Modeling solutions to Tanzania's physician workforce challenge

Abstract

Background: There is a great need for physicians in Tanzania. In 2012, there were approximately 0.31 physicians per 10,000 individuals nationwide, with a lower ratio in the rural areas, where the majority of the population resides. In response, universities across Tanzania have greatly increased the enrollment of medical students. Yet evidence suggests high attrition of medical graduates to other professions and emigration from rural areas where they are most needed. Objective: To estimate the future number of physicians practicing in Tanzania and the potential impact of interventions to improve retention, we built a model that tracks medical students from enrollment through clinical practice, from 1990 to 2025. Design: We designed a Markov process with 92 potential states capturing the movement of 25,000 medical students and physicians from medical training through employment. Work possibilities included clinical practice (divided into rural or urban, public or private), non-clinical work, and emigration. We populated and calibrated the model using a national 2005/2006 physician mapping survey, as well as graduation records, graduate tracking surveys, and other available data. Results: The model projects massive losses to clinical practice between 2016 and 2025, especially in rural areas. Approximately 56% of all medical school students enrolled between 2011 and 2020 will not be practicing medicine in Tanzania in 2025. Even with these losses, the model forecasts an increase in the physician-to-population ratio to 1.4 per 10,000 by 2025. Increasing the absorption of recent graduates into the public sector and/or developing a rural training track would ameliorate physician attrition in the most underserved areas. Conclusions: Tanzania is making significant investments in the training of physicians. Without linking these doctors to employment and ensuring their retention, the majority of this investment in medical education will be jeopardized.

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Modeling solutions to Tanzania's physician
workforce challenge
Alex J. Goodell, James G. Kahn, Sidney S. Ndeki, Eliangiringa Kaale, Ephata E.
Kaaya & Sarah B. J. Macfarlane
To cite this article: Alex J. Goodell, James G. Kahn, Sidney S. Ndeki, Eliangiringa Kaale, Ephata
E. Kaaya & Sarah B. J. Macfarlane (2016) Modeling solutions to Tanzania's physician workforce
challenge, Global Health Action, 9:1, 31597, DOI: 10.3402/gha.v9.31597
To link to this article: https://doi.org/10.3402/gha.v9.31597
© 2016 Alex J. Goodell et al.
Published online: 27 Jun 2016.
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CAPACITY BUILDING
Modeling solutions to Tanzania’s physician workforce
challenge
Alex J. Goodell
1
*, James G. Kahn
2
, Sidney S. Ndeki
3
, Eliangiringa Kaale
4
,
Ephata E. Kaaya
5
and Sarah B. J. Macfarlane
6
1
School of Medicine, University of California San Francisco, San Francisco, CA, USA;
2
Philip R Lee Institute for
Health Policy Studies, University of California San Francisco, San Francisco, CA, USA;
3
Independent
consultant, PRAXIS, Tanzania;
4
School of Pharmacy, Muhimbili University of Health and Allied Sciences, Dar es
Salaam, Tanzania;
5
School of Medicine, Muhimbili University of Health and Allied Sciences, Dar es Salaam,
Tanzania;
6
Global Health Sciences, University of California, San Francisco, CA, USA
Background: There is a great need for physicians in Tanzania. In 2012, there were approximately 0.31
physicians per 10,000 individuals nationwide, with a lower ratio in the rural areas, where the majority of the
population resides. In response, universities across Tanzania have greatly increased the enrollment of medical
students. Yet evidence suggests high attrition of medical graduates to other professions and emigration from
rural areas where they are most needed.
Objective: To estimate the future number of physicians practicing in Tanzania and the potential impact of
interventions to improve retention, we built a model that tracks medical students from enrollment through
clinical practice, from 1990 to 2025.
Design: We designed a Markov process with 92 potential states capturing the movement of 25,000 medical
students and physicians from medical training through employment. Work possibilities included clinical
practice (divided into rural or urban, public or private), non-clinical work, and emigration. We populated and
calibrated the model using a national 2005/2006 physician mapping survey, as well as graduation records,
graduate tracking surveys, and other available data.
