Toward a Policy Framework to Improve the Health Care of Homeless Individuals
Kirk A. Collins, PhD, LLM, MA, BA, CPA, CGA
ABSTRACT
Homeless (and otherwise displaced) individuals in Canada commonly experience inadequate access to healthcare services. This article considers policy options to incentivize family physicians to prioritize the healthcare needs of this vulnerable population. Typical policy responses seek to link enhanced compensation to the provision of services to homeless people. Various models for structuring physician compensation have been proposed or are already in use. Less attention has been paid to the overall difference in the value associated with any particular compensation model and how this could affect incentives. Using internal rates of return to measure the impact that policy changes have on family doctors’ investment considerations in the health care profession from medical school onward, this research explores the impact that alternative compensation structures, both in terms of time and money, have on the age-earnings profiles of family doctors. Findings show that policies designed to alleviate financial burdens (such as medical school tuition) earlier in the life-cycle have a much larger impact and can be done with a zero-net cost to public spending when enacted in conjunction with contractual obligations to provide direct patient care to homeless individuals, than similar policies that phase in benefits towards retirement; although, all such policies are preferred to the status quo and can be seen as making a Pareto improvement.
Keywords: Physicians, Family; Public Health; Homeless Persons; Emergency Service, Hospital.
| Acknowledgements: n/a Author(s) Affiliations: Associate Professor, School of Business, Trent University Author Contact: [email protected]. Cite: Collins, Kirk A (2023). Toward a Policy Framework to Improve the Health Care of Homeless Individuals. Canadian Health Policy, AUG 2023. https://doi.org/10.54194/MYRE6643 | canadianhealthpolicy.com. Disclosure: No conflict of interest declared. Open Access Sponsor: Not sponsored. Status: Peer reviewed. Submitted: 11 JUL 2023. Published: 14 AUG 2023. |
INTRODUCTION
In any given year, it is thought that around 235,000 people in Canada experience homelessness, with around 10-15% of those experiencing homelessness on any given night (Gaetz et al, 2016). While many of these individuals have long been marginalized by a medical system that by design is largely reactive to displaced people, the recent pandemic has shone a light once again on the plight of many homeless (and poor or underserved) people within our country and the medical care afforded to them (Salvalaggio et al, 2022; Schiff et al, 2020; Gilmer and Buccieri, 2020). Advocates of policy changes to address this shortcoming have often pointed to more public funding for all geographical areas across the country, whether rural or urban (Schiff et al, 2020; Buccieri and Schiff, 2016). The approach used here builds on this previous policy research, but rather than asking for more funding, it is suggested that a redistribution of funds might be the better option.
To explore the impact of the redistribution policies, changes to family physician’s rates of returns are examined. The methodology employed takes a wholistic perspective of the investment pathway when becoming a doctor and maps the implications from the progressive tax system and post-secondary education systems in Canada, to examine the impact on returns to the entire investment. Also explored is the possibility of tweaking the fee-for-service billing structure and other small changes to help account for the additional time, effort and care needed to deal with this vulnerable and underserved part of the population.
Previous research has shown that those experiencing homelessness tend to have higher mortality rates, in addition to a host of wide-ranging health problems with higher likelihood, than the general population (Hwang, 2001). Studies have shown that homeless individuals are likely to be admitted to hospital at a significantly greater rate, when compared to other segments of the population, use health care at a higher level, and to likely obtain their medical care through emergency rooms (Hwang, 2001; Strobel et al., 2021). Taken in conjunction with the recent pandemic and the ongoing impact on Canada’s emergency rooms, the policy considerations examined here are somewhat timely (Mehler-Paperney, 2022).
The health care system in Canada is simply not designed to care for homeless individuals to the same extent as other segments of the population, whether it comes in the form of accessibility in getting to a doctor’s office, the lack of having a health card, the elimination of good faith billing (Bellefontaine, 2019; OHIP Bulletin 4303, 1997), or simply the lack of a permanent address. These constraints are often broken down into predisposing factors, enabling factors and need factors (Hwang and Henderson (2010). The policy experiments examined here are designed to help address some of these factors by incentivizing the need for effective health care for homeless individuals and internalizing a factor that can help alleviate some constraints to the physician, when allowing part of their practice to be dedicated to the care of homeless individuals.
