6 Role of PAT Nurse.ppt - The University of Vermontkappatau/images/6 Role of PAT Nurse.pdf ·...

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Optimizing Patients for Surgery Optimizing Patients for Surgery Rl f th PAT i i Rl f th PAT i i Role of the PAT nurse in assessing Role of the PAT nurse in assessing patient risk patient risk Tanya Cowder, RN, CNS Sue Burns, RN Avis Hayden, PhD

Transcript of 6 Role of PAT Nurse.ppt - The University of Vermontkappatau/images/6 Role of PAT Nurse.pdf ·...

Optimizing Patients for SurgeryOptimizing Patients for Surgery

R l f th PAT i iR l f th PAT i iRole of the PAT nurse in assessing Role of the PAT nurse in assessing patient riskpatient risk

Tanya Cowder, RN, CNSSue Burns, RN

Avis Hayden, PhDy ,

PAT:  Pre‐Anesthesia 

Teaching

Southwestern Vermont Medical C tCenter

•3,100 surgeries per year•35 surgeons 2 PAT nurses•35 surgeons, 2 PAT nurses•80% ambulatory care; 20% inpatient•Physician affiliation DHMC

Objectives for Today:Objectives for Today:

•Factors leading to change•Factors leading to change•Key elements of new processy p•Expanded role of PAT nurse•Outcomes, data•Next steps•Next steps

Frank’s StoryFrank s Story

InterviewsInterviews•Chief Medical Officer•Patient Safety Specialist•Anesthesiologists•Anesthesiologists•Internists & PCP’s•Surgeons•Nurses•Nurses•Support Staffpp

Challenge #1:Challenge #1:

RISK IDENTIFICATION NOT RELIABLE

••Not well definedNot well defined

••No double checkNo double checkNo double checkNo double check

80% cases identified(too low)

Sample of 128 elective cases Mar, Apr 2011

Challenge #2:Challenge #2:

Q ti bl lQ ti bl lHIGH RISK PATIENTSDID NOT RELIABLY GET MEDICAL EVAL

••Questionable valueQuestionable value

••Not enough timeNot enough timeGET MEDICAL EVAL

••Unclear expectationsUnclear expectations

75% got evaluation(too low)

Sample of 128 elective cases Mar, Apr 2011

Challenge #3:Challenge #3:

HIGH RISK PATIENTS UNDERIDENTIFIED

••Identification not Identification not reliablereliable

••If missed, not detectedIf missed, not detected

Only 9.8% identified (too low)

Data from earlier phase of project, collected 2009

Summary:Summary: Develop reliable process for:Develop reliable process for:

Ri k id tifi ti•Risk identification

•Medical evaluation

•FOCUS: Timely flow of i f tiinformation

Change #1: Define High RiskChange #1: Define High Risk

• Polypharmacy (7 +)• Polypharmacy (7 +) • Active cardiac disease • Poorly controlled hypertension• Diabetes requiring medication• Diabetes requiring medication• Sleep apnea• Anticoagulation• If clinical intuition raises the• If clinical intuition raises the

question

Change #2: Booking ReportChange #2: Booking Report

DATE OF  DATE OF SURGERYREPORT

BOOKINGREPORT

RN VERIFY risk category

RN & Anesthesia UPGRADERN & Anesthesia UPGRADErisk category based on assessment

of patient history

Change #3: Medical EvalChange #3: Medical Eval

•HIGH RISK

•NORMAL RISK•NORMAL RISK

Change #4: Clinical InformationChange #4: Clinical Information

Orders, Consent, H&P

Assemble chart

Change #5: Medical EvalChange #5: Medical Eval

M di l bl• Medical problems• Medication list• Would delaying the procedure allow to better control any of theallow to better control any of the following:

H A1C 7• HgA1C over 7• Poorly controlled hypertension or heart disease• Active infections• Sleep apnea• Anticoagulant therapy

Change #6: Booking ScriptChange #6: Booking Script

•Urgent?•Urgent? Elective?

•High Risk? Normal Risk?Normal Risk?

