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RARE Conversations October 30, 2012 Hosted by RARE Operations Partners: Institute for Clinical Systems Improvement, Minnesota Hospital Association, Stratis.

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Presentation on theme: "RARE Conversations October 30, 2012 Hosted by RARE Operations Partners: Institute for Clinical Systems Improvement, Minnesota Hospital Association, Stratis."— Presentation transcript:

1 RARE Conversations October 30, 2012 Hosted by RARE Operations Partners: Institute for Clinical Systems Improvement, Minnesota Hospital Association, Stratis Health

2 Our host today will be… Kathy Cummings Kathy Cummings is an ICSI Project Manager for the Reducing Avoidable Readmissions Effectively (RARE) Campaign, a collaborative effort led by ICSI, the Minnesota Hospital Association and Stratis Health. These organizations have joined together to engage more than 80 hospitals and other partners across the continuum of care to prevent avoidable hospital readmissions in Minnesota. Kathy holds a bachelors degree in nursing from the University of Iowa and a masters degree in human resource development from the University of St. Thomas.

3 Why RARE Conversations? Networking opportunities Share Learn Conversation Engage

4 Octobers Conversation… Risk Stratification Sharing their work: Hennepin County Medical Center & Park Nicollet

5 More about the presenters… Sandy is a Director of Case Management at Hennepin County Hospital. She is an energetic, responsive, trusted self-starter with extensive experience in leadership. She has demonstrated success in process improvements and positive patient outcomes. Sandy Hilliker

6 More about the presenters… Scott Shimotsu is a healthcare analyst in the Performance Measurement and Improvement Department at Hennepin County Medical Center. Last year, he graduated from the University Minnesota PhD program in Epidemiology and Community Health. With over 12 years of healthcare experience, Scott brings expertise in advanced healthcare analytics, obesity prevention and biostatistics. His research areas include obesity prevention, diet and alcohol use, and social determinants of chronic disease. Scott Shimotsu

7 Towards the Development of a Readmissions Risk Tool Case Management/Performance Measurement and Improvement ICSI RARE Conversations October 30,2012 Sandy Hilliker RN,DNP and Scott Shimotsu, PhD MPH CPHQ

8 What did we do ? Created a adult high risk assessment tool High Risk Criteria Score –Two or more Admissions in the last 30 days –Two or more ED/APS visits in the last 30 days –Presence of: Drug Use Depression Renal Failure Heart Failure Asthma –Race

9 Low Risk Patients Low Risk Criteria –No Admission, Readmission, or ED/APS visit in the last 30 days –High Confidence in patient and family to give self-care, based on Teach Back Interventions –Phone number to call if needed –Follow-up appointment made –Medication Reconciliation Prior to DC –Initiate any additional services as needed

10 Moderate Risk Patients Moderate Risk Criteria –One Admission last 30 days –One ED/APS Visit in the last 30 days –Regarding self-care, moderate confidence that patient or family, based on Teach Back, can carry out the care needed. –Presenting Illness (Cardiovascular, Pulmonary, Renal, or Infectious) Interventions –Follow-up phone call post discharge within 48 hours –Medication Reconciliation Prior to DC –Follow-up Clinic Appointment within 5 days –Home care visit within 72 hours –Warm Hand off to clinic –Identify who patient calls with questions /concerns –Social Service assess within 24 hours of admission and implement discharge plan Identify community resources Identify transportation needs Identify tele-monitoring as needed (CHF, COPD, Diabetes) FUTURE

11 High Risk Patients Interventions –Follow-up phone call post discharge within 24 hours –Medication Reconciliation Prior to Discharge Follow-up Clinic Appointment within 72 hours –Home care visit within 48 hours ( Minnesota Visiting Nurses Association )

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13 Risk Tool Preliminary Evaluation 1.Retrospective Readmissions Factor Study –Social/Personal Risk Factors Among A Diverse Racial/Ethnic Minority and Immigrant Patient Population: A Multivariate Analysis –May 1, 2011-April 30, 2012 2.Preliminary Metrics Evaluation Study –ROC Curve Analysis –Timeframe: July 2012-September 2012

14 Results N=2508 Cases with a Risk Criteria Score Low Risk 60% Moderate Risk 13% High Risk 27% Overall Readmission Rate 9% C stat (95% CI)0.60 (0.56,0.64)

15 Risk Tool Preliminary Evaluation: Results Risk Category vs. Readmit (yes) N% READMIT LOW1057% MODERATE247% HIGH9314%

16 Next Steps Assess Measures to capture interventions and processes Year-to-Date Risk Tool Evaluation on Readmissions and Process Measures (January 2013) Reconsider New Risk Factors: Socio-demographic, Environmental, Social Support, Substance abuse

17 More about the presenters… Eva Gallagher is the Senior Director of Quality, Innovation and Population Health at Park Nicollet Health Services in Minneapolis, MN. Eva completed the adult nurse practitioner program at the College of St. Catherine and earned a PhD in nursing from the University of Minnesota. Eva Gallagher

18 More about the presenters… Gregg has worked at Park Nicollet Health Services for the past nine years leading various analytic and reporting departments (Demand Planning & Analysis, Clinical Reporting & Analytics, and Business Intelligence). He is currently working in a Lead Analytic Advisor role in support of enterprise level initiatives. His primary focus in this role is to support of Park Nicollets Population Health and Pioneer ACO activities. Gregg Teeter

