health human resources forecasting: understanding the ... (hhr).pdf · health human resources...

Health human resources forecasting: Understanding the

current and future requirements of PSW’s and nurses in

Ontario’s LTC sector

Presented by:

Adrian Rohit Dass, MA

IHPME, University of Toronto

Canadian Centre for Health Economics

PI’s: Audrey Laporte, Ivy Bourgeault

Team: Raisa Deber, Andrea Baumann, Janet Lum, Amy Hsu, Christine Kelly

Preliminary - Please do not cite or quote without permission from the authors

Presenter Disclosure 2

• Speaker: Adrian Rohit Dass

• Relationships with commercial interests: – Grants/Research Support: N/A

– Speakers Bureau/Honoraria: N/A Consulting Fees: N/A Other: N/A

This project is supported with funding from the Government of Ontario through the Bruyère Centre for Learning, Research and Innovation in Long Term Care.

The views expressed in this publication are the views of the author(s)/presenter(s) and do not necessarily reflect those of the funder.

Disclosure of Commercial Support 3

• This program has received financial support

– CIHR Operating Grant

• This program has received in-kind support

– N/A

• Potential for Conflict of Interest:

– N/A

Acknowledgements 4

• We thank Peter Walker, Melissa Donskov, Tracy Luciani, and the team at the

Bruyère Centre for Learning, Research and Innovation in Long Term Care for

their input and support on the project.

• We also thank the Ontario Long Term Care Association (OLTCA), Ontario

Association of Non Profit Homes and Services for Seniors (OANHSS),

Ontario Home Care Association (OHCA), Ontario Community Support

Association (OCSA), Nursing Health Services Research Unit (NHSRU),

Ontario Personal Support Worker Association (OPSWA), Canadian Home

Care Association (CHCA), Toronto Central Community Care Access Centre

(TC-CCAC), Ontario Health Human Resources Research Network (OHHRN)

and Canadian Centre for Health Economics (CCHE) for providing their

expertise and facilitating connections with those in the policy realms.

• All errors/omissions are the responsibility of the research team.

Objective for today’s presentation 5

• Outline the main components of the model

• Show how we marshaled various datasets to

produce the data inputs for the forecasting model

• Present preliminary forecasts from the model

• Present policy scenarios that can be explored

with the model

Motivation 6

• PSWs are essential in providing care in Long Term Care.

Approximately three-quarters of direct care staff in

Ontario’s LTC sector are PSWs (MOHLTC, 2012).

• Despite their importance in administering care, relatively

little is known about them

• Need for PSW services expected to grow over the years

as proportion of population aged 65+ continues to grow

• From a policy point of view knowing how many PSWs

will be required is essential

Hours of Direct Care Per Resident Day 7

0

0.5

1

1.5

2

2.5H

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Registered Nurses

Registered Practical Nurses

Other Direct Care Staff

Source: Residential Care Facilities Survey for Ontario (1996-2009)

LTC PSW Forecasting Model

• Goal: To predict the need and supply of Personal Support Workers

(PSWs) accounting for the supply of Nurses (RPNs and RNs) in

Ontario’s LTC sector by LHIN

• Approach:

– Multi-professional (PSW, RPN, RN)

• Model RN labour force as well as RPNs which has largely

been neglected to date in Canada.

– Currently focusing on one sector-LTC but working to expand to

the community

– Forecast at the level of the LHIN, rather than provincially

– Improve upon existing forecasting models, which have focused

on one profession and have not accounted for the effects of

different skill mixes on output.

8

Diagram for Forecasting LTC PSW labour force 9

Provider Supply (Continued)

• To estimate the future stock of the Nurse and PSW

workforces, we take the current stock, subtract the

expected outflows, and add to it the expected inflows (all by

age), which is outlined by Birch et al. (2007):

• For Nurses, the College of Nurses of Ontario (CNO) has a

rich, longitudinal database of all nurses in Ontario

• For PSWs, we have the PSW registry, which is cross-

sectional and only (currently) mandatory for PSWs working

in Home and Community Care

10

Employment Categories of PSWs 11

Source: Lum (2013) – Ontario PSW Registry Data

Analysis

Age Distribution of PSWs 12

Source: Lum (2013) – Ontario PSW Registry Data

Analysis

How to measure RN/RPN outflows from the LTC sector by

LHIN?

