PEDIATRIC TRAUMA ASSESSMENT AND MANAGEMENT DATABASEA TRAUMA REGISTRY-VPS PARTNERSHIP

VPS User Conference| March 24-26, 2015

Katherine T. Flynn-O’Brien, MDMary E. Fallat, MDTom B. Rice, MDChristine M. Gall, RN, MS, DrPHFrederick P. Rivara, MD

Outline

Motivation What we did How we did it What we discovered

I. More data (and better data)II. Risk-adjustment modeling III. Processes of care

Brainstorming

Motivation

Limited ability to study pediatric trauma NTDB / Pediatric TQIP Virtual Pediatric ICU Systems (VPS)

UDSMR, HCUP, PHIS, MarketScan

Objective

Create a comprehensive pediatric trauma database to assess quality of

care in critically injured children utilizing minimal new resources.

Methods

Merged 3 databases Trauma Registry

(TR) Virtual PICU Systems

(VPS) data PTAM-specific

RedCap 5 Level I/II PTC All children

discharged from PICU CY 2013

Process

PTAM

Trauma

Registry

(local export)

VPS(central export)

Additional

data eleme

nts(data entry)

95.5% match

Additional variables

C-spine clearance

Hgb prior to transfusion

FAST

Alcohol screening & counseling

(TQIP variables)

All CT scans

ICPM placement

Mech. VTE proph.

Lab upon arrival

Initiation of feeds

Bowel regimen

Breadth & depth

I. More data | Better data

Care continuum

Pre-hospital

ED PICU Floor Discharge

You are here.

Care continuum

• Vitals• GCS• Transfer

Pre-hospital

• Vitals• GCS• Labs*

ED arrival

• Disposition• LOS

Discharge

Care continuum

Variable Pre-hospital

ED PICU Floor

GCS X X X (X)

Pulse X X XX

Blood Pressure

X X XX

Hemoglobin XX XX

Base Deficit X X

AST X X

ALT X X

Hypoxemia X X

PT/PTT X X

CT scans X X X X

Care continuum

Variable Pre-hospital

ED PICU Floor

GCS X X X (X)

Pulse X X XX

Blood Pressure

X X XX

Hemoglobin XX XX

Base Deficit X X

AST X X

ALT X X

Hypoxemia X X

PT/PTT X X

CT scans X X X X

Care continuum

Variable Pre-hospital

ED PICU Floor

GCS X X X (X)

Pulse X X XX

Blood Pressure

X X XX

Hemoglobin XX XX

Base Deficit X X

AST X X

ALT X X

Hypoxemia X X

PT/PTT X X

CT scans X X X X

Care Continuum

What is the child’s cognitive/physiologic status immediately after injury?

What resuscitation is, or is not, occurring prior to ICU arrival?

How may this information change management in the ICU?

More data

Better data

Complications Cardiac arrest CLABSI Unplanned

return to the ICU

Pneumonia Re-intubation

Better data

Complications Cardiac arrest CLABSI Unplanned

return to the ICU

Pneumonia Re-intubation

4 37

Better data

Complications Cardiac arrest CLABSI Unplanned

return to the ICU

Pneumonia Re-intubation

1 2

Better data

Complications Cardiac arrest CLABSI Unplanned

return to the ICU

Pneumonia Re-intubation

3 14

Better data

Complications Cardiac arrest CLABSI Unplanned

return to the ICU

Pneumonia Re-intubation

5 5

Better data

Complications Cardiac arrest CLABSI Unplanned

return to the ICU

Pneumonia Re-intubation

0 20

Better data

Comorbidities Hx of CVA Prematurity Respiratory

distress

Better data

Comorbidities Hx of CVA Prematurity Respiratory

distress1 1

Better data

Comorbidities Hx of CVA Prematurity Respiratory

distress6 18

Better data

Comorbidities Hx of CVA Prematurity Respiratory

distress4 14

II. Risk adjustment modeling

Mortality

Model building Model diagnostics Multiple

imputation

PIM2 PRISM3 PELOD

Trauma Registry VPS

Mortality

Model AUC R2 value AIC

TR-only 0.9360 0.5286 127.57VPS-only 0.9917 0.6723 95.84

TR-VPS 0.9776 0.6843 91.69TR-only covariates: age, mechanism of injury, transfer status, ED systolic blood pressure, ED pulse, ED GCS motor score, max head AIS, max extremity AIS, congenital comorbiditiesVPS-only: PIM2TR-VPS: TR model + VPS-PIM2 model

