Electronic Health Record Data for Lyme Disease Surveillance, Massachusetts, USA, 2017-2018.

Lyme disease surveillance based on provider and laboratory reports underestimates incidence. We developed an algorithm for automating surveillance using electronic health record data. We identified potential Lyme disease markers in electronic health record data (laboratory tests, diagnosis codes, prescriptions) from January 2017-December 2018 in 2 large practice groups in Massachusetts, USA. We calculated their sensitivities and positive predictive values (PPV), alone and in combination, relative to medical record review. Sensitivities ranged from 57% (95% CI 47%-69%) for immunoassays to 87% (95% CI 70%-100%) for diagnosis codes. PPVs ranged from 53% (95% CI 43%-61%) for diagnosis codes to 58% (95% CI 50%-66%) for immunoassays. The combination of a diagnosis code and antibiotics within 14 days or a positive Western blot had a sensitivity of 100% (95% CI 86%-100%) and PPV of 82% (95% CI 75%-89%). This algorithm could make Lyme disease surveillance more efficient and consistent.

Can Machine Learning Help Identify Patients at Risk for Recurrent Sexually Transmitted Infections?

BACKGROUND: A substantial fraction of sexually transmitted infections (STIs) occur in patients who have previously been treated for an STI. We assessed whether routine electronic health record (EHR) data can predict which patients presenting with an incident STI are at greatest risk for additional STIs in the next 1 to 2 years. METHODS: We used structured EHR data on patients 15 years or older who acquired an incident STI diagnosis in 2008 to 2015 in eastern Massachusetts. We applied machine learning algorithms to model risk of acquiring ≥1 or ≥2 additional STIs diagnoses within 365 or 730 days after the initial diagnosis using more than 180 different EHR variables. We performed sensitivity analysis incorporating state health department surveillance data to assess whether improving the accuracy of identifying STI cases improved algorithm performance. RESULTS: We identified 8723 incident episodes of laboratory-confirmed gonorrhea, chlamydia, or syphilis. Bayesian Additive Regression Trees, the best-performing algorithm of any single method, had a cross-validated area under the receiver operating curve of 0.75. Receiver operating curves for this algorithm showed a poor balance between sensitivity and positive predictive value (PPV). A predictive probability threshold with a sensitivity of 91.5% had a corresponding PPV of 3.9%. A higher threshold with a PPV of 29.5% had a sensitivity of 11.7%. Attempting to improve the classification of patients with and without repeat STIs diagnoses by incorporating health department surveillance data had minimal impact on cross-validated area under the receiver operating curve. CONCLUSIONS: Machine algorithms using structured EHR data did not differentiate well between patients with and without repeat STIs diagnosis. Alternative strategies, able to account for sociobehavioral characteristics, could be explored.

RiskScape: A Data Visualization and Aggregation Platform for Public Health Surveillance Using Routine Electronic Health Record Data.

Automated analysis of electronic health record (EHR) data is a complementary tool for public health surveillance. Analyzing and presenting these data, however, demands new methods of data communication optimized to the detail, flexibility, and timeliness of EHR data.RiskScape is an open-source, interactive, Web-based, user-friendly data aggregation and visualization platform for public health surveillance using EHR data. RiskScape displays near-real-time surveillance data and enables clinical practices and health departments to review, analyze, map, and trend aggregate data on chronic conditions and infectious diseases. Data presentations include heat maps of prevalence by zip code, time series with statistics for trends, and care cascades for conditions such as HIV and HCV. The platform's flexibility enables it to be modified to incorporate new conditions quickly-such as COVID-19.The Massachusetts Department of Public Health (MDPH) uses RiskScape to monitor conditions of interest using data that are updated monthly from clinical practice groups that cover approximately 20% of the state population. RiskScape serves an essential role in demonstrating need and burden for MDPH's applications for funding, particularly through the identification of inequitably burdened populations.

More Screening or More Disease? Gonorrhea Testing and Positivity Patterns Among Men in 3 Large Clinical Practices in Massachusetts, 2010-2017.