13

RNs and RPNs: Since we have longitudinal data for nurses, we can

calculate transitional probabilities to determine the proportion remaining

in LTC from year to year

•This measure is also known as “stickiness”, a term coined by

Alameddine, Laporte, Baumann, O’Brien-Pallas, Mildon, & Deber

(2006)

– Defined as the transition probability of a nurse working in a

given setting in year ‘‘t’’ remaining in the same setting in year

‘‘t+1’’ (sector)

– We have calculated transitional probabilities for RNs and RPNs

over the years 2005-2010 by age group and LHIN

RN Stickiness by LHIN 14

2005/2006 2006/2007 2007/2008 2008/2009 2009/2010 Average

Total Outflows 1284 1253 1205 1086 902 1146

Stickiness 82% 82% 83% 84% 87% 84%

% Outflows by LHIN

Central 8% 10% 9% 11% 8% 9%

Central East 11% 11% 12% 9% 9% 10%

Central West 4% 4% 4% 3% 4% 4%

Champlain 9% 12% 11% 11% 11% 11%

Erie St. Clair 7% 6% 5% 4% 6% 6%

Hamilton Niagara Haldimand Brant 9% 10% 10% 11% 12% 10%

Mississauga Halton 6% 5% 6% 5% 6% 6%

North East 5% 5% 5% 6% 7% 6%

North Simcoe Muskoka 4% 3% 5% 6% 5% 5%

North West 3% 2% 3% 2% 3% 2%

South East 5% 7% 5% 7% 7% 6%

South West 10% 8% 9% 9% 8% 9%

Toronto Central 14% 11% 13% 13% 11% 12%

Waterloo Wellington 5% 5% 4% 5% 4% 5%

Source: CNO Database

RPN Stickiness by LHIN 15

2005/2006 2006/2007 2007/2008 2008/2009 2009/2010 Average

Total Outflows 1188 1151 1324 1451 1317 1286

Stickiness 82% 83% 83% 82% 84% 83%

% Outflows by LHIN

Central 5% 6% 6% 7% 9% 6%

Central East 10% 8% 9% 12% 8% 10%

Central West 2% 3% 4% 3% 4% 3%

Champlain 12% 10% 11% 10% 13% 11%

Erie St. Clair 7% 5% 6% 5% 5% 6%

Hamilton Niagara Haldimand Brant 11% 13% 14% 12% 10% 12%

Mississauga Halton 3% 4% 3% 5% 4% 4%

North East 6% 10% 9% 7% 10% 8%

North Simcoe Muskoka 5% 3% 4% 5% 4% 4%

North West 5% 5% 5% 5% 5% 5%

South East 6% 6% 6% 5% 4% 5%

South West 11% 10% 10% 8% 9% 10%

Toronto Central 11% 11% 10% 11% 11% 11%

Waterloo Wellington 6% 6% 5% 5% 4% 5%


How to measure outflows of PSWs from the LTC sector by

LHIN?

• Wodchis et al (2015) found the turnover rate of full-time PSW’s in

LTC to be 6.5%. We therefore assume that the LTC sector retains

93.5% of it’s FTE PSW workforce from year to year.

• In terms of outflows per LHIN, we use the same proportions as the

RPN labour force

• In terms of outflows by age, we calculate this based on the PSW

Registry Question: In the next 1-3 years, what do you plan on

doing?

– We obtained an age distribution of PSW’s intending to: retire,

seek employment outside of the PSW field, return to school for a

PSW Certificate, return to school for PSW professional

development or continuing education, or return to school for a

different career.

– We found intention to leave is not limited to the older ages, as a

high proportion of younger PSWs intend to leave as well.

16

How to measure Nurse (RN, RPN) inflows into the LTC

sector by LHIN?

• RNs and RPNs: Alameddine et al. (2006) also have an inflow

measure, defined as as the percentage of nurses that are working in

a particular setting in year ‘‘t’’, who were not working in that setting

in year ‘‘t-1’’, i.e., were fresh additions to that setting.

• This measure captures nurses who are new additions to the

workforce (new graduates, immigration), returning to the workforce,

and those switching sub-sectors.

• This was estimated using the CNO database for years 2005-2010.

17

Inflows of RN’s into LTC by LHIN 18


Inflows of RPN’s into LTC by LHIN 19


How to measure PSW inflows into the LTC sector by LHIN?

