A Proposed Method for the Measurement of Anesthetist Care Variability

A Proposed Method for the Measurement of Anesthetist Care VariabilityPaul 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 VariabilityPaul 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

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





Results: Fraction out of range – Diastolic Blood Pressure





Results: Fraction out of range – Pulse Oximeter Data





PGA Data

0

50

100

150

2000:

00

0:02

0:04

0:05

0:07

0:09

0:11

0:13

0:15

0:16

0:18

0:20

0:22

0:24

0:26

Time (Minutes)

BP

, H

R,

SaO

2

HR

SBP

DBP

SaO2

PGY2 Data

0

50

100

150

2000:

00

0:02

0:04

0:06

0:07

0:09

0:11

0:13

0:15

0:17

0:19

0:21

0:23

0:25

0:27

Time (Minutes)

BP

, H

R,

SaO

2

HR

SBP

DBP

SaO2

Novice Data

0

50

100

150

2000:

00

0:01

0:03

0:05

0:07

0:09

0:11

0:12

0:14

0:16

0:18

0:20

0:22

0:23

0:25

Time (Minutes)

BP

, H

R,

SaO

2

HR

SBP

DBP

SaO2

Conclusion

• The human patient simulator may be used as a testing device to do inter-individual 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?

A Proposed Method for the Measurement of Anesthetist Care Variability

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