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1.
Am J Public Health ; 111(12): 2133-2140, 2021 12.
Article in English | MEDLINE | ID: covidwho-1562412

ABSTRACT

The National Center for Health Statistics' (NCHS's) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133-2140. https://doi.org/10.2105/AJPH.2021.306519).


Subject(s)
COVID-19/mortality , Data Collection/standards , Public Health Surveillance/methods , Vital Statistics , Cause of Death , Clinical Coding/standards , Guidelines as Topic , Health Status Disparities , Humans , SARS-CoV-2 , Time Factors , United States/epidemiology
2.
J Med Virol ; 94(4): 1550-1557, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1540145

ABSTRACT

International Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD-10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods. OBJECTIVE: Compare COVID-19 cohort manual-chart-review and ICD-10-based comorbidity data; characterize the accuracy of different methods of extracting ICD-10-code-based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission. DESIGN: Retrospective cross-sectional study. MEASUREMENTS: ICD-10-based-data performance characteristics relative to manual-chart-review. RESULTS: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79-0.85; comorbidity range: 0.35-0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69-0.76; range: 0.44-0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63-0.71; range: 0.47-0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54-0.63; range: 0.30-0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43-0.53; range: 0.30-0.56). CONCLUSIONS AND RELEVANCE: ICD-10-based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual-chart-review.


Subject(s)
COVID-19/diagnosis , Clinical Coding/standards , International Classification of Diseases/standards , COVID-19/epidemiology , COVID-19/virology , Clinical Coding/methods , Comorbidity , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Philadelphia , Reproducibility of Results , Retrospective Studies , SARS-CoV-2
4.
Am J Public Health ; 111(S2): S101-S106, 2021 07.
Article in English | MEDLINE | ID: covidwho-1328027

ABSTRACT

Objectives. To examine age and temporal trends in the proportion of COVID-19 deaths occurring out of hospital or in the emergency department and the proportion of all noninjury deaths assigned ill-defined causes in 2020. Methods. We analyzed newly released (March 2021) provisional COVID-19 death tabulations for the entire United States. Results. Children (younger than 18 years) were most likely (30.5%) and elders aged 64 to 74 years were least likely (10.4%) to die out of hospital or in the emergency department. In parallel, among all noninjury deaths, younger people had the highest proportions coded to symptoms, signs, and ill-defined conditions, and percentage symptoms, signs, and ill-defined conditions increased from 2019 to 2020 in all age-race/ethnicity groups. The majority of young COVID-19 decedents were racial/ethnic minorities. Conclusions. The high proportions of all noninjury deaths among children, adolescents, and young adults that were coded to ill-defined causes in 2020 suggest that some COVID-19 deaths were missed because of systemic failures in timely access to medical care for vulnerable young people. Public Health Implications. Increasing both availability of and access to the best hospital care for young people severely ill with COVID-19 will save lives and improve case fatality rates.


Subject(s)
COVID-19/mortality , Clinical Coding/standards , Forms and Records Control/standards , Quality Assurance, Health Care/standards , Adolescent , Aged , COVID-19/epidemiology , Cause of Death , Child , Child, Preschool , Humans , Male , Middle Aged , Minority Groups/statistics & numerical data , Quality Control , Sex Distribution , United States , Young Adult
7.
JAMA Netw Open ; 3(8): e2017703, 2020 08 03.
Article in English | MEDLINE | ID: covidwho-713159

