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Leveraging Healthcare Analytics to Reduce Heart Failure Readmission RatesBy Kathleen Merkley


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.



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)

http://www.ncbi.nlm.nih.gov/pubmed/22653415



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


Heart Failure Readmissions: One of the Most Common Sources of ReadmissionsHeart failure readmission dashboard tracks patient care


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:

http://www.healthcatalyst.com/advanced-analytics-survive-healthcare-reform

http://www.healthcatalyst.com/advanced-analytics-survive-healthcare-reform



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



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.

http://www.healthcatalyst.com/late-binding-data-warehouse-platform



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)

http://www.healthcatalyst.com/patient-satisfaction-explorer/






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



As shown in the Health Catalyst Heart Failure Readmission Dashboard, you can lower readmission rates by using bundles intervention tracking.


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


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

‘‘

http://www.healthcatalyst.com/healthcare-analytics-solutions/


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


*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

http://www.healthcatalyst.com/success_stories/reduce-30-day-heart-failure-readmissions/

http://www.healthcatalyst.com/success_stories/reduce-30-day-heart-failure-readmissions/

http://www.healthcatalyst.com/demos/heart-failure-product-demo/






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

http://www.healthcatalyst.com/

http://www.healthcatalyst.com/overcome-clinical-data-problems

http://www.healthcatalyst.com/overcome-clinical-data-problems

http://www.healthcatalyst.com/Defining-Patient-Populations

http://www.healthcatalyst.com/Defining-Patient-Populations

http://www.healthcatalyst.com/healthcare-quality-improvement-ignite-aim-statements/