Results: The model projects massive losses to clinical practice between 2016 and 2025, especially in rural
areas. Approximately 56% of all medical school students enrolled between 2011 and 2020 will not be
practicing medicine in Tanzania in 2025. Even with these losses, the model forecasts an increase in the
physician-to-population ratio to 1.4 per 10,000 by 2025. Increasing the absorption of recent graduates into
the public sector and/or developing a rural training track would ameliorate physician attrition in the most
underserved areas.
Conclusions: Tanzania is making significant investments in the training of physicians. Without linking these
doctors to employment and ensuring their retention, the majority of this investment in medical education will
be jeopardized.
Keywords: workforce;modeling;doctor shortage;Tanzania
Responsible Editor: Stig Wall, Umea˚ University, Sweden.
*Correspondence to: Alex J. Goodell, 3333 California St, Suite 265, San Francisco, CA 94118, USA,
Email: alexgoodell@gmail.com
Received: 11 March 2016; Revised: 11 May 2016; Accepted: 24 May 2016; Published: 27 June 2016
Introduction
To provide universal health care by 2030, the World
Health Organization (WHO) estimates that the world will
need an additional 10.1 million health care workers (1).
Africa is the continent with the highest need, with a
predicted deficiency of 3.7 million health workers (1). In
particular, there is a shortage of physicians; in 2008,
Scheffler et al.estimated that an additional 120,000 to
230,000 doctors were needed by 2015 to meet the health
needs of Africans (2, 3). Governments and private
institutions make large investments to train these
highly-qualified individuals (4). However, doctors are
more likely than other health care workers to migrate
abroad, stay in already well-served urban areas, or enter
non-clinical professions such as non-profit management
(5, 6). To protect their investments in medical education,
governments must examine how best to encourage
doctors to serve national needs (7).
Global Health Action
æ
Global Health Action 2016. #2016 Alex J. Goodell et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to
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Citation: Glob Health Action 2016, 9: 31597 - http://dx.doi.org/10.3402/gha.v9.31597
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The Tanzania Development Vision 2025 commits the
nation to providing ‘access to quality primary health care
for all’ (8). To fulfill this vision, the government is work-
ing to increase the health workforce, including expanding
the number of doctors from the most recent estimate of
0.31 doctors per 10,000 population to meet the demands
of the population (9). In line with this effort, Tanzanian
universities are expanding their medical student intakes
dramatically. Whereas in 1991 the one medical school in
Tanzania admitted 55 students, in 2015 the Tanzanian
Commission for Universities approved 11 medical schools
to admit a total of 1,580 students per year (10). It is
vital that these students become quality physicians who
practice clinical medicine where they are most needed
in Tanzania.
Leon et al. reported that, on entering medical school,
students in Tanzania in 2005 were more interested in
good salaries and social status than in practicing medi-
cine and that, on graduation, only one-third reported
being more motivated towards medicine than when they
entered school (11). Upon graduation, many medical
graduates cannot find employment. For example, in 2010
the government provided only 280 immediate postings to
632 medical school graduates (12). There is little evidence
as to where the other new doctors went (13), although
some may have left the country or obtained non-clinical
positions (1315).
Rural areas are severely underserved by health workers.
In 2006, only 20% of doctors practiced in rural areas
where 73% of Tanzania’s population live (5). Young
doctors resist rural placement: according to Sikika, 26%
of Tanzanian medical graduates did not report at their
rural posting in 2009 (16). In another study, 48.5% of
medical students said they would reject a posting to a
rural area, giving adverse working conditions as the
primary reason (17).
The Tanzanian government, universities, and national
accreditation body need to revisit the investments being
made in physician education. This includes understand-
ing what happens to doctors when they graduate 
whether they work as clinicians in Tanzania and where
they are most needed in rural areas. Any assessment
should also include an evaluation of potential strategies
to ameliorate the loss of trained physicians from the
health workforce.
Mathematical simulation models of human resources
are useful tools in long-term strategic planning (7). As
part of a collaboration between the Muhimbili University
of Health and Allied Sciences (MUHAS) and the Uni-
versity of California San Francisco (UCSF), we devel-
oped the Increasing Clinically Active Doctors (ICAD)
tool, an interactive, mathematical model that predicts the
distribution and flow of doctors through the educational
and health system. We designed the tool to assist policy
makers to look at options for providing equitable access
to physicians throughout the country.
