To accomplish great things, we must not only act, but also dream; not only plan, but also believe.

170 Pages·2011·8.28 MB·English

by  Mike Taigman

IHI197_IA_Bro_4PGR 11/4/09 12:54 PM Page 7
SCHEDULE
This ten-month professional development program includes three four-day on-site
meetings,monthly conference calls, and a web-based follow-up session six months after
graduation. In addition to the on-site meetings, participants engage in monthly conference
calls, supportand mentor one anothervia listserv, and receive individualized support
from faculty. For details about the schedule, please visit www.IHI.org/IA.
ENROLLMENT PROCESS
To enroll, please go online to www.IHI.org/IA. Under the “Enroll” tab, you’ll find
detailed instructions about the application process, which includes two documents: the
Improvement Advisor Application and the Improvement Advisor Knowledge and Self-
Assessment Form. Upon acceptance into the program, you will receive a prework packet
to begin preparing for the first on-site meeting. Due to the intensity of the program and
work on real projects for the participating organizations, class size will be limited.
CHANGING HEALTH CARE TOGETHER
IHI is a not-for-profit organizationleading the improvement of health care throughout
the world. IHI helps accelerate change by cultivatingpromising concepts for improving
patient care and turning those ideas into action. Thousandsof health care providers
participate in IHI’s groundbreaking work.
IHI offers a wide variety of programs and activities for health care professionalsto
learn fromexpert faculty and collaborate with experienced colleagues around the world.
This particular professional development programis part of a family of programs designed
for leaderswhoseek to gain a particular set of skills that are required foran organization
to succeed in its improvement agenda. Additionallearning opportunities include world-
class conferences and seminars, web-based programs, and professional development
programs exploring other critical leadership roles.
Enroll online or call
[phone]•[phone]
For more information
www.IHI.org/IA
66
IHI197_IA_Bro_4PGR 11/4/09 12:54 PM Page 10
“
Printed on recycled paper that I have the tools and su much more confident lead plans in my hand. Not organizations. I returned to write actionable plans to practical application in our The course is organized www.IHI.org [phone](617) 301-4800Cambridge, MA 0213820 University Road, 7th Floor
”MNDC pport from this IHI program. ing people in our organization just a bunch of good ideas. I fe my organization with tangible apply the concepts in our own hospital’s operation, then to teach a concept, discuss its
ount Kisco, NYorthern Westchester Hospirector of Performance Imraig J. Brandt, RPh, MBA now el to
ital, Stellaris Hprovement
ealth
67
INITIAL STUDY OVERVIEW:
CLINICAL IMPACT OF AMBULANCE RESPONSE TIMES
FOR ECHO AND OTHER TIME-DEPENDENT EMS CALLS

The impact of response times has been a core aspect of EMS system design since
the early 1980s when system pioneer Jack Stout read Dr. Eisenberg’s original study on
cardiac arrest resuscitation. Jack built fractal response time performance requirements
with financial penalties for failure to perform into the contracts he wrote for Public
Utility Model EMS systems.
EMS systems have evolved since Dr. Eisenberg and Jack Stout first began
working with the concept of response time performance nearly thirty years ago. While
the science of EMS has evolved, much is left to be learned about optimal system design.
This series of studies explores the clinical impact of various ambulance response times
for 9-1-1 calls classified as Echo and other time sensitive calls in an EMS system with
ALS Fire First Response?
We will work with the Alameda County EMS Agency and experienced clinical
researchers to design a series of studies that shed more light on the impact of various
response times. The results of these studies can be used to inform EMS system design
including response time requirements in Alameda County and other EMS systems around
the Country.
STUDY QUESTIONS:

1. Is there a difference in the Rapid Acute Physiology Score (RAPS) for patients
where the transport ambulance arrives in 6 min or less, between 6 and 7 min, between 7
and 8 min, between 8 and 9 min, between 9 and 10 min, between 10 and 11 min, between
11 and 12 min, between 12 and 13 min, and over 14 min?
2. Is there a difference in the survival rate of patients where the transport
ambulance arrives in 6 min or less, between 6 and 7 min, between 7 and 8 min, between 8
and 9 min, between 9 and 10 min, between 10 and 11 min, between 11 and 12 min,
between 12 and 13 min, and over 14 min?

