Outcomes data for a Healthcare System: Helping make the case for Palliative Care

Topic: Measuring Impact and Value



The process and methodology of delivering outcomes data at a 12 hospital Healthcare System will be presented. Data from 7 hospitals on the same EMR will be shared. Common pitfalls, overcoming them and optimizing for accuracy will be discussed. Methods to optimize database for both internal and external reporting (CAPC Registry) will be highlighted. Strengths and weaknesses will be discussed.

Five studies were done.  Their results are summarized:

1.    One year outcomes data of a newly established program at one of the community based hospitals. Patients were severity adjusted.

  • If patients were seen by palliative care within the first 48 hours (N=353) versus later, the difference in length of stay per patient was 5.08 days. This led to a difference of 40% of the cost per case per day.
  • The mortality of patients seen within the first 48 hours versus later in the hospitalization was 1.01 versus 1.1 respectively.
  • The 30, 60 and 90 day readmissions dropped significantly after a palliative care consult by 61.5%, 47% and 42.1% respectively.
  • An increase in hospice referrals was noted.

2.    A seven hospital modified matched pair study was performed for patients with sepsis across the system (annualized from a 6 month data set).

  • There was an average difference of 1.67 days in length of stay of patients seen by palliative care within the first 48 hours of admission versus those not seen by palliative care. As an aggregate, palliative care patients in the ICU with sepsis that were seen within the first 48 hours had a shorter length of stay of 1.12 days.

3.    System financial impact: Patient/family directed care plan change methodology (annualized from a 2 month data set). Whenever a change was made to a more conservative treatment plan, the palliative care clinician, in real time, used a tab on the palliative care navigator developed in the EMR. On the back end, the system picked out the difference in the cost of care pre and post change in treatment plan.

  • Patient/family directed care plan change methodology to capture the drop in cost of treatments for the hospitals showed an overall cost avoidance that was 1.5 times of the total cost of the programs to the system. Each program more than recovered its costs through cost avoidance using this methodology.  

4.    A four month ICU pilot with a full time physician in one of the hospitals.

  • The same patient/family directed care plan change methodology in the ICU yielded an annualized cost avoidance of more than $600,000 (annualized form 2 moth dataset) and 315 (annualized from a 4 month data set) saved ICU days .
  • Other outcomes were measured – increase in referrals, nature of interventions, staff satisfaction and referrals to hospice.
  • 5.    System wide referrals to hospice (3 month data set).
  • On average, 15% (11.5%-32.3%) of all palliative care patients discharged from the hospitals were discharged with hospice care. Of all patients discharged with hospice care, 69.3% were referred by palliative care.
  • A recent trend in healthcare is for multiple hospitals to join to form a system. This calls for the case for palliative care to be made at both the hospital and system level. This comes with its own advantages and challenges.

Through this presentation, we would like to highlight, for our colleagues, the journey of gathering and processing data to show the advantages of palliative care by using outcomes data. This was done in 7 hospitals in which palliative care was established and developed differently. By developing a strategy involving various entities within and outside the system, the best case was developed to validate the current programs and initiate conversations at the system level to invest in its growth. The process and methodologies will be helpful to single site programs and system based programs in the country. We hope that the data in this presentation will help support programs that do not have the tools and resources to analyze outcomes data and provide the right tools to the ones that have them.



  • Aaron D. Bleznak
  • Douglas M. Thompson
  • J. Brian Cassel
  • Jennifer R. Ward
  • Joe Kim
  • John Patterson
  • Karen M. Helfen
  • Kathie S.Zimbro
  • Leo J. DeLeon
  • Sriram Yennu

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