HASA Presentation 20080609 - HASA Conference FINAL USE

7/31/2019 HASA Presentation 20080609 - HASA Conference FINAL USE

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1 2008 Deloitte Touche TohmatsuHASA NHRPL 2009

Exploring the HealthcarePrice Tag

Research on Private Hospitals.

Actuarial & Insurance Solutions

Ashleigh Theophanides

12 June 2008


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Overview of analysis

Private hospital building composition

Nurse staffing

Length of stay wards and theatres

Occupancy wards and theatres

Generalised Linear Modelling

Agenda


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Methodology Overview

Land and building

Surgicalward ICU Major theatre

Medical equipment

Overhead expenses

Staffingnursing and administrative

Working capital

Occupancy

Assets

Expenses


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Methodology Overview

Land and building

Surgical ICU Theatre

Medical equipment

Working capital

Assets

Ward

Theatre

Equipment U 3

U 2

U 1 Revenue

ROI

Target

Profit

M 3

M 2

M 1

Operating expenses


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Sample: 83% of private multi-disciplinary hospital beds

Distribution of hospitals by number of beds


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Distribution of beds and space per bed (m2)

0%

5%

10%

15%

20%

25%

30%

35%

0

5

10

15

20

25

30

35

40

45

Surgical

Medical

Paedia

tric

D

ay

ICU

Neonatal

HighCare

Matern

ity

Spaceperbed(m2)

Average hospital composition

Space per bed (m2) Percentage of beds


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Distribution of theatres

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2 76%

Females All ages 76%

Ages < 70 97%

Ages > 2 75%

Overall All ages 72%

Ages < 70 98%

Ages > 2 71%


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Length of stay Theatres by day of week

Week day Average time Average age Distribution

Monday 61.2 41.6 18.2%

Tuesday 61.1 41.8 20.1%

Wednesday 61.0 41.5 19.4%

Thursday 59.8 41.0 20.1%

Friday 57.3 38.8 16.5%

Saturday 67.9 37.1 3.9%

Sunday 71.4 37.2 1.8%Total 60.7 40.8 100.0%

Major Theatre Minutes - 2006

Week day Average time Average age Distribution

Monday 61.3 42.1 18.2%

Tuesday 61.4 41.9 19.8%

Wednesday60.6 41.6 19.7%

Thursday 59.3 40.9 20.2%

Friday 56.6 39.0 16.5%

Saturday 67.5 37.3 3.7%

Sunday 70.7 37.1 1.9%

Total 60.4 40.9 100%

Major Theatre Minutes - 2007


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Distribution of cases by month of year

Length of stay Theatres by month of year

8.2%8.7%

9.2%

7.5%

9.1% 8.7% 8.8% 8.8%

7.8%

8.9% 8.8%

5.6%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

January

February

March

April

May

June

July

August

September

October

November

December

Avgtimeinm

ins

Distribution of cases in major theatre per month - 2006 vs 2007

2006 2007


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Length of stay Impact of RVUs

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

00.0-01.5

01.5-03.0

03.0-04.5

04.5-06.0

06.0-07.5

07.5-09.0

09.0-10.5

10.5-12.0

12.0-13.5

13.5-15.0

15.0-16.5

16.5-18.0

18.0-19.5

19.5-21.0

21.0-22.5

22.5-24.0

24.0-25.5

25.5-27.0

27.0-28.5

28.5-30.0

30.0-31.5

31.5-33.0

33.0+

NoRVU

Averagetheatretime(minutes)

Relative Value Units (RVU)

Averrage theatre time by RVU


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Length of stay Theatres by age

0

10

20

30

40

50

60

70

80

90

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 106

Averagetimeintheatre(minutes)

Age

Average theatre time by age

Major


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GLM is a form of regression, which takes account of the effect of several different

factors at once.

It assumes an underlying structure for the relationship between the variable weare trying to model (e.g. average claims experience) - the response ordependant variable- and the factors that affect it (e.g. age, gender, number ofchronic conditions etc).