68
HYPOTHESIS:

There is no significant difference in RAPS scores or survival rates for Echo
patients where there is a different ambulance response time.
LITERATURE:

Eisenberg, MS, Bergner, L, Hallstrom, A 1979 Cardiac Resuscitation in the
Community: JAMA May 4, 1979 Vol 241, No 18
This study focused on the impact of several time-related variables involving
resuscitation from out-of-hospital cardiac arrest. The study focused on 569 patients with
witnessed cardiac arrest. Their study determined that there was a strong relationship
between discharge from the hospital with time to initiation of CPR and time to definitive
care. “If CPR was initiated within four minutes, 97 of the 348 patients (28%) were
discharged. If it took four or more minutes to initiate CPR, 25 of the 204 patients (12%)
were discharged (P<.001).
Discharge rates were similar up to a definitive care time of eight minutes. If the
time to definitive care was less than eight minutes, 78 of 197 patients (40%)were
discharged. If the time to definitive care was eight or more minutes, 44 of 352 patients
(13%) were discharged (p<.001). When this study was conducted EMTs could not
defibrillate. The study did not define what comprised definitive but discussed the arrival
of paramedics and suggested that resuscitation rates might be improved if EMTs could
defibrillate. This is the study cited by EMS system designer Jack Stout when he created
the 8 minute response time performance requirement back in the early 1980s.

Pons PT, Markovchick, VJ, 2002 Eight Minutes or Less: Does the Ambulance
Response Time Guidline Impact Trauma Patient Outcome, The Journal of Emregency
Medicine Vol. 23, No1, pp. 43-48
This is a retrospective study of 3490 priority 1 trauma patients transported to a
single level one trauma center by urban paramedics over a two year period. The patients
were placed into two groups, Group I having response times less than or equal to 8 min
and group II having a response time greater than 8 min. Survival for the response time
groups showed no significant differences weather the patients were evaluated in total or

69
by the subgroups mechanism of injury, patient age, or Injury Severity Score. Their
conclusion was, “Exceeding the ambulance industry response time criterion of 8 min
does not affect patient survival after traumatic injury.

De Maio, Stiell, IG, Wells, GA, Spaite, DW 2003 Optimal Defibrillation
Response Intervals for Maximum Out-Of-Hospital Cardiac Arrest Survival Rates
Annals of Emergency Medicine 42:2
This prospective cohort study of cardiac etiology out-of-hospital cardiac arrest
cases from phases I and II of the Ontario Prehospital Advanced Life Support (OPALS)
Study. There were 392 survivors among the 9,273 patients treated. There was a steep
decrease in the first 5 minutes of the survival curve, beyond which the slop gradually
leveled off.
At 9 minutes there were 18 survivors, 8 minutes 0 survivors, 7 minutes 23
survivors, 6 minutes 51 survivors and 5 minutes 86 survivors. In their conclusion they
said, “The 8-minute target established in many communities is not supported by our data
as the optimal EMS defibrillation response interval for cardiac arrest.”

Pons PT, Haukoos JS, Bludworth W, Cribley T, Pons KA, Markovchick VJ
2005 Paramedic Response Time: Does it Affect Patient Survival? Academic
Emergency Medicine Jul;12(7):549-600
This was a retrospective cohort study performed in an urban 911-based
ambulance service system. Patients transported to a single urban county teaching
hospital during 1998 were included. The 9,559 patients transported with data available
were categorized into groups based on their level of illness severity. A survival benefit
was identified for response times less than or equal to 4 minutes. No survival benefit was
identified when response time was modeled as a continuous variable or when
dichotomized at 8 minutes. Their conclusion said, “A paramedic response time within 8
minutes was not associated with improved survival to hospital discharge after controlling
for several important confounders, including level of illness severity. However a survival
benefit was identified when the response time was within 4 minutes for patients with
intermediate or high risk of mortality. Adherence to the 8-minute response time

70
guideline in most patients who access out-of-hospital emergency services is not
supported by these results.”

