Electronic case reporting (eCR) of COVID-19 to public health: implementation perspectives from the Minnesota Department of Health.
J Am Med Inform Assoc
; 29(11): 1958-1966, 2022 10 07.
Article
in English
| MEDLINE | ID: covidwho-1973187
ABSTRACT
Electronic case reporting (eCR) is the automated generation and transmission of case reports from electronic health records to public health for review and action. These reports (electronic initial case reports eICRs) adhere to recommended exchange and terminology standards. eCR is a partnership of the Centers for Disease Control and Prevention (CDC), Association of Public Health Laboratories (APHL) and Council of State and Territorial Epidemiologists (CSTE). The Minnesota Department of Health (MDH) received eICRs for COVID-19 from April 2020 (3 sites, manual process), automated eCR implementation in August 2020 (7 sites), and on-boarded â¼1780 clinical units in 460 sites across 6 integrated healthcare systems (through March 2022). Approximately 20â000 eICRs/month were reported to MDH during high-volume timeframes. With increasing provider/health system implementation, the proportion of COVID-19 cases with an eICR increased to 30% (March 2022). Evaluation of data quality for select demographic variables (gender, race, ethnicity, email, phone, language) across the 6 reporting health systems revealed a high proportion of completeness (>80%) for half of variables and less complete data for rest (ethnicity, email, language) along with low ethnicity data (<50%) for one health system. Presently eCR implementation at MDH includes only one EHR vendor. Next steps will focus on onboarding other EHRs, additional eICR data extraction/utilization, detailed analysis, outreach to address data quality issues, and expanding to other reportable conditions.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Public Health
/
COVID-19
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
/
Reviews
Limits:
Humans
Country/Region as subject:
North America
Language:
English
Journal:
J Am Med Inform Assoc
Journal subject:
Medical Informatics
Year:
2022
Document Type:
Article
Affiliation country:
Jamia
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