Development and validation of a case definition to identify hemophilia in administrative data

Validated administrative data based ICD-10 algorithms for chronic conditions: A systematic review

OBJECTIVE

This systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data.

METHODS

A comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70 %. Studies with either sensitivity or PPV <70 % were included as secondary outcomes.

RESULTS

Overall, the search identified 1686 studies of which 54 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. The study identified 40 chronic conditions with high validity and 22 conditions with moderate validity. The validated algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. The algorithms identified included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others.

CONCLUSION

With ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

Impact of inherited bleeding disorders on maternal bleeding and other pregnancy outcomes: A population-based cohort study

INTRODUCTION

Increasing rate of postpartum haemorrhage (PPH) has been observed between 2003 and 2010 in Canada. Inherited bleeding disorders contribute to the risk of PPH.

AIM

To identify the trend in PPH in the last decade, assess the impact of bleeding disorders on pregnancy outcomes and evaluate their coagulation workup during pregnancy.

METHODS

We conducted a population-based retrospective cohort study using the Alberta Pregnancy Birth Cohort from 2010 to 2018. We included women with von Willebrand disease (VWD) and haemophilia, identified by previously validated algorithm and matched with controls. Logistic regression was used to compute odds of PPH and other pregnancy outcomes.

RESULTS

We identified 311,330 women with a total of 454,400 pregnancies with live births. The rate of PPH did not change significantly from 10.13 per 100 deliveries (95% CI 10.10-10.16) in 2010-10.72 (95% CI 10.69-10.75) in 2018 (p for trend = .35). Women with bleeding disorders were significantly more likely to experience PPH (odds ratio [OR] 2.3; 95% CI 1.5-3.6), antepartum haemorrhage (OR 2.9; 95% CI 1.5-5.9) and red cell transfusion (OR 2.8; 95% CI 1.1-7.0). We observed a nonsignificant rise in the rate of PPH in women with VWD and haemophilia. Only 49.5% pregnancies with bleeding disorders had third trimester coagulation factor levels checked. Higher odds of PPH and antepartum haemorrhage were observed even with factor levels ≥0.50 IU/mL in third trimester.

CONCLUSION

Despite comprehensive care in women with bleeding disorders, they are still at higher risk of adverse pregnancy outcomes compared to population controls.

Raising the Bar for Real-World Data in Oncology: Approaches to Quality Across Multiple Dimensions

PURPOSE

Electronic health record (EHR)-based real-world data (RWD) are integral to oncology research, and understanding fitness for use is critical for data users. Complexity of data sources and curation methods necessitate transparency into how quality is approached. We describe the application of data quality dimensions in curating EHR-derived oncology RWD.

METHODS

A targeted review was conducted to summarize data quality dimensions in frameworks published by the European Medicines Agency, The National Institute for Healthcare and Excellence, US Food and Drug Administration, Duke-Margolis Center for Health Policy, and Patient-Centered Outcomes Research Institute. We then characterized quality processes applied to curation of Flatiron Health RWD, which originate from EHRs of a nationwide network of academic and community cancer clinics, across the summarized quality dimensions.

RESULTS

The primary quality dimensions across frameworks were relevance (including subdimensions of availability, sufficiency, and representativeness) and reliability (including subdimensions of accuracy, completeness, provenance, and timeliness). Flatiron Health RWD quality processes were aligned to each dimension. Relevancy to broad or specific use cases is optimized through data set size and variable breadth and depth. Accuracy is addressed using validation approaches, such as comparison with external or internal reference standards or indirect benchmarking, and verification checks for conformance, consistency, and plausibility, selected on the basis of feasibility and criticality of the variable to the intended use case. Completeness is assessed against expected source documentation; provenance by recording data transformation, management procedures, and auditable metadata; and timeliness by setting refresh frequency to minimize data lags.

CONCLUSION

Development of high-quality, scaled, EHR-based RWD requires integration of systematic processes across the data lifecycle. Approaches to quality are optimized through knowledge of data sources, curation processes, and use case needs. By addressing quality dimensions from published frameworks, Flatiron Health RWD enable transparency in determining fitness for real-world evidence generation.

Increased acute care utilisation, comorbidities and mortality in adults with haemophilia: A population-based cohort study from 2012 to 2019

INTRODUCTION

Improvements in treatment strategies have led to increased life expectancy of persons with haemophilia (PWH). Consequently, age-related comorbidities become increasingly relevant.

AIM

To evaluate the prevalence of age-related comorbidities, mortality, health service utilisation and predictors of hospitalisation in PWH compared to the general population.

METHODS

We conducted a population-based retrospective cohort study using linked administrative data. Men with haemophilia were identified in Alberta, Canada (2012-2019) with a validated case definition and were age-matched with male population controls. We calculated the prevalence of major comorbidities, all-cause mortality, and examined health service utilisation including Emergency Department visits and hospitalisations. Logistic regression was applied to identify predictors of hospitalisation.

RESULTS

We identified 198 and 329 persons with moderately severe haemophilia and mild/moderate, respectively. Moderately severe haemophilia had a higher risk of death (standardised mortality ratio 3.2, 95% confidence interval [CI] 1.4-6.3) compared to the general population. PWH had a significantly higher prevalence of hypertension, liver diseases and malignancies than controls. Moderately severe haemophilia was associated with significantly higher rates of hospitalisations (52.5% vs. 14.5%), Emergency Department visits (89.1% vs. 62.7%) and intensive care admissions (8.9% vs. 2.3%). Age > 65 years (adjusted odds ratio [aOR] 6.8) and presence of multiple comorbidities (aOR 3.9) were significant predictors of hospitalisations among PWH.

CONCLUSION

Despite advanced care, haemophilia is associated with higher acute care utilisation than the general population, highlighting the substantial burden of illness on patients and the health care system.