Blackwell, TH, Kline, JA, Willis, JJ, Hicks, GM 2009 Lack of Association
Between Prehsspital Response Tiems and Patient Outcomes Prehsopital Emergency
Care 2009;13:444-450
This case-control retrospective study tested the hypothesis that patient outcomes
do not differ substantially based on explicitly chosen advanced life support response time
upper limit of 10 minutes 59 seconds. This study was conducted in a system with BLS
first response followed by ALS transport. There were 373 study patients, Priority 1
transports were response times exceeding 10:59 minutes which, were compared with 373
control patients which were priority 1 calls with response time so of 10:59 or less.
Prehospital run reports and hospital outcomes were evaluated focusing on in-hospital
death and critical clinical interventions performed in the field.
The survival to hospital discharge was 80% for study patients vs. 82% for
controls. ALS procedures were performed in 47.7% of the study patients vs. 45.4% of
controls. The most frequently performed procedures were the administration of
nitroglycerine and endotracheal intubation. They concluded that “Compared with
patients who wait 10:59 minutes or less for ALS response, Priority 1 patients who wait
longer the 10:59 could experience between a 6% increase and a 4% decrease in mortality
and do not have an increase in critical procedures performed in the field.”

Bourn S, Stolz, U, Denninghoff, K, Spaite, D 2010 The Relationship between
the Rapid Acute Physiology Score (RAPS) and Prehospital Patient Acuity presented at
the 2010 National Association of EMS Physicians Annual Conference
This retrospective analysis of AMR’s database of 1,222,193 adult EMS patient
encounters evaluated the relationship between the Rapid Acute Physiology Score (RAPS)
and EMS patient acuity based on the following indicators.
• EMT/Paramedic primary impression of the patient’s criticality
• Performance of oral endotracheal intubation
• Administration of medications (excluding oxygen)

71
• Emergent transport to the hospital
This study showed very strong correlation between the RAPS score and patient
acuity. For example the likelihood of a patient being intubated increases by nearly two-
fold with each increase of the RAPS by one.

Unpublished analysis of RAPS and response time conducted by Scott Bourn
Ph.D. and the AMR Clinical Leadership Team
This retrospective study looked at the impact of delayed response times on patient
acuity. They evaluated 2 years worth of data from 53 AMR operations in 20 states and
included all 911 responses that resulted in transport to the hospital with complete data,
N= 269,346. They also looked at ALS First Responder Interventions for 4 operations
with ambulance response time standards between 10:30 and 12:30. They evaluated
300,747 non cardiac arrest patient care records that required ALS interventions.
IMPACT OF DELAYED RESPONSE TIMES ON PATIENT ACUITY:
o Initial and final average patient acuity was calculated using the Rapid Acute
Physiology Score (RAPS) for patients grouped by primary impression groups
(abdominal problem, altered LOC, behavioral/psych, breathing problems,
cardiac/respiratory arrest, cardiovascular, medical problems, OB, pain, sick,
toxicology, trauma, and other).
o RAPS scores by primary impression were then stratified by ambulance
response time within the following groupings (in minutes): < 8, 8-9, 9-10, 10-
11, 11-12, 12-13, >13.
o Patients in cardiac/respiratory arrest appeared to experience an increase in
average acuity for response times greater than 11 minutes. This group
requires further examination to better understand the relationship and the
relative impact of cardiac vs. respiratory arrest. .
o There were no identifiable changes in initial RAPS for ANY other group of
primary impressions related to response times.

