Clinical Decision Support System for Guidelines-Based Treatment of Gonococcal Infections, Screening for HIV, and Prescription of Pre-Exposure Prophylaxis: Design and Implementation Study.

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.

Evaluation of Automated Processing of Electronically Reported Serological Tests for Syphilis Using Current and Historical Syphilis Results Compared with Traditional Reactor Grid Processing in Florida.

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.

Automating Case Reporting of Chlamydia and Gonorrhea to Public Health Authorities in Illinois Clinics: Implementation and Evaluation of Findings.

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.

Estimated Cases Averted by COVID-19 Digital Exposure Notification, Pennsylvania, USA, November 8, 2020-January 2, 2021.

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.

Automating Case Reporting of Chlamydia and Gonorrhea to Public Health Authorities in Oregon Clinics.

BACKGROUND: Optimizing sexually transmitted disease (STD) reporting to state public health authorities is important to reduce incidence and manage outbreaks of STDs. Electronic laboratory 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 3 community health centers in Oregon between February 3, 2020 and May 15, 2020, we piloted an automated 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 CT, 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 GC, 44% (102 instances) reflected a diagnosis and 56% (130 instances) reflected laboratory results. Data completeness was uniformly equal or higher for eCRs versus ELRs. CONCLUSIONS: The eCR approach was successful in identifying CT and GC cases and provided a more complete set of information to assist public health authorities when compared with ELRs. Electronic case reporting has the potential to automate and relieve staff burden on an important reporting requirement for clinical providers.

Assessment of the Chad guinea worm surveillance information system: A pivotal foundation for eradication.

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.

A Modified Public Health Automated Case Event Reporting Platform for Enhancing Electronic Laboratory Reports With Clinical Data: Design and Implementation Study.

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.

An Automated Syphilis Serology Record Search and Review Algorithm to Prioritize Investigations by Health Departments.

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 data set containing serologies reported January 2016 to 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 result and a newly positive nontreponemal test result 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 with 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 for 3 years.

Fever among COVID-19 Patients in a Tertiary Care Hospital of Western Nepal: A Descriptive Cross-sectional Study.

INTRODUCTION: COVID-19 has a wide spectrum of clinical presentation ranging from asymptomatic infection to acute respiratory distress syndrome and multi organ dysfunction. Data regarding this is scarce in our setting. This study aims to study the prevalence of fever in confirmed COVID-19 cases in a tertiary care hospital of western Nepal. METHODS: We conducted a descriptive cross-sectional study among patients admitted to COVID-19 wards and intensive care units of a tertiary care hospital. We enrolled patients from August 2020 to January 2021 and the study proposal was approved by the Institutional Review Committee (reference number: 069/20). Convenience sampling method was used. Data entry and descriptive analysis were done in Statistical Package for the Social Sciences version 16.0. Point estimate at 95% Confidence Interval was calculated along with frequency and descriptive statistics. RESULTS: Among 206 cases of COVID-19, the most common symptom was fever 136 (66.1%) (95% Confidence Interval= 58.14.63-74.05). Sixty-seven (49.3%) of those with fever required intensive care units admission whereas 27 (19.9%) of patients with fever had mortality. Most common comorbidities in the patient having fever is Diabetes mellitus 41 (66.1%) followed by hypertension 20 (62.5%). CONCLUSIONS: Fever was the most common presenting complaint with high prevalence as compared to similar studies done in similar settings. We stress the importance of considering the presence of COVID-19 even in the absence of fever as many patients presented without fever.

Public health reporting and outbreak response: synergies with evolving clinical standards for interoperability.

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.

Quantitative MRI and X-ray analysis of disc degeneration and paraspinal muscle changes in degenerative spondylolisthesis.

BACKGROUND AND OBJECTIVE: The intervertebral disc degeneration changes and paraspinal muscles changes are believed to be risk factors for lumbar degenerative spondylolisthesis (LDS). But there is limited quantitative information about this progression. This study is to reveal their changes the in the progression of LDS. METHODS: Data were gathered from 149 middle-aged degenerative spondylolisthesis patients and same amount of age- and sex-matched control group with both lumber spine MRI and X-ray. Narrowed disc space were measured in percent as anterior inferior disc height (DHIA)/anterior superior disc height (DHSA), inferior disc height (DHI)/superior disc height (DHS), and posterior inferior disc height (DHIP)/posterior superior disc height (DHSP). Signal intensity ratio of multifidus muscle (RM) and erector spinae (RES) to psoas muscle, muscle atrophy ratio of lean CSA (LCSA) to gross CSA (GCSA) of paraspinal muscles were calculated. RESULTS: In the case group the most common slipped vertebra was L4 (75.84%). Disc height (DHIA/DHSA, DHI/DHS) and multifidus muscle atrophy ratio (M-LCSA/M-GCSA) tended to be lower than those in the control group, whereas the disc degeneration degree and T2 signal intensity ratio (RM,RES) of the paraspinal muscles and erector spinae muscle atrophy ratio were higher than control group. The difference between the two groups was statistically significant (P< 0.05). Using multivariate logistic regression analysis, it was confirmed that ES-LCSA/ES-GCSA, especially RM are independent predisposing factors to lumbar spondylolisthesis (OR > 1, P< 0.05) while DHIA/DHSA, M-LCSA/M-GCSA are independent protective factors (OR < 1, P< 0.05). CONCLUSIONS: Decreased anterior disc height and multifidus muscle atrophy are found in the LDS patients and thy could be the cause of LDS. The presence of erector spinae hypertrophy could be a compensatory mechanism to compensate for the instability.