To realize the goals set forth, a simple empirical analysis is employed, examining the implications of loan forgiveness, direct cost adjustments, and billing restructuring on recent medical graduates willing to take up, at least in part, the call to help the homeless receive effective medical care. Findings show that policies designed to help alleviate financial burdens early in the working life of family doctors (or medical students in family medicine) are most advantageous at incentivizing health care of marginalized and homeless individuals, but that all policies examined are seen as a Pareto improvement over the status quo.
METHOD
To illustrate the implications and impact that come from the policy recommendations, internal rates of returns (IRRs) are used to model the before and after-tax returns from changes in medical school graduates’ lifetime earnings. These measurements are also used to get an indication of the impact of the tax system on their earnings, by computing effective tax rates (ETRs). The concept and methodology of human capital IRRs and ETRs has been discussed in Collins and Davies (2004) and Burbidge et al (2012). Their methodology is applied here to the case of medical school graduates and used to explore the implications that come from various policy initiatives aimed at helping to alleviate costs to the medical system and redistribute funds where they can have more direct impact. As a corollary, the research here also advocates the need for street medicine to form an integral part of the medical school curriculum (Cohen et al, 2019).
The internal rate of return is calculated by setting the net present value (NPV) equation to zero and solving for the discount rate, which is in the equation below, where g represents the gross or before-tax IRR. The NPV equation can be written as,
[to access the formula download the PDF]
where i and j represent different programs of education (ie. the difference between earning a medical doctorate, MD, and an undergraduate bachelor’s degree). Computing after-tax values for earnings for education programs i and j, and any tax implications on direct costs , would provide us with the net-of-tax or after-tax IRR .
Finding the proportional difference between the before- and after-tax IRRs will give us an estimate of the impact of the tax system on the investment (ie. the ETR). The effective tax rate can be written, as follows,
[to access the formula download the PDF]
Knowing what the ETR is can help when exploring the policy implications designed to further incentivize the need for increased medical care for homeless individuals, since it is the after-tax impact on family physicians that plays the biggest part in policy changes. Ceteris paribus, a before tax increase in the IRR may or may not result in an after-tax increase, as well, due to the graduated structure of the tax system in Canada. It could be that the magnitude of the change in before-tax IRR’s is muted in an after-tax sense. It could also be the case that the nature of the comparison between alternative education streams results in an increase in ETRs, as Burbidge et al. (2012) found with more advanced degrees (MA, PHD’s). By its very nature, the ETR will also illustrate the implications to the public coffers, in terms of the tax revenue collected. So, a rise in after-tax IRRs, could be seen as a muted win-win (or 2nd best outcome) for all parties involved, since family physicians are taking home more income after-tax and the government is receiving additional revenue because of the higher income taxes being collected; the resulting increase in ETRs that is likely to result from this scenario, may not necessarily be seen as all bad, in other words.
It can prove difficult to accurately measure the recent salaries of physicians, by age, net of any overhead costs, due to the scarcity of available data. In an effort to explore the latest tax implications on investing in a medical education and examine timely policy experiments, current information on family physician earnings in Toronto, Ontario from Payscale.com, is used.[1]
The data are for January 2022, which are used to represent year-end 2021, when computing returns and the tax implications. The data are broken down by experience quintiles and mathematical interpolation is used to compute the missing data to complete the age-earnings profile for two ages ranges: 30-60 and 30-69.[2] FIGURE 1 illustrates the shape of the before-tax age earnings profile, which is characterized by four distinct steps: the outflow associated with undergraduate education, the outflow associated with medical school, the inflow from residency, and finally the inflow from being a licensed physician. The federal tax system in Canada and the Ontario tax system, in 2021, are used to get an indication of after-tax earnings, taking into consideration EI, CPP, and Ontario surtax, as well as non-refundable tax credits (e.g., Canada employment amounts).
