Filling An Evidence Gap

Transcription

1 Filling An Evidence Gap The Ontario Population Needs-Based Physician Simulation Model Presentation to the Royal College of Physicians and Surgeons of Canada, National Specialty Societies Human Resources for Health Conference, December 2010 Hussein Lalani, HHR Forecasting and Modelling Unit, HHR Policy Branch Ontario Ministry of Health and Long-Term Care

2 2 Project Overview Significant efforts to enhance physician supply in Ontario (see Appendix). In 2007, the ministry and Ontario Medical Association (OMA), sponsored a Request for Proposals (RFP) for the development of a Population Needs-Based Physician Simulation Model. Simulate a variety of scenarios that can help understand the potential impact on the gap between future physician supply and need in Ontario. The Conference Board of Canada was selected after a comprehensive evaluation process that included evaluators from the ministry, OMA and Canadian Medical Association (CMA).

3 3 Project Overview - Context and Limitations The model is a planning tool not a crystal ball. The future numbers will never be exactly right. All models are wrong, but some are useful. Real value is an indication of potential future trends and simulation of the possible impact of policy changes. Another piece of evidence amongst many others, both qualitative and quantitative, to help support physician HR planning (e.g. the Ontario Primary Care Access Survey, Health Care Connect, etc.). The model is constructed at a macro level and can help identify areas which require more detailed examination and research.

4 4 Model Structure - Overview The model translates various health needs of the population into need for physician services and compares this to the supply of the physician services. A gap is quantified and then converted into a physician requirement. Simulations are generated at the specialty and Local Health Integration Network (LHIN) levels. Supply Module Needs Module Supply of Physician Services GAP Population Need for Physician Services HHR Requirement

5 5 Model Structure - Supply Module The Ministry currently operates a successful supply-based physician simulation model called the Assessing Doctor Inventories and Net-Flows (ADIN) model. ADIN tracks the progression of a physician from entrance to medical school, through post-graduate training, to practise and then retirement while applying various migration and attrition rates. Requires data inputs from multiple sources. Historical success of ADIN: Supply Module Education Migration Attrition Supply 2008 OMA Physician Survey Productivity

6 6 Model Development 2008 OMA Physician Survey All physicians in Ontario were surveyed. Two surveys were developed: one for family medicine (FM) physicians and one for specialists. Survey asked for information on: total pt. encounters, total hours of patient care, time spent and # of encounters for all 22 major ICD-10 diagnostic categories and sub-categories, geographic location of pts, and total weeks of work in a typical year. The survey was conducted in May ,887 responses were received representing approximately 14% of Ontario physicians. Response rates were fairly representative based on age, sex, specialty and location of practise. Where there were gaps, targeted resurveying was completed. The survey determined the top 10 conditions/diseases that are treated in Ontario. These 10 are the basis for needs side of the model. The top 10 in order of most physician time spent are: 1. Mental and behavioral disorders 6. Diseases of the digestive system 2. Diseases of the circulatory system 7. Endocrine, nutritional and metabolic diseases 3. Diseases of the musculoskeletal system and connective tissue 8. Diseases of the genitourinary system 4. Neoplasms 9. Diseases of the nervous system 5. Diseases of the respiratory system 10. Diseases of the skin and subcutaneous tissue

7 7 Model Development Productivity Panels For purposes of model development, productivity is defined as: the number of patients seen by the physician s practice for a given amount of time. Four expert panels were convened in May 2008 to examine the impacts of four major categories on physician productivity. 1. Information and Communication Technology: to determine the impact of advancements such as electronic health record, etc. 2. Non-Physician Clinicians: to determine the impact of other health professions (e.g. NPs, PAs, etc.) through inter-disciplinary collaboration & team-based care. 3. Health System Change: to determine the impact of policy interventions such as the implementation of Family Health Teams and Ontario Wait Times Strategy. 4. Funding: to determine the impact of various physician compensation models such as fee-for-service, alternative payment programs and other blended models. An extensive literature review was completed for each category s impact on physician productivity. A background paper was prepared for each panel participant s advance review. A scoring workbook was also prepared for panel participants to record how they thought each category affected physician productivity. The panels did not yield definitive evidence regarding productivity for every single category. Some evidence suggests a productivity enhancement in certain areas (e.g. team-based care). However, the model contains all productivity data fields which can be populated in the future as better data and evidence becomes available.

8 8 Model Structure Needs Module The key component to this project is capturing and incorporating various population health needs into the forecasting model. Stats Can and the Canadian Community Health Survey are the major sources used to obtain quantifiable data for population demography and socio-economic & lifestyle risk factors. These wide range of risk factors are examined to determine their impact on the future incidence and prevalence of the top 10 diseases. Expert Panels were convened to determine how much each factor contributed to each disease. Needs Module Top 10 Diseases Socio-economic & Lifestyle Risk Factors Population Demographics Disease Weights Expert Panels

9 9 Model Development Disease Weights Expert Panels In June 2008, a 2-day Expert Panel was convened to determine how each demographic, socio-economic and lifestyle risk factor contributed to the future incidence and prevalence of the top 10 diseases. Participants included physicians, researchers, epidemiologists, representatives from disease associations and policy makers. A subsequent panel was held in September 2008 with participation from the OMA section chairs (i.e. physician reps of various specialties) to further refine and validate the results of the June expert panel. The demographic, socio-economic and lifestyle risk factors examined are: Age Sex Alcohol Consumption Consumption of Fruits and Vegetables Stress Lack of Sense of Belonging in the Community Obesity Smoking Second Hand Smoke Exposure Income Physical Inactivity Employment in the Mining Industry Also considered but removed due to lack of data were environmental and genetic factors.

