High-risk case identification for use in comprehensive complex care management Academic Article uri icon

abstract

  • The current study aimed to develop a patient selection process for muiltimorbid care management that balances the needs to accurately identify patients who are at risk for future high costs and assures that those selected can clinically benefit from proactive care management. Six physicians were surveyed on characteristics of their current (2012) patients to elicit clinical considerations for high-risk patient identification. Data from 2010– 2011 were extracted from Clalit Health Services'(Israel's largest managed care organization) comprehensive database to derive the Adjusted Clinical Groups (ACG) predictive model risk scores for risk of future high costs. Model discriminatory power was assessed using the c- statistic and positive predictive value (PPV), before and after application of the clinical exclusion criteria. Inclusion criteria were refined based on physician input from a survey …

publication date

  • February 1, 2015