BACKGROUND: Gonorrhea diagnosis rates in the United States increased by 75% during 2009-2017, predominantly in men. It is unclear whether the increase among men is being driven by more screening, an increase in the prevalence of disease, or both. We sought to evaluate changes in gonorrhea testing patterns and positivity among men in Massachusetts. METHODS: The analysis included men (aged ≥15 years) who received care during 2010-2017 in 3 clinical practice groups. We calculated annual percentages of men with ≥1 gonorrhea test and men with ≥1 positive result, among men tested. Log-binomial regression models were used to examine trends in these outcomes. We adjusted for clinical and demographic characteristics that may influence the predilection to test and probability of gonorrhea disease. RESULTS: On average, 306 348 men had clinical encounters each year. There was a significant increase in men with ≥1 gonorrhea test from 2010 (3.1%) to 2017 (6.4%; adjusted annual risk ratio, 1.12; 95% confidence interval, 1.12-1.13). There was a significant, albeit lesser, increase in the percentage of tested men with ≥1 positive result (1.0% in 2010 to 1.5% in 2017; adjusted annual risk ratio, 1.07; 95% confidence interval, 1.04-1.09). CONCLUSIONS: We estimated significant increases in the annual percentages of men with ≥1 gonorrhea test and men with ≥1 positive gonorrhea test result between 2010 and 2017. These results suggest that observed increases in gonorrhea rates could be explained by both increases in screening and the prevalence of gonorrhea.

Impact of an Electronic Medical Record Best Practice Alert on Expedited Partner Therapy for Chlamydia Infection and Reinfection.

BACKGROUND: Atrius Health implemented a best practice alert (BPA) to encourage clinicians to provide expedited partner therapy (EPT) in October 2014. We assessed (1) the impact of the BPA on EPT provision and chlamydial reinfection and (2) the impact of EPT on testing for chlamydia reinfection and reinfection rates. METHODS: We included patients ≥15 years with ≥1 positive chlamydia test between January 2013 and March 2019. Tests-of-reinfection were defined as chlamydia tests 28-120 days after initial infection, and corresponding positive results were considered evidence of reinfection. We used interrupted time series analyses to identify changes in (1) frequency of EPT, (2) tests-of-reinfection, and (3) reinfections after the BPA was released. Log-binomial regression models, with generalized estimating equation methods, assessed associations between (1) EPT and tests-of-reinfection and (2) EPT and reinfection. RESULTS: Among 7267 chlamydia infections, EPT was given to 1475 (20%) patients. Expedited partner therapy frequency increased from 15% to 22% of infections between January 2013 and September 2014 (ß = 0.003, P = .03). After the BPA was released, EPT frequency declined to 19% of infections by March 2019 (ß = -0.004, P = .008). On average, 35% of chlamydia infections received a test-of-reinfection and 7% were reinfected; there were no significant changes in these percentages after BPA implementation. Patients given EPT were more likely to receive tests-of-reinfection (prevalence ratio [PR] 1.09; 95% confidence interval [CI], 1.01-1.16) but without change in reinfections (PR 0.88; 95% CI, 0.66-1.17). CONCLUSIONS: Best practice alerts in electronic medical record systems may not be effective at increasing EPT prescribing and decreasing chlamydial reinfection. However, patients given EPT were more likely to receive a test of chlamydia reinfection.

Beyond compliance: environmental health problem solving, interagency collaboration, and risk assessment to prevent waterborne disease outbreaks.

A systems approach to environmental health problem solving was used to investigate two waterborne norovirus outbreaks in Wyoming and can serve in the development of improved prevention strategies. An interagency collaboration to prevent waterborne disease involving local, state, and federal partners was designed to coordinate response to outbreak investigations. Improved risk assessment and reporting procedures were also integrated to ensure better availability of necessary data. Public health entities should implement sustainable intersectoral interventions to prevent waterborne disease that not only improve regulatory compliance but also have a positive impact on community health outcomes. Collaborative preventive health and water system protection activities should receive priority attention for implementation in state and local jurisdictions.