The Camden Coalition of Healthcare. Management

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Camden Coalition of Healthcare Providers Camden Coalition of Healthcare Providers The Camden Coalition of Healthcare Providers Approach to Risk Stratified Care Management Presentation by: Kennen S. Gross, PhD, MPH Director, Research & Evaluation Camden Coalition of Healthcare Providers www.camdenhealth.org

The mission of CCHP is to improve the health status t of all Camden residents by increasing the capacity, quality and access to care in the city.

Hot Spotting Hot Spotting: the ability to identify in a timely manner patients who are heavy users of the system and their patterns of use, so that targeted intervention and follow-up programs can be put in place to address their needs and change the existing, potentially ineffective, utilization pattern. Understand the problem Develop interventions to target the problem Identify and engage patients needing intervention Evaluate the impact of the solutions

Diabetes COPD Multi-CC No-CC

Traditional Intervention Paradigm Diabetes COPD Multi-CC No-CC

Traditional Intervention Paradigm Diabetes COPD Multi-CC No-CC High Utilizer

Hotspotting Intervention Paradigm Diabetes COPD Multi-CC No-CC High Utilizer

Understand the problem Develop interventions to target the problem Identify and engage patients needing intervention Evaluate the impact of the solutions

CCHP Data Access Solution: Camden Health Database Yearly Clams Data Data Use Agreements IRB Agreement Data processing/cleaning i Probabilistic matching Geocoding Camden Residents All-Payer Claims Longitudinal Dataset Demographics Inpatient and Emergency visits Diagnosis codes Charges/receipts Insurance

Methodology Cluster analysis an exploratory data analysis tool for solving classification problems. Its object is to sort cases (patient utilization history) into groups, or clusters, so that the degree of association is strong between members of the same cluster and weak between members of different clusters. E h l t th d ib i t f th d t ll t d th l t Each cluster thus describes, in terms of the data collected, the class to which its members belong.

Cluster Analysis Results % total 60 Cluster % total % total ED % total IP % total LOS % total charges % total receipts readmits Total charges Total receipts Low Utilization 36.9% 16.7% 0.0% 0.0% 4.1% 3.9% 0.0% $29,459,067 $3,216,749 Average Utilization 20.3% 21.2% 0.0% 0.0% 5.0% 4.7% 0.0% $35,843,429 $3,867,264 % total 60 Cluster % total % total ED % total IP % total LOS % total charges % total receipts readmits Total charges Total receipts High ED Utilizers 10.1% 23.8% 3.0% 1.7% 6.5% 6.6% 0.0% $46,579,465 $5,505,723 Borderline ED/IP Utilizers Moderate ED Utilizers Outlier ED Utilizers 7.9% 3.3% 8.1% 7.5% 7.8% 7.7% 0.0% $56,204,358 $6,439,403 7.8% 9.5% 6.2% 3.7% 6.3% 6.5% 0.0% $45,433,623 $5,391,079 2.1% 11.6% 2.5% 1.7% 3.9% 3.4%.3% $28,203,522 $2,829,333 Cluster % total % total ED % total IP % total LOS % total charges % total receipts Borderline IP/ED Utilizers % total 60 readmits Total charges Total receipts 11.3% 6.6% 41.9% 34.9% 27.3% 27.3% 0.0% $196,526,193, $22,735,172, Moderate Inpatient Utilizers 2.8% 3.6% 24.5% 22.5% 18.5% 20.4% 75.9% $133,209,990 $16,957,202 High Inpatient Utilizers Extreme Utilizers Total.8% 1.5% 13.0% 27.5% 20.0% 18.8% 23.0% $144,148,652 $15,652,705.1% 2.1%.7%.5%.7%.6%.9% $5,192,345 $537,555 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% $720,800,645 $83,132,186

Mean # ED visits High ED Utilizers 2,854 patients (10%) Mean % of all unique primary Mean % of IP ICD classified as that are 60 day Mean total Mean # IP visits Mean total LOS chronic readmissions charges Mean total receipts Median Age 5.24.09.25 8% 0% $16,321 $1,929 31 % total % total ED % total IP % total LOS % total charges % total receipts % total 60 readmits Total charges Total receipts 10.1% 23.8% 3.0% 1.7% 6.5% 6.6% 0.0% $46,579,465 $5,505,723 34 UV 611 17 43 27 676 48 15 24 17 18 36 35 37 UV 611 59 19 18 19 33 41 # 45 54 25 38 95 29 33 40 36 # 63 v 86 38 40 47 0 30 42 0 54 38 28 18 30 40 27 54 27 20 59 v 39 676 16 92 # v 45 41 66 25 41 99 90 UV 168 44 58 130 # 130 UV 70 UV 38 Patients Percent URIN TRACT INFECTION NOS 382 2.8 ABDOM PAIN NOS (Begin 1994) 319 2.4 ACUTE PHARYNGITIS 302 2.2 BACKACHE NOS 277 2.0 NO PROC/PATIENT DECISION 265 2.0 HEADACHE 224 1.7 ACUTE URI NOS 215 1.6 45 CHEST PAIN NOS 214 1.6 117 35 130 30 ABDOM PAIN NEC (Begin 1994) 190 14 1.4 76 76 40 47 Copyright: 2012 Esri, DeLorme, NAVTEQ VAGINITIS NOS 189 1.4