ABSTRACT

Importance: International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes are used to characterize coronavirus disease 2019 (COVID-19)-related symptoms. Their accuracy is unknown, which could affect downstream analyses. Objective: To compare the performance of fever-, cough-, and dyspnea-specific ICD-10 codes with medical record review among patients tested for COVID-19. Design, Setting, and Participants: This cohort study included patients who underwent quantitative reverse transcriptase-polymerase chain reaction testing for severe acute respiratory syndrome coronavirus 2 at University of Utah Health from March 10 to April 6, 2020. Data analysis was performed in April 2020. Main Outcomes and Measures: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ICD-10 codes for fever (R50*), cough (R05*), and dyspnea (R06.0*) were compared with manual medical record review. Performance was calculated overall and stratified by COVID-19 test result, sex, age group (<50, 50-64, and >64 years), and inpatient status. Bootstrapping was used to generate 95% CIs, and Pearson χ2 tests were used to compare different subgroups. Results: Among 2201 patients tested for COVD-19, the mean (SD) age was 42 (17) years; 1201 (55%) were female, 1569 (71%) were White, and 282 (13%) were Hispanic or Latino. The prevalence of fever was 66% (1444 patients), that of cough was 88% (1930 patients), and that of dyspnea was 64% (1399 patients). For fever, the sensitivity of ICD-10 codes was 0.26 (95% CI, 0.24-0.29), specificity was 0.98 (95% CI, 0.96-0.99), PPV was 0.96 (95% CI, 0.93-0.97), and NPV was 0.41 (95% CI, 0.39-0.43). For cough, the sensitivity of ICD-10 codes was 0.44 (95% CI, 0.42-0.46), specificity was 0.88 (95% CI, 0.84-0.92), PPV was 0.96 (95% CI, 0.95-0.97), and NPV was 0.18 (95% CI, 0.16-0.20). For dyspnea, the sensitivity of ICD-10 codes was 0.24 (95% CI, 0.22-0.26), specificity was 0.97 (95% CI, 0.96-0.98), PPV was 0.93 (95% CI, 0.90-0.96), and NPV was 0.42 (95% CI, 0.40-0.44). ICD-10 code performance was better for inpatients than for outpatients for fever (χ2 = 41.30; P < .001) and dyspnea (χ2 = 14.25; P = .003) but not for cough (χ2 = 5.13; P = .16). Conclusions and Relevance: These findings suggest that ICD-10 codes lack sensitivity and have poor NPV for symptoms associated with COVID-19. This inaccuracy has implications for any downstream data model, scientific discovery, or surveillance that relies on these codes.


Subject(s)
Clinical Coding/standards , Coronavirus Infections/diagnosis , Cough/diagnosis , Dyspnea/diagnosis , Electronic Health Records , Fever/diagnosis , International Classification of Diseases , Pneumonia, Viral/diagnosis , Adult , Aged , Betacoronavirus , COVID-19 , Clinical Coding/methods , Cohort Studies , Coronavirus Infections/complications , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Cough/etiology , Dyspnea/etiology , Female , Fever/etiology , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Polymerase Chain Reaction , Reproducibility of Results , SARS-CoV-2 , Sensitivity and Specificity , Utah/epidemiology
8.
Radiography (Lond) ; 27(1): 90-94, 2021 02.
Article in English | MEDLINE | ID: covidwho-610978

ABSTRACT

INTRODUCTION: The United Kingdom (UK) has experienced one of the worst initial waves of the COVID-19 pandemic. Clinical signs help guide initial diagnosis, though definitive diagnosis is made using the laboratory technique reverse transcription polymerase chain reaction (RT-PCR). The chest x-ray (CXR) is used as the primary imaging investigation in the United Kingdom (UK) for patients with suspected COVID-19. In some hospitals these CXRs may be reported by a radiographer. METHODS: Retrospective review of CXR reports by radiographers for suspected COVID-19 patients attending the Emergency Department (ED) of a hospital in the UK. Interpretation and use of the British Society of Thoracic Imaging (BSTI) coding system was assessed. Report description and code use were cross-checked. Report and code usage were checked against the RT-PCR result to determine accuracy. Report availability was checked against the availability of the RT-PCR result. A confusion matrix was utilised to determine performance. The data were analysed manually using Excel. RESULTS: Sample size was 320 patients; 54.1% male patients (n = 173), 45.9% female patients (n = 147). The correct code matched report descriptions in 316 of the 320 cases (98.8%). In 299 of the 320 cases (93.4%), the reports were available before the RT-PCR swab result. CXR sensitivity for detecting COVID-19 was 85% compared to 93% for the initial RT-PCR. CONCLUSION: Reporting radiographers can adequately utilise and apply the BSTI classification system when reporting COVID-19 CXRs. They can recognise the classic CXR appearances of COVID-19 and those with normal appearances. Future best practice includes checking laboratory results when reporting CXRs with ambiguous appearances. IMPLICATIONS FOR PRACTICE: Utilisation of reporting radiographers to report CXRs in any future respiratory pandemic should be considered a service-enabling development.


Subject(s)
COVID-19/diagnostic imaging , Clinical Coding/standards , Radiographic Image Interpretation, Computer-Assisted/standards , Radiography, Thoracic , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Research Design/standards , Retrospective Studies , Societies, Medical , United Kingdom , Young Adult
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