We describe how the model tracks cohorts of medical
students through career pathways in Tanzania and iden-
tifies losses to the system. We make projections about the
numbers of clinically active doctors up to 2025 and about
the number working in rural areas. We demonstrate huge
losses to the current national investments in physician
education and highlight the need for reforms to retain
and incentivize physicians to work where they are most
needed. We conclude by highlighting the relevance of our
findings for other countries that are expanding their
physician education programs.
Methods
Career pathways for doctors in Tanzania
After discussion with Tanzanian stakeholders and med-
ical education experts, we identified the major career
pathways for doctors in Tanzania. We focused on when
doctors enter or leave clinical practice and enter or leave
rural areas (Fig. 1).
Secondary school students qualify for medical school
on the basis of A-level exams. After a 5-year medical
training program, most graduates take up a 1-year intern-
ship at a national/referral hospital or regional/municipal
hospital, where they learn under the guidance of regis-
tered medical doctors. Upon completion of that year,
they register with the Tanganyika Medical Council. Most
continue to public service positions as registrars for about
2 years. Others bypass the registrar period and directly
enter general practice in rural or urban areas. After at
least 2 years of clinical practice, some individuals will
enter specialized training programs, after which they
are posted to regional, specialized/referral, or academic
hospitals, often in urban areas.
We identified major loss points (LPs) in the system
whereby clinically active doctors are ‘lost’ from the most-
needed areas by transitioning to non-clinical positions or
from rural areas to urban areas (Fig. 1). Some medical
students change disciplines while at university or do
not complete their course (LP1); some decide not
to pursue clinical careers after graduation; and others
change careers after practicing, become unemployed, or
die (LP2). Some doctors leave to work abroad (LP3).
Most clinically active doctors choose not to practice in
rural areas (LP4) and some later shift from rural to urban
areas (LP5).
Model structure
We developed a mathematical model in Excel version
15.17 using a Markov state process (18, 19) with 92
potential states to predict the movement of doctors
through the pathways described in Fig. 1. We based the
input data on available data (such as past medical school
Alex J. Goodell et al.
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enrollment, reported migration rates, tracking surveys of
graduates) and then calibrated the model by estimating
and adjusting variables until the resulting figures repre-
sented the majority of our evidence. In this way, we
created a model that dynamically represented the situa-
tion described in a national facility mapping survey
undertaken in 2005/2006 (5). Table 1 provides the model
parameters. The model utilized constant transition prob-
abilities between the various states, except for the number
of individuals choosing to work in the public sector,
which was modeled as a function of the number of
available positions.
We created a class of medical student admissions for
each year starting in 1990 and tracked their movements
using a yearly time-step through graduation and until
2025, the end point of the Tanzanian Development
Vision 2025 (8). Until 2001, MUHAS was the only
accredited university producing medical doctors (20).
To create a retrospective cohort, we used MUHAS
graduation data from 1990 to 2000 (21), data for 2001
2010 graduates from all schools reported by Sirili et al.
(15), and approved admissions information from 2011
to 2015 from the Tanzania Commission for Universities
(10, 2224). For the prospective cohort, we assumed a
constant number of admissions equal to the number
approved by the Tanzania Commission for Universities
for the 2015/2016 academic year (10), a figure that may
be higher than the actual number recruited. Records were
insufficient to estimate the number of students who
dropped out of medicine by changing disciplines or not
graduating; we used an estimate of 10% of all admissions
suggested by a study from the United Kingdom (25).
We assumed that 20% of graduates did not enter the
clinical workforce after graduation, as suggested by
Bryan et al. (26).
We classified graduate doctors in each time-step by
their state in the system laid out in Fig. 1, as well as by
whether they were clinically active and whether they
worked in urban or rural areas. A doctor could become
clinically inactive by undertaking a master’s degree in
public health, taking a position with an NGO, taking
an administrative position, choosing another profession,
becoming unemployed, or dying. We classified the re-
maining doctors as clinically active, employed in either
the public or private sector. We constrained the number
employed from graduation by the available government
positions, which were set at 280, the figure available in
2010 (12). We assumed an average 7% annual growth in
Fig. 1. Pathways through medical education and graduate employment in Tanzania.