PSWs •Every year, over 7000 PSWs graduate from Ontario

programs (“PSW Educational Program Accreditation”

http://www.pswepa.ca/)

•According to the Ontario Ministry of Training, Colleges,

and Universities website, 54% of new PSW graduates go

into the “Nursing and residential care facilities” sector

– We therefore assume that 54% of 7000, or 3780 new

PSW graduates enter the LTC sector in each year.

•In the absence of data on inflows across LHINs for PSWs,

we apply the same proportions as the RPN labour force.

20

Demand for Providers

• Before we can estimate the number of required providers, we need

to estimate the number of services required, which can be done

using the following indicators:

21

(1) (2) (3)

This is the needs based approach for estimating the number of services

required by the population, originally created by Birch et al (2007), and

used by CNA (2009) and Murphy et al (2012) to estimate the number of

required services in each sector of Ontario (including Long Term Care).

Predicting Services Required 22

0

5000000

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20000000

25000000

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19961997199819992000200120022003200420052006200720082009

P

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Year

Total Patient Days (Predicted)

Total Patient Days (Actual)


How does this translate to the number of staff

required? And what about productivity?

Under the traditional uni-professional approach, once the services

required have been estimated, the next step is usually to divide this

number by the rate at which FTE workers can perform them

(productivity) to yield the required number of health workers. The

conceptual framework is usually modeled as follows (adapted from

Murphy et al 2012):

23

Why might this approach be incomplete?

From Auditor General of Ontario (2013 report), as a recommendation to

the MOHLTC:

“…further refine its forecasting models and their capabilities to assess

the impact of various factors on service-provider productivity”

From Health Workforce Australia’s “National Health Workforce

Productivity Modelling – Final Report” (2012):

“Current workforce planning models examine labour productivity of

each health worker (e.g. number of visits per doctor), though in reality

the number of visits each doctor produces is also influenced by nurses,

equipment, and other resources... Models that estimate requirements

for a particular group of health professionals do so independently of

other groups of health professionals, leading to inaccurate results”

24

Predicting the Number of FTE RN’s in Ontario, 1996-2009 25

0

1000

2000

3000

4000

5000

6000

F

T

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Year

FTE RN"s Required (Estimated)

FTE RN's Required (Actual)


Predicting the Number of FTE RPN’s in Ontario, 1996-2009 26

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

F

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Year

FTE RPN"s Required(Estimated)

FTE RPN's Required (Actual)


Predicting the Number of FTE PSW’s in Ontario, 1996-

2009

27

0

5000

10000

15000

20000

25000

30000

F

T

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Year

FTE PSW's Required (Estimated)(Silo)

FTE PSW's Required (Actual)


How to model workers together?

We need a way to relate services required (output) with the

factors that influence it (PSWs, RNs, RPNs, drug

expenditures, etc.). Conceptually, it would look like this for

the LTC sector:

28

This can be done by estimating a production function

Multi-professional Approach

• We estimate a translog production function, which allows for interactions of the

inputs, thereby allowing for the productivity of one input to depend on the level

of other inputs. It also has a history in the economics literature for use of

determining the complementarity/substitutability of inputs (Hsu et al, 2015).

– We find a statistically significant interaction effect of -0.016 between PSWs

and RPNs, This implies that a 1% increase in the number of RPN hours

leads to a 0.016% decrease in the productivity of a PSW, all else being

equal.

– We also found a positive (though not significant) interaction between RN’s

and PSW’s of 0.008, implying an increase in PSW productivity of 0.008% for

every 1% increase in RN hours.

• These results are supported by qualitative work performed by members of the

team (see Kelly 2015).

– PSWs feel their role is very similar, overlapping, or even identical to that of

RPNs

– The PSWs and key informants do not make comparisons of this nature with

RNs

29

Predicting the Number of FTE PSW’s in Ontario, 1996-

2010

30

0

5000

10000

15000

20000

25000

30000

F

T

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s

R

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q

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r

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Year

FTE PSW's Required (Estimated)(Silo)

FTE PSW's Required (Actual)

FTE PSW's Required (Estimated)(Concert) (RN's + RPN)


