Medical Workforce Supply Estimates (MWSE)
Col White
and
Chris Mitchell
Queensland Rural Medical Support Agency
Queensland Rural Medical Support Agency 2002
This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no
part may be reproduced without prior written permission from the Queensland Rural Medical
Support Agency. Requests and enquiries concerning reproduction and rights should be
directed to the Queensland Rural Medical Support Agency, PO Box 167, Kelvin Grove DC,
Qld 4067.
Suggested citation
White, C., & Mitchell, C. (2002). Medical workforce supply estimates (MWSE). Paper
presented at the ARRWAG Third National Conference Rural and Remote Health, Adelaide.
Medical Workforce Supply Estimates (MWSE)
The Medical Workforce Supply Estimates (MWSE) is a planning tool, refined by the
QRMSA, based on a methodology developed by the Australian Medical Workforce Advisory
Committee (AMWAC, 2000).
The AMWAC General Practice Workforce Working Party was established in 1999 and was
asked to provide a report to AMWAC on the optimal supply and appropriate distribution of
general practitioners across Australia, including projections of future supply requirements.
The Working Party presented a final report to AMWAC on 16th August 2000 and this report
was accepted by the Australian Health Ministers’ Advisory Council (AHMAC) at their
meeting on 19th October 2000.
The final report, The General Practice Workforce in Australia: Supply and Requirements
1999-2000 utilised two methodologies in developing the conclusions of the report. Firstly, a
needs based approach was used to determine GP workload. Secondly, a benchmark approach
was used to compare that workload across different geographic areas and access the adequacy
of GP supply.
The assumptions and data sources utilised by the AMWAC General Practice Workforce
Working Party are detailed in the report and are primarily based on whole patient equivalents
(WPE’s) from HIC data for 1998-1999. Further adjustments were made for the population in
rural and remote areas who are being treated in services not billing Medicare or the
Department of Veterans Affairs. Once the baseline WPE’s have been calculated, further
adjustments were made for:
 socioeconomic advantage and disadvantage;
 higher morbidity of the Aboriginal and Torres Strait Islander population;
 the lower proportion of the population in other rural and remote areas receiving GP
services through Medicare; and
 age and sex of patients.
These adjustments and data sources are fully detailed in the AMWAC (2000) report. Based
on these adjustments, AMWAC contended that for the rural workforce, the average patient
encounters per capita per year needing to be serviced for GPs was 7.1, comprising 6.2 private
practice and an estimated 0.9 public hospital outpatients.
In 1998-99 the average full-time GP provided 6,440 Medicare/DVA patient billed
attendances and this equates to 7,185 patient encounters per year after adjusting for nonMedicare/DVA work.
It is these figures, (7.1 average patient encounters per capita per year) and the 7,185 patient
encounters per year which provide the basis of AMWAC supply requirements.
Acceptance of the AMWAC methodology provides a means of estimated medical practitioner
supply requirements for individual communities, Local Government Areas, Divisions of
General Practice or Statistical Divisions.
In adopting the AMWAC methodology, the QRMSA has accepted that it provides a
reasonable theoretical basis for estimating current and potential medical supply and demand
MWSE
3
requirements. The QRMSA also acknowledges that there are many factors that may in
isolation, or combination impact on medical workforce supply and demand projections and
the imperative to validate ‘on ground realities’. A number of these limitations are discussed
below.
Medical Workforce Supply Estimates (MWSE)
AMWAC projections of medical workforce supply requirements form the basis of MWSE. In
addition, data provided by the Queensland Department of Local Government and Planning
were used to derive current Estimated Resident Population (ERP) projections for Urban
Centres and Localities (UCL’s) and Local Government Areas (LGA’s). While based on
Census of Population and Housing statistics (ABS, 1998), population numbers and
projections may vary for some localities in that the QDLG&P estimates are based on resident
population and do not include visitors. For UCL’s population data are based on year 2000
projections, while for LGA’s population estimates are based on year 2001 projections. Minor
differences in these two estimates have been assigned to LGA Balance.
The MWSE spreadsheet has also been designed in a way that medical workforce estimates
can be perused and examined in a variety of ways including by Locality, LGA, Division of
General Practice, RRMA, ARIA or known number of practitioners or practitioners required.
