P EDIATRIC T RAUMA A SSESSMENT AND M ANAGEMENT DATABASE A TRAUMA REGISTRY-VPS PARTNERSHIP

Katherine T. Flynn-O’Brien, MD Mary E. Fallat, MD Tom B. Rice, MD Christine M. Gall, RN, MS, DrPH Frederick P. Rivara, MD

VPS User Conference| March 24-26, 2015

Outline

     Motivation What we did How we did it I.

What we discovered II.

III.

More data (and better data) Risk-adjustment modeling 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

Trauma Registry

(local export)

VPS

(central export)

PTAM Additional data elements

(data entry)

95.5% match

Additional variables

 All CT scans  ICPM placement  Mech. VTE proph.

 Lab upon arrival  Initiation of feeds  Bowel regimen  C-spine clearance  Hgb prior to transfusion  FAST  Alcohol screening & counseling  (TQIP variables)

I. More data | Better data

Breadth & depth

Care continuum

Pre-hospital ED PICU You are here.

Floor Discharge

Care continuum

• Vitals • GCS • Transfer

Pre hospital ED arrival

• Vitals • GCS • Labs* • Vitals • Labs • Vent data

ICU stay Floor

• Nutrition • Constipation • VTE ppx • Disposition • LOS

Discharge

Care continuum

Variable

GCS Pulse Blood Pressure Hemoglobin Base Deficit AST ALT Hypoxemia PT/PTT CT scans

Pre-hospital X X X X ED X X X X X X X XX X X PICU X X X X X XX XX XX X X Floor (X) X

Care continuum

Variable

GCS Pulse Blood Pressure Hemoglobin Base Deficit AST ALT Hypoxemia PT/PTT CT scans

Pre-hospital X X X X ED X X X X X X X XX X X PICU X X X X X XX XX XX X X Floor (X) X

Care continuum

Variable

GCS Pulse Blood Pressure Hemoglobin Base Deficit AST ALT Hypoxemia PT/PTT CT scans

Pre-hospital X X X X ED X X X X X X X XX X X PICU X X X X X XX XX XX X X Floor (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 distress

1 1

Better data

 Comorbidities  Hx of CVA   Prematurity Respiratory distress

6 18

Better data

 Comorbidities  Hx of CVA   Prematurity Respiratory distress

4 14

II. Risk adjustment modeling

Mortality

Trauma Registry

 Model building  Model diagnostics  Multiple imputation  PIM2  PRISM3  PELOD

VPS

Mortality

Model AUC R 2 value AIC TR-only VPS-only

0.9360

0.9917

0.5286

0.6723

127.57

95.84

TR-VPS

0.9776

0.6843

91.69

TR-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 comorbidities VPS-only: PIM2 TR-VPS: TR model + VPS-PIM2 model

Mortality

ROC by Data Source 0.00

P = .0165

0.25

TR TR+VPS 0.50

1-Specificity VPS 0.75

1.00

Mortality

ROC by Data Source 0.00

P = .0165

0.25

TR TR+VPS 0.50

1-Specificity VPS 0.75

1.00

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?

Non-mortality outcomes

PCPC POPC PELOD Length of hospital stay Discharge to home (vs. rehab)

Hospital disposition

What are predictors of discharge home? What are predictors of discharge to a rehab facility?

What factors are most strongly associated with (poor) functional status?

III. Processes of Care

VTE prophylaxis Site A Site B Site C Site D Site E mechvte_hrs dvt_hrs

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?

VPS Predicted LOS PCPC POPC PIM2 PRISMIII PELOD Lab data Discharge status Pre-hospital data Initial vitals GCS Patient Outcomes Injury patterns Procedures Bedside procedures TR

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 

TR

 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

TR

Pre-hospital & ED

  Physiologic data  11% tachycardia*  3% hypotension*  9% GCS <9 EMS transport  42% ambulance  14% air

TR

*Age-based    Physiologic data  29% tachycardia*   5% hypotension* 17% GCS <9 ED disposition  14% OR Transfer status

TR

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 P a O2, P a CO2 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        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

TR

  Hosp length of stay   Mean 7.3 (SD 10.9) Median 4 (IQR 2-8)    Hosp disposition 82% home 11% rehab 2% transferred

VPS