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Inpatient capacity margin at
children's hospitals during the
fall 2009 H1N1 influenza
pandemic
Marion R. Sills, MD, MPH,
Objectives
• Objectives:
 Compare occupancy—non-ICU and ICU—during the fall
2009 pandemic to baseline numbers
 Measure how close each hospital came to threshold
occupancy—non-ICU and ICU
 Measure how much of an increase in ED admissions it
would have taken to fill each hospital (and each ICU)
Background
• March 2009: “swine flu” reported with 6% case fatality rate in
Mexico; Mexico City shut down
• April 2009: public health emergency declared in US
• April 2010: CDC estimate of
 H1N1 case fatality rate in US: 0.02% (0.006% in children 0-17 years)
 H1N1 case hospitalization rate: 0.45% (0.44% in children 0-17 years)
Background
• Case hospitalization and
case fatality rates much
less than prior pandemics
Background
• Per-population hospitalization rate comparable to
recent seasonal flu years
Methods
• Inpatient data from Pediatric Health Information System
(PHIS) database
• 41 children’s hospitals
Methods
Data
• All hospitalizations
 Non-ICU bed-days
 ICU bed-days
• Known # active beds
• Historic occupancy
data
• All ED visits for
influenza-like-illness
(23 hospitals)
Calculate
• Percent occupancy
by day (non-ICU,
ICU)
• ED ILI admission rate
Methods
• Objective 1: Compare occupancy—non-ICU and ICU—during
the fall 2009 pandemic to baseline numbers
• Same weeks (35-45) for 2008 (charted below)
• Seasonal flu (weeks 4-11 of 2009) for 2008-09
Methods
• Objective 2: Measure how close each hospital came to
threshold occupancy—non-ICU and ICU
• 2 definitions of threshold occupancy:
 Normative: 100% of all active beds occupied
 Relative: the own-hospital 95th percentile of occupancy (2008)
Methods
• Objective 2: Measure how close each hospital came to
threshold occupancy—non-ICU and ICU
 How best to express this?
• Proportion of days over threshold occupancy during pandemic period?
• Some component of duration: X weeks of Y% of days over threshold?
• Number of bed-days that could have been filled daily before threshold
occupancy was reached?
• Number of additional patients that could have been accepted daily
before threshold occupancy was reached?
Methods
Methods
• Part of the story: many children’s hospitals are already
nearing or over threshold occupancy (2006 data)
Methods
 Objective 3: Measure how much of an increase in ED
admissions it would have taken to fill each hospital (and each
ICU)
 For each hospital, calculate actual ED-to-non-ICU and ED-to-
ICU admit rate among all patients with ILI
 Calculate how much higher this rate would have had to be to
fill all beds
 Select a bad flu year (pandemic flu year? recent seasonal flu
year?) and re-do the modeling for Objective 2 to show how
full hospitals would have been, and how many excess beds
we would have needed (i.e., how many would have boarded
in the ED)
Methods
 Objective 3: Measure how much of an increase in ED
admissions it would have taken to fill each hospital (and each
ICU)
 Assumptions:
• All ED-to-hospital admissions with discharge diagnosis of
ILI had H1N1 influenza
• All inpatients with influenza were admitted via that
hospital’s ED
• ED-to-hospital admissions were distributed evenly
throughout the study period
CEMRC H1N1 Presentation 20100614

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CEMRC H1N1 Presentation 20100614

  • 1. Inpatient capacity margin at children's hospitals during the fall 2009 H1N1 influenza pandemic Marion R. Sills, MD, MPH,
  • 2. Objectives • Objectives:  Compare occupancy—non-ICU and ICU—during the fall 2009 pandemic to baseline numbers  Measure how close each hospital came to threshold occupancy—non-ICU and ICU  Measure how much of an increase in ED admissions it would have taken to fill each hospital (and each ICU)
  • 3. Background • March 2009: “swine flu” reported with 6% case fatality rate in Mexico; Mexico City shut down • April 2009: public health emergency declared in US • April 2010: CDC estimate of  H1N1 case fatality rate in US: 0.02% (0.006% in children 0-17 years)  H1N1 case hospitalization rate: 0.45% (0.44% in children 0-17 years)
  • 4. Background • Case hospitalization and case fatality rates much less than prior pandemics
  • 5. Background • Per-population hospitalization rate comparable to recent seasonal flu years
  • 6. Methods • Inpatient data from Pediatric Health Information System (PHIS) database • 41 children’s hospitals
  • 7. Methods Data • All hospitalizations  Non-ICU bed-days  ICU bed-days • Known # active beds • Historic occupancy data • All ED visits for influenza-like-illness (23 hospitals) Calculate • Percent occupancy by day (non-ICU, ICU) • ED ILI admission rate
  • 8. Methods • Objective 1: Compare occupancy—non-ICU and ICU—during the fall 2009 pandemic to baseline numbers • Same weeks (35-45) for 2008 (charted below) • Seasonal flu (weeks 4-11 of 2009) for 2008-09
  • 9. Methods • Objective 2: Measure how close each hospital came to threshold occupancy—non-ICU and ICU • 2 definitions of threshold occupancy:  Normative: 100% of all active beds occupied  Relative: the own-hospital 95th percentile of occupancy (2008)
  • 10. Methods • Objective 2: Measure how close each hospital came to threshold occupancy—non-ICU and ICU  How best to express this? • Proportion of days over threshold occupancy during pandemic period? • Some component of duration: X weeks of Y% of days over threshold? • Number of bed-days that could have been filled daily before threshold occupancy was reached? • Number of additional patients that could have been accepted daily before threshold occupancy was reached?
  • 12. Methods • Part of the story: many children’s hospitals are already nearing or over threshold occupancy (2006 data)
  • 13. Methods  Objective 3: Measure how much of an increase in ED admissions it would have taken to fill each hospital (and each ICU)  For each hospital, calculate actual ED-to-non-ICU and ED-to- ICU admit rate among all patients with ILI  Calculate how much higher this rate would have had to be to fill all beds  Select a bad flu year (pandemic flu year? recent seasonal flu year?) and re-do the modeling for Objective 2 to show how full hospitals would have been, and how many excess beds we would have needed (i.e., how many would have boarded in the ED)
  • 14. Methods  Objective 3: Measure how much of an increase in ED admissions it would have taken to fill each hospital (and each ICU)  Assumptions: • All ED-to-hospital admissions with discharge diagnosis of ILI had H1N1 influenza • All inpatients with influenza were admitted via that hospital’s ED • ED-to-hospital admissions were distributed evenly throughout the study period