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.

Aerosol Generation and Mitigation During Methacholine Bronchoprovocation Testing: Infection Control Implications in the Era of COVID-19.

BACKGROUND: Methacholine bronchoprovocation or challenge testing (MCT) is commonly performed to assess airway hyper-responsiveness in the setting of suspected asthma. Nebulization is an aerosol-generating procedure, but little is known about the risks of MCT in the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic. We aimed to quantify and characterize aerosol generation during MCT by using different delivery methods and to assess the impact of adding a viral filter. METHODS: Seven healthy subjects performed simulated MCT in a near particle-free laboratory space with 4 different nebulizers and with a dosimeter. Two devices continuously sampled the ambient air during the procedure, which detected ultrafine particles, from 0.02-1 µm, and particles of sizes 0.3, 0.5, 1.0, 2.0, 5.0, and 10 µm, respectively. Particle generation was compared among all the devices, with and without viral filter placement. RESULTS: Ultrafine-particle generation during simulated MCT was significant across all the devices. Ultrafine-particle (0.02-1 µm) concentrations decreased 77%-91% with the addition of a viral filter and varied significantly between unfiltered (P < .001) and filtered devices (P < .001). Ultrafine-particle generation was lowest when using the dosimeter with filtered Hudson nebulizer (1,258 ± 1,644 particle/mL). Ultrafine-particle concentrations with the filtered nebulizer devices using a compressor were higher than particle concentrations detected when using the dosimeter: Monaghan (3,472 ± 1,794 particles/mL), PARI (4,403 ± 2,948), Hudson (6,320 ± 1,787) and AirLife (9,523 ± 5,098). CONCLUSIONS: The high particle concentrations generated during MCT pose significant infection control concerns during the COVID-19 pandemic. Particle generation during MCT was significantly reduced by using breath-actuated delivery and a viral filter, which offers an effective mitigation strategy.

Aerosol Generation During Peak Flow Testing: Clinical Implications for COVID-19.

BACKGROUND: Peak flow testing is a common procedure performed in ambulatory care. There are currently no data regarding aerosol generation during this procedure. Given the ongoing debate regarding the potential for aerosol transmission of SARS-CoV-2, we aimed to quantify and characterize aerosol generation during peak flow testing. METHODS: Five healthy volunteers performed peak flow maneuvers in a particle-free laboratory space. Two devices continuously sampled the ambient air during the procedure. One device can detect ultrafine particles 0.02-1 µm in diameter, while the second device can detect particles 0.3, 0.5, 1.0, 2.0, 5.0, and 10 µm in diameter. Five different peak flow meters were compared to ambient baseline during masked and unmasked tidal breathing. RESULTS: Ultrafine particles (0.02-1 µm) were generated during peak flow measurement. There was no significant difference in ultrafine particle mean concentration between peak flow meters (P = .23): Respironics (1.25 ± 0.47 particles/mL), Philips (3.06 ± 1.22), Clement Clarke (3.55 ± 1.22 particles/mL), Respironics Low Range (3.50 ± 1.52 particles/mL), and Monaghan (3.78 ± 1.31 particles/mL). Ultrafine particle mean concentration with peak flow testing was significantly higher than masked (0.22 ± 0.29 particles/mL) and unmasked tidal breathing (0.15 ± 0.18 particles/mL, P = .01), but the ultrafine particle concentrations were small compared to ambient particle concentrations in a pulmonary function testing room (89.9 ± 8.95 particles/mL). CONCLUSIONS: In this study, aerosol generation was present during peak flow testing, but concentrations were small compared to the background particle concentration in the ambient clinical environment. Surgical masks and eye protection are likely sufficient infection control measures during peak expiratory flow testing in asymptomatic patients with well controlled respiratory symptoms, but COVID-19 testing remains prudent in patients with acute respiratory symptoms prior to evaluation and peak expiratory flow assessment while the community prevalence of SARS-CoV-2 cases remains high.