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Special Report: Early Use of ICD-10-CM Code “U07.1, COVID-19” to Identify 2019 Novel Coronavirus Cases in Military Health System Administrative Data

Image of Hospital ship USNS Comfort returns to its homeport after treating patients in New York and New Jersey in support of the COVID-19 pandemic. The hospital ship USNS Comfort returns to its homeport after treating patients in New York and New Jersey in support of the COVID-19 pandemic. (U.S. Navy photo by Mass Communication Specialist 1st Class Joshua D. Sheppard/Releaseds)

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What Are the New Findings?

This study identified possible cases of COVID-19 in distinct data record systems that included laboratory tests for the coronavirus, DRSi reports of cases, and records of health care encounters that included the new ICD-10 code U07.1 for the disease. Examination of 150 encounter records for individuals who were not identified in the laboratory or DRSi records revealed that 69% had confirmatory lab results in separate records or met clinical criteria for a case of COVID-19.

What Is the Impact on Readiness and Force Health Protection?

The findings provide evidence that use of the new ICD-10 diagnostic code for COVID-19 is occurring more frequently since its introduction. Search of encounter records for this code will augment the other methods of performing surveillance for this disease. Such enhanced surveillance will enable actions to prevent and control the current COVID-19 epidemic, which threatens the health of the force.

Abstract

This report describes early exploratory analysis of ICD-10-CM code U07.1 (2019-nCoV acute respiratory disease [COVID-19]) to assess the use of administrative data for case ascertainment, syndromic surveillance, and future epidemiological studies. Out of the 2,950 possible COVID-19 cases identified between 1 April 2020 and 4 May 2020, 600 (20.3%) were detected in the Defense Medical Surveillance System (DMSS) and not in the Disease Reporting System internet (DRSi) or in Health Level 7 laboratory data from the Composite Health Care System. Among the 150 out of 600 cases identified exclusively in the DMSS and selected for Armed Forces Health Longitudinal Technology Application (AHLTA) review, 16 (10.7%) had a certified positive lab result in AHLTA, 17 (11.3%) met Council of State and Territorial Epidemiologists (CSTE) criteria for a probable case, 46 (30.7%) were not cases based on CSTE criteria, and 71 (47.3%) had evidence of a positive lab result from an outside source. Lack of full capture of lab results may continue to be a challenge as the variety of available tests expands. Administrative data may provide an important stopgap measure for detecting lab positive cases, pending incorporation of new COVID-19 tests and standardization of test and result nomenclature.

Background

On 30 Jan. 2020, the World Health Organization (WHO) declared that an outbreak of disease named 2019-nCoV, later named coronavirus disease 2019 (COVID-19), was a Public Health Emergency of International Concern.1 One day later, on 31 Jan. 2020, WHO convened an emergency meeting of the WHO Family of International Classifications Network and Statistics Advisory Committee to create a specific International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) code for the new coronavirus: U07.1, 2019-nCoV acute respiratory disease.2 On 20 Feb. 2020, the U.S. Centers for Disease Control and Prevention (CDC) National Center for Health Statistics announced that it would implement the new ICD-10-CM code on 1 October 2020.3

Following the WHO declaration that the novel coronavirus was a global pandemic (11 March 2020) 4 and the President's activation of the Stafford Act (13 March 2020),5 CDC, under sections 201 and 301 of the U.S. National Emergencies Act, announced that the effective date of the new diagnosis code would be moved from 1 Oct. 2020 to 1 April 2020.6

The Military Health System (MHS) made ICD-10-CM code U07.1 available for selection by appointers and other administrative personnel in MHS GENESIS and the Composite Health Care System (CHCS) in early April 2020. Soon thereafter, the code became available to medical providers utilizing MHS GENESIS and the Armed Forces Health Longitudinal Technology Application (AHLTA) to document the diagnosis of COVID-19. Since the end of April 2020, epidemiologists and analysts have been able to query administrative databases including the MHS Data Repository (MDR), MHS Mart (M2), the CHCS, and the Defense Medical Surveillance System (DMSS) using the new code.