Mean # ED visits Moderate Inpatient Utilizers 786 patients (2.8%) Mean % of all unique primary Mean % of IP ICD classified as that are 60 day Mean total Mean # IP visits Mean total LOS chronic readmissions charges Mean total receipts Median Age 2.91 2.72 12.15 32% 49% $169,478 $21,574 53 % total % total ED % total IP % total LOS % total charges % total receipts % total 60 readmits Total charges Total receipts 2.8% 3.6% 24.5% 22.5% 18.5% 20.4% 75.9% $133,209,990 $16,957,202 10 UV 611 5 11 9 676 24 7 5 5 4 13 4 10 UV 611 5 27 8 4 21 29 7 # 19 7 16 95 6 8 16 10 # 29 v 19 24 14 12 30 15 0 14 9 4 9 7 14 12 15 5 6 6 v 8 676 7 5 v 10 6 11 8 2 26 23 UV 168 6 130 15 # 76 22 10 15 5 8 130 30 0 # 10 Copyright: 2012 Esri, DeLorme, NAVTEQ 130 UV 70 UV 38 Patients Percent CHEST PAIN NOS 74 2.0 URIN TRACT INFECTION NOS 65 1.8 SHORTNESS OF BREATH (Begin 1998) 56 15 1.5 RESPIRATORY ABNORM NEC 53 1.5 NO PROC/PATIENT DECISION 51 1.4 ABDOM PAIN NOS (Begin 1994) 50 1.4 PNEUMONIA ORGANISM NOS 50 1.4 CEREBR ART OCCLUS NOS W/ INFARCT (Begin 19 40 1.1 CHEST PAIN NEC 40 1.1 ACUTE RENAL FAILURE NOS 38 1.0

Mean # ED visits High Inpatient Utilizers 215 patients (1%) Mean % of all unique primary Mean % of IP ICD classified as that are 60 day Mean total Mean # IP visits Mean total LOS chronic readmissions charges Mean total receipts Median Age 4.48 5.33 54.71 34% 55% $673,592 $73,143 57 % total % total ED % total IP % total LOS % total charges % total receipts % total 60 readmits Total charges Total receipts.8% 1.5% 13.0% 27.5% 20.0% 18.8% 23.0% $144,148,652 $15,652,705 2 UV 611 4 UV 611 676 95 9 1 4 5 1 2 1 0 4 1 1 3 6 1 4 7 5 # 3 5 3 0 0 4 7 5 # 10 v 9 2 3 7 30 0 3 2 0 3 2 3 1 2 1 1 2 v 0 676 0 1 v 2 2 1 3 1 7 5 UV 168 1 5 130 # 0 # 130 UV 70 UV 38 Patients Percent RESPIRATORY ABNORM NEC 34 2.2 CHEST PAIN NOS 29 1.9 SHORTNESS OF BREATH (Begin 1998) 28 18 1.8 REHABILITATION PROC NEC 26 1.7 ABDOM PAIN NOS (Begin 1994) 25 1.6 SEPTICEMIA NOS 23 1.5 6 ACUTE RENAL FAILURE NOS 21 1.4 0 URIN TRACT INFECTION NOS 21 1.4 1 130 30 30 PNEUMONIA ORGANISM NOS 19 1.2 76 2 3 6 Copyright: 2012 Esri, DeLorme, NAVTEQ ACUTE ON CHRONIC SYSTOLIC HEART FAILR(Begi 17 1.1

Understand the problem Develop interventions to target the problem Identify and engage patients needing intervention Evaluate the impact of the solutions

CCHP Data Access Solution: Camden Health Information Exchange Web based HIE system Daily HL-7 Feeds HIE Vendor Daily Data Share Customized data cleaning and processing HIE Daily Report List of patients currently in hospital with 2+IP and/or 6+ ED in last 6 months CCHP care teams review cases Enroll patients in Care Management / Care Transitions program before discharge

Risk Stratification Workflow Identify HIE daily admissions data Access to medical charts Triage tool www.camdenhealth.org