19 For everything you love. Eva Gallagher Gregg Teeter Identifying Patients At Risk For Readmission At Methodist Hospital

20 For everything you love. Aligning Resources Developing A Care Model Identifying High Risk Patients Discussion

21 For everything you love. Reengineered Support for Patients Care Integration Role Definition – RN Care Coordinators and Social Work

22 For everything you love. Reengineered Support for Patients Care Integration Focus Before - LOSAfter - Transitions

23 For everything you love. Reengineered Support for Patients RN Care Coordinators paired with Hospitalists Pilot found improved teamwork, better able to prioritize work, potential discharge errors found

24 For everything you love. Reengineered Support for Patients RN Care Coordinators paired with Hospitalists

25 For everything you love. Inpatient –Consults as needed: pharmacy, nutrition, CDE, PT, OT, spiritual care Post-Discharge –Post discharge phone calls –Discharge appointments – 3-5 days for high risk –Home visits to all high risk patients –Transition call to NH, TCU –Care consultant assigned as needed Care Model Enhancements

26 For everything you love. Vision: What if we could predict which patients have a high probability of being readmitted? If we could, what could we do, while that patient is under our care, to decrease that risk? Challenge: Which combination of variables are key drivers for risk of readmission? Predicting Which Patients Are At High Risk Of Readmission ABCD Probability of Readmission

27 For everything you love. Model 1.0 –Developed in the Spring, 2012 –Design based on variables identified from literature review –Subjective weighting and scoring of the variables added up to a total score –Aggregated and displayed results in Epic with a banner on the inpatient record –Most important: the tool became part of the process Model 2.0 –Developed concurrently –Based on data in our enterprise data warehouse –Identified the drivers of readmissions from an analysis of historical data to develop a regression equation that has actual predictive power –Went live in October, 2012 Readmission Model Details

28 For everything you love. Patient demographic variables Account type/subtype Admit source Admit status Admit service Discharge disposition Length of stay Infection control status High risk diagnoses within past year High risk diagnoses during index admission HCC score Admits in past 3yrs, 2yrs, 1yr, 6mo, 3mo, 1mo # days since last admit EC visits in past 3yrs, 2yrs, 1yr, 6mo, 3mo, 1mo # days since last EC visit UC visits in past 3yrs, 2yrs, 1yr, 6mo, 3mo, 1mo # days since last UC visit PC visits in past 3yrs, 2yrs, 1yr, 6mo, 3mo, 1mo # days since last PC visit CAM scores (# of positive scores, most recent result during admission, most recent result prior to index admission) PHQ9 score (max score during admission, most recent score prior to admission) Systolic BP (highest, lowest, most recent during admission) Pulse (highest, lowest, most recent during admission) BMI Bun/Creatinine lab values (count, min, max, std dev, most recent) Glucose values (count, min, max, std dev, most recent) Hemoglobin A1c values (count, min, max, std dev, most recent) Serum albumin values (count, min, max, std dev, most recent) Braden score Falls risk score Medications Homecare in past 6-12 months Assistive devices during index admission Level of assist during index admission Model 2.0 Readmission Driver Variables Evaluated

29 For everything you love. Model Differences Previous Model VariablesCurrent Model Variables Age Living arrangementsRace Type of residenceMarital status Readmit or ER visit w/in past 2 weeksGender Multiple medical problemsHCC score Falls risk scoreLength of current stay CAM score# of admits in past 6 months Braden score# of ED visits in past 6 months Patient type (medical or surgical) Analysis suggested that the prior models predictive power was low, while Model 2.0s predictive power was significantly better (as good as anything that has been published) Model Limitations: Variables in the prior model were dependent nurse input Model 2.0 dependent on patient having prior utilization data

30 For everything you love. Operations –Visibility of the banner post discharge –Automated communication back to PC regarding acute events (EC, inpatient, obs) Measures & Models –Analyze and track the impact of the change –Expand model to Observation and EC patients –Real time census updates and automating the transfer of the score into Epic –Evaluate condition specific predictive models Next Steps

31 Kathy Cummings is an ICSI Project Manager for the Reducing Avoidable Readmissions Effectively (RARE) Campaign, a collaborative effort led by ICSI, the Minnesota Hospital Association and Stratis Health. These organizations have joined together to engage more than 80 hospitals and other partners across the continuum of care to prevent avoidable hospital readmissions in Minnesota. Kathy holds a bachelors degree in nursing from the University of Iowa and a masters degree in human resource development from the University of St. Thomas. Kathy Cummings Our host today…

32 Questions Question # 1 How are you identifying patients at high-risk for readmissions? Question # 2 How does it impact the care and services you provide for these patients? Now we will take questions from the field…

33 RARE Conversations Upcoming RARE Events: RARE Rapid Action Learning Day, Thursday November 8, 2012 Crown Plaza Conference Center, Plymouth, MN, 8:30am-3:30pm RARE Webinar, Analyzing Your Portal Data, Friday December 7, 2012, 12 noon -1p.m.

34 RARE Conversations To suggest future topics for this series, RARE Conversations networking, contact Kathy Cummings, kcummings@icsi.org kcummings@icsi.org

35 Thank You for Your Participation! A recording of this RARE Conversation will be available within 3 days and posted on the RARE website, www.rarereadmissions.orgwww.rarereadmissions.org


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