Results of Forecasts – Gap

(Surplus) of Workers by LHIN

31

Results of Forecasts – Gap of PSW Labour Force 32

-2500

-2000

-1500

-1000

-500

0

500

2010201120122013201420152016201720182019202020212022202320242025

Central

Central East

Central West

Champlain

Erie St. Clair

Hamilton Niagara HaldimandBrant

Mississauga Halton

North East

North Simcoe Muskoka

North West

South East

South West

Toronto Central

Waterloo Wellington

Results of Forecasts – Gap of RN Labour Force 33

-600

-500

-400

-300

-200

-100

0

100Central

Central East

Central West

Champlain

Erie St. Clair

Hamilton Niagara HaldimandBrant

Mississauga Halton

North East


North West

South East

South West

Toronto Central

Waterloo Wellington

Results of Forecasts – Gap of RPN Labour Force 34

-800

-600

-400

-200

0

200

400

Central

Central East

Central West

Champlain

Erie St. Clair

Hamilton Niagara Haldimand Brant

Mississauga Halton

North East


North West

South East

South West

Toronto Central

Waterloo Wellington

Policy Scenarios

35

Policy Scenario 1: Initial Gap

• In our base-case scenario, we assume supply is equal to demand in

the base period and do not allow for unmet need.

– This assumption is likely to be false in Ontario, as it does not

take into account clients in the community or hospital waiting for

an LTC bed

• According to a report by the MOHLTC, there was an average of

25,322 clients in the Community and in the Hospital on the waitlist

for LTC in the 2009/10 fiscal year (MOHLTC, 2012).

– Unfortunately, this was not broken down by LHIN, so we

approximated how many individuals per LHIN were on the wait-

list this year by the number of facilities in each of the LHINs.

36

Policy Scenario 2: Diversion of home-care clients on LTC

Wait-list to Community

• Williams et al conducted 11 Balance of Care

(BOC) projects across 10 of the 14 LHINs in

Ontario

• They found that individuals on the LTC wait-list

could be “diverted” safely and cost-effectively

cared for in the family home or in supported

housing. This generally ranged from 14-50%

• We simulate from the lower and upper ends to

explore the effects on the estimated gap in LTC.

37

Policy Scenario 3: Level of staffing and Quality of

Care

• One issue related to LTC Homes in Ontario is the level of staffing used by

homes.

• Data from RCFS suggests that residents were receiving 1.94 PSW hours,

0.91 nurse hours (RN and RPN), and 0.22 Therapist Hours per resident day

in 2009, totaling 3 hours of direct care per resident day.

– These figures are below the recommended 2.5, 1, and 0.5 hours for

PSWs, Nurses, and Other Staff recommended by Shirlee Sharkey’s

2008 report on LTC Homes in Ontario, which equates to 4 hours of care

per resident day.

– To date, these staffing levels have not been implemented (OANHSS,

2015).

• OANHSS’s 2015 report suggests implementing these ratios to improve the

quality of care in LTC homes in Ontario.

• We simulate the effects of these ratios on the projected gap of workers.

38

Summary of Forecasts: Gap of FTE Workers in

LTC by 2025 in Ontario

39

PSWs RNs RPNs

Scenario Gap % Change Gap % Change Gap % Change

Base Case - Silo 5698 - 3162 - 2754 -

Base Case - Multiprofessional 11475 101% 3162 - 2754 -

Policy Scenario 1-2 - Unmet Need (50% cared for in HCC) 17036 48% 4069 29% 4127 50%

Policy Scenario 1-2 - Unmet Need (14% cared for in HCC) 21043 24% 4723 16% 5115 24%

Policy Scenario 3 - Staffing Ratios 39609 88% 5836 24% 7003 37%

Limitations

Demand Side data

•Residential Care Facilities Survey (RCFS)

– Quality of care measures not available. This is not a limitation of the methodology, but rather, the data used

in the study.

• Although we used a volume based measure of care (patient days of care), we could have explored quality

outcomes as well. Such data was not available to use at the time of the study. Future work may look into

exploring this should such data become available

– Only reports total direct care hours (including casuals).

• Future work may explore variation in hours worked across class of works (Full-time, Part-time Casual, etc.)

Supply Side Data

•PSW Registry

– PSW labour force is unregulated, so we don’t have a robust, representative dataset.

– Is only currently mandatory for PSWs working for publicly funded employers in the home and community

sector, so may be unrepresentative (selection bias).

