Pediatric Population Management Classification for Children with Medical Complexity.
Christian D PulciniXianqun LuanElizabeth S BrooksAnnique HoganTina PenroseChen C KenyonDavid M RubinPublished in: Population health management (2024)
Improving the overall care of children with medical complexity (CMC) is often beset by challenges in proactively identifying the population most in need of clinical management and quality improvement. The objective of the current study was to create a system to better capture longitudinal risk for sustained and elevated utilization across time using real-time electronic health record (EHR) data. A new Pediatric Population Management Classification (PPMC), drawn from visit diagnoses and continuity problem lists within the EHR of a tristate health system, was compared with an existing complex chronic conditions (CCC) system for agreement (with weighted κ) on identifying CCMC, as well as persistence of elevated charges and utilization from 2016 to 2019. Agreement of assignment PPMC was lower among primary care provider (PCP) populations than among other children traversing the health system for specialty or hospital services only (weighted κ 62% for PCP vs. 82% for non-PCP). The PPMC classification scheme, displaying greater precision in identifying CMC with persistently high utilization and charges for those who receive primary care within a large integrated health network, may offer a more pragmatic approach to selecting children with CMC for longitudinal care management.
Keyphrases
- primary care
- electronic health record
- healthcare
- quality improvement
- young adults
- machine learning
- deep learning
- magnetic resonance
- emergency department
- adverse drug
- cross sectional
- magnetic resonance imaging
- risk assessment
- pain management
- big data
- affordable care act
- network analysis
- study protocol
- human health
- acute care
- artificial intelligence
- data analysis