Modeling solutions to Tanzania’s physician workforce challenge
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private sector employment, consistent with gross domes-
tic product growth (27).
We categorized as rural all districts outside of major
cities without a regional hospital (73% of the population)
and all other areas as urban. The 2005/2006 national
facility mapping exercise confirmed that the areas we
classified as urban were the most heavily populated with
doctors (1.15 per 10,000 population), versus rural areas
at 0.1 per 10,000 (5).
The Tanzanian government has not specified how
many physicians it needs in order to fulfill its Deve-
lopment Vision 2025 and meet the health needs of
the population. An often-cited physician-to-population
recommendation comes from the 1993 World Develop-
ment Report, suggesting a level between one and two
physicians per 10,000 population as a minimum (28),
compared to a global average of 14 per 10,000 in 2012
(9). A detailed model of the health needs of Tanzania,
a nation with a high burden of disease, estimated a
minimum requirement of 1.5 physicians per 10,000 popu-
lation by 2015, once non-physician medical and clinical
officers (COs) were excluded (29).
Results
Projected numbers of doctors
Figure 2 shows the career trajectories of graduating
students, assuming that admission rates remain constant
Tabl e 1. Input parameters to the model
Input parameter
Best estimate
used in model Source
Total medical school graduates (selected years)
1990 35 Number of admissions approved by the Tanzania Commission for
1995 35 Universities in 2015 (10), MUHAS records of graduates (21),
2000 49 and (15).
2005 170
2010 400
2015 675
2020 1,422
a
Number of public positions available to graduates
each year
280 Number available in Tanzania in 2010 (12).
Percent of graduating physicians who practice
entirely in the public sector
45% Varies in the model depending on the number of public positions
available and number of graduates seeking clinical practice.
Percent of students who do not graduate (LP1) 10% No data for Tanzania; estimate based on rates from the
United Kingdom (25).
Percent of graduates who choose not to practice
clinically (LP2)
20% Used by Bryan et al. in their model of Tanzanian human resources
for health (26).
Leon et al. report 21% of Tanzanian students plan on studying for
a master’s in public health (11).
Percent of clinically active physicians who leave to
NGO positions per year (LP2)
2.5% Assumed and calibrated in the model to match graduation data
and 2006 mapping survey (5).
Percent of clinically active physicians who enter
non-health-care positions per year (LP2)
2% Assumed and calibrated in the model to match graduation data,
2006 mapping survey (5), and Sikika tracking survey (45).
Percent of clinically active physicians who leave
Tanzania per year (LP3)
1.6% Assumed and calibrated in the model to match (2, 45, 47).
Annual mortality rate 0.9% World Development Indicators for Tanzania, 2014 (27).
Percent of graduates who do not take up positions
in rural areas (LP4)
26% Estimated for Tanzania in 2010 by Sikika (16).
Percent of employed graduates who leave rural
areas per year (LP5)
3.3% Assumed and calibrated to match graduation data and the 2005/
2006 Tanzania Service Availability Mapping survey (5).
Population living in urban areas 27% Estimated by the 2005/2006 Tanzania Service Availability
Mapping survey (5).
Population living in rural areas 73% Estimated by the 20052006 Tanzania Service Availability
Mapping survey (5).
Population growth rate 3% World Development Indicators for Tanzania, 2014 (27).
a
Assuming 90% of enrollees graduate. MUHAS, Muhimbili University of Health and Allied Sciences; LP, loss point.
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at 1,580 a year from 2015. The model predicts that in
2025, with no attrition, there would be approximately 2.6
practicing doctors per 10,000 population in Tanzania.
That is, if all students admitted actually graduate and
stay in clinical practice, there will be an eightfold increase
in the physician-to-population ratio from 2012 levels.
