Readmission Explorer

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Product Overview

Readmission Explorer is intended for hospital administrators, clinical and operations directors, and members of quality improvement teams. The application provides a broad spectrum of readmission metrics for all-cause, unplanned readmissions for inpatient stays and emergency department visits. For cohort selection, users can start with one of seven predefined, CMS-based cohorts, a hospital-wide specialty cohort, use the Health Catalyst Care Process Hierarchy, or define custom cohorts by ICD9 diagnosis and/or procedure codes. Regardless of the starting point for analysis in Readmission Explorer, each cohort and/or method can be further refined by patient demographics, discharge status, provider, and other metrics.

Features

  • Highlight trends associated with readmissions and identify areas where readmissions could be reduced.
  • Users can filter on index admissions (LACE score) and/or readmission conditions
  • Supports CMS specific readmission conditions: AMI, Heart Failure, Pneumonia, Total Hip/Total Knee, CABG and COPD.

Benefits

Benefits Include:

  • More efficient and accurate reporting of readmission data.
  • Increased ability to perform meaningful investigation on factors related to readmission and their implications for specific groups of patients, across the health system.
  • Avoidance of CMS penalties, due to increased ability to recognize and address trends that may trigger penalties.

Measures

Index (Denominator) Filters:

  • Clinical Program
  • Care Process Family
  • Care Process
  • Primary ICD9 Diagnosis Description
  • Primary ICD9 Diagnosis Code
  • Primary ICD9 Procedure Description
  • Primary ICD9 Procedure Code
  • Primary Service
  • Attending Provider Specialty
  • Attending Provider Name
  • Discharge Location
  • Discharge Department
  • Discharge Status
  • Financial Class
  • Patient Age Group
  • Discharge Year
  • Discharge Quarter
  • Discharge Month

Readmission (Numerator) Filters:

  • Clinical Program
  • Care Process Family
  • Care Process
  • Primary ICD9 Diagnosis Description
  • Primary ICD9 Diagnosis Code
  • Primary ICD9 Procedure Description
  • Primary Service
  • Attending Provider Specialty
  • Financial Class
  • Discharge Status

See Sample Screenshots of Readmission Explorer

Data Sources

  • EMR billing

Readmission Explorer: A Deeper View

Background

Hospital readmission rates represent an important, if imperfect, proxy measure for poor-quality inpatient and outpatient care and poor care transitions (Axon 2011). Furthermore, as mandated by the Patient Protection and Affordable Care Act and related legislation, CMS reduces payments to hospitals with excess readmissions (42 CFR part 412). For these reasons, hospital systems do significant work to report and analyze readmissions within their system.

What type of problems do Readmission Explorer address?

To meet the demand for data and insight related to readmissions, hospitals need analytic tools that can provide both breadth and depth for investigating a facility’s historical readmission performance. Clinicians and administrators alike benefit from an array of measures and filters to ask and answer significant questions regarding historical performance. It’s also helpful to have a tool that provides a foundation for further investigation into factors that contribute to readmissions and for other analysis focused on specific cohorts of patients.

Use Case

  • A Cardiovascular clinical improvement team wants to explore readmissions among different stratifications of their heart failure patient population and gauge the impact of recent efforts to lower heart failure readmissions.
  • A pediatric team wants to explore asthma care and asthma education. How many children hospitalized for asthma were seen again for asthma exacerbations in the ED?

Anticipated Improvements

  • More efficient and accurate reporting of readmission data.
  • Increased ability to perform meaningful investigation on factors related to readmission and their implications for specific groups of patients, across the health system.
  • Avoidance of CMS penalties, due to increased ability to recognize and address trends that may trigger penalties.

Success Measure Examples

  • Opportunity Identification: Potential $ saved from more efficient querying and reporting.
  • Outcomes Improvement: Reduce or eliminate CMS penalties related to readmissions.