•If High Risk, gname of PCP

Change # 7: Booking Window•High Risk PatientsHigh Risk Patients

Optimal interval 14 days

All Oth P ti t•All Other Patients Minimal interval -- 7 days

Change #8: FeedbackC a ge #8 eedbac

Risk Factors

AnesthesiaSignatures

Methods & ToolsMethods & Tools

•Process maps•Algorithms•Data

Process MapsProcess Maps

Decision for

surgery

Complete risk form

Call OR to schedule case;

(risk score)

Complete H&P, consent, orders

Fax to PAT

Schedule PAT appt< 5

Schedule medical evaluation with PCP or specialist

> 5

Decision AlgorithmDecision AlgorithmDECISION TO PERFORM SURGERY

URGENT OR "ADD ON" ELECTIVE

Based on medical need

Booking < 7 days

Requires call to anesthesia

NORMAL RISK HIGH RISK

Based on assessment of i di l di i

Based on assessment of patients medical conditionanesthesia patients medical condition patients medical condition

Medical Evaluation Completed?

NO NO

Booking > 7 days

Allow time for Anesthesia,

RECOMMENDED BOOKING INTERVAL

Booking > 14 daysYES

Allow time for Anesthesia,

RECOMMENDED BOOKING INTERVAL

,PAT review PAT review & medical

evaluation

Booking < 14 days

Short Notice or Convenience

Booking < 7 days

Short Notice or Convenience

Booking < 7 days

Exceptions: ESWL, Dental, Short Notice or ConvenienceBooking

Condenses time for Anesthesia, PAT review

Condenses time for Anesthesia, PAT review

Short Notice or Convenience BookingPort-A-Cath, Pacemakers,

ENT cases < 16 yo

Condenses time for Anesthesia, PAT review

Challenge #1Challenge #1

RISK IDENTIFICATION NOT RELIABLE

SIMPLIFYDEFINITIONS, GIVE FEEDBACK

100% cases identified(88% surgeon, 12% PAT nurse)

80% cases identified(too low)

Sample of 128 elective cases Mar, Apr 2011; project data 2012.

)

1.2UCL=1.129

Hit or Miss FAX

Patient Risk Identification, Surgeons

1.0

0.8

_X=0.88

77%

0.6

0.4

Rat

e LCL=0.63477%

0.2

0.0

14-S

ep

17-A

ug20

-Jul

22-Ju

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25-M

ay

27-A

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30-M

ar2-M

ar3-

Feb

6-Jan

9-De

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11-N

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Week Ending

Challenge #2:Challenge #2:

HIGH RISK PATIENTSDID NOT RELIABLY GET MEDICAL EVAL

WORKFLOW CHANGE“HARD STOP”

GET MEDICAL EVAL

100% got evaluation75% got evaluation(too low)

Sample of 128 elective cases Mar, Apr 2011; project data 2012

Challenge #3Challenge #3

HIGH RISK PATIENTS UNDERIDENTIFIED

RELIABLE PROCESS CLEAR EXPECTATIONS

Now 26% identifiedOnly 9.8% identified (too low)

Data from earlier project collected 2009; new project data 2012

1.0 EXISTING NEW

Proportion of High Risk Patients Identified in our Surgical Population

0.8

0 60.6

0.4

Perc

ent

_X=0 26

UCL=0.451

18%

0.2

0.0

X=0.26

LCL=0.071

14-S

ep

17-A

ug20

-Jul

22-Ju

n

25-M

ay

27-A

pr

30-M

ar2-M

ar3-

Feb

6-Jan

9-De

c

11-N

ov

Week Endingg

Optimizing Patients for SurgerySurviellance of High Risk Patients

Comparison 2009 and 2012

1600

1400

1200 CASES MISSED high risk 26%

1000

800

Case

s normal risk

high risk 9.8%

normal risk

600

400

200

Year 2012 (n=1431)2009 (n=1338)

200

0

Data Sources: PICIS Booking Data/Loomis/Reed

Issues Still to be Addressed:Issues Still to be Addressed:

• ClinicalClinical• Anticoagulation **• Beta blockersBeta blockers• Poorly controlled diabetes• Sleep apnea **• Obesity

• Process• Post op co-management• Short notice booking

SummarySummary

• Identified a problem•Identified a problem•Interviewed key stakeholders•Reviewed literature•Developed a new process•Developed a new process•Used data to keep the process on track

•After 1 yr – reliable processAfter 1 yr reliable process

Questions Contact emails:[email protected]@phin.orgy @p g