Transitioning Nursing Home Residents during Hurricane Emergencies: The Mortality & Morbidity Consequences of Evacuating Versus Sheltering in Place

Transcription

1 Transitioning Nursing Home Residents during Hurricane Emergencies: The Mortality & Morbidity Consequences of Evacuating Versus Sheltering in Place Kathy Hyer, PhD, MPP School of Aging Studies, University of South Florida, Tampa, FL David Dosa, MD, MPH Providence VA Medical Center Center for Gerontology and Health Care Research Brown University, Providence, RI The Safe Haven Study Grant Funded by NIA AG#30619

2 The devastating effects of Hurricane Katrina on the Gulf Region highlighted the importance of emergency preparedness and cast a sharp media spotlight on nursing homes Nursing Homes such as St. Rita s experienced well publicized loss of life after failing to evacuate their residents prior to the storm. Overview:

3 Four weeks later, the most resounding image of Hurricane Rita was the burned out bus where 23 NH evacuees lost their lives. Overview

4 Evacuation of NH Residents While county level emergency management orders evacuations for the county, the responsibility of deciding whether or not to evacuate falls to facility administrators (U.S. GAO, 2006) The plans are designed to Shelter in Place Risks associated with moving sick and frail people

5 To Evacuate or Not to Evacuate That is the Question

6 Overview: Strategic Approach to Facilitating Evacuation by Health Assessment of Vulnerable Elderly in Nursing Homes (Safe Haven Study) NIA Grant: AG#30619 Awarded to Brown University and The University of South Florida in October 2008 Aims of the Grant: Aim 1: To describe and compare nursing homes which evacuated or sheltered in place during hurricanes and to describe the 30 day, 3 month, and 6 month mortality and morbidity outcomes that residents experienced. Aim 2: To estimate the effect of the decision to evacuate or shelter in place in the face of hurricane warnings on the mortality and morbidity outcomes of nursing home residents.

7 Methodology

8 Background 2005 Storms Hurricane Katrina Hurricane Rita 2008 Storms Hurricane Gustav Hurricane Ike All storms affected the Gulf Region All storms preceded by 2 non hurricane years

9 Background (2) Key Questions: What happened to nursing home residents affected by each of the 4 storms? How did they fare compared to those residing at the same nursing homes during non storm years?

10 Methodology (1) Determine Risk Area Identify At Risk Nursing Homes/Resident Sample Determine Comparison Groups 2003/2004 for Hurricanes Katrina and Rita 2006/2007 for Hurricanes Gustav and Ike

11 Methodology (2) Outcomes 30 and 90 day Mortality 30 and 90 day Hospitalizations

12 Hurricane Katrina 19% Evacuated

13 Hurricane Rita 32% Evacuated

14 Hurricane Gustav 82% Evacuated

15 Hurricane Ike 43% Evacuated

16 Resident Sample/Cohort Selection Identified all NH residents from the federally mandated NH resident assessment Minimum Data Set (MDS) Assessments completed upon NH admission and at least quarterly, thereafter MDS assessment data linked by person were matched to Medicare enrollment and Hospitalization claims Included are long stay residents in at risk NHs in the path of Katrina in 2003, 04 and 05.

17 Resident Sample/Cohort Selection(2) Final analysis included at risk NHs in LA and MS only (no evacuation was reported in AL or FL) Further restricted to at risk NHs that were present in all three years (N=141) Evacuated after Katrina Evacuated before Katrina Sheltered in place Total LA MS Total

18 Resident Sample/Cohort Selection(3) Baseline samples: Drawn at June 1in each year, based on residential history file (RHF) which tracks location of care for each resident by linking MDS, Medicare enrollment, and claims Baseline MDS: The most complete & recent MDS assessment prior to 8/25 in each year.

19 Baseline sample: 2005 (as example) Inclusion/Exclusion Criteria: N With any days in at risk facilities at 6/1/ ,311 Begin With valid MDS* within 120 days before 8/25/ ,011 Matched to Medicare Denominator record 12,675 Drop those age < 65 at baseline MDS 11,299 Drop those in Medicare HMO at baseline 10,785 Restrict to long stay residents only 9,280 Restrict to 138 homes present in all 3 years ,056 Final Sample + Identified in the Residential History File (RHF). * Valid here excludes persons having only a preadmission screening, readmission assessment, or discharge record within the baseline window.