The Armed Forces Health Surveillance Branch (AFHSB) creates a daily master positive list of COVID-19 cases by combining data from the Disease Reporting System internet (DRSi) and Health Level 7 (HL7)-formatted laboratory data (HL7 data) extracted from the CHCS and MHS GENESIS by the Navy and Marine Corps Public Health Center. The availability of the specific ICD-10-CM code U07.1 provides a new source of data for identification of possible cases of COVID-19 using the electronic health record (EHR). It also provides an opportunity to create a COVID-19-like illnesses (CLI) case definition for syndromic surveillance modeled after influenza-like illness (ILI) surveillance. This report documents early exploratory analysis of ICD-10-CM code U07.1 to assess the potential use of administrative data for case ascertainment and use of the code for syndromic surveillance and future epidemiological studies (Figure 1).

Methods

On 4 May 2020, the DMSS was searched for all patient encounters that contained ICD-10-CM code U07.1 in any diagnostic position. This list of possible COVID-19 cases was compared to the master positive list (cases identified based on positive test for severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, the virus that causes COVID-19, and/or those who were reported as cases in the DRSi between 1 April 2020 and 4 May 2020). A convenience sample (25%) of these cases was selected for record review in AHLTA. Within AHLTA, for each case, information contained in the lab, radiology, previous encounters, Joint Legacy Viewer, and Health Artifact and Image Management Solution sections was reviewed by a licensed medical provider using a standardized Excel spreadsheet and systematic AHLTA review process. Cases in the DMSS-only subset were categorized as probable, confirmed, or determined not to be a case based on the guidelines established by the Council of State and Territorial Epidemiologists (CSTE)7 (Table).

On 8 May 2020, a 10-day "look-back" was performed. A separate DMSS list (U07.1 ICD-10-CM code list) from 28 April 2020 was compared with the master positive list (DRSi and/or HL7 data list) from 8 May 2020 to determine the number of DMSS U07.1 coded cases that were subsequently identified on the master positive list and, therefore, would have been captured without the use of administrative data.

Note that MHS GENESIS medical encounters did not become available in the DMSS until after this analysis was performed. While laboratory results from MHS GENESIS sites were included in this analysis, MHS GENESIS medical encounters were not included here.

Results

There were 2,350 individuals captured on the master positive list (cases identified based on positive lab test and/or those who were reported as cases in the DRSi between 1 April 2020 and 4 May 2020) and 865 individuals who were identified as having an encounter for COVID-19 (ICD-10-CM code U07.1) during the same time period. Among the 2,950 total individuals identified, 2,085 were exclusively on the master positive list, 600 were exclusively on the ICD-10-CM U07.1 diagnosis code list, and 265 were on both (Figure 2).

Among the 150 out of 600 cases identified exclusively in the DMSS and selected for AHLTA review, 16 (10.7%) had a certified positive lab result in the laboratory section of AHLTA, 17 (11.3%) met CSTE criteria for a probable case, 46 (30.7%) were not cases based on CSTE criteria, and 71 (47.3%) had evidence of a positive lab result from an outside source (Figure 3). Among the 46 cases that were determined not to be cases, 26 (56.5%) were seen for screening (e.g., pre-deployment screening rather than COVID-19 itself).

On 28 April 2020, there were 64 individuals on the U07.1 code-only list. By 8 May 2020, 7 (10.9%) had made it onto the master positive list (3 cases were represented exclusively in the DRSi, 2 cases were represented exclusively in HL7 data, and 2 were represented in both data sources) (Figure 4).

Editorial Comment

Availability of ICD-10-CM code U07.1 in administrative data is an important new development in COVID-19 surveillance. Given that 600 out of the 2,950 possible cases (20.3%) reviewed here were detected in administrative data and not in DRSi or HL7 data, addition of encounter data appears to be important to ensuring complete case capture moving forward.