[to access figures download the PDF]
| FIGURE 1. Estimated Age-Earnings Profile, Family Physicians, Ontario, 2021 |
Similar to medical school graduates, it can be difficult to obtain recent university earnings by age and field of study for undergraduate BA’s in Canada. As such, the data for undergraduate bachelor students are retrieved via a novel project being run out of the United States, entitled the Hamilton Project.[3] Earnings by degree, and field, are provided by age throughout the entire life cycle and are provided for as recent as 2018. To convert the 2018 US earnings to Canadian, we use the annual exchange rate in 2018, and inflate the earnings to 2021, the year of the policy experiments, based on the inflation rate from 2018-2021, which is derived from the Bank of Canada inflation calculator.[4] Since students who pursue medical degrees tend to be of a higher quality, than the average undergraduate student, the earnings for accounting and actuarial science are used, as the base case.[5] The earnings profile of these undergraduates is higher than the mean and are believed to more accurately reflect where medical students would likely have ended up, had they not gone on to pursue their medical degree (MD); that is, the opportunity cost of the MD is more accurately reflected by using an upper quartile earnings profile, such as that received by accounting and actuarial graduates.[6]
Using the age-earnings profiles of MD and BA graduates, the earnings differential of the two graduates, both before and after-tax, are derived. These values, derived for ages 30 until retirement (at age 60 or 69), provide a representation of the cost/benefit of going to medical school and graduating to become a licensed family physician. Tuition values for medical students and undergraduate students represent the direct cost (outflow) part of the investment in post-secondary education.
Before-tax internal rates of return are calculated as a sum of all the costs and earnings associated with the acquisition of a medical degree, as per the earlier NPV equation. Similarly, after-tax IRRs are akin to this, except they consider the implications that come from the tax system to acquiring a medical degree, as well as any eligible credits.
The path to becoming a doctor is described as follows: 19-22 Undergraduate Degree, 23-26 Medical School, 27-29 Residency, 30+ Licensed Doctor. Ages 19-26 represent the period with which a student must go to post-secondary education to achieve her/his medical degree. These years are characterized by having to pay tuition and realize opportunity costs of earnings otherwise forgone, since the individual is still in school. So, 19-22 year-old undergraduate students are forgoing the earnings of high school graduates (less summer earnings), while those aged 23-26 are forgoing the earnings of bachelor graduates, while in medical school. The yearly cost of undergraduate tuition is $6,145, for four years, while medical school tuition amounts to $27,304/year.[7] Once medical school is completed, there is a period of residency (27-29), before these individuals become licensed doctors (at age 30).[8]
RESULTS
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TABLE 1 provides estimates for IRRs and ETRs for family physicians in Ontario, in 2021. The early retirement option (60) and the later retirement option (69) are both explored in the policy experiments, as per Collier (2017). Not surprising, as can be seen in TABLE 1, the reduction in the earnings lifecycle by leaving the profession at 60, as opposed to 69, is met with a reduction in rates of return and an increase in ETRs. The latter being a direct result of the graduated rate structure in income taxes and the reduction in earning years.
The magnitudes of the rates, and high ETRs, are consistent with the earlier findings for graduate students (MA and PHD’s) in Burbidge et al. (2012). The base case results in TABLE 1 are designed as a reference point for the subsequent policy experiments. Therefore, any changes to the status quo can be assessed based on the overall impact to these measurements.
For the first policy experiment, the implications that come from offering free medical school tuition to students who opt to go into family medicine, on the condition that they earmark part of their future patient base to the care of homeless individuals, are explored. The results are illustrated in TABLE 2. As expected, the returns for both retirement ages are increased quite substantially over the base case. It is also interesting to note that free tuition, while impacting the direct costs to schooling, also indirectly impacts the effective tax rates of graduates. So, while it does not directly impact the post-graduate earnings profiles, the overall impact on the rates of return are lessened due to the cost structure being alleviated earlier in the lifecycle, resulting in a larger numerator in the earlier NPV equation.