It is in effect, a flexible planning tool. This flexibility of design can also allow for the
application of weightings for selected towns/regions or the input of differing numbers of
patient encounters.
Underlying Assumptions and limitations
While the AMWAC methodology provides a reasonably sound theoretical estimate of
potential demand, the medical workforce supply needed to match this demand and the actual
medical workforce supply in nominated locations; AMWAC and other similar methodologies
do have some limitations.
1. Firstly, the models assume that potential supply should match potential demand.
There are many factors that mitigate against this ‘ideal’ including geography,
distance, settlement patterns and economic viability. For example, in many
Queensland communities, Queensland Health employees are significant providers of
GP type services.
These employees are salaried and are provided with
accommodation, vehicle, supportive hospital infrastructure and in many cases also
have the right to private practice. In such a marketplace, it is often very difficult for a
private practitioner to compete bearing in mind establishment and insurance costs and
the well-documented difficulties in selling practices in rural and remote locations.
2. The models also tend to assume that the population of a given locality or LGA will
only access services in that locality/LGA, or that potential supply should match
potential demand in the locality. The on-ground ‘reality’ is that in many localities, a
significant proportion of the population may access services in larger adjoining
centres. For example, the Miriam Vale shire has a projected 2001 population of
4,950. The largest centre in the shire (Miriam Vale) has a population of 420, while
the next largest centres Agnes Water and Seventeen Seventy have population of 290
MWSE
4
and 140 respectively. The balance of the shire has a population of 4100. None of the
three major centres in the shire has, in its own right a population sufficient to sustain a
general practice. Projections as modeled by AMWAC would suggest that the Miriam
Vale shire is capable of sustaining 4.9 GPs. The on-ground ‘reality’ is that only one
GP has had a fulltime presence in the LGA in recent times and current GP services
appear to be provided by part-time locum arrangements. It would appear that a large
proportion of the LGA’s population may access services in larger centres such as
Gladstone and Bundaberg.
3. Modeling methodologies tend to assume that national averages with particular
weightings factored in are an appropriate starting point in estimating potential supply
and demand. It is possible that the use of national averages may have the effect of
reflecting urban oversupply rather than rural undersupply in supply and demand
estimations.
4. The methodologies do not take account of the fact that a condition of undersupply in a
particular locality may be financially advantageous for current medical practitioners.
5. The availability/non-availability of bulk billing procedures may/will impact on
medical service utilization.
Next Steps
The QRMSA appreciates that a statistical tool such as the MWSE will need to be tested
against ‘on-ground’ reality for each location considered. This process may involve
consultations with local practitioners, Divisions of General Practice, community
organizations and a consideration of adjoining catchment areas and flows to larger
regional centres. Additionally, medical services provided by others such as RFDS,
ACCHS’s and in some cases Queensland Health will need to be factored into the
estimates.
Summary
Modeling projections as utilised in AMWAC and other similar methodologies are based
on the assumption of a level playing field and that potential demand should generate a
balanced supply. As detailed above, there are a number of factors including distance,
settlement patterns, establishment costs, practice sustainability and subsidised
competition which can act in combination, or in isolation to mitigate against the ‘ideal’ or
‘theoretical’ balance.
While providing a reasonable basis for the estimation of supply and demand in localities
and LGA’s, methodologies as developed by AMWAC can only be used as a guide or
starting point. Accurate measurement of medical practitioner supply and demand in a
particular communities need to be undertaken in consultation with local practitioners and
communities and take into account ‘on ground realities’.
MWSE
5
While not an exhaustive list, it is envisaged that many and/or all of the following factors
may need to be explored in order to provide an accurate assessment of ‘on-ground
realities’.
1. Calculation of the actual number of GP’s/MSRPP’s providing primary care services
on a relatively permanent basis for the community/region in question.