Among the 150 cases selected for AHLTA review, 16 cases (10.7%) identified in encounter data were found to have a military treatment facility (MTF)-certified lab result in the AHLTA labs section but were not identified in the DRSi or the HL7 data and, therefore, were not represented on the master positive list. The 10-day look-back revealed that 7 cases were subsequently identified and entered into the master positive list, 2 of which were found exclusively in HL7 data, 3 of which were exclusively in DRSi data, and 2 of which were in both. While some of the remaining lab cases may eventually make it into the HL7 data, 2 of the missed lab results were from early April (2 April 2020 and 3 April 2020), suggesting that they might escape recognition altogether. Given that SARS-CoV-2 laboratory test names and results are not standardized in CHCS or HL7 data, this is understandable. While capture of these cases will likely improve as naming conventions are standardized and algorithms aimed at capturing COVID-19 test results evolve, lack of full capture of lab results may continue to be a challenge as the variety of tests available continues to expand. Administrative data may provide an important stopgap measure for detecting lab positive cases, pending incorporation of new COVID-19 tests and standardization of test and result nomenclature.

The CSTE definitions for confirmed and probable cases of COVID-19 are provided in the Table.7 Among the 150 cases reviewed, there were 17 probable cases of COVID-19: 2 had presumptive positive lab test results and met clinical or epidemiologic criteria; 15 met clinical and epidemiologic criteria. Among the 150 cases reviewed, 8 patients were hospitalized and 11 had chest imaging (x-ray or computed tomography [CT] scan) consistent with COVID-19.

It could be argued that cases with both clinical and radiographic evidence of COVID-19 should be categorized as cases. This approach is substantiated by Ai and colleagues, who performed serial analyses of reverse transcriptase polymerase chain reaction (RT-PCR) and CT scans and found that, using RT-PCR as a reference, the sensitivity of chest imaging for COVID-19 was 97%.8 Use of radiographic criteria for case identification would increase the proportion of individuals identified as cases in the EHR from 87 total cases (58.0%) to 98 total cases (65.3%). In this analysis, the CSTE case definition was applied to remain consistent with current public health practice.

Among the 150 AHLTA cases reviewed, the largest group of patients, 71 (47.3%), received lab testing at an outside facility, such as an urgent care center, hospital, or state health department, along with a documented encounter (most frequently a telephone consult) at an MTF. Lab results were sometimes scanned into the record and the test location was documented in 51/71 cases (71.8%). Given that these tests were not entered into the CHCS, they had no opportunity to be detected in HL7 data. The DRSi, a passive surveillance system with known limitations related to personnel, training, and accessibility, also did not identify these cases.9 This again demonstrates the value of using administrative data for comprehensive case capture.

Outsourced medical encounter data are available in MHS systems (e.g., the MDR, M2, and DMSS) after an encounter is billed. The billing process can take weeks to months, especially if a patient is hospitalized for a prolonged period of time. In the current analysis, many outsourced encounters not reported in the DRSi were detected because they were associated with a telephone consult undertaken for case management or public health purposes. Coding of the telephone consultations in the EHR allowed identification of cases at the time of illness rather than weeks later, as would be the case had these consults not been recorded. This finding suggests that the EHR may be an important adjunct to the DRSi for identification of cases requiring contact tracing.

The current analysis included 46 individuals (30.7%) who did not meet CSTE criteria for COVID-19 but who were, nonetheless, documented as having COVID-19, based solely on the ICD-10-CM U07.1 code. This misclassification was due to the use of ICD-10-CM code U07.1 for documentation of pre-deployment screening among asymptomatic service members rather than the appropriate screening code (ICD-10-CM code Z11.59, encounter for screening for other viral disease) in 56.5% of the 46 cases. Given the prospect of increased screening among recruits and other large military groups, continued improper use of this code for screening purposes could lead to significant misclassification of cases in the future, undermining the value of ICD-10-CM code U07.1 for case identification and development of a case definition for CLI syndromic surveillance. “ICD-10-CM Official Coding and Reporting Guidelines, 1 April 2020 through 30 Sept. 2020 advises against assigning ICD-10-CM code U07.1 to unconfirmed cases, including suspected, possible, probable, and inconclusive cases. It further directs the use of ICD-10-CM code Z11.59 for asymptomatic screening.10 The 13 May 2020 Defense Health Agency memorandum "Standardizing COVID-19 Laboratory Orders to Distinguish Among Diagnostic, Screening and Surveillance Testing Purposes" elaborates on these recommendations.11 Wide dissemination of these guidelines is warranted.

