Dataset Information

Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.

ABSTRACT:

Objectives

As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterise the epidemiology of infectious diseases. The objective of this study is to investigate the strengths and limitations of sources currently being used for research.

Design

Retrospective descriptive analysis.

Primary and secondary outcome measures

Yearly number of national-level and state-level disease-specific case counts and disease clusters for three diseases (measles, mumps and varicella) during a 5-year study period (2013-2017) across four different data sources: Optum (health insurance billing claims data), HealthMap (online news surveillance data), Morbidity and Mortality Weekly Reports (official government reports) and National Notifiable Disease Surveillance System (government case surveillance data).

Results

Our study demonstrated drastic differences in reported infectious disease incidence across data sources. When compared with the other three sources of interest, Optum data showed substantially higher, implausible standardised case counts for all three diseases. Although there was some concordance in identified state-level case counts and disease clusters, all four sources identified variations in state-level reporting.

Conclusions

Researchers should consider data source limitations when attempting to characterise the epidemiology of infectious diseases. Some data sources, such as billing claims data, may be unsuitable for epidemiological research within the infectious disease context.

SUBMITTER: Majumder MS

PROVIDER: S-EPMC9980358 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.

Majumder Maimuna S MS Cusick Marika M Rose Sherri S

BMJ open 20230228 2

<h4>Objectives</h4>As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterise the epidemiology of infectious diseases. The objective of this study is to investigate the strengths and limitations of sources currently being used for research.<h4>Design</h4>Retrospective descriptive analysis.<h4>Primary and secondary outcome measures</h4>Yearly number of national-level and state-level disea ...[more]

PMID: 36854597

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Project description:BackgroundMultimorbidity is a global health issue, particularly for older adults in the primary care setting. An adequate portrayal of its epidemiology is essential to properly identify and understand the health care needs of this population. This study aimed to compare the differences in the prevalence of selected chronic conditions and multimorbidity, including its associated characteristics, using health survey/self-reported (SR) information only, administrative (Adm) data only and the combined (either) sources.MethodsThis was a secondary analysis of survey data from the first cycle of the Longitudinal Survey on Senior's Health and Health Services Use linked to health-Adm data. The analytical sample consisted of 1625 community-dwelling older adults (≥65 years) recruited in the waiting rooms of primary health clinics in a selected administrative region of the province of Quebec. Seventeen chronic conditions were assessed according to two different data sources. We examined the differences in the observed prevalence of chronic conditions and multimorbidity and the agreement between data sources.ResultsThe prevalence of each of the 17 chronic conditions ranged from 1.2 to 68.7% depending on the data source. The agreement between different data sources was highly variable, with kappa coefficients (κ) ranging from 0.05 to 0.73. Multimorbidity was very high in this population, with an estimated prevalence of up to 95.9%. In addition, we found that the association between sociodemographic and behavioural factors and the presence of multimorbidity varied according to the different data sources and thresholds.ConclusionsThis is the first study to simultaneously investigate chronic conditions and multimorbidity prevalence among primary care older adults using combined SR and health-Adm data. Our results call attention to (1) the possibility of underestimating cases when using a single data source and (2) the potential benefits of integrating information from different data sources to increase case identification. This is an important aspect of characterizing the health care needs of this fast-growing population.

Project description:BACKGROUND: Administrative data are a valuable source of estimates of diabetes prevalence for groups such as coronary heart disease (CHD) patients. The primary aim of this study was to measure concordance between medical records and linked administrative health data for recording diabetes in CHD patients, and to assess temporal differences in concordance. Secondary aims were to determine the optimal lookback period for identifying diabetes in this patient group, whether concordance differed for Indigenous people, and to identify predictors of false positives and negatives in administrative data. METHODS: A population representative sample of 3943 CHD patients hospitalized in Western Australia in 1998 and 2002-04 were selected, and designated according to the International Classification of Diseases (ICD) version in use at the time (ICD-9 and ICD-10 respectively). Crude prevalence and concordance were compared for the two samples. Concordance measures were estimated from administrative data comparing diabetes status recorded on the selected CHD admission ('index admission') and on any hospitalization in the previous 1, 2, 5, 10 or 15 years, against hospital medical records. Potential modifiers of agreement were determined using chi-square tests and multivariable logistic regression models. RESULTS: Identification of diabetes on the index CHD admission was underestimated more in the ICD-10 than ICD-9 sample (sensitivity 81.5% versus 91.1%, underestimation 15.1% versus 4.4% respectively). Sensitivity increased to 89.6% in the ICD-10 period using at least 10 years of hospitalization history. Sensitivity was higher and specificity lower in Indigenous patients, and followed a similar pattern of improving concordance with increasing lookback period. Characteristics associated with false negatives for diabetes on the index CHD hospital admission were elective admission, in-hospital death, principal diagnosis, and in the ICD-10 period only, fewer recorded comorbidities. CONCLUSIONS: The accuracy of identifying diabetes status in CHD patients is improved in linked administrative health data by using at least 10 years of hospitalization history. Use of this method would reduce bias when measuring temporal trends in diabetes prevalence in this patient group. Concordance measures are as reliable in Indigenous as non-Indigenous patients.

Dataset Information

Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.

Objectives

Design

Primary and secondary outcome measures

Results

Conclusions

Publications

Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.

Similar Datasets

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