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Critical Decisions in the Emergency Department. University of Pennsylvania: Brendan G. Carr, MD MS Sage Myers, MD MS Scott Lorch, MD MS Patrick Reilly, MD Dylan Small, PhD Charles C. Branas, PhD Agency for Healthcare Research & Quality Ryan Mutter, PhD.
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Critical Decisions in the Emergency Department University of Pennsylvania: Brendan G. Carr, MD MS Sage Myers, MD MS Scott Lorch, MD MS Patrick Reilly, MD Dylan Small, PhD Charles C. Branas, PhD Agency for Healthcare Research & Quality Ryan Mutter, PhD
How do we design and measure the emergency care system?(Trauma as a case study) University of Pennsylvania: Brendan G. Carr, MD MS Sage Myers, MD MS Scott Lorch, MD MS Patrick Reilly, MD Dylan Small, PhD Charles C. Branas, PhD Agency for Healthcare Research & Quality Ryan Mutter, PhD
Disclosures • Federal research funding • AHRQ, NICHD, CDC, NINDS • www.traumamaps.org • www.strokemaps.org • AHA research funding • NRCPR/GWTG • National Quality Forum • RECS Steering Committee • HHS/ASPR Senior Policy Advisor • I am not appearing in this role today
Conceptual Framework • Ambulatory Care Sensitive Conditions • Conditions for which good outpatient care can potentially prevent the need for hospitalization, or for which early intervention can prevent complications or more severe disease. • Emergency Care Sensitive Conditions • Conditions for which rapid diagnosis and early intervention in acute illness or acutely decompensated chronic illness improves patient outcomes
Background:The Volume-Outcome relationship • 12 surgical procedures • CABG, AAA, TURP, etc. • 1500 hospitals Mortality Procedures =
Cardiac Arrest Mortality 70% Hospitals that treated over 50 pts/year had lower mortality 65% 60% Standardized Mortality 55% 50% 45% 20 40 60 80 100 120 Cardiac Arrest Patients Admitted to ICU/year
STEMI 30+% of STEMI patients get no reperfusion therapy
3% of ischemic strokes treated at TJC certified centers 3-8.5% receive rt-PA
Sepsis 5-7% of EDs perform EGDT
26% of physicians have used hypothermia (ever)
Time Volume
What is regionalization? • the organization of a system for the delivery of health care within a region to avoid costly duplication of services and to ensure availability of essential services. • Mosby’s medical dictionary
Trauma Model. All success? • 27,130,283 injuries treated in US hospitals in 2006 • 32% in trauma centers • 68% in non-trauma centers • Severely injured patients (ISS>15) • - More likely to be treated in trauma centers • (51.3% TC vs. 48.7% nTC, p<0.001) • Critically injured patients (ISS>25) • - More likely to be treated in non-trauma centers • (41.6% TC vs. 58.4% nTC, p<0.001)
Research questions with policy implications • Have we improved population outcomes for injury? • 1. In a nationally representative analysis – Do trauma centers save lives? • 2. What is the relationship between access to trauma care and injury outcomes? (supply and demand)
Research questions with policy implications • (What can understanding population outcomes for trauma teach us about examining other systems created to focus on unplanned critical illness?) • Stroke • STEMI • Cardiac arrest…
Q1. In a nationally representative analysis – Do trauma centers save lives? • Population: • All injured patients treated at trauma centers and non-trauma centers in the US • Data: • Nationwide Emergency Department Sample (HCUP) • Trauma Center Level (American Trauma Society) • Geography • Patient location, hospital location (US census, ArcGIS) • Prehospital transport time estimates • - empirically derived & arcGIS network analyst
Q1. In a nationally representative analysis – Do trauma centers save lives? • Analysis • Logistic regression • Survey weights • Confounders • Age, injury severity, comorbid conditions, region, insurance, hospital size, teaching status, hospital ownership, (prehospital time) • Sub groups • Severely injured, penetrating, blunt, age > 55, only patients surviving to admission
Characteristics of hospitals with ED encounters for injury - 2009
Relation between treatment at a level 1 or 2 trauma center and death * P < 0.05, ** p < .01
Relation between treatment at a level 1 or 2 trauma center and death * P < 0.05, ** p < .01
Unmeasured confounders? • Have not fully controlled for case mix? • Have not fully controlled for injury severity? • (no physiologic data) • The system is intentionally (and effectively) regionalized • the sickest and most complex patients are taken to the highest tier centers • Ideally, we would conduct a trial in which we randomize to treatment at a trauma center
Relation between treatment at a level 1 or 2 trauma center and death * P < 0.05, ** p < .01
Final model examining impact of trauma center on mortality* * With IV
Question 2. Population outcomes for trauma • Data Sources (trauma system - supply) • US Census Data • Location of residence at the level of the block group and county • CDC, American Trauma Society, Penn Cartographic Modeling Lab • Trauma center access • Data sources (injury death - demand) • National Center for Vital Statistics • Multiple Cause of Death (MCOD) Data
Question 2. Population outcomes for trauma • Methods • Supply Side – Access to trauma care • Access to level 1/2 trauma center within an hour • Demand Side – Injury Deaths • ICD codes to identify injury death location • Population data to calculate injury death rate • Analysis • Examine relation between injury death rates and access to trauma care using poisson distribution
Question 2. Population outcomes for trauma • Results • Supply • 60 minute access to trauma care • 84.7% of US residents • 46.4% of US counties • Mean time to care = 43 minutes +/- 22 • Demand • 152,766 injury deaths in 2005 • 27,964 in counties without access within 60 min • 124,802 in counties with access to care within 60 min
Counties without access to trauma care within 60 minutes had higher rates of injury death when compared to counties with access to trauma care within 60 minutes (OR 1.24, 95% CI 1.18-1.30) The relative risk of death increased at a rate of 3.4% for each 10 minute increase in time to trauma care (95% CI 2.4% - 4.4%).