– In contrast to nursing registry, PSW registry is (at least for now) cross-sectional so that we cannot get a

sense of dynamics that are driven by changes in the age distribution.

– Had to source data from other sources (accreditation websites, survey research, Ontario Ministry of

Training, Colleges, and Universities, etc.) to obtain relevant data for forecasting model.

– Inflows from the Home and Community Care and Hospital sectors was assumed to be zero, since data on

these transitions do not currently exist

• Future work will allow for workers to inflow from other sectors (see Berta et al 2015).

40

Value of Forecasting

• Having the appropriate level of staffing available

in LTC will become essential in the upcoming

years as proportion of population aged 65+

continues to grow

• Knowing how may RNs, RPNs, and PSWs will

be required, as well as the projected supply, will

assist us as we plan for this

41

Conclusions

• Health Human Resource planning is a complex science

requiring detailed data

– Requires longitudinal data to get a sense of dynamics

of workers over time and across regions

• Need to model workforces simultaneously to take into

account interactive effects between workforces

• Vital for LTC with the expected increase in demand for

these services in the upcoming years.

42

Next Steps

• Funding leveraged through CIHR to expand model to

Home and Community care sector

– Survey data is currently being collected from PSWs

working in LTC and HCC

– With the data collected, we will be able to examine

the factors that affect hours of work and influence

intentions to leave the labour force, as well as

likelihood of working in a particular sector

– The results of the analysis will be used as inputs to

extend the current model to other sectors

43

References

• Alameddine M, Laporte A, Baumann A, O'Brien-Pallas L, Mildon B, Deber R (2006). 'Stickiness' and 'inflow' as proxy

measures of the relative attractiveness of various sub-sectors of nursing employment. Social Science & Medicine 63: 2310-

2319

• Birch, S. et al. (2007). Human resources planning and the production of health: A needs-based analytical framework.

Canadian Public Policy 33, supplement.

• Canada. Office of the Auditor General of Ontario. 2013 Annual Report of the Office of the Auditor General of Ontario. 2013.

Web. April 7th, 2014.

• CNA (2009). Tested Solutions for Eliminating Canada's Registered Nurse Shortage, report prepared by Tomblin Murphy, G.

et al., Canadian Nurses Association, Ottawa

• Hamilton, Lynelle. “PSW Educational Program Accreditation”. Web. April 7th, 2014.

<http://www.pswepa.ca>

• HWA (2012). National Health Workforce Productivity Modelling - Final Report, Health Workforce Australia, Adelaide.

• Lum, Janet. (2013) Ontario PSW Registry Data Analysis Results. Canadian Research Network for Care in the Community.

April 7th, 2014.

<http://www.ryerson.ca/crncc/knowledge/events/pdf/PSW%20Registry%20Data%20Analysis%20Results%20Final.pdf>

• Ministry of Health and Long-Term Care (2012). Long-term Care in Ontario: Sector Overview. Health Analytics Branch.

• Murphy et al (2012). Eliminating the shortage of registered nurses in Canada: An exercise in applied needs-based planning.

Health Policy 105: 192-202

• OANHSS (2015). The Need Is Now: Addressing Understaffing in Long Term Care.

• Singh, D. et al. (2010), Ontario Population Needs-Based Physician Simulation Model, Ministry of Health and Long-Term

Care and the Ontario Medical Association, Toronto.

• Wodchis et al (2015). Factors Associated with Personal Support Worker Turnover in Ontario LTC Homes. Accessed online

August 19, 2015 http://ihpme.utoronto.ca/wp-content/uploads/2015/05/psw-poster.pdf

44

http://www.pswepa.ca

http://ihpme.utoronto.ca/wp-content/uploads/2015/05/psw-poster.pdf





Extra Slides

45

Base Case – Gap of PSW’s 46

PSW's (Concert)

FTE's by LHIN (Predicted)

2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central 116 150 182 209 233 253 265 266 264 257 245