What’s particularly interesting about TABLE 2 is that the early retirement option, which is an option that most doctors would like to have (Collier 2017), now has a reasonable return on the investment; in fact, the after-tax return for the early retirement option is roughly 29.5% higher in TABLE 2, than it was in the base case. Furthermore, the early retirement option in TABLE 2 is 18.6% higher than the age 69 retirement in TABLE 1. A similar conclusion is reached, when looking at phased retirement in the last experiment in the table. In this case, the physician works full time, full year, until age 60, at which point their workload changes to 60% of their full-time hours. Given the heavy discounting that takes place at the end of the earnings profile in the IRR calculation, the phased retirement has only a marginal impact on the net IRR and ETR calculations, when compared to early retirement; although, the effects are indeed positive. So, while phasing in retirement does provide additional pensionable security post retirement, it does not add significantly to the return of working past 60. Of course, in terms of work-life balance, the benefit of phased-in retirement may be a preferred choice.
It is interesting to note that even if the government were to directly fund the “free tuition” program (i.e., pay the tuition for family physicians in this program directly to medical schools, so no lost revenues were experienced by such schools), the recouped future costs from reduced emergency rooms visits are more than enough to offset the investment. To make this point clearer, consider the following calculations.
The American Medical Association, reporting on a profile survey done by the American Academy of Family Physicians, stated that a typical family doctor would spend about 34 hours per week in direct patient care, 47 weeks per year, and see on average 78 patients a week in the office (plus 8 others outside of the office).[9] A simple analysis of the costs of being seen in an emergency room department ($304 for a typical visit according to CIHI (2020)) versus the costs of being seen by a family physician in or outside of the office (around $50-150 for a typical visit, according to the more common OHIP billing codes) suggests that even if doctors were required to commit only 5% of their patient workload to treating the homeless (so, roughly 4 homeless patients, on average, per week), the resulting outcome would be that their free tuition was effectively “paid off” in just under 4 years of working (3 years, 9 months approximately), assuming the higher cost of a typical office visit ($150). Note that this is roughly the same amount of time they would have had to pay for medical school tuition, during their time in school.
Logistics of enacting the policy aside, for the moment, if a city had 10,000 homeless, these calculations suggest that you would need roughly 54 doctors to be taking part in the “free tuition” policy to be able to provide effective health care needs to all homeless; and this would all be done outside of an emergency department. Considering how many medical doctors are graduating in Ontario a year, that number does not seem all that insurmountable. The policy itself may also help alleviate, in part, the structural problem of not having as many medical school graduates choose family medicine as their specialty (McKeen, 2022). And with medical schools in Ontario expanding their numbers, the time seems opportune for such innovation (Rushowy, March 2022).
Before moving on to the next experiment, note that while the hope, of course, is that any physician taking part in this program would continue to offer care to their homeless patients beyond any arbitrary time requirement placed on participation in the program, it is recognized that such a requirement may not be the most practical, when considering the need for uptake. For instance, requiring participation in perpetuity could result in doctors feeling unable to further their training into more specialized areas or to expand their practices in desired ways. This time constraint issue is examined a little later in the paper (TABLE 4).
In TABLE 3, the first two experiments explore the possibility of letting medical school students, who are interested in choosing family medicine as their speciality, study for free during their time at school, but being required to repay an interest-free loan equivalent to the full tuition amount they would have paid, in equal installments for 10 or 20 years, starting upon their licensing (age 30). The repayments will come out of after-tax income, and therefore have no impact on the gross IRRs. What’s interesting here is that shifting the financial burden of paying for medical school until after family physicians get licensed, results in some significant improvements to the IRR over the base case scenario in TABLE 1; net IRR increases 12.4% for the 10-year repayment plan, while the 20-year leads to an 18.7% increase. Given the requirement of paying for tuition out of after-tax earnings, the ETR is biased upwards, due to the proportional difference only being impacted by the change in the net IRR.
