Presentation on theme: "Barb Simons, RN Cate Ranheim, MD October 2010 Madison, WI."— Presentation transcript:
Barb Simons, RN Cate Ranheim, MD October 2010 Madison, WI
Overview: 1.The Need 2.The Program 3.The Patients 4.The Analysis
Defining the Needs for a Solution: PATIENTS: ED is not the right care for increasing chronic care management needs CLINICIANS: under or over-treating ED patients PAYORS: insurance premiums rise in response to hospitals increasing costs to cover bad debt and uncompensated care HOSPITAL: capacity constraints in ED require targeting avoidable ED admissions – we began with those who, upon intake, stated homelessness, provided shelter addresses, or did not give an address
Retrospective, medical record review 330 homeless and unstably housed patients in MADISON, WI seen in ED or hospitalized at Meriter Hospital between 1/07- 10/08 manually reviewed to identify and evaluate barriers to good health: -Housing-Literacy -Lack of primary care provider-Transportation -AODA-Medications -Mental Illness- Insurance Overcoming Barriers to Good Health in the Medically Underserved
Where Should We Focus Our Resources? *Each identified in 15% of population Housing Lack of primary care provider AODA* Mental Illness* Medications Insurance Literacy Transportation
HEALTH Patients Meriter Medical Record Numbers Program patients sought Meriter emergency services 138 times in the 10 months before the program started. Over $86K COST savings potential from these visits alone*. *Based on Medicaid reimbursement for ED visits of $0.13/$1.00 charge
November 2009 Helping Educate and Link the Homeless (HEALTH) Program is born: Four outreach locations open in an effort to overcome identified barriers to good health One outreach clinic/week, four alternating sites, volunteer-staffed Funded with $250,000 grant from Meriter Foundation for 2010
Overcoming Barriers in the Medically Underserved Project Jan-Nov 2009 HEALTH Program Four Mobile Sites Open Nov 2009 HEALTH Full-time RN Starts Feb 2010 HEALTH Hut Opens Mar 2010 HEALTH Program Five Mobile Sites Daily Hut Visits Jul 2010-Present HEALTH Program Timeline
LOCATIONSTAFFHOURSCARE “Hut”1 FTE RN40+ hrs/weekFollow-up to mobile sites, receive referrals Mobile clinics 5-8 volunteers; MD, NP, RN, SW, Admin 3 hours/week per team Identify and treat patient medical needs HEALTH Program Logistics
HEALTH Program Data Cardio- Respiratory 36% Infection 9% Musculo- Skeletal 17% Endocrine 2% Program patients Nov 2009 – Aug 2010 185 unique patients 393 visits PRIMARY DIAGNOSIS CATEGORY: Other 15% Mental Illness 21% 1% unknown
HEALTH Patients Medical Diagnoses by Bucket Most cardiorespiratory patients have a secondary cardiorespiratory diagnosis Mental Illness: secondary diagnosis prevalence is only 2% higher than primary diagnosis prevalence Secondary Diagnosis Group Primary Diagnosis Group
HEALTH Patient Patterns Top 5 diagnoses represent just 22% of all diagnoses: Hypertension, Depression, Anxiety, Type II Diabetes Transitionally-housed patients made more repeat visits to the Hut per person, on average, than those reported as homeless or permanently housed.
Patient Pathways % of Patients Incurred CostsAvoided Costs A 41% ProgramED visit B 55% Program x X visitsED x program visits C 3% Program + ED D 0.5% Program + ED + IPNone, plus program-sponsored care E <.05% EDAdditional ED visits F ED visitNone G ED visit + I/PNone H Multiple ED + I/PNone Value: avoiding unnecessary ED visits, reducing need for I/P admissions
Where do the underserved go for care? ED Control Group HEALTH Program Participants E C, D D F GH E A, B I/P Before After
Measuring Value Estimating What Would Have Happened … The estimated likelihood of a substitute ED visit … times the median ED cost per Medicaid patient … plus the estimated likelihood of an inpatient admission times the median cost of a Medicaid I/P admit times Elixhauser co-morbidity weight …minus What Did Happen The cost of care provided at the Hut… and any ED visit incurred times the median cost of a Medicaid ED visit and any I/P visit incurred times Elixhauser co-morbidity weight [Probability of ED admit x Median ED Visit Cost + (Probability of I/P Admit x Median Cost of I/P Admit) x (Elixhauser Index Value)] – [(N hut visits x Median Hut Costs of Care per Patient +(ED Visits Incurred x Median ED Visit Cost ) + ( I/P Admit x Median I/P Cost* Elixhauser Index Value)]
How It Works *all patient and cost data listed here is fictitious Costs = total direct expenses only (salaries, supplies, bus passes, equipment) and excludes building depreciation, overhead, etc. Average Inpatient cost of care is specific to diagnosis bucket (i.e., Service Line) The greater the ALOS and Median Inpatient Cost of Care the greater the avoided cost opportunity: analyze your current volumes to estimate your potential savings
Quick and Dirty ROI Recipe 1. Gather ingredients from Finance Department: – Cost per Medicaid ED visit: (total direct costs *Medicaid % payor mix)/N Medicaid patients – Number of ED admits from either local shelters or no address in one year: assess common ED diagnoses by service line – Average I/P costs = total direct expenses for Service Line/N patients (use 1 year of data at least) 2. Calculate your current costs for these patients to date using the above data 3. Use the formula presented to determine your cost reduction potential Sample at least 30 patients: estimate probability of ED avoidance through record review Use Elixhauser comorbidity values (see supplemental) Assume a indigent care program estimated cost per patient: we used $50 4. If the cost of program startup – donations is less than #3, consider implementing an off-site indigent care program like HEALTH.
www.healthprogram.us Meriter Foundation St. Vincent de Paul UCC-Memorial Church Meriter Hospital Masimo Corporation Association of Spiritual Caregivers Wisconsin Medical Project Dr. Bernie Micke Dr. Jack Kenney Nicole Heide, RN Mandy McGowan, RN McGovern & Sons Jo Hoffman/Ellen Boyce John Warden Home Depot Hometown Flooring Sherwin-Williams Meriter Medical Staff Office Thank you to our donors!
www.healthprogram.us A special thank you to our friends and colleagues, Heidi Kimble and Melissa Strayer, for data analysis and volunteer time!
Supplemental B: Elixhauser Comorbidity Index Elixhauser, Anne; Steiner, Claudia; MD, MPH; Harris, D; Coffey, Rosanna. Comorbidity Measures for Use with Administrative Data. Medical Care. 36(1):8-27, January 1998. Source: Effects of Specific Comorbidities on Outcomes Controlling for Demographic, Insurance, and Other Clinical Factors of Adult, Nonmaternal Patients Who Were Hospitalized in California in 1992 (n = 1,779,167)