Where No Universal Health Care Identifier Exists: Comparison and Determination of the Utility of Score-Based Persons Matching Algorithms Using Demographic Data.
Anthony WaruruAgnes NatukundaLilly M NyagahTimothy A KelloggEmily Zielinski GutierrezWanjiru WaruiruKenneth MasamaroRichelle HarklerodeJacob OdhiamboEric-Jan MandersPeter W YoungPublished in: JMIR public health and surveillance (2018)
Without deduplication, over reporting occurs across the care and treatment cascade. Jaro-Winkler score-based matching performed the best in identifying matches. A pragmatic estimate of duplicates in health care settings can provide a corrective factor for modeled estimates, for targeting and program planning. We propose that even without a UHID, standard national deduplication and persons-matching algorithm that utilizes demographic data would improve accuracy in monitoring HIV care clinical cascades.
Keyphrases
- healthcare
- quality improvement
- machine learning
- electronic health record
- big data
- deep learning
- palliative care
- affordable care act
- cancer therapy
- artificial intelligence
- study protocol
- randomized controlled trial
- health information
- solid phase extraction
- pain management
- replacement therapy
- neural network
- clinical evaluation