Limitations on cross-correlations of single indicators: The case for

a WHA clinical outcomes (unit-record) database.

Peter BaghurstPublic Health Research Unit

Women’s and Children’s HospitalWomen’s and Children’s Healthcare Network

North Adelaide, South Australia

percent epidurals in all vaginal births (2009-10)

pe

rce

nt

inst

rum

en

tals

in v

ag

ina

l bir

ths

in a

ll w

om

en

10 20 30 40

10

15

20

25

22

47

11

33

49

2593

35

31

4319

27

307

18

52

42

55

29

56

32

5763

48

5962

Spearman's r = 0.72, p = 0.00024

percent inductions in selected primiparous women (2009-10)

pe

rce

nt

cae

sare

an

se

ctio

n in

se

lect

ed

pri

mip

aro

us

wo

me

n

15 20 25 30 35 40

20

25

30

22

19

43

33

31

9

11

27

35

3

18

49

7

25

30

5763

52

42

62

55

21

56

32

48 29

59Spearman's r = 0.17, p = 0.38

percent women requiring instrumental assistance for a vaginal birth (2009-10)

% w

om

en

giv

ing

bir

th b

y C

ae

sare

an

se

ctio

n

10 15 20 25

20

25

30

35

22

47

11

33

31 9

3

25

18

35

30

7

49

271943

55 56

485257

63

292142

59

62

32

Spearman's r = 0.66, p = 0.00065

percent epidurals in all vaginal births (2009-10)

Po

st-p

art

um

ha

em

orr

ha

ge

(1

50

0+

ml)

fo

llow

ing

va

gin

al b

irth

10 20 30 40

0.5

1.0

1.5

2.0

2.5

3.0

22

47

11

33

49

25

9

335

31

43

19

27

30

7

18

52

42

29

32

57

63

48

59

62

Spearman's r = 0.56, p = 0.0061

Epidurals and PPH within one hospital

13,778 vaginal births with PPH volumes at Women’s and Children’s Hospital

No severe PPH

PPH > 1500 mls

No epidural in labour

98.09% 1.91%

Epidural 98.06% 1.99%

No significant risk associated with epidural use (Odds ratio=1.05, p = 0.70) – and after adjusting for known risk factors, the Odds Ratio fell to 0.80, (p = 0.14).

No PPH PPH > 500 mls

No epidural in labour

86.2% 13.8%

Epidural 81.9% 18.1%

Highly significant increased risk,Odds ratio 1.38, (p < 0.001) – but after adjustment the Odds Ratio fell to 0.91, (p = 0.10).

% third and fourth degree tears in SABy parity and epidural use

Parity

Epidural use Nulliparous Parous

no 4.14 0.89

yes 6.02 1.30

By instrument assistance, parity and epidural use

Instrument assistance

Not required Forceps assistance Vacuum assistance

Epidural use Nulliparous Parous Nulliparous Parous Nulliparous Parous

No 3.1 0.8 15.2 6.8 7.0 3.2

Yes 2.8 0.7 12.5 5.4 5.3 2.3

Epidural use is associated with increased perineal trauma

Epidural use is associated with less perineal trauma in all groups!!(But we needed data on individual women to construct this table)

Is stratification (selected primiparas) enough?

• Recall a selected primip is a woman giving birth– For the first time– At term (with vertex presentation)– Aged 20-34 years

• We examine outcomes in this group under the assumption that these women are more homogeneous with res[pect to their risk of particular outcomes

• But…. If we look at, say, severe perineal tears in selected primips, the probability of a tear may vary from less than 1% in a Caucasian woman giving birth spontaneously to a 2200g baby; to 50% in a Chinese woman having a 4200g baby and requiring assistance with forceps

• Also……selected primips comprise only 25% of the obstetric population. Shouldn’t we be paying more attention to the others?

The message…

• Cross-correlation of single clinical indicators is interesting – but interpretation is severely restricted – because most clinical outcomes are determined by multiple ‘risk’ factors.

• In order to compare hospital-outcomes fairly, we need to adjust for major risk factors – and this requires access to data on individual women (some times referred to as “unit-record” data).

How might it work?• Member hospitals would send de-identified data files

(e.g., Excel spreadsheets, in which each row contained data-items on every individual in their care over the past twelve months) - to WHA. – If neonatal outcomes are held in separate file – two files would

have to be uploaded

• A data analyst at WHA, in consultation with each member hospital) would pre-process these files to extract and compute common items required for the construction of clinical indicators (i.e., there would be NO demand for the uploaded data to be in a common format!)

• Clinical indicators would be generated for all members at WHA. (No more having to do it yourself!)

Advantages

• Current WHA indicators could be automatically calculated from such a database (no more pestering from me!)

• The database would become an extremely useful research tool for studies approved by WHA members

• This could well attract research funding

Potential problems

• AIHW is currently considering establishing a national database. The list of data items currently proposed is huge – and it might take many years – and a lot of good will - for all hospitals to collect data in a standardised format.

• Overlap with local jurisdictional data collections?