So, in these experiments, the policy results in a positive impact on the earnings profile, it defers the direct cost impacts, and it results in more doctors helping to provide care to the homeless population, which, in turn, decreases the amount of cost required to administer such care in emergency departments, as shown above. Furthermore, the logistics aren’t all that difficult to administer, either. Medical Schools would oversee the tuition waivers, while the repayment would be akin to the provincial loan management systems (for instance, OSAP) that already have the infrastructure and systems in place to track.
The last experiment in TABLE 3 takes the repayment of the interest-free loan from having to be paid out of after-tax income and moves it to before-tax income. Withholding loan payments here is designed to be somewhat akin to withholding taxes that are used by employers for income tax purposes. Physicians would have their gross billing payments reduced by the loan payment. Taxes would then be applied to the remaining income to determine after-tax income. The impact of the change is positive, when compared to the base case, for every measurement; the gross and net IRRs rise, while the ETR is reduced. The innovation of withholding the loan payment from before-tax income lessens the impact of the progressive tax system. Combine this with the delay in paying for medical school, in addition to the requirement of treating homeless individuals as a part of the medical practice, and the policy has positive implications for government funding and physician returns. In fact, in this case, the policy would result in two streams of revenue for the government: a direct one and an indirect one. The indirect one is the one spoken of earlier in having homeless individuals be seen by family physicians in or out of office, rather than in the emergency room, while the direct impact is the repayment of the interest-free loan.
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In TABLE 4, time constraints and billing incentives are introduced to the program. To do so, a similar policy to one that is used to for medical doctors for the U.S. military, is explored; namely, that they are required to commit to 7 years of active service after residency (the Uniformed Services University of the Health Sciences program). Adding a twist to this policy, the care of homeless patients is re-incentivized past the 7-year window by allowing family physicians to start billing at +50% the normal rate, when treating homeless patients. It is important to note that even with a 50% increase in associated fees, the resulting cost to the public system is still less than the average trip to the emergency room department, according to the numbers reported earlier. The frequency of the doctor visits could even marginally increase and still result in a favourable cost-benefit.
One must also not lose sight of the fact that the positive externalities on being healthy are far reaching and the overall impact of increased health care for homeless individuals will likely far outweigh any monetary benefit that results from the proposed policies. To contrast the results in TABLE 4 with the earlier experiments, the implications of having increased billing rights, past the 7-year window, for physicians who paid full tuition, while in medical school, are also explored.
For each respective case in TABLE 4, when compared to the base case (TABLE 1) and TABLE 2 experiments, the outcomes are positive, with higher IRRs and lower ETRs (except for phased-in retirement). So, even with such a small percentage of the patient workload being earmarked for homeless individuals (5%), the resulting increase over the age-earnings profile is overwhelmingly positive, as is the impact on the health care system, in general.
CONCLUDING REMARKS
Policy considerations are provided to incentivize family physicians to further help alleviate the inadequate health care homeless (and otherwise displaced) individuals receive in Canada. Using internal rates of return as means to measure the impact that policy changes have on family doctors’ investment considerations in the health care profession from medical school onward, the impact that alternative compensation structures, both in terms of time and money, have on the age-earnings profiles of family doctors, are explored.
Findings show that policies designed to alleviate financial burdens (such as medical school tuition) earlier in the life-cycle have a much larger impact and can be done with a zero-net cost to public spending when enacted in conjunction with direct patient care to homeless individuals, then similar policies that phase in benefits towards retirement; although, all such policies are preferred to the status quo and can be seen as providing a Pareto improvement for health care stakeholders.
What’s more is that all of this can be done with (a small subset of) family physicians only earmarking 5% of their practice to the health care of homeless individuals. The logistics of enacting such a change are also not insurmountable, as discussed. Given the plight that the recent pandemic shone on homeless individuals, the redistributive policy being proposed is a simple, yet effective way to help alleviate some of the issues currently plaguing the health care system in Canada.
REFERENCES
Bellefontaine, M. (2019, Dec 3). Ending ‘Good Faith Billing’ could hurt Homeless without Health Cards, NDP says.” CBC News. https://www.cbc.ca/news/canada/edmonton/alberta-health-care-homeless-1.5383057
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Card, D. (1999). The causal effect of education on earnings. in Handbook of Labor Economics, Vol. 3A, ed. Orley Ashenfelter and David Card (Amsterdam: North-Holland).