72
FIRST RESPONDER INTERVENTIONS:
o ALS interventions by first responders are very uncommon:
 Any ALS intervention: 431/300,747 (0.14% of total sample)
 ALS interventions are most commonly required in cardiac arrest:
405/431 (94%)
o Distribution of interventions
 Advanced airway management: 283/431 (66%)
 Defibrillation: 190/431 (44%)
o Impact of ALS interventions performed in non-cardiac arrest
 There were 26/431 (6%) non-cardiac arrest patients who received
first responder intervention. Electronic prehospital medical
records were reviewed for all cases.
 First responder airway management was successful in 62% of
cases
 Using the RAPS acuity analysis 12/26 (46%) of patients had an
improved condition following first responder intervention
STUDY TYPES:
Prospective observational, retrospective case review, scientific literature meta analysis.
POSSIBLE METHODS:
Prospective and retrospective comparison of initial RAPS score, survival to
discharge, and procedures performed for a convenience sample of Echo and other time
sensitive clinical calls grouped by their naturally occurring ALS ambulance response
time in Alameda County and other similar EMS systems.
NEXT STEPS:
The details of this series of studies including power computations and
Institutional Review Board application is proposed to be developed in collaboration with
the County EMS Agency’s Medical Director.

73
Rapid Acute Physiology Score.enl Page 1
Howell, M. D., M. W. Donnino, et al. (2007). "Performance of Severity of Illness Scoring
Systems in Emergency Department Patients with Infection." Acad Emerg Med.
Objectives To validate the Mortality in Emergency Department Sepsis (MEDS)
score, the Confusion, Urea nitrogen, Respiratory rate, Blood pressure, 65 years
of age and older (CURB-65) score, and a modified Rapid Emergency Medicine
Score (mREMS) in patients with suspected infection. Methods This was a
prospective cohort study. Adult patients with clinically suspected infection
admitted from December 10, 2003, to September 30, 2004, in an urban
emergency department with approximately 50,000 annual visits were eligible.
The MEDS and CURB-65 scores were calculated as originally described, but
REMS was modified in neurologic scoring because a full Glasgow Coma Scale
score was not uniformly available. Discrimination of each score was assessed
with the area under the receiver operating characteristics curve (AUC). Results
Of 2,132 patients, 3.9% (95% confidence interval [CI] = 3.1% to 4.7%) died.
Mortality stratified by the MEDS score was as follows: 0-4 points, 0.4% (95% CI
= 0.0 to 0.7%); 5-7 points, 3.3% (95% CI = 1.7% to 4.9%); 8-12 points, 6.6%
(95% CI = 4.4% to 8.8%); and >/=13 points, 31.6% (95% CI = 22.4% to 40.8%).
Mortality stratified by CURB-65 was as follows: 0 points, 0% (0 of 457 patients);
1 point, 1.6% (95% CI = 0.6% to 2.6%); 2 points, 4.1% (95% CI = 2.3% to 6.0%);
3 points, 4.9% (95% CI = 2.8% to 6.9%); 4 points, 18.1% (95% CI = 11.9% to
24.3%); and 5 points, 28.0% (95% CI = 10.4% to 45.6%). Mortality stratified by
the mREMS was as follows: 0-2 points, 0.6% (95% CI = 0 to 1.2%); 3-5 points,
2.0% (95% CI = 0.8% to 3.1%); 6-8 points, 2.3% (95% CI = 1.1% to 3.5%); 9-11
points, 7.1% (95% CI = 4.2% to 10.1%); 12-14 points, 20.0% (95% CI = 12.5%
to 27.5%); and >/=15 points, 40.0% (95% CI = 22.5% to 57.5%). The AUCs
were 0.85, 0.80, and 0.79 for MEDS, mREMS, and CURB-65, respectively.
Conclusions In this large cohort of patients with clinically suspected infection,
MEDS, mREMS, and CURB-65 all correlated well with 28-day in-hospital
mortality.
Goodacre, S., J. Turner, et al. (2006). "Prediction of mortality among emergency
medical admissions." Emerg Med J 23(5): 372-5.
BACKGROUND: The Rapid Acute Physiology Score (RAPS) and Rapid
Emergency Medicine Score (REMS) are risk adjustment methods for emergency
medical admissions developed for use in audit, research, and clinical practice.
Each predicts in hospital mortality using four (RAPS) or six (REMS) variables
that can be easily recorded at presentation. We aimed to evaluate the predictive