2. Estimation of Fulltime Equivalents (FTE’s)
3. Consultation with local Division of General Practice.
4. Consultation with a selection of local GP’s.
5. Consultation with local community representatives.
6. Examination of bulk bill practices and ratios.
7. Examination of the age/gender profile of current GP’s.
8. Details as to RLRP placements in town/region.
9. Practice ownership structure for town/community.
10. HIC data for town/region with examination of 3 to 4 year trends.
11. Population demographics and Seifa values for town/region.
12. State health and Region Health Service provision in town/region.
13. Number of Temporary Resident Doctors’s in town/region.
14. Current ‘District of workforce shortage’ status.
15. Available data in relation to GP length of stay and turnover.
Table 1 provides an example of the MWSE spreadsheet sorted by Division of General
Practice while Table 2 provides a more conventional, static view organised by Local
Government Area. It is the first table that provides considerable flexibility in exploration of
the data.
References
Australian Medical Workforce Advisory Committee. (2000). The General Practice
Workforce in Australia: AMWAC Report 2000.2. Sydney.
Australian Bureau of Statistics. (1998). 1996 Census of population and housing: selected
characteristics for urban centre and localities. Canberra: ABS.
Queensland Department of Local Government and Planning (2001). Data file. Brisbane
Queensland Department of Local Government and Planning. (2001). Population trends and
prospects for Queensland 2001 edition. Brisbane: QDLG&P.
MWSE
6
Table 1. MWSE sorted by Division of General Practice
Avg
Patient
patient
encounters
encounter
per year
per capita (AMWAC)
per year
(AMWAC)
Shire
UCL_Name
Banana (S)
Banana (S)
Banana (S)
Bauhinia (S)
Belyando (S)
Banana (S)
Duaringa (S)
Duaringa (S)
Fitzroy (S)
Broadsound (S)
Peak Downs (S)
Broadsound (S)
Broadsound (S)
Belyando (S)
Banana (S)
Duaringa (S)
Duaringa (S)
Duaringa (S)
Broadsound (S)
Emerald (S)
Emerald (S)
Livingstone (S)
Fitzroy (S)
Nebo (S)
Banana
Banana Balance
Baralaba (L)
Bauhinia Balance
Bellyando Balance
Biloela
Blackwater
Bluff (L)
Bouldercombe (L)
Broadsound Balance
Capella (L)
Carmilla
Clairview
Clermont
Cracow
Dingo
Duaringa (L)
Duaringa Balance
Dysart
Emerald
Emerald Balance
Emu Park
Fitzroy Balance
Glenden
MWSE
ARIA
RRMA
3.56
5
4.12
5
2.72
4.02
3.96
2.00
5
6
6
5
6.15
4.97
7
7
6.99
5.45
3.89
3.81
6
5
6
6
6.10
5.06
7
6
2.32
5
6.16
7
7.1
Expected
consults
710
35,429
1,704
10,295
12,283
37,346
40,186
2,982
4,544
48,280
5,112
781
1,065
15,762
355
852
1,633
9,798
8,591
70,929
18,460
20,874
35,358
9,443
Known/
Practit
Estimated Required
FTE's
7185.0
Expected Known No. Practit's
GP FTE's
Practit's Required
0.1
4.9
0.2
1.4
1.7
