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June 9, 2008 Making Mortality Measurement More Meaningful Incorporating Advanced Directives and Palliative Care Designations Eugene A. Kroch, Ph.D. Mark.

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Presentation on theme: "June 9, 2008 Making Mortality Measurement More Meaningful Incorporating Advanced Directives and Palliative Care Designations Eugene A. Kroch, Ph.D. Mark."— Presentation transcript:

1 June 9, 2008 Making Mortality Measurement More Meaningful Incorporating Advanced Directives and Palliative Care Designations Eugene A. Kroch, Ph.D. Mark Johnson, M.D., CMO Mercy Health John Martin, M.P.H., Premier Michael Duan, M.S., Premier

2 2 Community Acquired Pneumonia Outcome Profile (n =397) Risk Calculation: Select Practice Data source: CMS 7/1/01-6/30/02 * 75% statistical significance ** 90% statistical significance -4 -3 -2 0 1 2 3 4 StandardSelect Better---DEVIATION---Worse MortalityMorbidityComplicationsGM LOS ** * *

3 3 The Issue In-hospital mortality measurement may be improved by taking into account “Do Not Resuscitate” (DNR) orders and “Palliative Care” (PC) designations. Previous research in a single facility (Kroch-Samaha, Cooper University Hospital, 2005) demonstrated that DNR orders were significantly related to in-hospital mortality risk NB: Cooper study did not have reliable PC data.

4 4 Study Objectives Primary Objective : –Assess the value of incorporating DNR and PC information in the Wharton/CareScience mortality model (Medical Care) Secondary Objectives : –Characterize the incidence of DNR and PC by service line and physician type –Characterize the incidence of DNR and PC among patient types, e.g. age, disease/treatment, gender, transfer status, financial class, admit type, etc. –Evaluate the relationship between DNR and PC orders and inpatient mortality –Explore the DNR timing dimension with respect to the above –Explore the relationship between DNR and PC

5 5 Study Sample Facility: Mercy Health Center in Oklahoma City Timeframe: 9/2005 - 10/2006 Patient Data: –All discharges –DNR patients: All patients that signed DNR’s during hospitalization from 9/05 – 10 /06 –Palliative Care patients: All patients with palliative care consult order Model calibration on 265 hospitals in 38 states, 4.5 millions discharges over two years.

6 6 Mercy Health Center – OKC Palliative Care Service Palliative Care Program established in January 2001 Medical Director Physician order required for consult Physician retains patient on his service Clinical Nurse Specialist and RN provide consults Consult service with 2 dedicated beds See approximately 300 patients per year

7 7 DNR Orders DNR orders are portable from one facility to another Patient can present with DNR form on admission Physician writes order once aware of patient wishes Physician can write order when he feels treatment futile Orders then entered into order entry in Meditech Nursing intervention activated with Date DNR initiated during stay

8 8 Informational Realities StrengthWeakness PCStrong association with mortality risk Lack of defined standards for identifying PC patients (inconsistent use of V66.7 code) DNRCommon usage across facilities, systems, and states Not consistently captured in electronic record systems; Timing dependency

9 9 Half of hospitals have less than 2 per thousand Distribution of Palliative Care Coding Among Premier QUEST Hospitals

10 10 Mean = 53% Palliative Care Mortality Distribution among Premier QUEST Hospitals

11 11 Summary of Findings: –DNR and PC patients systematically differ from other patients. –PC and DNR can and should be incorporated into a mortality risk model. PC/DNR information explains some of patient risk at the margin (after accounting for other mortality risk factors already in the CareScience model) The marginal contribution of PC/DNR information to mortality risk depends on other patient attributes (diagnosis, age, etc.) PC in itself is a very strong risk indicator and DNR less so. –ACTION: Improve PC and DNR documentation to be consistent across hospitals (and service lines).

12 12 How are DNR/PC patients different from other hospital inpatients?

13 13 Patients by Service N=2059 N=928 N=917 N=775 N=684 N=668 N=572 N=458 N=398 N=2795 N=6229 The proportion of DNR/PC patients varies by service. N=2059 N=928 N=917 N=775 N=684 N=668 N=572 N=458 N=398 N=2795 N=6229

14 14 Patients by Admit Source N=4894 N=3653 N=538 N=32 N=12 Hospital transfers and emergent patients are over- represented among DNR patients.

15 15 Age distribution N=471 N=261 N=332 N=354 N=527 N=677 N=805 N=759 N=838 N=904 N=945 N=947 N=808 N=358 N=130 N=22 The proportion of DNR patients rises with age.

16 16 Where is the mortality deviation for DNR/PC patients greatest? NB: Where mortality deviation is greatest is where the model’s mortality prediction would potentially be most affected by including DNR/PC information.

17 17 Mortality Deviation by Age The mortality deviation is greater among younger DNR patients.

18 18 Mortality Deviation by Service* *Results shown for Attendings with >2% of all cases Mortality deviation is greater for GI, Oncology, Cardiology.

19 19 Mortality Deviation of Hospitalists Mortality deviation is less among hospitalists. Hospitalists have a higher proportion of DNR patients (slide 13).

20 20 Mortality Deviation by Order Timing The later the PC/DNR order, the greater the Mortality deviation.

21 21 Adding DNR/PC to the Model Modeling the Mortality Rate –DNR alone explains 23% - 45% of mortality variation within disease group. Adding PC increases the explained variation to 31% - 55%. –The CareScience risk model alone explains 30% to 54% of mortality variation. Adding DNR and PC to the model increases explained variation to 38% - 65%. Modeling Mortality Deviation –DNR/PC explains 8% – 40% of the variation in mortality deviation (raw – risk), depending on disease group. –Issuance of a DNR order later in the hospital stay was associated with a higher mortality rate. Regression Analysis Summary

22 22 Relative Explanatory Power

23 23 Marginal Effects for Selected Conditions

24 24 Explaining DNR… Modeling DNR with CareScience risk factors –CareScience risk factors explain 36% - 48% of DNR orders, indicating relatively high correlation (60% - 70%) between DNR and the standard set of CareScience risk factors. –The interaction between age and DNR was particularly strong in the Circulatory Disease group. The younger a patient was the higher mortality rate. Among Cancer patients, the interaction was the opposite. NOTE: Within the data set that we received from OKLC, V667 did NOT always correspond to the palliative care flag.

25 25 Conclusion Actual and expected mortality rates for DNR/PC patients are higher than non-DNR patients. Some aspects of risk associated with DNR & PC are captured in the CareScience model, but not all. –Hence, risk assessment can be improved by adding DNR & PC indicators. Adding DNR and PC indicators into a risk assessment model will have the greatest impact on certain sub-populations (e.g., younger patients and selected diagnostic groups). Patients with DNR orders later in their stay have higher mortality rates (and higher mortality deviations). This observation raises the danger that accounting for DNR in such patients may mask opportunities for better care. ACTION: Improve PC and DNR documentation to be consistent across hospitals (and service lines).


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