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DECREASING MEDICARE READMISSIONS
The Capstone Group
Marinka Bulic - Jyothi Golkonda - Diane Hunt - Aziz Lalji - Emad Osman
INTRODUCTION
2
• Readmission rate at University Hospital is
above national average
– Hospital Readmissions Reduction Program will
result in reduced payments if this is not improved
• Program aims to reduce hospital readmissions in patients
with certain diagnoses by reducing payments to hospitals
with higher-than-average readmission rates
• Diagnoses included in this program include
– Acute Myocardial Infarction (AMI)
– Congestive Heart Failure (CHF)
– Pneumonia
BACK GROUND
3
• University Hospital is part of a multi-site Accountable
Care Organization (ACO)
• Outpatient clinics in the ACO use Epic EHR
• Hospitals in the ACO use Centricity EHR
• The 3 pharmacies that are part of the ACO receive
eRx and respond back with prescription fill data.
• 3 labs are part of the ACO
– Labs receive electronic orders and report back electronically
to the EHRs
– Terminology is not consistent within the three labs. All three
labs use different terms and different test combinations.
IMPACT
4
• Financial
– Cost to the hospital if readmission rates not
improved over the next 3 years
• 2013: $130,000
• 2014: $265,000
• 2015: $409,000
– Total projected losses of $803,000
• Clinical
– Quality measure metrics below national standards
as well, impacting reputation of organization overall
GOAL
5
• To reduce admissions in patients with AMI,
CHF, and pneumonia from 21% to 10% over
the next two years
CLINICAL WORKFLOWS AND OPERATIONS
6
• Discharge Medications Process
– Opportunities for improvement at all transitions of
care
• Standardize admission medication reconciliation to
improve discharge medication reconciliation process
• Utilize e-prescribing at discharge
• Enhance pharmacy to primary care provider
communication in cases where prescriptions are not filled
appropriately
CLINICAL WORKFLOWS AND OPERATIONS
7
• Transition Planning
– BOOST model to assess risk for readmission at
time of presentation
• Utilize Clinical Decision Support tools within the EMR
system to stratify patients based on risk
• Specialized transitional care program from time of
admission based on individual risk factors
– Development of Transitional Care Team to
individualize care plans from time of presentation
• Facilitate follow-up post discharge
• Help with financial and social barriers at home
CARE COORDINATION
8
• Primary Care Providers
– Incentivize Primary Care Providers to see
discharged patients within 72 hours of discharge
• Helps to ensure follow-up during most critical point of
transition from inpatient to outpatient care
– Encourage effective information exchange between
acute and ambulatory care settings with integrated
EMR system
CARE COORDINATION
9
• Home Healthcare Providers
– Develop partnership with entities that can provide
care to patients after discharge from the hospital
• Home Healthcare intervention can start within 24-48 hours
post discharge
– Care Transition Coordinator (CTC) to help
coordinate patient care during transition from
hospital to home healthcare
CONTINUOUS QUALITY IMPROVEMENT (CQI)
10
• Quality improvement program to evaluate
current processes and improve systems and
processes
– Outcome to reduce readmissions
– Monitor care coordination data
– Determine the effectiveness of the proposed
solutions
COST VS. BENEFITS ANALYSIS
11
• Benefits
Before Implementation After Implementation
Overall readmission rate 21.33%
Overall readmission rate 11.73%
Readmission rate with one or combination of three diagnoses 65%
Readmission rate with one or combination of three diagnoses 36%
Medicare penalties $813,073
Medicare penalties $250,176
COST VS. BENEFITS ANALYSIS
12
• Costs of implementing proposed solutions
– $470,000
• Savings from implementing proposed solutions
– $562,897
• Return on Investment (ROI)
– 20%
CMS MEASURES
13
• Goal of the measures is to reduce the
readmissions rates of patients 30 days post
discharge
• Financial incentive
• Measures are implemented at various steps
during a patient’s visit including:
– At admission
– During care
– Discharge
– Post Discharge
CHRONIC HEART FAILURE
14
• 1,900 patients hospitalized at University
Hospital annually with a 5% mortality rate.
• Measures include:
– Left ventricular function assessment
– Monitoring of diet/fluid intake
– Medication reconciliation
ACUTE MYOCARDIAL INFARCTION
15
• 2,000 of patients admitted are due to AMI
• ⅔ of patients do not make a complete
recovery
• Great potential measure to increase quality of
care
• Measures include:
– Aspirin at arrival
– Beta blocker prescription
– Adult smoking cessation counseling
PNEUMONIA
16
• 4th leading cause of deaths in patients 65 + in
the area
• Measures
– Vaccine status for influenza and pneumonia
– Antibiotic timing with 6 hrs of arrival
– Smoking cessation counseling
PATIENT SURVEY
17
• HCAHPS - Hospital Consumer Assessment of
Healthcare Providers and Systems
• National standard of collection patient
satisfaction
• Public reporting creates:
– Competition amongst hospitals to create better care
– Transparency which allows patients to chose the
better hospital for their care
PATIENT EDUCATION
18
• Education includes:
– How to take their medication
– Follow up appointments
• 30% drop in ED readmissions when patient receive
education
• Project RED - Re-Engineered Hospital Discharge Program
Pilot Program
– Follow-up appointments
– Confirmation of medication routines
– Understanding diagnosis
– Results:
• from the 370 participants, there was a 30% fewer readmissions
• 94% of patients had a follow-up appointment with their primary care
physician
INTEGRATION OF SYSTEMS
19
• Use CCDAs to exchange patient data between University
Hospital (using Centricity system) and the primary care
physicians or home healthcare providers (using Epic
systems)
• Work with the labs to formulate the standard terminology
(for example CPT codes for procedures, LOINC codes for
labs with a standard unit of measure) for data exchange
between the clinics/hospitals and the labs
• Add a data warehouse to collect data from labs,
pharmacies, hospitals and outpatient clinics
DATA FLOW DIAGRAM
20
USE CASE DIAGRAM
21
PROJECT PLAN
Medicare Readmission Reduction: Timeline
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MRR
Univ.