5.2
5.6
0.4
0.6
6.7
0.7
0.1
0.1
2.2
0.0
0.1
0.2
1.4
1.2
9.9
2.6
2.9
4.9
1.3
0.0
0.0
1.0
0.0
0.0
5.0
2.0
0.0
0.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
0.0
0.0
1.0
9.0
0.0
4.0
0.0
1.0
7
0.1
4.9
-0.8
1.4
1.7
0.2
3.6
0.4
0.6
6.7
0.7
0.1
0.1
0.2
0.0
0.1
0.2
1.4
0.2
0.9
2.6
-1.1
4.9
0.3
Division
Pop
2000
Shire
Total
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
100
4990
240
1450
1730
5260
5660
420
640
6800
720
110
150
2220
50
120
230
1380
1210
9990
2600
2940
4980
1330
13700
13700
13700
2130
10590
13700
8940
8940
10880
7090
3000
7090
7090
10590
13700
8940
8940
8940
7090
13690
13690
27850
10880
2160
Shire
UCL_Name
Banana (S)
Fitzroy (S)
Broadsound (S)
Monto (S)
Monto (S)
Belyando (S)
Mount Morgan (S)
Mount Morgan (S)
Banana (S)
Nebo (S)
Nebo (S)
Peak Downs (S)
Bauhinia (S)
Emerald (S)
Emerald (S)
Bauhinia (S)
Broadsound (S)
Banana (S)
Banana (S)
Peak Downs (S)
Emerald (S)
Duaringa (S)
Banana (S)
Jericho (S)
Aramac (S)
Aramac (S)
Barcaldine (S)
Barcaldine (S)
Barcoo (S)
Diamantina (S)
Blackall (S)
Blackall (S)
Boulia (S)
Goovigen
Gracemere
Middlemount
Monto
Monto Balance
Moranbah
Mount Morgan
Mount Morgan (S) Bal
Moura
Nebo
Nebo Balance
Peak Downs Bal
Rolleston
Rubyvale (L)
Sapphire (L)
Springsure (L)
St Lawrence
Thangool (L)
Theodore (L)
Tieri
Willows Gemfields (L)
Woorabinda
Wowan
Alpha (L)
Aramac (L)
Aramac Balance
Barcaldine
Barcaldine Balance
Barcoo Balance
Birdsville
Blackall
Blackall Balance
Boulia (L)
MWSE
ARIA
RRMA
Expected
consults
3.05
1.86
6.01
4.10
5
5
7
5
5.17
2.36
6
5
4.03
5.42
5
7
6.39
6.59
6.43
6.25
5.60
2.96
4.79
6.36
6.47
4.85
3.18
9.05
11.05
7
6
6
7
7
5
5
7
6
6
5
7
7
11.03
7
11.67
10.91
7
7
11.04
7
355
37,346
14,555
8,733
10,650
47,144
17,040
2,343
14,058
1,136
4,757
5,112
710
3,124
3,337
4,118
1,065
2,698
3,621
11,076
1,349
8,023
994
2,982
2,769
2,130
10,650
1,704
2,272
497
8,733
3,408
1,846
Expected Known No. Practit's
GP FTE's
Practit's Required
0.0
5.2
2.0
1.2
1.5
6.6
2.4
0.3
2.0
0.2
0.7
0.7
0.1
0.4
0.5
0.6
0.1
0.4
0.5
1.5
0.2
1.1
0.1
0.4
0.4
0.3
1.5
0.2
0.3
0.1
1.2
0.5
0.3
0.0
2.0
1.0
2.0
0.0
2.5
2.0
0.0
2.0
0.0
0.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
3.0
2.0
0.0
1.0
0.0
1.0
1.0
0.0
2.0
0.0
0.0
0.0
1.0
0.0
0.0
8
0.0
3.2
1.0
-0.8
1.5
4.1
0.4
0.3
-0.0
0.2
0.7
0.7
0.1
0.4
0.5
-1.4
0.1
0.4
-2.5
-0.5
0.2
0.1
0.1
-0.6
-0.6
0.3
-0.5
0.2
0.3
0.1
0.2
0.5
0.3
Division
Pop
2000
Shire
Total
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CQR
CWQR
CWQR
CWQR
CWQR
CWQR
CWQR
CWQR
CWQR
CWQR
CWQR
50
5260
2050
1230
1500
6640
2400
330
1980
160
670
720
100
440
470
580
150
380
510
1560
190
1130
140
420
390
300
1500
240
320
70
1230
480
260
13700
10880
7090
2730
2730
10590
2730
2730
13700
2160
2160
3000
2130
13690
13690
2130
7090
13700
13700
3000
13690
8940
13700
1000