However, the model predicts a steady loss of doctors to
the health system, with about 44% of all Tanzanian-
trained doctors practicing in Tanzania in 2025 and thus
a ratio of 1.4 practicing doctors per 10,000 population
(Fig. 2). Further, with these trends and physician pre-
ferences to work in urban areas, the ratio of practicing
doctors to population in 2025 would be 0.55 per 10,000 in
rural areas versus 2.6 per 10,000 in urban areas.
Losses from clinical practice
Figure 3a demonstrates the distribution of losses of doctors
to clinical practice from 2016 onwards, with reasons for
attrition. By 2025, 56% of all medical school students
enrolled between 2011 and 2020 will not be practicing
medicine in Tanzania. The greatest and escalating loss
is not through emigration but through doctors leaving
the workforce or taking up non-clinical positions (more
than 80% of the total loss). The figure also shows the
impact of students not graduating (at the assumed rate
of 10%).
Losses from rural areas
Figure 3b shows the distribution of doctor losses from
rural areas from 2016 onwards. Beyond the losses shown
in Fig. 3, the graph indicates the loss to rural areas of
doctors not accepting rural posts or leaving them to
return to urban areas. This represents 37% of all rural
losses.
Impact of interventions
We developed ICAD to enable policy makers to evaluate
interventions to address the identified key LPs. ICAD
allows the user to specify an intervention and hypothesize
the impact on the LPs. We illustrate the model’s predic-
tions for two interventions.
Increase the number of public sector clinical positions
available
Many medical graduates are unable to find government
employment. In 2010, the Tanzanian government pro-
vided only 280 immediate post-graduate postings, though
there were over 632 medical school graduates (12).This
situation has persisted since 2010 (15). This is particularly
problematic for rural areas, as approximately 83% of
clinically active doctors in rural areas worked in public
facilities, according to the 2005/2006 mapping project (5).
In order to employ the increasing numbers of graduat-
ing medical students who expect to enter the public
Fig. 2. Projected density of clinically active physicians in urban areas, rural areas, and overall, 20092025, with and without
attrition in 2015 graduates onward.
Modeling solutions to Tanzania’s physician workforce challenge
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sector, the government needs to scale up the number
of available positions. If, for example, the government
were to offer 800 positions for its graduates (just over
half of the matriculating students), we estimate that
the nation would reach 1.68 doctors per 10,000 popula-
tion by 2025. Smaller increments in the number of
students absorbed would still have a notable effect
(Table 2).
Fig. 3. (a) Projected density of clinically active physicians and those lost to clinical practice, 20092025; (b) projected density of
clinically active physicians in rural areas and those lost to rural clinical practice, 20092025.
Alex J. Goodell et al.
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Fellowship for students from rural areas to increase the
number of clinically active doctors taking up rural
positions
Studies suggest that students with parents in rural areas
and those expressing a desire to ‘help the poor’ are more
likely to accept rural postings (11, 30). Students from
rural areas in South Africa and Washington State, USA,
were 300800% more likely to accept a rural posting
after undertaking a rural training track (31, 32). We used
the model to explore retention of doctors in rural areas
through the development of a fellowship for rural students
who plan on practicing in rural areas. Such fellowship
programs require additional training and support during
school. Assuming a program could accommodate 400
fellows and that 90% of those fellows enter rural areas
with an annual attrition rate of 0.5% to urban centers
(compared to the current estimate of 3.3%), the model
projects a doubling of the number of doctors clinically
active in rural areas by 2025. Scenarios using a different
number of fellows or different assumptions about their
acceptance of rural postings and rate of attrition still
exhibit a favorable effect on rural physician-to-population
ratios in 2025 (Table 3).
Limitations
This model, like any other, is limited by uncertain input
parameter values and structural assumptions. First, since
we could not find appropriate data for many model
parameters for doctor movement, we made assumptions
and calibrated the model to reflect the doctor distribution
in the 2005/2006 mapping survey. If the dynamics of
doctors’ workforce choices are markedly different before
or after the mapping survey, our assumptions are less
realistic. Unfortunately, data on the current number of
doctors are contradictory. The Ministry of Health and
Social Welfare (MoHSW) published figures for the num-
ber of clinically active doctors that were considerably lower
than our estimates: 1,481 medical doctors (including
specialists) in 2012, only 200 more than the number
reported by the 2006 mapping project (5, 33). For 2013,
their estimate had risen to 2,194 (13). During 2012 and
2013, our model estimates 2,300 and 2,700 practicing
doctors, respectively. Some of this discrepancy may be due
to a 2012 doctors’ strike, whereby 300 physicians were
dismissed (34); deficiencies in our model assumptions; or
challenges encountered by the MoHSW’s new human
resources for health information system (35). Our model
thus may overestimate the number of practicing physicians.
