Identifying High-Need Patient Profiles That Respond to Intensive Care Management: Insights from the Camden Health Care Hotspotting RCT
Abstract
ABSTRACT:
Background: Evaluations of complex care programs for high-need patients have yielded mixed results, and identifying patient subgroups may reveal differential intervention effects. This study aimed to use latent class analysis (LCA) to identify high-need patient subgroups within a randomized trial of the Camden Coalition’s Core Model and to examine differences in healthcare utilization and care team engagement.
Methods & Findings: We conducted a post-hoc exploratory analysis of a randomized controlled trial (ClinicalTrials.gov: NCT02090426 ) involving 780 adults aged 18 ― 80 years in Camden, New Jersey, who had multiple chronic conditions and frequent hospitalizations. Participants were assigned to receive multidisciplinary care management delivered by nurses, social workers, and community health workers for 3 ― 4 months following hospital discharge, or to usual care. LCA incorporated medical, behavioral, and social risk factors, as well as prior hospital utilization, to identify patient subgroups. Outcomes included inpatient readmissions and emergency department visits over two consecutive 6-month post-discharge periods, along with service hours delivered to intervention patients. Four patient classes emerged: (1) Behavioral Health & Housing Instability, (2) Multi-system Medical Complexity, (3) Pulmonary Health & Substance Use, and (4) Lower Overall Complexity. In the second 6-month follow-up period, intervention patients had lower readmission rates compared with…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design. Reported size: 780 participants or records.
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