810
810
1740
1740
440
350
1710
1710
530
Table 2. MWSE sorted by LGA
Avg patient
Patient
encounters encounters
per capita
per year
per year (AMWAC)
(AMWAC)
LGA_Name
UCL_Name
Banana (S)
Baralaba (L)
Banana
Biloela
Banana (S) Balance
Moura
Thangool (L)
Theodore (L)
4.12
3.56
2.72
5
5
5
4.03
2.96
4.79
5
5
5
Bowen
Collinsville
Bowen (S) Bal
Merinda (L)
5.03
6.26
6
6
5.1
6
Ayr
Brandon (L)
Giru (L)
Home Hill
Kalamia Estate (L)
Burdekin (S) Balance
4.03
4.02
4.08
4.23
4.09
5
5
5
5
5
Bundaberg
Bundaberg (C) Bal
2.07
3
Banana (S) Total
Bowen (S)
Bowen (S) Total
Burdekin (S)
Burdekin (S) Total
Bundaberg (C)
Bundaberg (C) Total
MWSE
ARIA RRMA
7.1
Expected
consults
1,704
710
37,346
37,133
14,058
2,698
3,621
97,270
55,522
14,342
20,732
1,775
92,371
61,202
6,532
3,124
21,939
2,627
39,547
134,971
305,584
17,608
323,192
7185
Expected
Known/ Practit's Pop2000
GP FTE's Estimated Required
FTE's
0.2
0.1
5.2
5.2
2.0
0.4
0.5
13.5
7.7
2.0
2.9
0.2
12.9
8.5
0.9
0.4
3.1
0.4
5.5
18.8
42.5
2.5
45.0
1.0
0.0
6.0
0.0
2.0
0.0
3.0
12.0
10.0
2.0
0.0
0.0
12.0
9.0
0.0
0.0
3.0
0.0
0.0
12.0
45.0
0.0
45.0
9
-0.8
0.1
-0.8
5.2
0.0
0.4
-2.5
1.5
-2.3
0.0
2.9
0.2
0.9
-0.5
0.9
0.4
0.1
0.4
5.5
6.8
-2.5
2.5
0.0
240
100
5260
5230
1980
380
510
13700
7820
2020
2920
250
13010
8620
920
440
3090
370
5570
19010
43040
2480
45520
LGA_Name
UCL_Name
Burnett (S)
Bargara
Burnett Heads
Elliott Heads (L)
Innes Park (L)
Burnett (S) Bal
Moore Park (L)
2.39
2.42
2.53
2.44
3
3
3
3
2.49
5
Childers
Cordalba (L)
Isis (S) Bal
Woodgate (L)
3
2.84
5
5
3.26
5
Gin Gin (L)
LGA Balance
2.86
5
Agnes Water (L)
Miriam Vale (S) Bal
Miriam Vale (L)
Seventeen Seventy (L)
3.89
5
3.05
4.02
5
5
4.18
5
5
4.43
5
4.69
4.86
5
5
Burnett (S) Total
Isis (S)
Isis (S) Total
Kolan (S)
Kolan (S) Total
Miriam Vale (S)
Miriam Vale (S) Total
Perry (S)
Perry (S) Balance
Perry (S) Total
Cairns (C) Pt B
Cairns Pt B Bal
Babinda
Yarrabah
Cairns (C) Pt B Total
Douglas (S)
Craiglie
Douglas (S) Bal
Mossman
Newell (L)
MWSE
ARIA RRMA
Expected
consults
35,145
16,969
4,828
5,325
99,826
4,544
166,637
10,295
1,633
28,400
4,757
45,085
7,100
30,459
37,559
2,059
29,110
2,982
994
35,145
2,627
2,627
26,270
8,449
15,549
50,268
15,762
31,808
13,490
2,769
Expected
Known/ Practit's Pop2000
GP FTE's Estimated Required
FTE's
4.9
2.4
0.7
0.7
13.9
0.6
23.2
1.4
0.2
4.0
0.7
6.3
1.0
4.2
5.2
0.3
4.1
0.4
0.1
4.9
0.4
0.4
3.7
1.2
2.2
7.0
2.2
4.4
1.9
0.4
4.0
0.0
0.0
0.0
0.0
0.0
4.0
3.0
0.0
0.0
0.0
3.0
5.0
0.0
5.0
1.0
0.0
0.0
0.0
1.0
0.0
0.0
0.0
2.0
2.0
4.0
0.0
0.0
5.0
0.0
10
0.9
2.4
0.7
0.7
13.9
0.6
19.2
-1.6
0.2
4.0
0.7
3.3
-4.0
4.2
0.2
-0.7
4.1
0.4
0.1
3.9
0.4
0.4
3.7
-0.8
0.2
3.0
2.2
4.4
-3.1
0.4
4950
2390
680
750
14060
640
23470
1450
230
4000
670
6350
1000
4290
5290
290
4100
420
140
4950
370
370
3700
1190
2190
7080
2220
4480
1900
390