Identify Eligible Patients Health Information Exchange (HIE) Daily Feed Real time snapshot of currently hospitalized patients from 2 local hospitals Emailed to teams each day Eligibility criteria 2 or more inpatient admissions in last 6 months ER utilization data is also collected & reported Access to Cooper and Lourdes EMR More in-depth information i about patients used to further determine eligibility through triage

Step 1: Identify patients with 2+ inpatient visits in last 6 months

Triaging Eligible Patients Triage utilized with patients who meet initial iti eligibility ibilit criteria i Semi-structured qualitative tool collecting patient data from EMR Data on current and historical inpatient admissions that help assess complexity PCP & insurance information Chronic conditions diagnoses Inpatient admission causes Medication information Histories of social comorbidities homelessness, lack of social support, barriers to accessing services, substance use

Rule-out Criteria at Triage Current & historical inpatient admission data from EMR used to rule-out patients t Was the primary cause of admission: Oncology-related? Pregnancy-related? Related to a surgical procedure for an acute condition? Mental health-related without other conditions? Acute disease-related? Due to complications of a condition with limited treatment options? Was patient discharged prior to triage?

Static Risk Score at Triage Certain data collected at triage form a static ti triage risk score Sum of score for 3 risk factors Inpatient admissions 2 visits = +1 point 3 or more = +2 points ED visits 4 to 5 visits = +1 point 6 or more visits = +2 points Medication information 5 or more medications = +1 point Used as a subtotal in calculation of patient s Total Risk Score at bedside

Risk Stratification Workflow Identify HIE daily admissions data Access to medical charts Eligibility Assign Flexible rule-out criteria

Assign to Care Teams Assignment to a care team made based on most current primary care provider (PCP) Gives care teams an in-depth understanding of a limited set of PCP practices Allows care teams to begin developing relationships with PCP practices

Rule-Out Criteria at Assignment Flexible set of rule-out criteria Adjusted based on qualitative information from care team members & programmatic needs Current criteria: Discharged prior to pre-enrollment (result of time lapse between triage & assignment) Uninsured Over the age of 80 years old/dementia comorbidity Increased probability of diminished mental capacity Not conducive to behavior change needed to manage advanced chronic conditions in age group Non-Camden primary care provider

Risk Stratification Workflow Identify HIE daily admissions data Access to medical charts Eligibility Assign PCP-focused assignment Increase relationship building with practices Stratify Bedside outreach Risk Tool administration HIE Admissions Flag: 2+ hospital admissions < 6 months Triage: In-depth analysis of medical record to complete triage tool Flexible Rule-Out Criteria: Uninsured Discharged prior to triage (no longer in hospital) Over 80 years old Non-Camden PCP Identify Risk Factors: Behavioral health issues Language barriers Homelessness Poor Self-Rating of Health Mobility limitations Lack of social support www.camdenhealth.org

Stratify by Risk Teams conduct bedside outreach to assigned patients (pre-enrollment) Consent form process Administration of risk stratification tool Mean total risk score for each team is monitored To prevent over assignment of higher risk To prevent over-assignment of higher risk patients to one team over the other

Assessment of Risk Factors Static risk factors (assessed only at pre-enrollment) Language barrier Number of chronic conditions Increased # of risk points for increased # of conditions Behavioral health co-morbidities weighted separately Stroke history risk weighted separately Dynamic Risk Factors (can change throughout course of intervention) Lack of PCP (or lack of recent PCP visit) Housing barrier Poor self-rating of health Mobility barrier Social support

Rule-out Criteria at Pre-enrollment Flexible set of risk-factors at pre- enrollment that rule-out official enrollment at hospital discharge Currently receiving other care management services Pass away in hospital Decline to participate in services Discharge to long-term rehabilitation

Enrollment Patients will be enrolled upon discharge from hospital or sub-acute rehabilitation ti Goal of first home visit within 24-48 hours Care plan is developed between pre-enrollment & discharge Validation of risk tool through tracking of hours spent with each patient by each care team staff member Higher risk patients should require more intensive intervention/more hours Constant monitoring of re-admissions to hospital following discharge

Risk Follow-up Risk tool is re-administered at 30 days, 60 days, & 6 months post-discharge Monitoring short-term & long-term reductions in risk following intervention Reducing risk through targeting of dynamic risk factors from pre-enrollment Dramatic changes in self-rating of health, mobility, & social support scored to reduce risk score accordingly Re-admissions are factored into follow-up risk score First re-admission = +1 point All re-admissions after first = + 0.5 points

Understand the problem Develop interventions to target the problem Identify and engage patients needing intervention Evaluate the impact of the solutions

Thank you for your time Questions/comments please contact me at ken@camdenhealth.org www.camdenhealth.org