This review attempted to rapidly evaluate early use of ICD-10-CM code U07.1 in order to assure the accuracy of AFHSB's master positive list and to develop of a reliable CLI case definition. In the interest of timeliness, information in the medical record was extracted by a single individual rather than multiple providers, as would be required in a formal case series or systematic review. In addition, a convenience sample (the first 150 out of 600 cases) rather than a randomly selected sample of AHLTA cases was designated for review. These factors limit the validity and generalizability of the analysis. This analysis is further limited by the small number of cases reviewed and the fact that it was performed soon after adoption of ICD-10-CM code U07.1. Recognizing these limitations, it appears that use of ICD-10-CM code U07.1 to query administrative databases allows identification of cases that would not otherwise be detected using DRSi and HL7 data alone. Advocacy for use of administrative data to identify cases is tempered somewhat not only by the potential for misclassification but also by the manpower required to review the electronic medical record and apply CSTE guidelines for appropriate case classification. Lipstitch and colleagues astutely recognized that "case-based surveillance places exponentially increasing burdens on public health systems" and highlighted the importance of transitioning from case-based surveillance to automated syndromic surveillance as pandemics evolve.12

The use of ICD-10-CM code U07.1 for syndromic surveillance and future epidemiological studies warrants continued exploration, especially given use of this code for screening purposes and resultant misclassification. Continued addition of codes such as ICD-10-CM U07.2 COVID-19, virus not detected13 and refinement of codes sets used for syndromic surveillance will provide greater understanding of how COVID-19 is affecting military members and military-associated populations and ensure the integrity of future epidemiological studies related to COVID-19.

References

  1. World Health Organization. Coronavirus disease (COVID-19) outbreak. https://www.who.int/westernpacific/emergencies/covid-19. Accessed 1 May 2020.
  2. World Health Organization. Emergency use ICD codes for COVID-19 disease outbreak https://www.who.int/classifications/icd/covid19/en/. Accessed 1 May 2020.
  3. Centers for Disease Control and Prevention. ICD-10-CM Official Coding Guidelines-Supplement. Coding encounters related to COVID-19 coronavirus outbreak. Effective: Feb. 20, 2020. https://www.cdc.gov/nchs/data/icd/ICD-10-CMOfficial-Coding-Gudance-Interim-Advice-coronavirus-feb-20-2020.pdf. Accessed 1 May 2020.
  4. World Health Organization. Rolling updates on coronavirus disease (COVID-19). https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen. Accessed 2 May 2020.
  5. United States White House. Proclamation on Declaring a National Emergency Concerning the Novel Coronavirus Disease (COVID-19) Outbreak. https://www.whitehouse.gov/presidential-actions/proclamation-declaring-national-emergency-concerning-novel-coronavirus-disease-covid-19-outbreak/. Accessed 3 May 2020.
  6. Centers for Disease Control and Prevention. New ICD-10-CM code for the 2019 novel coronavirus (COVID-19), April 1, 2020. Effective: March 18, 2020. https://www.cdc.gov/nchs/data/icd/Announcement-New-ICD-code-for-coronavirus-3-18-2020.pdf. Accessed 1 May 2020.
  7. Council of State and Territorial Epidemiologists. Standardized surveillance case definition and national notification for 2019 novel coronavirus disease (COVID-19). 4 April 2020.
  8. Ai T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 Cases. Radiology. 2020;26:200642.
  9. Ambrose JF, Kebisek JK, Gibson KJ, White DV, O’Donnell FL. Gaps in reportable medical event surveillance across the Department of the Army and recommended training tools to improve surveillance practices. MSMR. 2019;26(8):17–21.
  10. 1Centers for Disease Control and Prevention. ICD-10-CM Official Coding and Reporting Guidelines April 1, 2020 through Sept. 30, 2020. https://www.cdc.gov/nchs/data/icd/COVID-19-guidelines-final.pdf. Accessed 3 May 2020.
  11. Department of Defense. Defense Health Agency. Memorandum. Standardizing COVID-19 Laboratory Orders to Distinguish Among Diagnostic, Screening, and Surveillance Testing Purposes. 13 May 2020.
  12. Lipsitch M, Hayden FG, Cowling BJ, Leung GM. How to maintain surveillance for novel influenza A H1N1 when there are too many cases to count. Lancet. 2009;374(9696):1209–1211.
  13. World Health Organization. Emergency use ICD codes for COVID-19 disease outbreak. https://www.who.int/classifications/icd/covid19/en/. Accessed 5 May 2020.