Mortality

P = .0165

0.0

00

.25

0.5

00

.75

1.0

0S

ens

itivi

ty

0.00 0.25 0.50 0.75 1.001-Specificity

TRTR+VPS

VPS

ROC by Data Source

Mortality

0.0

00

.25

0.5

00

.75

1.0

0S

ensi

tivity

0.00 0.25 0.50 0.75 1.001-Specificity

TRTR+VPS

VPS

ROC by Data Source

P = .0165

Mortality

VPS Can we appropriately risk adjust

without controlling for mechanism of injury? Injury severity?

Trauma Registry Can we do better? Can we improve

model fit? Improve accuracy? Efficiency?

PCPCPOPCPELODLength of hospital stayDischarge to home (vs. rehab)

Non-mortality outcomes

Hospital disposition

What factors are most strongly associated with (poor) functional

status?

What are predictors of discharge home?

What are predictors of discharge to a rehab facility?

III. Processes of Care

VTE prophylaxis0

200

400

600

mechvte_hrs dvt_hrs

Site A

Site B

Site C

Site D

Site E

More…

Nutrition management Parenteral Enteral

Daily bowel regimen C-spine clearance Alcohol and drug screening Alcohol counseling

Limitations

Non-mortality outcomes lack precision

No quality of life measures Limited generalizability

Scope

75+VPS institutions w/ trauma ~40% ACS trauma centers ~60% state trauma centers

50+ centers can immediately merge data

Hurdles

Pediatric Trauma Assessment and

Management Database

Conclusion

Combining databases is an innovative, feasible, cost-effective

way to evaluate management practices and to explore critical

questions related to pediatric trauma management.

Thank you

Special thanks to all trauma registrars and VPS coordinators at participating

sites

Challenges…

…are worth it

Thank you

Questions?

TRVPS

Patient Outcom

es

Discharge status Pre-

hospital data

Initial vitals GCS

Injury patterns

ProceduresBedside

procedures

Lab data

PIM2 PRISMIII PELOD

PCPC POPC

Predicted

LOS

Patient population

67 % male Mean age 7.2y

(6.0) Race/Ethnicity

51% White 21% African

American 7% Hispanic

Payer 35% Private 48% Medicaid/Gov.

Injury characteristics

Mechanism of injury 32% Falls 25% MVC 4% Penetrating

Intent 84% unintentional 14% assaults

Place 31% residential

Maximum Head AIS 15% AIS 4/5 43% AIS 3

Other max AIS 67% abd AIS 3-5 57% thoracic AIS 3-

5 Injury Severity

Score 13% ISS>25 22% ISS 16-25

TRTR

Pre-hospital & ED

Physiologic data 11%

tachycardia* 3% hypotension* 9% GCS <9

EMS transport 42% ambulance 14% air

Physiologic data 29%

tachycardia* 5%

hypotension* 17% GCS <9

ED disposition 14% OR

Transfer statusTRTR *Age-based

ICU first hr & first 12 hrs

SBP 10%

hypotension* Base excess

-5.2 (4.2) Pupil reaction PF ratio

VPS

Physiologic/lab data BP, HR, RR, temp,

pH PaO2, PaCO2 Hgb, WBC Plt, PT, PTT, bili K, Na, Ca, albumin,

BUN, Cr Ventilation data Infection data VPS

ICU course & outcomes

Baseline POPC 89% Normal 10% Mild/Mod 1% Severe

Discharge POPC 34% Normal 57% Mild/Mod 4% Severe/Coma 5% Brain Death

VPS

Intensivist (98%) 83% Concurrent

care 5% Consulting only 10% Primary service

PELOD baseline, daily, POD

PRISM3 PIM2

VPS

Hospital disposition

ICU Length of stay Mean 2.8 (SD

5.0) Median 1.1 (.6-

2.6) ICU disposition

69% floor, SDU 0.7% rehab 1.3% transferred

Hosp length of stay Mean 7.3 (SD

10.9) Median 4 (IQR 2-8)

Hosp disposition 82% home 11% rehab 2% transferred

VPSTR