Central East -247 -254 -265 -282 -299 -323 -358 -410 -468 -534 -609

Central West -71 -81 -95 -119 -146 -177 -212 -254 -301 -357 -418

Champlain -654 -710 -782 -864 -949 -1041 -1156 -1298 -1453 -1621 -1792

Erie St. Clair -84 -103 -119 -139 -158 -188 -225 -271 -323 -379 -443


-931 -1014 -1102 -1192 -1284 -1386 -1497 -1640 -1801 -1975 -2156

Mississauga Halton -283 -304 -326 -351 -376 -415 -461 -510 -569 -631 -709

North East -94 -119 -147 -170 -191 -220 -258 -300 -348 -405 -462

North Simcoe Muskoka -471 -507 -548 -592 -636 -684 -736 -796 -868 -938 -1013

North West -143 -151 -163 -177 -192 -211 -234 -255 -281 -310 -339

South East -267 -314 -365 -415 -469 -525 -586 -655 -730 -811 -891

South West -547 -609 -673 -749 -825 -909 -1004 -1120 -1246 -1381 -1516

Toronto Central -652 -645 -634 -629 -614 -604 -604 -622 -649 -686 -738

Waterloo Wellington -157 -180 -211 -241 -275 -314 -361 -419 -483 -554 -631

Base Case – Gap of RN’s 47

RN’s


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -49 -53 -57 -61 -65 -69 -74 -81 -88 -95 -103

Central East -94 -110 -126 -142 -157 -173 -189 -208 -228 -249 -270

Central West -39 -49 -60 -72 -84 -96 -109 -123 -138 -154 -170

Champlain -190 -217 -246 -276 -305 -335 -367 -404 -442 -482 -522

Erie St. Clair -1 -10 -18 -26 -34 -43 -53 -64 -76 -88 -101


-148 -162 -176 -190 -203 -216 -230 -249 -271 -294 -317


North East -72 -83 -94 -104 -112 -122 -132 -142 -154 -166 -179


North West 12 8 4 0 -4 -8 -13 -18 -24 -30 -36

South East -33 -43 -52 -61 -70 -79 -88 -98 -110 -122 -133

South West -141 -163 -184 -207 -229 -251 -275 -301 -329 -358 -387

Toronto Central -81 -99 -116 -132 -146 -160 -175 -193 -211 -231 -253


Base Case – Gap of RPN’s 48

RPN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central 58 77 96 114 133 150 166 179 192 203 213

Central East 3 3 0 -5 -5 -7 -10 -18 -27 -38 -52

Central West 72 74 76 75 73 70 66 61 53 44 34

Champlain 130 100 66 28 -10 -51 -90 -134 -182 -233 -285

Erie St. Clair 19 8 -1 -12 -23 -37 -50 -64 -80 -96 -114


-221 -261 -304 -348 -393 -441 -491 -549 -611 -671 -728

Mississauga Halton 27 30 33 35 37 35 32 28 21 14 3

North East -8 -21 -34 -45 -56 -69 -85 -101 -119 -139 -154


North West -23 -33 -43 -55 -66 -78 -87 -95 -104 -114 -123

South East -132 -155 -180 -204 -226 -248 -271 -293 -316 -341 -365

South West -248 -282 -317 -356 -395 -437 -478 -519 -563 -610 -656

Toronto Central -24 -24 -25 -27 -28 -30 -34 -43 -54 -67 -84


50% cared for in HCC – PSW’s 49

PSW's (Concert)


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -298 -265 -233 -206 -182 -162 -151 -150 -152 -159 -171

Central East -850 -857 -868 -886 -903 -927 -962 -1014 -1073 -1139 -1214

Central West -264 -275 -289 -312 -340 -371 -406 -448 -496 -551 -612

Champlain -1187 -1244 -1315 -1397 -1483 -1575 -1690 -1832 -1987 -2155 -2327

Erie St. Clair -411 -431 -447 -466 -486 -516 -553 -598 -651 -707 -771


-1698 -1780 -1868 -1959 -2051 -2153 -2265 -2408 -2569 -2743 -2924


North East -510 -534 -563 -586 -607 -636 -674 -716 -765 -822 -879


North West -319 -326 -338 -353 -367 -386 -410 -431 -457 -486 -515

South East -602 -650 -700 -750 -805 -861 -922 -991 -1066 -1147 -1228

South West -1214 -1275 -1340 -1416 -1491 -1575 -1671 -1787 -1913 -2049 -2184

Toronto Central -974 -966 -956 -951 -935 -926 -925 -944 -971 -1008 -1060


50% cared for in HCC – RN’s 50

RN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -117 -121 -125 -129 -133 -138 -143 -149 -156 -163 -171

