Using Population Health Data Tools to Target Care Coordination Interventions David A. Mann, MD, PhD Epidemiologist, Office of Minority Health and Health.

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Presentation transcript:

Using Population Health Data Tools to Target Care Coordination Interventions David A. Mann, MD, PhD Epidemiologist, Office of Minority Health and Health Disparities Maryland Department of Health and Mental Hygiene Maryland Health Enterprise Zones Data and Evaluation All-Zone Meeting May 11,

Generic HEZ Logic Model 2

Relevance to Waiver/Global Budgets New CMS waiver in Was cost per admission, now hospital cost per capita MD to generate $330 million in Medicare savings over a five year period Maryland must limit annual all-payer per capita total hospital cost growth to 3.58% MD will shift virtually all hospital revenue into global payment models. Maryland’s aggregate Medicare 30-day all-cause, all-site hospital readmission rate to match national 3

Recipe for Success Do enough (productivity) Of the right things (logic model) For the right people (high user targeting) 4

High Utilizer Focusing Greatest impact on utilization if we can succeed with the high utilizers (obviously). CRISP analysis of PG HEZ (one zip code) admissions over 2 yrs: – Top 10% of high users – had 30% of admissions – and 78% of readmissions – This was 269 people. HIPAA issues in who CRISP can inform? 5

High Utilizer Identification How defined? – Relative vs. Absolute Who are these people? Who is entitled to know? – HIPAA issues

What Network is Needed? How Does the PHI* Flow? Patient PCP PCMH HospitalsInsurers CRISP (TPO Triangle*) *TPO = Treatment, Payment, Operations PHI = Protected Health Information Home Health CBOs

CRISP runs High User Analysis for Zip Code(s) [Admits?, ED visits?] Example: 2-year analysis of admits 20743: top 10% is 269 pts, 1085 admits (30%), 306 readmits (78%). (Hypothetical Breakdown: 69 dead, 150 with known PCP 50 without PCP) 150 known PCP see 50 different PCP CRISP Sends 50 PCP a list of their HUs (average 3 HU per PCP) CRISP Sends HEZ a list of the 50 PCP who have HU HEZ informs PCPs of available case management and CHW services PCP informs HU of HEZ services, asks HU to contact HEZ, or gets consent for HEZ to call/contact HU Who can be informed for the 50 without known PCP? Maybe the insurer? Perhaps insurer gets all 200? Which leaves is with the question of who can be informed for uninsured no PCP? The hospital?

HOSP runs High User Analysis for Zip Code(s) [Admits?, ED visits?] Example: 2-year analysis of admits 20743: top 10% is 269 pts, 1085 admits (30%), 306 readmits (78%). (Hypothetical Breakdown: 69 dead, 150 with known PCP 50 without PCP) 150 known PCP see 50 different PCP HOSP Sends 50 PCP a list of their HUs (average 3 HU per PCP) HOSP Sends HEZ a list of the 50 PCP who have HU HEZ informs PCPs of available case management and CHW services PCP informs HU of HEZ services, asks HU to contact HEZ, or gets consent for HEZ to call/contact HU Who can be informed for the 50 without known PCP? Maybe the insurer? Perhaps insurer gets all 200? Which leaves is with the question of who can be informed for uninsured no PCP? The hospital?

Next Steps HEZs need to identify network members State needs to clarify HIPAA compliance issues in this process CRISP needs to determine its capacity to meet such data requests, and associated costs HEZ network members need to meet and discuss feasibility and obstacles