reducing 30-day readmissions with smooth transitions of care · 2013: observed-to-expected (o/e),...

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Event #669 795 785

“Reducing 30-Day Readmissions with Smooth Transitions of Care”

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Event #669 795 785

Housekeeping

• Moderator – Anthony Guerra, editor-in-chief, healthsystemCIO.com

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Event #669 795 785

Agenda — Approximately 45 Minutes

• 20-30 minutes: Dwayne McNeil, Assistant VP, IS, Carolinas HealthCare System

• 5 minutes: A Word From Our Sponsor: Deborah Bulger, VP, Product Marketing, McKesson

• 10-15 minutes: Q&A w/Dwayne McNeil


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Event #669 795 785

Reducing 30-Day Readmissions

PCPCS

5

Carolinas HealthCare System Introduction

Readmissions Background

Applying Analytics to Readmissions

Results

Next Steps – Current Focus

Q&A

Today’s Topics:


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Carolinas HealthCare System Introduction

PCPCS

6

39 hospitals and 900+ care locations in North Carolina, South Carolina and

Georgia

More than 7,400 licensed beds

11 million patient encounters per year

2,500+ system-employed physicians, 15,000+ nurses and 60,000 teammates

$1.5 billion in community benefit in 2013

More than $8 billion in annual revenue

More than 50 disease-specific certifications from The Joint Commission –

one of the highest totals in the country among comparable systems

The region’s only Level I trauma center

One of five academic medical centers in North Carolina

One of the largest HIT and EMR systems in the country


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CHS Information Services

PCPCS

7

Overall Information Services responsibility for Acute and Ambulatory Care, Continuing Care, Corporate Operations and our physician practice Medical Group

2 Main Data Center Locations: 801 S. McDowell Data Center and CMC-NorthEast campus, plus disaster recovery location on the CMC Campus (LCH Data Center)

Information Services By-the-Numbers (yearly totals):

• 490,000 customer support calls through the 24/7 Support Center

• 60,000 IS customer requests (OSRs), and 9,800 non-IS related requests

• 2,500 training sessions for staff and physicians (35,000+ attendees)

• 3,700 system, file and print servers, with 3,500+ terabytes of storage

• 42,000 email accounts and 67,000+ devices (PC’s, Laptops, Tablets, Printers and Mobile Phones)

• 12.7 million sq. ft. of wireless network coverage across our care locations

• 800+ applications supported

• 700+ IS teammates


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Readmission Imperative

PCPCS

8

The Right Thing to Do. Better Care for Our Patients.

Medicare Payment Advisory Commission. 2007. Report to the

Congress: Promoting Greater Efficiency in Medicare.

18 percent of Medicare

patients discharged from the

hospital have a readmission

within 30 days of discharge,

accounting for $15 billion in

spending.

• Pay for Performance programs

• Value Based Purchasing

• Insurance contracting

• Mitigate/eliminate CMS financial

readmission penalties

• Benchmarked & public quality

metrics

• One of most significant drivers of

higher cost (payer perspective)


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Readmission Imperative

9

CMS Hospital Readmission Reduction Program

Objectives: Improve Quality and Reduce Cost

Initial conditions (2013):

• Acute Myocardial Infarction

• Heart Failure

• Pneumonia

2015 expansion:

• COPD

• Elective Hip and Knee


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Readmissions as a CHS Goal

10

2009: Readmission baseline established

2010: Number of 30-day all-cause readmissions for AMI, HF and PN; Medicare only

2011: Rate of 30 day all cause readmissions following an index admission for AMI, HF and

PN; patients age ≥ 18 years; all payers

2012: Rate of 30-day all cause readmissions following an index admission for AMI, HF and

PN; patients age ≥ 18 years; all payers (definition modified to match CMS)

2013: Observed-to-expected (O/E), defined as the number of unplanned readmissions within

30 days of index admission, divided by the expected number of readmissions; patients age ≥

18 years; all payers

2014: Same as 2013 with minor definition change to match CMS


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Reducing 30-Day Readmissions

11

Recent Areas for Readmission Action:

• Awareness & Education

• Identification of high risk patients (analytics)

• Standardize interventions for high risk patients

• Communication of high risk patients to providers

• Evaluation of each readmission cause


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Patient-Centered, Point of Care

Clinical Decision Support

Learning Collaborative

AnalyticsClinical Practice

PCPCS

12


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Analytically-driven, Personalized Care Value

13

Point-of-Care“Touch points”

UniqueIndividuals

Cost of Healthcare

Value

Population Health

Patient Experience

of Care: Quality and

Satisfaction

Applications

Rules

Interventions

Analytics

PatientProfile

Transactions

Social MediaEHR

Vendors

Pharmacy

Consumer Data

Claims

Lab

Information Infrastructure

Clinical Expertise

Learning Collaborative


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Project Vision

14

“We will analyze health and consumer data for

insights into individuals’ clinical risks and through the CHS Learning Collaborative…

…enable the best intervention and treatment decisions at the point-of-care…

…that optimize quality and cost-effective health services.”


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Patient Risk Assessment

15

Case Manager VariationCare manager ability to find and assess

risk factors varies

Done at AdmissionCare managers only have capacity to

assess patient risk at admission

Automation Decreases

VariationPatient risk is automatically calculated for

the care managers

Updated HourlyA patient’s condition and likelihood for

readmission can change throughout a

hospital stay; our tool captures these

changes hourly as clinical data change

Historical Future State

Limited CapabilityCare managers assign risk based on a

a few simple criteria that group patients

into two buckets: low risk and high risk

Risk Assessed from Predictive

Model Patient risk for readmission is predicted,

automatically, from over 40 key variables

pulled from Cerner

Done After EMR and

Patient ReviewCare managers need to review the

patient’s chart and examine the patient

prior to assessing risk

Done Prior to Seeing PatientAllows care managers to work more

effectively by prioritizing their workflow and

more efficiently through automating the

risk assessment.