Formula 1:Response variable = k x ffactor 1 x ffactor 2 x x ffactor n + e

Where k is a constant and ffactor n is a parameter which depends on the level offactor i (so if factor i is age, then ffactor i might be something like 0.8 if age < 35,1.00 if 35 age< 50 and 1.25 otherwise).

The factor e allows for statistical variability and is called the error term. In the

modelling, various statistical distributions are fitted to the error term with the aimof minimising such variability.

Generalised Linear Modelling - Introduction


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Generalised Linear Modelling Results All Wards

Estimate Lower CI (5%) Upper CI (95%)

2.013 2.003 2.023

Age band Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

A: Under 1 3.7% 1.836 1.825 1.846

B: 01-04 6.5% 0.823 0.818 0.828

C: 05-09 3.5% 0.745 0.740 0.751

D: 10-14 2.5% 0.834 0.827 0.842

E: 15-19 4.1% 0.831 0.826 0.837

F: 20-24 5.5% 0.887 0.881 0.892

G: 25-29 7.8% 0.950 0.945 0.955H: 30-34 9.7% 1.000 1.000 1.000

I: 35-39 9.0% 1.043 1.038 1.048

J: 40-44 7.6% 1.066 1.061 1.072

K: 45-49 7.2% 1.061 1.055 1.066

L: 50-54 6.5% 1.040 1.034 1.046

M: 55-59 6.1% 1.022 1.016 1.028

N: 60-64 5.3% 1.031 1.025 1.037

O: 65-69 4.6% 1.057 1.051 1.063

P: 70-74 3.8% 1.112 1.105 1.118

Q: 75-79 3.0% 1.174 1.167 1.182

R: 80-84 1.9% 1.230 1.221 1.239

S: 85+ 1.3% 1.362 1.350 1.373

1.029 1.024 1.035

Intercept

Age Results

Exposure weighted factor


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No of Proceduires Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimateA: 0 32.5% 1.340 1.336 1.344

B: 1 33.6% 1.000 1.000 1.000

C: 2 17.5% 1.042 1.039 1.046

D: 3 7.9% 1.199 1.194 1.204

E: 4 4.0% 1.381 1.373 1.388

F: 5 2.0% 1.592 1.582 1.602

G: 6 1.0% 1.845 1.831 1.860

H: 7 0.6% 2.088 2.069 2.108

J: 8 0.3% 2.448 2.420 2.476

K: 9 0.2% 2.351 2.321 2.382

L: 10 0.1% 3.124 3.073 3.177

M: 10+ 0.2% 4.582 4.542 4.623

1.193 1.190 1.197

No of ICD10 Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

A: 0 0.1% 0.602 0.567 0.638

B: 1 50.1% 1.000 1.000 1.000

C: 2 26.7% 1.305 1.301 1.308

D: 3 12.5% 1.626 1.621 1.631

E: 4 5.5% 1.932 1.925 1.940F: 5 2.5% 2.319 2.307 2.331

G: 6 1.2% 2.663 2.646 2.681

H: 7 0.6% 3.095 3.069 3.121

J: 8 0.3% 3.543 3.507 3.580

K: 9 0.2% 3.924 3.874 3.974

L: 10 0.1% 3.543 3.488 3.599

M: 10+ 0.2% 5.258 5.205 5.311

1.300 1.297 1.303

Procedures Results


ICD10 Results



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Weekday Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

Monday 19.0% 1.000 1.000 1.000

Tuesday 18.6% 0.954 0.951 0.957

Wednesday 17.7% 0.943 0.940 0.947

Thursday 17.8% 0.933 0.930 0.937

Friday 15.1% 0.967 0.963 0.970

Saturday 6.3% 1.091 1.086 1.095

Sunday 5.5% 1.123 1.118 1.128

0.977 0.974 0.980

Year Patient distribution Risk factorestimate

Risk factorLower CI estimate

Risk factorUpper CI estimate

2006 49.2% 1.023 1.021 1.025

2007 50.8% 1.000 1.000 1.000

1.011 1.010 1.012

Gender Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

Female 56.5% 1.000 1.000 1.000

Male 43.5% 1.011 1.009 1.013

1.005 1.004 1.006

Maternity indicators Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

No 93.7% 1.000 1.000 1.000

Yes 6.3% 1.085 1.079 1.090

1.005 1.005 1.006

Exposure weighted factorMaternity Results


Weekday Results



Gender results

Year results


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Ward Factors

Exposure we g te

factor

No of ICD10 1.300

No of Proceduires 1.193

Age band1.029

Year 1.011

Maternity indicators 1.005

Gender 1.005

Weekday 0.977


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Generalised Linear Modelling Results Theatres