10 10 Model Structure How It All Fits Together Supply Module Needs Module Education Migration Attrition Supply Productivity Top 10 Diseases Socio-economic & Lifestyle Risk Factors Population Demographics Productivity Expert Panels Disease Weights Expert Panels 2008 OMA Physician Survey Supply of Physician Services GAP Population Need for Physician Services HHR Requirement

11 11 Provincial and LHIN Level Results Base Simulation

12 12 Base Simulation Physician Variance Over the next few years, Ontario will move from a shortage of specialists and family doctors to a point where there may be a sufficient number of physicians in the province to meet population needs. However, as the next slide will demonstrate, it is not appropriate to aggregate all specialists together.

13 13 Base Simulation - Select Specialists Gaps If we examine the specialist group in further detail, it shows that some specialties will continue to experience shortages into the future. For other specialties, there may be a sufficient number provincially in the future, however it is also important to examine geography. This a select group of specialties for illustration.

14 14 Base Simulation Family Physician Gap for Select LHINs Just as it s important to examine specialties individually, it is also important to examine various geographies across the province. For family doctors, although there may be a sufficient number provincially, certain LHINs will continue to experience a shortage in the future.

15 15 2,000 1,500 1,000 Phy sician Gap , WHAT IF SCENARIO: All Physicians in Ontario Reduce Their Avg Clinical Hours Worked by 2% Over 10 Years Year The power of this simulation model is in it s ability to help us understand various scenarios. In this example, the average number of clinical hours physicians work has been reduced by a total of 2% over 10 years to understand the impact on the gap between supply and need. This has actually occurred over the last 10 years. Family Medicine - Base Family Medicine - Hrs Simulation Specialtists - Base Specialists - Hrs Simulation

16 16 Next Steps The OMA has briefed their Board and Council. They have approved the release of the results. A final report including results has been posted on the HFO public website at: on_model.aspx Further technical work is underway to review the method to determine the current shortage of EM physicians and anesthetists. The PSC working group that sponsored the development of this model will also examine alternate simulations and work with health system experts to further understand results and implications for workforce planning. Psychiatry, general internal medicine and lab medicine will be examined first. Certain parts of the model will be streamlined and enhanced. The Conference Board is under contract for one year to provide support and assist with the first full data update of the model.

17 APPENDIX Physician Supply Trends in Ontario

18 18 Confidential: Not for Distribution First Year Undergraduate Enrollment in Ontario Medical Schools, 1991/92 to 2011/12 1,100 1, Med Students / / /94 10% Cut 1994/ / / / / / / / / / / / / / / / / /12 Sources: For Years 1991/92 to 2009/10: Office of Research and Information Services, Association of Faculties of Medicine of Canada (AFMC), Dec 2009 For Years 2010/11 and 2011/12: Ontario Ministry of Training, Colleges and Universities, Spring 2010 Note: The AFMC data will contain a small number of trainees not funded by the Ontario Government. It also includes a small number of repeaters and returnees from leaves of absence.

19 19 Confidential: Not for Distribution First Year Post-Graduate Residents in Ontario Medical Schools, 1995/96 to 2009/10 1,100 1,087 1,000 Residents / / / / / / / / / / / / / / /10 Source: Ontario Physician Human Resources Data Centre, Post-Graduate Medical Trainees in Ontario Reports, Various Years

20 20 Confidential: Not for Distribution Actual and Projected Residency Graduates in Ontario, 2003 to ,400 1,200 Actuals Projections 1,159 Number of Post Graduates Exiting 1, Year Family Medicine Specialists Total Physician Graduates Source: Ontario Physician Human Resources Data Centre, Various Years and the Assessing Doctor Inventories and Net-Flows Model (ADIN), 2007 Base Year

21 21 # of Physicians Total Ontario Physician Supply, 1995 to ,500 24,000 23,500 23,000 22,500 22,000 21,500 21,000 20,500 20,000 19,500 19,000 18,500 18,000 17,500 17,000 16,500 16,000 15,500 15, ,358 Source: Ontario Physician Human Resources Data Centre, Physicians in Ontario Reports, Various Years

22 22 Net Gain in Ontario Physicians, 1996 to 2009 # of Physicians Gain About 115/Yr Gain About 350/Yr Gain About 500/Yr Source: Ontario Physician Human Resources Data Centre, Physicians in Ontario Reports, Various Years

23 23 Physicians per 100,000 Population in Ontario, 1995 to Physicians/100, Source: Ontario Physician Human Resources Data Centre, Physicians in Ontario Reports, Various Years