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Care Interventions

16

Difficult to HardwireCare managers required to

recognize a certain patient type

and remember what interventions

are to be assigned to the patient

Difficult to Measure

InterventionsCurrent care management tools

do not allow for evaluation of

intervention efficacy; limits our

ability to leverage our System

Recommendations

Assigned AutomaticallyPatients automatically assigned

interventions based on their

personal characteristics

Measure Efficacy of

InterventionsCapture of interventions and

data around outcomes will allow

us to measure the efficacy of

interventions and determine

patients who optimally benefit

Historical Future State


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Analytics: Risk Model Accuracy

17

• CHS risk model accuracy

of 79%

• Our model is better than

most other predictive

models in published

literature

• Based on 2 years of

readmission modeling by

our Dickson Advanced

Analytics (DA2) teamFalse Positive Rate

Tru

e Po

siti

ve R

ate

0%0%

100%

100%


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Analytics: Segmentation Model

18

• Purpose of Segmentation Model

• Example Segments

Population Segments Low Risk Medium Risk High RiskVery High

RiskTotal

Insured Healthy Adult 14.37% 10.91% 6.04% 4.18% 35.50%

Medicaid Pediatric 4.13% 2.54% 1.18% 0.36% 8.21%

Medicare Independent 5.13% 6.56% 6.10% 5.12% 22.91%

Medicare w/ Frequent Visits

and 9X90.78% 2.65% 5.61% 5.19% 14.24%

Middle Age w/ Frequent

Visits and Comorbidity0.55% 2.31% 6.03% 10.25% 19.14%

Total 25.00% 25.00% 25.00% 25.00% 100.00%


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Analytics: Risk Model Design

19

• Risk model predicts a patient’s individual risk for a 30-day,

unplanned readmission

• Our Canopy EMR and Enterprise Data Warehouse are

primary data sources

– Pulling over 40 predictive fields hourly to risk score

patients

– Using over 15 operational fields hourly to support

decision making


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Validation of our Readmission Risk Model

0% 10% 20%

Low

Medium

High

Very High

Pre

dic

ted R

isk

Actual Readmission Rate


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21

Readmission Analytics Current Status

Solution fully-deployed during Q3 2013 at our Metro hospitals

65,000+ Patients have had their risk for readmission automatically

calculated on an hourly basis

97,000+ Interventions have been assigned by our Case Managers

to patients based on their risk for readmission and clinical segment

208 Case Managers actively use the tool


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22

Readmission Analytics Key Points

Our analytics model is accurately identifying patients

with low/high risk of readmission

Case management teams are able to focus their

resources on the right patients and we are improving

our interventions to “best fit” patients

Impacting readmission requires interventions,

collaboration and a team approach


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Our Readmission Trends

23

0.60

0.70

0.80

0.90

1.00

2010 2011 2012 2013 Baseline

Readm

issio

ns O

/E

SA Average

Carolinas HealthCare System

SA Top Quartile

SA Top Decile

Carolinas HealthCare System Hospital-Wide ReadmissionsSystem and SA Benchmark Performance


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Highlight: Readmissions and Heart Failure

24

CHS developed the Heart Successprogram in 2013

Key components: • Risk assessment• Transition clinic• Co-management of the

patient with PCP• Telehealth interaction• Remote patient monitoring

when needed

Results:

• Reduction in all-cause CHFreadmissions by 3.5% to 13.89


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Readmissions and Heart Failure

25


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26

Other Resources We Use to Tackle

Readmissions Customer Relationship Management: eVariant

• Discharge call management

• Transitional Care Management team

• Interfaced with our analytics warehouse

Interactive Patient Education: GetWell

• Patient education readmission intervention options

• Interfaced with our EMR for tracking & analytics

Fully leverage our clinical call center: TeleHealth Solutions

• 24x7 access

• Integrated with acute, specialty, primary care and

continuing care (post acute)

Online patient portal (web & mobile): MyCarolinas


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Next Steps

27

Continue to refine our interventions & personalized

solutions, and spread across our enterprise

Enhance our view of patients through care transitions

transitions across all care locations

Improve our population health care management

solutions – broaden the team of support using

clinical decision support and automated workflow

Leverage virtual visit and online patient engagement initiatives

Innovate with new strategies and technologies


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Deborah Bulger, VP, Product Marketing, McKesson

Connected Care & Analytics

29

Readmissions is a $25B issuePart of a larger $700B cost reduction opportunity

Source: NEHI health policy institute


30

Readmission Management Continuum

Post acute

Acute

Risk

identification

1


31


Post acute

Acute

Risk

identification

Care

transition

1

2


32


Post acute

Acute

Risk

identification

Care

transition

Post

discharge

1

2

3


33


Post acute

Acute

Risk

identification

Care

transition

Post

discharge

Measurement

1

2

3

4

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Event #669 795 785

Q&A

Click on the Q&A panel located in the lower right corner of your screen, type in your questions in the text field and hit send. Please keep the

send to default as “All Panelists.”

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Event #669 795 785

Thank You!

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• Thanks to our sponsor: McKesson!

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reducing 30-day readmissions with smooth transitions of care · 2013: observed-to-expected (o/e),...

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