tetano
Editor, Senior Moderator
J Am Med Dir Assoc
. 2025 Jan 6:105440.
doi: 10.1016/j.jamda.2024.105440. Online ahead of print. Evaluation of COVID-19 Diagnosis Codes for Identification of SARS-CoV-2 Infections in a Nursing Home Cohort, 2022-2023
Arshiya Patel[SUP] 1 [/SUP], Amanda B Payne[SUP] 2 [/SUP], Dustin W Currie[SUP] 3 [/SUP], Thomas Franceschini[SUP] 4 [/SUP], Amber Gensheimer[SUP] 4 [/SUP], Joseph D Lutgring[SUP] 3 [/SUP], Sujan Reddy[SUP] 3 [/SUP], Kelly M Hatfield[SUP] 3 [/SUP]
Affiliations
Objectives: This study aimed to evaluate the utility of electronic health record (EHR) diagnosis codes for monitoring SARS-CoV-2 infections among nursing home residents.
Design: A retrospective cohort study design was used to analyze data collected from nursing homes operating under the tradename Signature Healthcare between January 2022 and June 2023.
Setting and participants: Data from 31,136 nursing home residents across 76 facilities in Kentucky, Tennessee, Indiana, Ohio, North Carolina, Georgia, Alabama, and Virginia were included.
Methods: Resident demographics, diagnosis codes associated with clinical diagnoses (including COVID-19), and SARS-CoV-2 testing information were collected from the EHR and supplemental testing data sources. We described the rates of infection and the clinical characteristics of residents with incident-positive SARS-CoV-2 tests and new-onset COVID-19 diagnoses. Positive predictive values (PPVs) of COVID-19 diagnosis codes were calculated for residents stratified by whether a resident was continuously present in a facility for ±3 days from the diagnosis onset date listed in EHRs, using positive SARS-CoV-2 tests to confirm infection.
Results: A total of 4876 incident-positive SARS-CoV-2 tests and 6346 new-onset COVID-19 diagnoses were recorded during the study period. Weekly rates of new-onset diagnoses were significantly higher than positive test rates, although trends followed similar trajectories. Among residents continuously present in the nursing home ±3 days from the diagnosis onset date, the PPV of COVID-19 diagnosis codes was high (3395 of 3685 = 92%; 95% CI, 91%-93%). The PPV among this group significantly varied by study quarter (P < .001). The PPV was substantially lower for 2661 diagnoses among residents not continuously present in the nursing home (24%; 95% CI, 22%-26%).
Conclusions and implications: This study demonstrates the utility of diagnosis codes for assessment of COVID-19 epidemiology and trends when testing data are unavailable for residents during their stay in a nursing home. Future research should explore strategies to evaluate the utility of diagnosis codes at admission and discharge to nursing homes to enhance surveillance efforts.
Keywords: COVID-19; ICD-10; SARS-CoV-2; electronic health record; nursing home; respiratory infections.
. 2025 Jan 6:105440.
doi: 10.1016/j.jamda.2024.105440. Online ahead of print. Evaluation of COVID-19 Diagnosis Codes for Identification of SARS-CoV-2 Infections in a Nursing Home Cohort, 2022-2023
Arshiya Patel[SUP] 1 [/SUP], Amanda B Payne[SUP] 2 [/SUP], Dustin W Currie[SUP] 3 [/SUP], Thomas Franceschini[SUP] 4 [/SUP], Amber Gensheimer[SUP] 4 [/SUP], Joseph D Lutgring[SUP] 3 [/SUP], Sujan Reddy[SUP] 3 [/SUP], Kelly M Hatfield[SUP] 3 [/SUP]
Affiliations
- PMID: 39788487
- DOI: 10.1016/j.jamda.2024.105440
Objectives: This study aimed to evaluate the utility of electronic health record (EHR) diagnosis codes for monitoring SARS-CoV-2 infections among nursing home residents.
Design: A retrospective cohort study design was used to analyze data collected from nursing homes operating under the tradename Signature Healthcare between January 2022 and June 2023.
Setting and participants: Data from 31,136 nursing home residents across 76 facilities in Kentucky, Tennessee, Indiana, Ohio, North Carolina, Georgia, Alabama, and Virginia were included.
Methods: Resident demographics, diagnosis codes associated with clinical diagnoses (including COVID-19), and SARS-CoV-2 testing information were collected from the EHR and supplemental testing data sources. We described the rates of infection and the clinical characteristics of residents with incident-positive SARS-CoV-2 tests and new-onset COVID-19 diagnoses. Positive predictive values (PPVs) of COVID-19 diagnosis codes were calculated for residents stratified by whether a resident was continuously present in a facility for ±3 days from the diagnosis onset date listed in EHRs, using positive SARS-CoV-2 tests to confirm infection.
Results: A total of 4876 incident-positive SARS-CoV-2 tests and 6346 new-onset COVID-19 diagnoses were recorded during the study period. Weekly rates of new-onset diagnoses were significantly higher than positive test rates, although trends followed similar trajectories. Among residents continuously present in the nursing home ±3 days from the diagnosis onset date, the PPV of COVID-19 diagnosis codes was high (3395 of 3685 = 92%; 95% CI, 91%-93%). The PPV among this group significantly varied by study quarter (P < .001). The PPV was substantially lower for 2661 diagnoses among residents not continuously present in the nursing home (24%; 95% CI, 22%-26%).
Conclusions and implications: This study demonstrates the utility of diagnosis codes for assessment of COVID-19 epidemiology and trends when testing data are unavailable for residents during their stay in a nursing home. Future research should explore strategies to evaluate the utility of diagnosis codes at admission and discharge to nursing homes to enhance surveillance efforts.
Keywords: COVID-19; ICD-10; SARS-CoV-2; electronic health record; nursing home; respiratory infections.