Central East -192 -208 -224 -240 -255 -271 -288 -307 -327 -347 -369

Central West -71 -81 -92 -103 -116 -128 -141 -155 -170 -186 -202

Champlain -277 -304 -333 -363 -392 -422 -454 -491 -529 -569 -609

Erie St. Clair -55 -64 -72 -80 -88 -97 -107 -117 -129 -142 -155


-273 -287 -301 -314 -327 -341 -355 -374 -395 -418 -442


North East -140 -151 -162 -172 -180 -190 -200 -211 -222 -235 -247


North West -17 -21 -25 -29 -33 -37 -42 -47 -53 -59 -65

South East -89 -98 -107 -116 -125 -134 -143 -153 -165 -177 -188

South West -250 -272 -293 -316 -337 -360 -383 -410 -438 -467 -495

Toronto Central -133 -152 -168 -185 -198 -213 -228 -245 -264 -283 -305


50% cared for in HCC – RPN’s 51

RPN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -45 -26 -7 11 30 47 63 76 89 100 110

Central East -146 -147 -149 -154 -155 -156 -159 -167 -176 -188 -201

Central West 23 26 28 27 25 22 18 12 5 -4 -14

Champlain -1 -31 -66 -103 -142 -183 -221 -266 -314 -364 -416

Erie St. Clair -62 -73 -82 -93 -104 -118 -131 -145 -161 -177 -195


-409 -450 -493 -537 -582 -630 -680 -738 -800 -859 -917


North East -111 -124 -137 -148 -159 -172 -188 -204 -222 -242 -257


North West -67 -77 -87 -98 -110 -122 -131 -139 -148 -158 -167

South East -215 -239 -263 -287 -309 -331 -354 -376 -399 -424 -448

South West -412 -446 -482 -521 -560 -601 -642 -684 -728 -774 -820

Toronto Central -103 -103 -104 -106 -106 -108 -113 -122 -133 -146 -163


14% cared for in HCC – PSW’s 52

PSW's (Concert)


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -598 -564 -532 -506 -481 -462 -450 -449 -451 -459 -471

Central East -1285 -1292 -1303 -1321 -1338 -1363 -1398 -1449 -1508 -1574 -1650

Central West -404 -414 -429 -452 -480 -511 -546 -588 -636 -691 -752

Champlain -1572 -1628 -1700 -1782 -1867 -1960 -2075 -2217 -2372 -2540 -2712

Erie St. Clair -647 -666 -682 -702 -721 -752 -789 -835 -887 -943 -1008


-2250 -2333 -2421 -2511 -2604 -2706 -2818 -2961 -3122 -3296 -3478


North East -810 -834 -863 -886 -907 -936 -974 -1017 -1065 -1122 -1180


North West -445 -453 -465 -479 -494 -513 -536 -558 -583 -612 -641

South East -844 -892 -942 -992 -1047 -1103 -1164 -1233 -1308 -1390 -1470

South West -1694 -1755 -1820 -1896 -1972 -2056 -2152 -2267 -2394 -2530 -2665

Toronto Central -1205 -1198 -1187 -1182 -1167 -1157 -1157 -1176 -1202 -1239 -1292


14% cared for in HCC – RN’s 53

RN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -166 -170 -174 -178 -182 -187 -192 -198 -205 -212 -220

Central East -263 -279 -295 -311 -326 -342 -359 -378 -398 -418 -440

Central West -94 -104 -115 -126 -139 -151 -164 -178 -193 -209 -225

Champlain -339 -367 -396 -425 -455 -484 -517 -553 -592 -632 -672

Erie St. Clair -93 -102 -110 -119 -126 -135 -145 -156 -168 -180 -194


-363 -377 -391 -404 -417 -430 -445 -463 -485 -508 -532


North East -189 -200 -211 -221 -229 -239 -249 -260 -271 -284 -296


North West -38 -42 -46 -50 -54 -58 -63 -68 -74 -80 -86

South East -128 -137 -147 -155 -165 -173 -183 -193 -204 -216 -228

South West -328 -350 -371 -394 -416 -438 -462 -488 -516 -545 -574

Toronto Central -171 -189 -206 -222 -236 -250 -265 -283 -301 -321 -343


14% cared for in HCC – RPN’s 54

RPN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -119 -100 -82 -63 -44 -27 -11 2 14 26 36