20 Source: AP Photo Results

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25 Excess Exposure Deaths Excess Deaths Storm 30 Days 90 Days Katrina (19%)* Rita (32%)* Gustav (82%)* Ike (43%)* Aggregate *= Percent of At Risk that Evacuated

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27 Excess Exposure Hospitalizations Excess Hospitalizations Storm 30 Days 90 Days Katrina (19%)* Rita (32%)* Gustav (82%)* Ike (43%)* Aggregate *= Percent of At Risk that Evacuated

28 How much did evacuation affect morbidity/mortality?

29 Evacuation Status Data Sources Texas Department of Aging & Disability Services Mississippi Department of Health Louisiana Department of Health and Hospitals External Factors National Weather Service Tropical Cyclone Advisory Archive National Oceanic and Atmospheric Administration (NOAA) Internal Factors OSCAR

30 Methodology Using Safe Haven Data we evaluated the differential mortality and morbidity associated with evacuation versus sheltering in place Data on who evacuated and sheltered in place collected from: Lousiana and Texas Department of Healths, Louisiana Nursing Home Association

31 Analytic Approach Relative to 2002 and 2003, estimated the increase in # of deaths and hospitalizations during and after the storms Modeled the effect of being in an evacuated home relative to one that sheltered in place, controlling for patient characteristics and distance of the home from the storm path Predicted the percentage of excess (due to storm) deaths and hospitalizations attributable to the decision to evacuate

32 Mortality Katrina P e r c e n t a g e Within 90 days before landfall Within 30 days after landfall Shelter in Place Evacuated Within 90 days after landfall

33 Hospitalizations Katrina P e r c e n t a g e Within 90 days before landfall Shelter in Place Within 30 days after landfall Evacuated Within 90 days after landfall

34 Mortality Gustav P e r c e n t a g e Within 90 days before landfall Within 30 days after landfall Within 90 days after landfall Shelter in Place Evacuated

35 Hospitalizations Gustav P e r c e n t a g e Within 90 days before landfall Shelter in Place Within 30 days after landfall Evacuated Within 90 days after landfall

36 Fraction of excess deaths/hospitalizations attributable to evacuation before storm Hospital 30 Days Death 30 Days Hospital 90 Days Death 90 Days Katrina (%) 14% 5% 15% 10% Rita(%) 92% x 95% 21% Gustav(%) 95% x 95% 31% Ike(%) x x x x Notes: All fractions are significant at the 10 percent level. [x] cells are those where the excess deaths in storm year were not significantly different from zero.

37 Excess Mortality 90 Days Katrina Rita Gustav Ike Expected Actual Excess Fraction Due to Evacuation

38 Excess Hospitalizations 90 Days Expected Actual Excess Fraction Due to Evacuation Katrina Rita Gustav Ike

39 Summary Clearly see that there is a cost to evacuation independent of the actual storm even making very conservative assumptions The cost of evacuation is more than just the buses, the double payment, the extra medicine; must consider the hidden morbidity and mortality in this frail population On positive side Ike was very powerful but low excess mortality, so much so we couldn t tell with confidence if due to evacuation. So few recent storms hard to tell if we got it right

40 Implications Given costs of evacuation, long term solution to not build NHs on coast or near flood water and harden those already there Strongly suggest limiting or refusing entry to sickest patients in homes most likely to evacuate May need to rethink when the evacuation trigger gets pulled since at least as many false alarms as big storms

41 Others Collaborating: Vincent Mor, Ph.D Zhanlian Feng, Ph.D Lisa Brown, Ph.D Kali Thomas, Ph.D Shailender Swaminathan, Ph.D Gary Blanchard, MD Collective staffs at Brown University, Providence VA, and the University of South Florida John Haaga Program Officer, NIA

42 Others to Thank: John A. Hartford Foundation Veteran s Administration Florida Health Care Association Louisiana Nursing Home Association Mississippi Nursing Home Association Texas Nursing Home Association American Health Care Association