Health
Projects
Go Live
MU Stage
2
Planning
Design PLAN BUILD
2014
TODAY
PREP, TEST & TRAIN
ICD-10
Go-Live
24
PROJECT GOVERNANCE
MRR Project GovernanceUniversity Health COO
MRR Oversight Commitee
MRR Operational
Leadership
Team
MRR Project Mgt Team
Project Team/s
CMOs
CMIO
Clinical Adoption
Mgr
- University Health CIO,
Chairman
- Medical Director
- CNO
- ITS Clinical Applications
Program Director
- ITS Medical Director
- Director of Pharmacy
Services
Organization
Communication
Lead
Benefits & Metrics
Coordinator
HR
Support
Strategic Governance
Project Execution
Tactical / Operations Governance
Responsibility Key
ITS Liaison /
PCIS Director
Assoc
Administrators
PCS
Clinical Governance
ITS Governance
Physician Lead
ITS Program
Director
ITS ClinApps
Project Director
MRR Clinical
Advisory Team
ASSUMPTIONS
• Accurate and Timely Documentation – For decision support logic to be effective, To be effective, the data in the
patient record will need to be wholly, accurate and timely.
• Decision Support – For the project to be effective the care instructions developed as part of the
MRR initiative will need to be reviewed and executed accordingly.
• Integration – Project assumes significant investment in integration and interoperability
efforts between both systems and standardization of data standards
CONSTRAINTS / LIMITATIONS
26
• Data Standards – In the current state the University Health existing architecture hosts (2)
separate EMRs. This is identified as a limitation to this project with regards to
the lack of standardization of data across both EMRs.
Recommendation • To counter this constraint we propose significant work be invested in identifying organizational
data standards with respect to patient data being documented by provider and exchanged from
system to system
• Data Sources – With the existing architecture and use of (2) separate EMRs, clinician’s
application workflow, data mining/reporting will be constrained.
Recommendation
• Significant investment and time into the development of future state
workflows and development of clear policies and procedures for use of
both EMRs.
KEY GROUPS
27
ROLES / RESPONSIBILITIES
28
RISKS
29
SYSTEM REQUIREMENTS
30
• General
– Integrates with existing Centricity and EPIC EMR architecture
• Integration
– Full integration ability with all ancillary systems
• Decision Support
– Alert Functionality based on core measures identified
• Printing
– Patient Discharge Summary
• Workflow
– Complies with ICD-10 documentation requirements
– Complies with MU requirements
• Reports
– Ability to assess increase/decrease of readmission within core measure
population
TESTING
31
• The objectives of testing for the University Hospital Readmission Reduction
project are to: – Document that the system reliably and repeatedly performs as designed.
– Ensure regulatory documentation standards are met.
– Verify business and system requirements are satisfied.
– Capture discrepancies (problems) to eliminate defects.
– Establish testing documentation that can be reused for system maintenance.
– Provide information to assess go-live readiness.
– Practice a dress rehearsal build and testing
• Unit Testing – focus on application components (i.e. a unit of functionality) as they are built.
• Application / Functional Testing – Confirms that the component functions of the product/application perform to meet the business and
technical design requirements.
• Regression / Performance Testing – Performance Testing validates the ability of the application to function under maximum volumes and
peak transaction loads.
• Integration Testing – Validates the ability of the application of the MRR system, to communicate and exchange data between
BOTH EMR’s in the normal or proposed course of a clinical encounter.
TRAINING
32
• Training Plan –
– The training strategy will have two core focuses:
• Curriculum Development
– Developed by SME’s, Analysts
– Based on Stakeholder Analysis
• Education
– Classroom
– Online
– Self-Study
– Job Aids
– Blended solution of classroom and online
DEPLOYMENT
33
• Recommendation
– Deployment of the MRR project will be a big bang approach of
implementing ALL functionality at once, commonly known as a
big bang approach.
• Fully Staffed Command Center
• At the elbow support for end-users
• Command Center team responsible for triage of service requests,
troubleshooting, testing and education needed.
The Capstone Group
Marinka Bulic
Jyothi Golkonda
Diane Hunt
Aziz Lalji
Emad Osman
1 Research park, Chicago, IL 11111
Phone: 666-555-4444
Email: capstone@cg.com
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