Central East -253 -254 -257 -261 -262 -263 -267 -274 -284 -295 -308

Central West -11 -9 -7 -8 -10 -13 -17 -22 -29 -39 -49

Champlain -96 -126 -160 -198 -237 -278 -316 -361 -408 -459 -511

Erie St. Clair -121 -131 -141 -152 -163 -177 -190 -204 -219 -235 -254


-545 -586 -629 -673 -718 -765 -816 -873 -936 -995 -1053


North East -186 -198 -211 -222 -233 -246 -262 -278 -296 -316 -331


North West -99 -108 -119 -130 -142 -154 -162 -170 -180 -189 -199

South East -275 -299 -323 -347 -369 -391 -414 -436 -459 -484 -508

South West -531 -565 -600 -639 -678 -720 -761 -802 -846 -892 -938

Toronto Central -160 -160 -161 -163 -163 -165 -170 -179 -190 -203 -220


Wait List + Staffing Ratios – PSW’s 55

PSW's (Concert)


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -1269 -1256 -1243 -1237 -1232 -1233 -1244 -1268 -1296 -1330 -1370

Central East -2419 -2456 -2497 -2545 -2591 -2646 -2713 -2801 -2899 -3004 -3121

Central West -874 -902 -934 -978 -1027 -1080 -1138 -1204 -1277 -1361 -1451

Champlain -2889 -2976 -3082 -3199 -3320 -3448 -3605 -3796 -4003 -4225 -4452

Erie St. Clair -1414 -1450 -1479 -1513 -1546 -1593 -1647 -1712 -1786 -1864 -1952


-4074 -4193 -4317 -4443 -4570 -4708 -4858 -5047 -5259 -5486 -5722


North East -1660 -1704 -1752 -1792 -1829 -1875 -1932 -1993 -2062 -2142 -2222


North West -751 -763 -780 -799 -819 -843 -873 -901 -935 -973 -1010

South East -1518 -1582 -1649 -1715 -1787 -1859 -1937 -2026 -2122 -2225 -2327

South West -2993 -3079 -3169 -3272 -3373 -3484 -3610 -3759 -3923 -4098 -4272

Toronto Central -3147 -3165 -3177 -3195 -3198 -3208 -3229 -3273 -3328 -3395 -3481


Wait List + Staffing Ratios – RN’s 56

RN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -200 -205 -210 -215 -220 -225 -232 -239 -247 -256 -265

Central East -320 -338 -355 -373 -389 -406 -425 -445 -467 -490 -514

Central West -118 -129 -140 -153 -166 -180 -194 -209 -225 -242 -260

Champlain -405 -434 -465 -496 -527 -559 -593 -632 -673 -716 -759

Erie St. Clair -132 -142 -151 -159 -168 -178 -188 -200 -213 -227 -241


-454 -470 -486 -501 -515 -530 -547 -567 -592 -617 -644


North East -232 -244 -256 -266 -276 -286 -297 -309 -321 -335 -348


North West -53 -57 -62 -66 -70 -75 -80 -86 -92 -98 -105

South East -162 -172 -182 -192 -202 -211 -222 -233 -245 -258 -271

South West -393 -416 -439 -463 -486 -509 -535 -563 -593 -624 -654

Toronto Central -268 -287 -305 -323 -337 -353 -369 -387 -407 -428 -452


Wait List + Staffing Ratios – RPN’s 57

RPN's


2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Central -179 -161 -144 -128 -111 -95 -81 -70 -60 -51 -43

Central East -353 -356 -361 -369 -372 -375 -382 -393 -406 -420 -437

Central West -53 -52 -52 -54 -58 -63 -69 -77 -86 -98 -110

Champlain -211 -244 -281 -322 -364 -408 -450 -499 -551 -607 -663

Erie St. Clair -188 -200 -211 -223 -235 -251 -265 -281 -298 -316 -337


-705 -748 -794 -842 -890 -940 -994 -1055 -1122 -1186 -1248


North East -260 -275 -289 -302 -314 -329 -346 -364 -384 -405 -423


North West -126 -136 -147 -158 -170 -183 -192 -201 -211 -221 -231

South East -334 -359 -385 -411 -434 -458 -482 -506 -531 -558 -584

South West -645 -681 -719 -760 -801 -845 -888 -933 -980 -1030 -1079

Toronto Central -329 -332 -334 -339 -341 -344 -350 -362 -375 -391 -411


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