Integrating Data to Support Care Management Transformation
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1 Integrating Data to Support Care Management Transformation The Washington State Experience David Mancuso, PhD Director, Research and Data Analysis Division Washington State Department of Social and Health January 14, Getty Images, istock
2 Our Challenge A small proportion of the Medicaid population accounts for a disproportionate share of Medicaid costs High-cost clients are far more likely to be served in multiple Medicaid delivery systems Behavioral health conditions are key drivers of disability-related Medicaid caseload growth and expenditures Getty Images, Hemera 2
3 Complex Clients Drive Medicaid Costs High medical risk disabled adult Medicaid enrollees TOTAL PER MEMBER PER MONTH COST, ALL MEDICAID DELIVERY SYSTEMS WASHINGTON STATE SFY 2010 $5,721 Clients with Significant Functional Impairments $3,183 ALL High Medical Risk $3,439 Clients with Serious Mental Illness $3,036 Clients with Substance Use Disorders $1,999 High medical risk clients without these 3 conditions TOTAL = 29,008 n = 7,327 n = 16,843 n = 11,962 n = 6,921 NOTE: There is some duplication across client categories. 3
4 Integrated Data Capacity in Washington State Dental Medical Eligibility Medicaid, State Only Hospital Inpatient/ Outpatient Arrests Charges Convictions Incarcerations Community Supervision Managed Care Physician Prescription Drugs Hours Wages Births Deaths Homelessness Housing Assistance Washington State Patrol Administrative Office of the Courts Department of Corrections Health Care Authority Employment Security Department Department of Health Department of Commerce External Internal WASHINGTON STATE Department of Social and Health INTEGRATED CLIENT DATABASE DSHS Aging and Long- Term Support DSHS Children s DSHS Developmental Disabilities DSHS Behavioral Health and Service Integration Mental Health and Substance Abuse DSHS Economic DSHS Juvenile Rehabilitation DSHS Vocational Rehabilitation Nursing Facilities In-home Community Residential Functional Assessments Child Protective Child Welfare Adoption Adoption Support Child Care Out of Home Placement Voluntary Case Management Community Residential Personal Care Support Residential Habilitation Centers and Nursing Facilities Assessments Detoxification Opiate Substitution Treatment Outpatient Treatment Residential Treatment Child Study Treatment Center Children s Longterm Inpatient Program Community Inpatient Evaluation/ Treatment Community Food Stamps TANF and State Family Assistance General Assistance Child Support Working Connections Child Care Institutions Dispositional Alternative Community Placement Parole Medical and Psychological Training, Education, Supplies Case Management Vocational Assessments Job Skills Family Reconciliation State Hospitals State Institutions 4
5 High-risk targeting approaches Extreme ER/ED utilization Expected future medical costs Prospective inpatient risk Care gaps and quality indicators Getty Images, TongRo Images 5
6 Getty Images, istock Prospective Inpatient Admission Risk Model Example condition within risk group Sickle-cell disease Dialysis catheter infection Pneumonia Hemophilia/von Willebrands Lung transplant Secondary malignant neoplasm Congestive heart failure Age 85 or above Chronic skin ulcer Liver transplant Chronic renal failure Ulcerative colitis Diabetes, type 1 with complications Septicemia Chronic obstructive asthma Chronic nephritis Decubitis ulcer Heart transplant Rx for Liver Disease Alcohol dependence 12.9% 11.2% 9.4% 8.8% 8.0% 8.0% 7.1% 6.1% 6.0% 5.3% 5.3% 5.2% 5.1% 5.0% 5.0% 4.9% 15.6% 18.7% 21.4% 27.7% 6
7 Getty Images, istock Prospective Inpatient Admission Risk Model continued Hospital Admission Impact... Additional impact per hospital admission in prior 30 days Additional impact per hospital admission in prior days Additional impact per hospital admission in prior days Additional impact per hospital admission in prior days Outpatient Emergency Room Utilization Impact... Additional impact per OP ER visit in prior 30 days Additional impact per OP ER visit in prior days Additional impact per OP ER visit in prior days Additional impact per OP ER visit in prior days 0.3% 0.2% 2.1% 1.7% 0.9% 4.2% 5.8% 9.8% Patient Example Jane has been diagnosed with congestive heart failure (9.4%), poorly controlled type 1 diabetes (6.0%), and chronic obstructive asthma (5.3%). She was hospitalized once in the prior days (5.8%), and twice in the prior days (2 x 2.1% = 4.2%). She has been to the ED twice in the past month without being admitted to the hospital (2 x 1.7% = 3.4%). Her risk of an inpatient admission in the next 6 months is 28.3%. 7
8 DSHS Research and Data Analysis Division AUGUST January 8, (MANCUSO) 8
9 9
10 10
11 DSHS Research and Data Analysis Division AUGUST January 8, (MANCUSO) 11
12 Drug Adherence CLOSE-UP DSHS Research and Data Analysis Division January 14, (MANCUSO) 12
13 Provider Reporting Ability Getty Images, istock CLOSE-UP 13
14 Intervention strategy: health home interventions focused on management of high-risk patients Nurse care manager to client ratio 1:50 Primarily face-to-face Telephone support as needed Evidence-based protocols including: Diabetes management Pain management Fall assessment and prevention planning Medication management Health Action Planning Coaching for Activation Getty Images, istock Comprehensive Assessment including Patient Activation Measure (PAM ) Client-centered Health Action Plan and Goal Setting Worksheet Set goals with client according to activation level Education towards self-management of chronic illness 14
15 Early returns show promise Chronic Care Management evaluation Modest net savings Driven by reduced Hospital IP and SNF costs Reduced mortality Increased patient satisfaction Cost Detail Estimated per member per month impact + $ 180 OVERALL Savings $ 27 Medical Costs + $ 46 Long-term Care Costs Intervention Costs $
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