Estimate Lower CI (5%) Upper CI (95%)

27.296 27.168 27.425

Age band Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

A: Under 1 1.0% 0.938 0.929 0.948

B: 01-04 4.9% 0.882 0.877 0.887

C: 05-09 3.6% 0.925 0.920 0.931

D: 10-14 2.6% 0.982 0.976 0.988

E: 15-19 4.4% 0.970 0.965 0.975

F: 20-24 5.8% 0.971 0.967 0.976

G: 25-29 8.2% 0.988 0.984 0.992H: 30-34 10.4% 1.000 1.000 1.000

I: 35-39 9.9% 1.007 1.003 1.011

J: 40-44 8.3% 1.009 1.005 1.013

K: 45-49 7.7% 1.018 1.014 1.022

L: 50-54 7.0% 1.021 1.017 1.025

M: 55-59 6.6% 1.028 1.024 1.032

N: 60-64 5.8% 1.022 1.017 1.026

O: 65-69 4.9% 1.007 1.002 1.011

P: 70-74 3.8% 0.983 0.978 0.988

Q: 75-79 2.8% 0.950 0.945 0.956

R: 80-84 1.6% 0.911 0.904 0.917S: 85+ 0.8% 0.899 0.890 0.907

0.990 0.986 0.994

Intercept

Age Results



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No of Procedures Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

A: 0 7.1% 0.427 0.414 0.439

B: 1 45.0% 1.000 1.000 1.000

C: 2 25.7% 1.149 1.146 1.151

D: 3 11.1% 1.288 1.284 1.291

E: 4 5.3% 1.408 1.403 1.413

F: 5 2.6% 1.530 1.523 1.537

G: 6 1.3% 1.697 1.687 1.707

H: 7 0.7% 1.837 1.824 1.850

J: 8 0.4% 1.935 1.917 1.953

K: 9 0.2% 2.070 2.047 2.093

L: 10 0.2% 1.953 1.929 1.977M: 10+ 0.3% 2.636 2.615 2.658

1.093 1.091 1.096

No of ICD10 Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

A: 0 0.1% 1.026 0.988 1.067

B: 1 54.9% 1.000 1.000 1.000

C: 2 25.0% 1.059 1.056 1.061

D: 3 11.4% 1.085 1.082 1.088

E: 4 4.6% 1.138 1.133 1.142

F: 5 2.0% 1.187 1.181 1.193G: 6 0.9% 1.206 1.198 1.215

H: 7 0.5% 1.261 1.249 1.273

J: 8 0.3% 1.304 1.288 1.320

K: 9 0.2% 1.320 1.300 1.340

L: 10 0.1% 1.189 1.170 1.207

M: 10+ 0.2% 1.406 1.389 1.422

1.040 1.038 1.041

ICD10 Results

Procedures Results




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Weekday Patient distribution Risk factorestimate

Risk factorLower CI estimate

Risk factorUpper CI estimate

Monday 19.0% 1.010 1.008 1.013

Tuesday 20.0% 1.000 1.000 1.000

Wednesday 19.3% 1.007 1.005 1.010

Thursday 19.4% 0.995 0.992 0.997

Friday 16.1% 0.988 0.985 0.991

Saturday 3.7% 1.072 1.067 1.077

Sunday 2.6% 1.113 1.107 1.118

1.006 1.004 1.008

Year Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

2006 49.5% 1.007 1.005 1.008

2007 50.5% 1.000 1.000 1.000

1.003 1.002 1.004

Gender Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

Female 57.2% 1.000 1.000 1.000

Male 42.8% 1.052 1.050 1.054

1.022 1.021 1.023

Maternity indicators Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate

No 93.0% 1.000 1.000 1.000

Yes 7.0% 0.629 0.626 0.633

0.974 0.974 0.974




Weekday Results

Maternity Results

Year results

Gender results



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RVU band Patient distribution

