Transcript A_Proposed_Method

A Proposed Method for the
Measurement of Anesthetist
Care Variability
Paul King
Definitions:
• Anesthesiology = the practice of
medicine dedicated to the relief of pain
and total care of the surgical patient
during and after surgery.
• Anesthesiologist = MD trained (4+4+4)
• Anesthetist = MD, CRNA (4+3), …
Statistics
• 40 Million + anesthetics/year USA
• 90% by MD Anesthesiologists
Role of Anesthesiologist
• Perioperative care =
• Preop evaluation
• Intraoperative care
• Postoperative care
Intraoperative Role:
• Provide continuous medical assessment
• Monitor & control vital life functions
• Control Pain & level of consciousness
•
safe surgery
Intraoperative Role Reworded:
• NO Pain
• NO Memory/Consciousness
• NO Movement
A Proposed Method for the
Measurement of Anesthetist
Care Variability
Paul King
Who/Where
• Paul King, PhD, PE.
Bme/me/anesth.
• Don Pierce MD, PhD. Anesth. HPS & Pre. OP
• Mike Higgins MD
Anesth., Peri. OP
• Charles Beattie PhD, MD
Chairman, $
• Russ Waitman, MS PhD candidate, data mining
•
… all at Vanderbilt
What? When?
• A Proposed Method (demo/technique) for the
Measurement of Anesthetist (resident
anesthesiologist– novice to final, faculty, CRNA, others)
Care Variability ( controllability)
• Testing done at VU, ~ 1 year ago, to be
published (JOCM).
Why?
• To Err Is Human: Building a Safer Health
System (2000) – National Academy Press
(anesthetic only)
• ~1 death/2-300,000 v 2/10,000 (80’s) pg 32.
• Human error ~82% of preventable pg 53.
• 72 year lifespan = ~ 1 death/630,720 hours.
How 2/10,000  1/(2-300,000)?
• Technological changes (new dev, std.)
• Guidelines & strategies
• Use of human factors, including
simulators
• APSF
• Leaders (Pierce, Cooper, Schwid, …)
Why?
• U. S. Anesthesiologists are ~ 100%
certain of at least one major lawsuit
during their careers…
Maintain?
• Continue the above…
• Increase/improve training (MD v CRNA).
• Morbidity/Mortality conferences.
• Periodic Reviews of cases & records.
• Test. Test for competency. Test safely.
Test in an unbiased fashion. Test.
Hypotheses
• A challenging protocol may be developed
using a simulator that tests anesthetists'
skills at maintaining patient homeostasis
within limits, and
• An analytical technique may be
demonstrated that will suggest that "skill
level" may be inferred from the data
collected from the simulator.
Method: METI Simulator
Method: METI Simulator
Why a simulator?
• Standardization of “cases.”
• Standardization of “patient.”
• Data collection q 5 sec, not circa 5 min. (20+
variables, important HR, BP, pOx)
• Other (biased?) modalities possible –
observation, taping, etc.
• Safe, not sorry.
Simulation Method
• Inform examinee who the patient is (Stan,
normal young male)
• Operation type: low anterior bowel resection
• SOP please …
• Inform re stage of surgery…
• Start!
And we are off…
The protocol (“Stable Anesthesia”)
• Induction  Intubation (epi)  Maintenance
•  Incision (epi)  Fluid loss (~ 3L) 
•  Maintenance  Ischemia & Desaturation
( & lung changes)
•  Maintenance  Emergence
•  Extubation ( adequacy)
This Scenario was designed to
discriminate between subjects at
different levels of anesthesia
training
• Events range from minor to severe
• Events and responses (drug & gas
admin.) are recorded real time
• Maintenance periods for reality
• Instructor available for simple requests
only, but does forewarn per real OR
Data Analysis Criteria
• Blood pressure wrt preop. +/- 20%
• +/- 20%  hypertensive/hypotensive  cardiac/renal
disorders.
• HR wrt preop.+/- 20%
• Probably need to set +60%/-30%, give me a reference?
• pOx wrt preop. +/- 5%
• Based upon thoughts about significant changes…
Literature re limits & analysis?
• Reich, et al, “Validation of an Algorithm
for Assessing Intraoperative Mean
Arterial Pressure Lability” Anesthesiology
87:156-161
• … rolling 2 min map values exceeding +/6% swing
Analysis Method
• Fractional time out of range (King)
• +/- 20% BP
• +/- 20% HR
• +/- 5% pOx
Subjects
• First year new student – “novice”
• Second year - “PGY2”
• Graduate/Faculty – “PGA”
• All physician data from outpatient clinic,
cases > ~60 samples, 1543 cases
Results: Fraction out of range
– Heart Rate
• Simulator: PGA
.310
• Simulator: PGY2
.328
• Simulator: Novice
.685
• Outpatient data set:
.311
Results: Fraction out of range
– Systolic Blood Pressure
• Simulator: PGA
.036
• Simulator: PGY2
.145
• Simulator: Novice
.236
• Outpatient data set:
.318
Results: Fraction out of range
– Diastolic Blood Pressure
• Simulator: PGA
.131
• Simulator: PGY2
.224
• Simulator: Novice
.236
• Outpatient data set:
.642
Results: Fraction out of range
– Pulse Oximeter Data
• Simulator: PGA
.158
• Simulator: PGY2
.197
• Simulator: Novice
.170
• Outpatient data set:
.081
Time (Minutes)
0:26
0:24
0:22
0:20
0:18
0:16
0:15
0:13
0:11
0:09
0:07
0:05
0:04
0:02
0:00
BP, HR, SaO2
PGA Data
200
150
HR
100
SBP
DBP
50
SaO2
0
Time (Minutes)
0:27
0:25
0:23
0:21
0:19
0:17
0:15
0:13
0:11
0:09
0:07
0:06
0:04
0:02
0:00
BP, HR, SaO2
PGY2 Data
200
150
HR
100
SBP
DBP
50
SaO2
0
Time (Minutes)
0:25
0:23
0:22
0:20
0:18
0:16
0:14
0:12
0:11
0:09
0:07
0:05
0:03
0:01
0:00
BP, HR, SaO2
Novice Data
200
150
HR
100
SBP
DBP
50
SaO2
0
Conclusion
• The human patient simulator may be
used as a testing device to do interindividual comparison of anesthetist
response to simulated stresses during
anesthetic procedures.
• A simple measure of competency of
intervention may be derived by a “time
out of range” measure as discussed
here.
Thank you for your attention,
from Dr. King & patient…
Questions?