Using big data analytics to improve HIV medical care utilisation in South Carolina: A study protocol.
Bankole OlatosiJiajia ZhangSharon WeissmanJianjun HuMohammad Rifat HaiderXiaoming LiPublished in: BMJ open (2019)
The study team applied for data from different sources and submitted individual Institutional Review Board (IRB) applications to the University of South Carolina (USC) IRB and other local authorities/agencies/state departments. This study was approved by the USC IRB (#Pro00068124) in 2017. To protect the identity of the persons living with HIV (PLWH), researchers will only receive linked deidentified data from the RFA. Study findings will be disseminated at local community forums, community advisory group meetings, meetings with our state agencies, local partners and other key stakeholders (including PLWH, policy-makers and healthcare providers), presentations at academic conferences and through publication in peer-reviewed articles. Data security and patient confidentiality are the bedrock of this study. Extensive data agreements ensuring data security and patient confidentiality for the deidentified linked data have been established and are stringently adhered to. The RFA is authorised to collect and merge data from these different sources and to ensure the privacy of all PLWH. The legislatively mandated SC data oversight council reviewed the proposed process stringently before approving it. Researchers will get only the encrypted deidentified dataset to prevent any breach of privacy in the data transfer, management and analysis processes. In addition, established secure data governance rules, data encryption and encrypted predictive techniques will be deployed. In addition to the data anonymisation as a part of privacy-preserving analytics, encryption schemes that protect running prediction algorithms on encrypted data will also be deployed. Best practices and lessons learnt about the complex processes involved in negotiating and navigating multiple data sharing agreements between different entities are being documented for dissemination.
Keyphrases
- big data
- electronic health record
- healthcare
- machine learning
- artificial intelligence
- randomized controlled trial
- clinical trial
- palliative care
- data analysis
- mental health
- human immunodeficiency virus
- deep learning
- social media
- antiretroviral therapy
- radiofrequency ablation
- hiv aids
- hiv testing
- health insurance
- anti inflammatory