value of REMS, RAPS, and their constituent variables. METHODS: Age, heart
rate, respiratory rate, blood pressure, Glasgow Coma Score (GCS) and oxygen
saturation were recorded for 5583 patients who were transported by emergency
ambulance, admitted to hospital and then followed up to determine in hospital
mortality. The discriminant power of each variable, RAPS, and REMS were
compared using the area under the receiver operator characteristic curve
(AROCC). Multivariate analysis was used to identify which variables were
independent predictors of mortality. RESULTS: REMS (AROCC 0.74; 95% CI
0.70 to 0.78) was superior to RAPS (AROCC 0.64; 95% CI 0.59 to 0.69) as a
74
Rapid Acute Physiology Score.enl Page 2
predictor of in hospital mortality. Although all the variables, except blood
pressure, were associated with mortality, multivariate analysis showed that only
age (odds ratio 1.74, p < 0.001), GCS (2.10, p < 0.001), and oxygen saturation
(OR 1.36, p = 0.01) were independent predictors. A combination of age, oxygen
saturation, and GCS (AROCC 0.80, 95% CI 0.77 to 0.83) was superior to REMS
in our population. CONCLUSION: REMS is a better predictor of mortality in
emergency medical admissions than RAPS. Age, GCS, and oxygen saturation
appear to be the most useful predictor variables. Inclusion of other variables in
risk adjustment scores, particularly blood pressure, may reduce their value.
Hargrove, J. and H. B. Nguyen (2005). "Bench-to-bedside review: outcome predictions
for critically ill patients in the emergency department." Crit Care 9(4): 376-83.
The escalating number of emergency department (ED) visits, length of stay, and
hospital overcrowding have been associated with an increasing number of
critically ill patients cared for in the ED. Existing physiologic scoring systems
have traditionally been used for outcome prediction, clinical research, quality of
care analysis, and benchmarking in the intensive care unit (ICU) environment.
However, there is limited experience with scoring systems in the ED, while early
and aggressive intervention in critically ill patients in the ED is becoming
increasingly important. Development and implementation of physiologic scoring
systems specific to this setting is potentially useful in the early recognition and
prognostication of illness severity. A few existing ICU physiologic scoring
systems have been applied in the ED, with some success. Other ED specific
scoring systems have been developed for various applications: recognition of
patients at risk for infection; prediction of mortality after critical care transport;
prediction of in-hospital mortality after admission; assessment of prehospital
therapeutic efficacy; screening for severe acute respiratory syndrome; and
prediction of pediatric hospital admission. Further efforts at developing unique
physiologic assessment methodologies for use in the ED will improve quality of
patient care, aid in resource allocation, improve prognostic accuracy, and
objectively measure the impact of early intervention in the ED.
Olsson, T., A. Terent, et al. (2005). "Charlson Comorbidity Index can add prognostic
information to Rapid Emergency Medicine Score as a predictor of long-term mortality."
Eur J Emerg Med 12(5): 220-4.
OBJECTIVES: To investigate whether co-existing medical disorders, summed
up in a comorbidity index, in nonsurgical patients attending the emergency
department could predict short-term and long-term mortality, and whether the
index could add prognostic information to the Rapid Emergency Medicine Score.
METHODS: This was a prospective cohort study. In all, 885 nonsurgical
patients, presenting to an adult emergency department and admitted to a
medical department of a 1200-bed university hospital during 2 months, were
enrolled consecutively. The Rapid Emergency Medicine Score (including blood
pressure, oxygen saturation, respiratory rate, pulse rate, age and Glasgow coma
scale) was calculated within 20 min in all those admitted to the emergency
department. The history of coexisting disorders (Charlson Comorbidity Index)
75