Risk factor

estimate

Risk factor

Lower CI estimate

Risk factor

Upper CI estimate0 3.2% 1.657 1.647 1.666

000 - 001.5 0.6% 1.677 1.660 1.695

001.5 - 003 5.9% 1.007 1.001 1.013

003 - 004.5 4.6% 1.021 1.014 1.027

004.5 - 006 4.9% 1.195 1.188 1.202

006 - 007.5 4.9% 1.147 1.140 1.153

007.5 - 009 13.4% 1.000 1.000 1.000

009 - 010.5 5.5% 1.188 1.181 1.194

010.5 - 012 3.9% 1.493 1.484 1.501

012 - 013.5 3.7% 1.574 1.565 1.583

013.5 - 015 3.4% 1.459 1.451 1.468

015 - 016.5 3.9% 1.477 1.469 1.485

016.5 - 018 4.8% 1.868 1.859 1.877

018 - 019.5 5.2% 1.766 1.758 1.775

019.5 - 021 1.9% 2.371 2.357 2.385

021 - 022.5 2.9% 2.145 2.133 2.157

022.5 - 024 1.3% 2.342 2.325 2.358

024 - 025.5 8.0% 2.639 2.626 2.653

025.5 - 027 0.8% 2.708 2.686 2.729

027 - 028.5 1.2% 3.024 3.004 3.044

028.5 - 030 1.2% 3.061 3.041 3.081030 - 031.5 0.7% 3.182 3.158 3.207

031.5 - 032 0.6% 3.367 3.340 3.395

033+ 4.6% 4.052 4.035 4.069

BLANK_CPT 6.8% 4.562 4.431 4.697

NO MATCH 1.8% 1.682 1.669 1.694

1.907 1.890 1.924Exposure weighted factor

RVU band Results


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Summary of GLM factors

Theatre Factors

Exposure weighted

factor

RVU band 1.907

No of Procedures 1.093

No of ICD10 1.040

Gender 1.022

Weekday 1.006Year 1.003

Age band 0.990


Ward Factors

Exposure weighted

factorNo of ICD10 1.300

No of Proceduires 1.193

Age band 1.029

Year 1.011


Gender 1.005Weekday 0.977


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Ward and Theatre GLM factors by Age

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1.800

2.000

A:U

nder1

B:01-04

C

:05-09

D

:10-14

E:15-19

F:20-24

G

:25-29

H

:30-34

I:35-39

J

:40-44

K:45-49

L

:50-54

M:55-59

N

:60-64

O

:65-69

P:70-74

Q

:75-79

R

:80-84

S:85+

Riskfac

torestimate

Risk factor estimates by age

Theatre Ward


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Ward and Theatre GLM factors by Weekday

0.000

0.200

0.400

0.600

0.800

1.000

1.200

Mo

nday

Tue

sday

Wednesday

Thursday

F

riday

Saturday

Su

nday

Risk factor estimates by day of week

Theatre Ward


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Theatre GLM factors by RVU

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

4.500

0

000-001.5

001.5-

003

003-004.

5

004.5-

006

006-007.5

007.5-

009

009-010.5

010.5-

012

012-013.

5

013.5-

015

015-016.5

016.5-

018

018-019.

5

019.5-

021

021-022.5

022.5-

024

024-025.5

025.5-

027

027-028.

5

028.5-

030

030-031.5

031.5-

033

033+

Riskfactorsestimate

RVU band

GLM factors by RVU

Consolidated


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Increase in occupancy from 62.09% to 64.52% between 2006 and 2007

Reason for the increase in occupancy?

Analysis of change in Occupancy

Utilisation Length of stay

1.91% 0.52%

Driven by changes in disease

profiles among those with 2 or

more ICD10s


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Documents

HASA Presentation 20080609 - HASA Conference FINAL USE