rare conversations october 30, 2012 hosted by rare operations partners: institute for clinical...

RARE ConversationsOctober 30, 2012

Hosted by RARE Operations Partners:

Institute for Clinical Systems Improvement, Minnesota Hospital Association, Stratis Health

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 hospitalreadmissions in Minnesota.

Kathy holds a bachelor’s degree in nursing from the University of Iowa and a master’s degree in human resource development from the University of St. Thomas.

Why RARE Conversations?

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October’s Conversation…

Risk Stratification

Sharing their work:Hennepin County Medical Center &

Park Nicollet

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


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

Towards the Development of a Readmissions Risk Tool

Case Management/Performance Measurement and Improvement

ICSI RARE ConversationsOctober 30,2012

Sandy Hilliker RN,DNP and Scott Shimotsu, PhD MPH CPHQ

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

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

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

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 )

Risk Tool Preliminary Evaluation1. 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

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)

Risk Tool Preliminary Evaluation: Results

Risk Category vs. Readmit (yes)

N % READMIT

LOW 105 7%

MODERATE 24 7%

HIGH 93 14%

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


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


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 Nicollet’s Population Health and Pioneer ACO activities.

Gregg Teeter

For everything you love.

Eva Gallagher

Gregg Teeter

Identifying Patients At Risk For Readmission At Methodist Hospital

For everything you love.For everything you love.

• Aligning Resources• Developing A Care Model• Identifying High Risk Patients

Discussion


Reengineered Support for PatientsCare Integration Role Definition – RN Care Coordinators and Social Work


Reengineered Support for PatientsCare Integration Focus

Before - LOS After - Transitions


Reengineered Support for PatientsRN Care Coordinators paired with Hospitalists

Pilot found improved teamwork, better able to prioritize work, potential discharge errors found


Reengineered Support for PatientsRN Care Coordinators paired with Hospitalists


• 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


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

A B C DProbability of Readmission


• 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


• 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


Model Differences

Previous Model Variables Current Model Variables

Age Age

Living arrangements Race

Type of residence Marital status

Readmit or ER visit w/in past 2 weeks Gender

Multiple medical problems HCC score

Falls risk score Length 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 model’s predictive power was low, while Model 2.0’s 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


• 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

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 hospitalreadmissions in Minnesota.

Kathy holds a bachelor’s degree in nursing from the University of Iowa and a master’s degree in human resource development from the University of St. Thomas.

Kathy Cummings

Our host today…

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…

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.

RARE Conversations

To suggest future topics for this series, “RARE Conversations” networking, contact Kathy Cummings, [email protected]

mailto:[email protected]

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.org

http://www.rarereadmissions.org/

rare conversations october 30, 2012 hosted by rare operations partners: institute for clinical...

Documents

needed slide

stratis health slide

scott shimotsu slide

sandy hilliker slide

eva gallagher slide

results risk category

nurses association slide

diabetes future slide