A false promise of COVID-19 'big' health data? Health data integrity and the ethics and realities of Australia's health information management practice.
Monique F KilkennyPublished in: Health information management : journal of the Health Information Management Association of Australia (2020)
Context: Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has precipitated an unprecedented volume of medical research. Articles reporting two studies were recently retracted from prestigious journals for reasons including the (thus far) unverifiable provenance of data. This commentary adopts a health information management lens to focus on aspects of data in one of the studies (investigating the use of hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19). The issues: Referencing the Australian context, the current article considers some of the study's reported hospital administrative and coded data categories within the context of Australian hospitals' health information management practices. It highlights potential risks associated with the collection and interpretation of 'big' health data. Implications: This article identifies pitfalls that confront researchers undertaking multi-country studies and the need to consider country-specific: (i) collected administrative data items; (ii) health information-related ethical, legal and management policy constraints on the use of confidential hospital records and derived data; and (iii) differences in health classification systems and versions used in the coding of diagnoses and related procedures, interventions and health behaviours. Conclusions: The article concludes that the inclusion of a qualified, senior Health Information Manager in research teams and on institutional Human Research Ethics Committees would help to prevent potential problems.
Keyphrases
- health information
- healthcare
- big data
- sars cov
- coronavirus disease
- social media
- electronic health record
- respiratory syndrome coronavirus
- public health
- mental health
- machine learning
- primary care
- emergency department
- climate change
- data analysis
- dna methylation
- human health
- systematic review
- risk assessment
- smoking cessation
- genome wide
- drug induced