. The architecture is modular in design, thereby allowing it to be used for any reportable condition, including evolving outbreaks. PACER allows for the creation of an enhanced and more complete case report that contains relevant case information that helps us to better understand the epidemiology of a disease.

BACKGROUND: Reactive syphilis serologies are investigated by health departments to determine if they represent new infection, reinfection, or treatment failure. Serologies prioritized for investigation based on nontreponemal test titer and age (using a 'reactor grid') undergo manual record search and review. We developed a computerized algorithm that automates the record search and review. METHODS: We developed and tested the algorithm using a Florida Department of Health dataset containing serologies reported January 2016-December 2018 and previous records linked to each individual. The algorithm was based on the syphilis case definition, which requires (except primary cases with signs and symptoms) 1) a positive treponemal test and a newly positive nontreponemal test or, 2) a 4-fold increase in nontreponemal test titer. Two additional steps were added to avoid missing cases. New York City Department of Health and Mental Hygiene validated this algorithm. RESULTS: The algorithm closed more investigations (49.9%) than the reactor grid (27.0%). The algorithm opened 99.4% of the individuals investigated and labeled as cases by the health department; it missed 75 cases. Many investigations opened by the algorithm were closed by the 'reactor grid'; we could not assess how many would have been cases. In New York City, the algorithm closed 70.9% of investigations, likely because more individuals had previous test in the database (88.2%) compared to Florida (56.5%). CONCLUSIONS: The automated algorithm successfully searched and reviewed records to help identify cases of syphilis. We estimate the algorithm would have saved Florida 590 workdays over 3 years.

Public health needs up-to-date information for surveillance and response. As healthcare application programming interfaces become widely available, a novel data gathering mechanism could provide public health with critical information in a timely fashion to respond to a fast-moving epidemic. In this article, we extrapolate from our experiences using a Fast Healthcare Interoperability Resource-based architecture for infectious disease surveillance for sexually transmitted diseases to its application to gather case information for an outbreak. One of the challenges with a fast-moving outbreak is to accurately assess its demand on healthcare resources, since information specific to comorbidities is often not available. These comorbidities are often associated with poor prognosis and higher resource utilization. If the comorbidity data and other clinical information were readily available to public health workers, they could better address community disruption and manage healthcare resources. The use of FHIR resources available through application programming and filtered through tools such as described herein will give public health the flexibility needed to investigate rapidly emerging disease while protecting patient privacy.