Cohen, A., Falzone, N., Feeney, B., Hardy, C., Hasmi, S.S., Hoang, T., Leps, C., Mithani, K., St.Hilaire, B., Yu, A., and Wen, S. (2019). Medical Education Coverage of Homelessness within Canadian Curricula. Canadian Federation of Medical Students, Position Paper, March, pp.12.
Collier, R. (2017). The Challenges of Physician Retirement. Canadian Medical Association Journal, January 16; 189: E90-1.
Collins, K.A., and J.B. Davies (2004). Measuring Effective Tax Rates on Human Capital: Methodology and an application to Canada. In Measuring the Tax Burden on Capital and Labor, ed. Peter Birch Sorensen (Cambridge, MA: MIT Press).
Gaetz S, Dej E, Richter T, Redman M. (2016). The State of Homelessness in Canada 2016. Toronto: Canadian Observatory on Homelessness Press.
Gilmer, C., & Buccieri, K. (2020). Homeless patients associated clinician bias with suboptimal care for mental illness, addictions, and chronic pain. Journal of Primary Care & Community Health, special collection on how socioeconomic status affects patient perceptions of health care (11), 1-7.
Hwang, Stephen W. (2001). Homelessness and Health. Canadian Medical Association Journal, January 164(2): 229-233.
Hwang SW, Henderson MJ. (2010). Health Care Utilization in Homeless People: Translating Research into Policy and Practice. Agency for Healthcare Research and Quality Working Paper No. 10002, October, http://gold.ahrq.gov
McKeen, A. (2022, April 27). Amid Shortages of Family Doctors across Canada, Med School Grads increasingly don’t want the jobs. The Toronto Star. https://www.thestar.com/news/canada/2022/04/27/amid-shortages-of-family-doctors-across-canada-med-school-grads-increasingly-dont-want-the-jobs.html
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Strobel, S., Burcul, I., Dai, J.H., Ma, Z., Jamani, S., and Hossain, R. (2021). Characterizing people experiencing homelessness and trends in homelessness using population-level emergency department visit data in Ontario, Canada. Statistics Canada Health Reports, Vol 32 (1), January. https://www.doi.org/10.25318/82‐003‐x202100100002‐eng
[1] Data was retrieved on May 31, 2022, and last updated on the website for January 15, 2022. This early 2022 data is used as an indication of the salaries for the calendar year-end 2021. (https://www.payscale.com/research/CA/Job=Family_Physician_%2F_Doctor/Salary/ef577e40/Toronto-ON)
[2] Collier (2017) states that most physicians expect to retire by age 60, but most end up retiring closer to 69. The implications of both retirement ages for the policy experiments are examined.
[3](https://www.hamiltonproject.org/charts/career_earnings_by_college_major?_ga=2.246120643.634132521.1651774746-1206365249.1651774746).
[4] (https://www.bankofcanada.ca/rates/related/inflation-calculator/).
[5] While it is recognized that there is no consensus on the magnitude of ability biases, many authors have suggested the existence of one. Burbidge et al. (2012) calculate an ability bias of 1/3, while other authors suggest 10-15% (Card, 1999).
[6] Similar conclusions are reached in Burbidge et al. (2012).
[7] Undergraduate tuition are from Ontario and taken from Statistics Canada, The Daily https://www150.statcan.gc.ca/n1/daily-quotidien/210908/dq210908a-eng.htm, while Ontario medical school tuition is the average of all Ontario medical schools, taken from The Association of Faculties of Medicine in Canada (https://www.afmc.ca/en/learners/future-md-canada).
[8] For consistency of comparison, high school earnings are derived from the Hamilton Project, while residency salaries are stated on the Professional Association of Residents of Ontario website (see, https://myparo.ca/your-contract/#annual-salary-scale).
[9] See, https://freida.ama-assn.org/specialty/family-medicine.