FIGURE 1. COVID-19 data sources and products

FIGURE 2. COVID-19 case identification using the master positive list and ICD-10-CM code U07.1, 1 April 2020–1 May 2020

FIGURE 3. Cases reviewed in AHLTA (150 cases out of 600 total)
FIGURE 4. Ten-day look-back for identification of cases that were initially not found but subsequently identified in DRSi and/or HL7 data

TABLE. CSTE standardized surveillance case definition for COVID-19

 

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Malaria infection remains an important health threat to U.S. service mem­bers who are located in endemic areas because of long-term duty assign­ments, participation in shorter-term contingency operations, or personal travel. In 2018, a total of 58 service members were diagnosed with or reported to have malaria. This represents a 65.7% increase from the 35 cases identi­fied in 2017. The relatively low numbers of cases during 2012–2018 mainly reflect decreases in cases acquired in Afghanistan, a reduction due largely to the progressive withdrawal of U.S. forces from that country. The percentage of cases of malaria caused by unspecified agents (63.8%; n=37) in 2018 was the highest during any given year of the surveillance period. The percent­age of cases identified as having been caused by Plasmodium vivax (10.3%; n=6) in 2018 was the lowest observed during the 10-year surveillance period. The percentage of malaria cases attributed to P. falciparum (25.9 %) in 2018 was similar to that observed in 2017 (25.7%), although the number of cases increased. Malaria was diagnosed at or reported from 31 different medical facilities in the U.S., Afghanistan, Italy, Germany, Djibouti, and Korea. Pro­viders of medical care to military members should be knowledgeable of and vigilant for clinical manifestations of malaria outside of endemic areas.

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Medical Surveillance Monthly Report

Thyroid Disorders, Active Component, U.S. Armed Forces, 2008–2017

Article
12/1/2018
A U.S. naval officer listens through his stethoscope to hear his patient’s lungs at Camp Schwab in Okinawa, Japan in 2018. (Photo courtesy of U.S. Marine Corps) photo by Lance Cpl. Cameron Parks)

This analysis describes the incidence and prevalence of five thyroid disorders (goiter, thyrotoxicosis, primary/not otherwise specified [NOS] hypothyroidism, thyroiditis, and other disorders of the thyroid) among active component service members between 2008 and 2017. During the 10-year surveillance period, the most common incident thyroid disorder among male and female service members was primary/NOS hypothyroidism and the least common were thyroiditis and other disorders of thyroid. Primary/NOS hypothyroidism was diagnosed among 8,641 females (incidence rate: 43.7 per 10,000 person-years [p-yrs]) and 11,656 males (incidence rate: 10.2 per 10,000 p-yrs). Overall incidence rates of all thyroid disorders were 3 to 5 times higher among females compared to males. Among both males and females, incidence of primary/NOS hypothyroidism was higher among non-Hispanic white service members compared with service members in other race/ethnicity groups. The incidence of most thyroid disorders remained stable or decreased during the surveillance period. Overall, the prevalence of most thyroid disorders increased during the first part of the surveillance period and then either decreased or leveled off.31.6 per 100,000 active component service members in 2017. Validation of ICD-9/ICD-10 diagnostic codes for MetS using the National Cholesterol Education Program Adult Treatment Panel III criteria is needed to establish the level of agreement between the two methods for identifying this condition.

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Medical Surveillance Monthly Report
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Last Updated: October 24, 2022
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