Leveraging Healthcare Analytics to Reduce Heart Failure Readmission Rates
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Transcript of Leveraging Healthcare Analytics to Reduce Heart Failure Readmission Rates

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Leveraging Healthcare Analytics to Reduce Heart Failure Readmission RatesBy Kathleen Merkley

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Heart Failure Readmissions: One of the Most Common Sources of Readmissions
Heart failure, including what was formerly referred to as congestive heart failure,* is an extremely serious problem in the United States for many reasons.
First, there are a high number of patients who are suffering and dying from this disease.
Second, the financial burden to treat heart disease patients is becoming an alarming public health issue.
• Heart failure accounts for $38 billion of annual healthcare spending.
• Heart failure accounts for 43% of Medicare spending on 14% of Medicare beneficiaries.

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Heart Failure Readmissions: One of the Most Common Sources of Readmissions
Many of these patients will be readmitted to the hospital soon after being seen for their heart condition adding cost to the patient’s treatment.
More than 25 percent of patients hospitalized for heart failure will be readmitted to the hospital within 30 days of discharge.
The top reason for readmission with the Medicare fee-for-service patient population is for patients suffering from heart failure. (2012 research)

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Heart Failure Readmissions: One of the Most Common Sources of Readmissions
Excessive readmissions tend to indicate suboptimal care, so government and commercial payers are focusing on 30-day readmission rates as a new quality measure for hospitals.
Some proposed methods of reducing heart related readmissions include:
• Patient education at discharge
• Appropriate medications prescribed
• Medication reconciliation
• Timely access to care after discharge
• Hand-off communications between primary care providers and acute care facilities
• Rapid distribution of hospital documentation to primary care providers
• Home health interventions
• Follow-up phone calls

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Heart Failure Readmissions: One of the Most Common Sources of ReadmissionsHeart failure readmission dashboard tracks patient care

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
4 Ways to Leverage Healthcare Analytics to Reduce Heart Failure Readmission Rates
Now that hospitals have to comply with this new quality measure or face financial penalties, how should they address heart failure readmission rates? There is a solution: advanced analytics
Sophisticated analytics are able to comb through terabytes of clinical data to reveal opportunities to improve quality and efficiency.
Here are four ways hospitals can use their data to improve heart failure readmission goals:

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
4 Ways to Leverage Healthcare Analytics to Reduce Heart Failure Readmission Rates
You can’t improve what you don’t measure. It is very important to establish readmission baselines, track performance metrics, and distribute information to everyone who is trying to reduce readmissions. This is the first step towards quality improvement.
FOUR WAYS TO
REDUCE READMISSIONS
1 Understand your current readmission rates for your heart patients

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4 Ways to Leverage Healthcare Analytics to Reduce Heart Failure Readmission Rates

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
4 Ways to Leverage Healthcare Analytics to Reduce Heart Failure Readmission Rates
Realize, however, that if you’re looking old data, it’s difficult to engage clinicians in clinical improvement initiatives. Adopting an enterprise data warehouse (EDW) could help ensure the data is current.
FOUR WAYS TO
REDUCE READMISSIONS
2Establish 30- and 90-day
readmission baseline measures for heart failure patients.

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
4 Ways to Leverage Healthcare Analytics to Reduce Heart Failure Readmission Rates
For heart patient readmissions, there are three types of balance measures:
1. Patient satisfaction rates2. Emergency department
(ED) visits3. Observation stays
FOUR WAYS TO
REDUCE READMISSIONS
3Be aware of balance measures
(changes designed to improve one part of the system without causing new problems in another part of the system)

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4 Ways to Leverage Healthcare Analytics to Reduce Heart Failure Readmission Rates
Integrate clinical, financial, and patient satisfaction data using an EDW to identify all patients with a primary diagnosis of heart failure and then stratifies the populations as either high- or low-risk for readmission and plan intervention accordingly.
FOUR WAYS TO
REDUCE READMISSIONS
4 Use an enterprise healthcare data warehouse

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Heart Failure Readmissions: One of the Most Common Sources of Readmissions
As shown in the Health Catalyst Heart Failure Readmission Dashboard, you can lower readmission rates by using bundles intervention tracking.

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Positive Results using the EDW and the Heart Failure Advanced Application
21 percent reduction (seasonally adjusted) in 30-day heart-failure readmissions
2X increase in the number of phone calls made to patients within 48 hours of discharge
63 percent increase in physician medication reconciliation post discharge
One Health Catalyst client saw these results using the late-bindingTM Data Warehouse.
14 percent reduction (seasonally adjusted) in 90-day heart-failure readmissions

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Gratitude for Readmissions Improvements
From a professional perspective, it’s important to understand the challenges health systems face as they work to reduce heart failure readmissions. But from the personal perspective watching a loved one suffer from a potentially preventable readmission, I’m grateful for the progress we’re making in healthcare. In specific, I am thankful for government scrutiny, progressive clinicians, and healthcare IT solutions that are beginning to contribute to the reduction in heart failure readmissions.
– Kathleen MerkleyHealth Catalyst
‘‘

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
More about this topic
How to Use Analytics to Reduce 30-day Heart Failure Readmissions An academic medical center case study
Product Demo – Heart Failure ReadmissionsWatch a 7-minute demo of our heart failure readmission application
References
http://cms.hhs.gov/Research-Statistics-Data-and-Systems/Research/HealthCareFinancingReview/Downloads/08Springpg1.pdf
http://www.ncbi.nlm.nih.gov/pubmed/22653415
*The American College of Cardiology and the American Heart Association prefer the use of “heart failure” over “congestive heart failure.” http://content.onlinejacc.org/article.aspx?articleID=1695825

© 2013 Health Catalystwww.healthcatalyst.com
Other Clinical Quality Improvement ResourcesClick to read additional information at www.healthcatalyst.com
Kathleen Merkley joined Health Catalyst in March 2013, as an Engagement Executive. Prior to coming to HC, she worked for Intermountain Healthcare as the corporate clinical IT implementation manager. Kathleen is a registered nurse/nurse practitioner and just received her doctorate in nursing practice from the University of Utah in May 2013.
More by this author:Overcoming Clinical Data Problems in Quality Improvement Projects
Defining Patient Populations Using Analytical Tools: Cohort Builder and Risk Stratification
A Key to Measurable Healthcare Quality Improvement: Use AIM Statements