Cancer Care Ontario s Approach to Health Human Resource Planning

Transcription

1 Cancer Care Ontario s Approach to Health Human Resource Planning Presentation to: CAPCA- Chief Operating Officer Roundtable Meeting Presented by : Elaine Meertens, Director- Cancer Planning & Regional Program Development September 11, 2013

2 Models of Care Health Human Resource Planning History of HHR planning Overview- Models of Care Enhancing HHR Prediction and Planning Medical Oncology- an example 2012 approach and methodology 2013 approach and methodology Future of HHR Prediction and Planning 2

3 Two signature events Motivated by similar pressures and themes 3

4 ONTARIO CANCER PLAN

5 ONTARIO CANCER PLAN III 5

6 Goal 1 Goal 2 Goal 3 Models of Care Goals Develop and implement best practice models of care to promote value for money. Identify and address regulatory, funding and other policy barriers to enable new models of care. Enhance the ability to accurately predict human resources demand while incorporating changes in model of care. 6

7 Continuous enhancing HHR Prediction and Planning Future Demand based on utilization/existing capacity Focus on ambulatory care Separate methodologies to calculate provincial demand to identify additional FTE & perform regional allocation Scope Radiation & Medical Oncologists Demand incorporates growth in incidence Scope expands to Gynecologic Oncologists Engagement and collaboration with clinical business groups enhanced Demand based on visit types, incorporates inpatient care, prevalence & impact of new models of care Review of workload measure One methodology to calculate provincial demand & additional FTE & regional allocation HHR PNP working group consolidated for 3 specialties Further enhancements to visit types, complexity, impact of new models of care, changes in utilization Scope potential to expand to other oncology HHR Alignment with health system initiatives (ex. Patient based funding model) 7

8 Methodology to identify need for additional AFP positions at the Provincial level A data driven, transparent approach Need based on provincial incremental demand for services ( care gap ) Growth in cancer incidence rate used to determine the projected demand Pre-established workload factor per FTE used to determine number of new positions required to support care gap Assumptions: Current state adequate to support current demand- no right sizing of the system Utilization for systemic treatment does not change over time 8

9 Estimating provincial demand & additional FTE required % Incidence growth % Incidence growth % Incidence growth Baseline (demand based on utilization/ capacity) Future demand Future demand Future demand Incremental demand Incremental demand Incremental demand Workload per FTE Workload per FTE Workload per FTE Additional FTE required Additional FTE required Additional FTE required 9

10 New Cases as a standard measure of workload Reference Year Community Academic Systemic Therapy Task Force Report Human Resource Planning for Medical Oncology in Ontario Principles for Allocation of ONTMOA APP Positions Regional Systemic Treatment Program Provincial Plan* *This describes current activity as a maximum For medical oncology HHR planning a workload factor of 232 new patient consults per FTE is used for incremental demand only. 10

11 Organization & Infrastructure

12 2012 Regional Allocation Methodology - Principles 1. Allocation process- fair, transparent and data driven. 2. Allocations- to enable additional patient services and not to convert a FFS position to AFP. 3. Allocation- made to institutions, through regional cancer programs. Institutional level allocation authorized through a consultative process involving the Regional Vice President (RVP), Cancer Services and Regional Systemic Treatment Program Medical Oncology Lead 4. In assessing current HHR resources, all medical oncologists, where possible, will be counted. 5. In assessing current activity all activity, where possible, considered and benign work excluded. This was done using a mix of data sets. 6. Modifiers to workload measures defined. 7. Additional considerations made for special circumstances. 12

13 Regional Allocation Methodology* Inputs into Core Model for Medical Oncology HHR regional census Adjustment factors Core Model Hospital Administrative Data/ Treated Cases Physician Billing Data/ New Consults Regional consultation * For positions requested based on 2011/12 care gap 13

14 Allocation Methodology Measured clinical activity using OHIP consults and NACRS treated cases Measured HR by FTE through a nominal census Adjusted for academic and community; clinical scientist and complex malignant hematology Compared clinical activity per FTE after adjustments and ranked them. Performed sensitivity testing Needed to fit within the available # of positions If there are insignificant differences between institutions or obvious outliers- considered other mitigating factors to inform the allocations 14

15 Performance Management New position best meets the needs of the region Monitor recruitment Volumes tied to new positions Position supported by the appropriate infrastructure and resources If unable to recruit may use physician extenders i.e. GPOs and APNs (temporary solution only) 15

16 Summary of recent allocations 10 MOs 13 MOs 14 MOs * 07/08 08/09 * * 09/10 * 10/11 11/12 12/13 * * Recruitment period Recruitment period * Recruitment opportunity for new grads (positions available early enough for recruits to start July) 16

17 Results FTE request based on incremental demand (care gap) 12 FTE Medical Oncologists 5 FTE 7 FTE 7 FTE 8 FTE 2012/ / / /16 Timing of HHR required may be impacted by qualitative factors such as infrastructure (ex. clinic space) 17

18 Provincial Oncology Alternate Funding Plan (POAFP) Purpose: Single oncology Alternate Funding Plan modeled on Academic Health Sciences Centre agreement. CCO s interest are as follows: Under the MOC umbrella, CCO and Ontario s specialist oncologists business groups are working collaboratively to merge and align these funding agreements with a view to ensuring support and enabling of clinical best practices, continuous quality improvement and evolving models of care. Barriers: Process slowed due to OMA negotiations Competing MOHLTC priorities 18

19 Future of HHR Prediction and Planning (PNP) Led by CCO s Models of Care HHR PNP Working Group Current scope includes medical oncologists, radiation oncologists, gynecologic oncologists only Clinical membership includes business groups: o Ontario Medical Oncology Association (ONT MOA) o Ontario Association of Radiation Oncologists (OARO) o Gynecology Oncology Group of Ontario (GOGO) Goal 3 Enhance the ability to accurately predict human resources demand while incorporating changes in model of care. 19

20 Conceptual architecture of 2013 model Will be projected for 3 years based on incidence and prevalence. Incorporate changes in # visits based on impact of models of care. # visits type1 Relative workload intensity visit type 1 Workload units needed for visit type 1 # visits type2 Relative workload intensity visit type 2 Workload units needed for visit type 2 Total workload units needed Annual workload capacity Total FTE required # visits type3 Relative workload intensity visit type 3 Workload units needed for visit type 3 Adjustment - clinician scientist Current FTE Adjusted Current FTE Adjustment - teaching Additional FTE required 20

21 Key success factors Understanding the context and drivers Accurate and timely data KISS rule in model development Collaboration, Collaboration, Collaboration Clinical business groups MOHLTC Clinicians Administrators 21