Second, the model does not capture the wide range
in service availability, but simplifies the situation into
‘urban’, classified as those areas that were best served,
and ‘rural’, classified as those areas that were least
well served. This simplification may obscure significant
heterogeneity in access in both urban and rural areas.
It is possible that in areas with higher doctor densities,
the nature of their employment (private practice, military
hospitals) make them less accessible to the public.
Conversely, it is possible that areas classified as rural
bordered transportation systems that increased access to
health facilities.
Third, the model does not account for mid-level medi-
cal providers, such as assistant-medical officers (AMOs)
Tabl e 2. Predicted numbers of clinically active physicians
resulting from increasing the number of public positions
available to recent graduates
Number of public
positions offered
Number of clinically active
physicians per 10,000 population,
nationwide, by 2025
280 1.33
400 1.41
500 1.48
600 1.55
700 1.61
800 1.68
Tabl e 3. Predicted number of clinically active physicians resulting from offering rural fellowships given the annual number of
fellows and their characteristics
Number of
fellows
Percent of fellows who choose
to work in rural areas
Percent of fellows who leave rural areas to
work in urban areas each year
Clinically active physicians per 10,000
population in rural areas by 2025
0 0.55
100 80 1 0.66
100 90 0.5 0.67
200 80 1 0.79
200 90 0.5 0.81
300 80 1 0.93
300 90 0.5 0.97
400 80 1 1.1
400 90 0.5 1.2
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and COs. COs receive a 3-year post-secondary education
in primary care and are meant to serve in rural postings.
AMOs receive an additional 2 years of training after
3 years of experience as a CO and have training in
emergency surgery and obstetrics. In 2006, there were
slightly fewer medical doctors practicing than AMOs
and over fivefold fewer than COs (5). These mid-level
providers are essential components of the health care
system and complement, but depend on, the availability
of medical doctors (36). Future changes in the number
of AMOs and COs may alter the required number of
physicians.
Fourth, our model did not account for productivity.
The predicted increases in the number of medical stu-
dents in Tanzania may result in a lower quality of
education, as there are limited clerkship and laboratory
spots as well as strained teacher-to-student ratios (37, 38).
With the large number of new students graduating, the
majority of doctors in Tanzania over the next 10 years
will be relatively inexperienced junior doctors, who,
combined with insufficient clinical experience during
medical school, may not be able to meet the health care
demands of the population. In addition, clinics are often
challenged by lack of equipment, poor supervision, and
absenteeism (39, 40). Because our model did not take
into account productivity or skill, these findings are not
evident.
Last, as with any economic model, there exists the
possibility of unpredictable market forces. For example,
perhaps an increase in the number of public positions
available will have little effect if the private sector grows
by an unprecedented amount or if emigration to other
nations’ medical systems becomes easier or more finan-
cially appealing.
Discussion
Tanzania is a long way from having sufficient doctors to
serve its population. According to a 2012 estimate of 0.31
doctors per 10,000 population, Tanzania has the seventh-
lowest physician-to-population ratio of all nations (9).
In addition, there is a dramatic difference in access
between people living in rural versus urban areas. For
example, the 2010 Tanzanian Demographic and Health
Survey reported that out of all women who had given
birth in urban areas in the last 5 years, 7.8% had received
antenatal care from a doctor and 10.4% had been deli-
vered by a doctor compared to 2.1 and 3.5%, respectively,
for women in rural areas (41).
It is appropriate that Tanzanian universities are ad-
mitting more medical students in order to have more
doctors to deliver the Tanzania Development Vision 2025
and beyond. In fact, our model suggests that Tanzania
will have trained enough doctors to reach 1.4 practicing
doctors per 10,000 population by 2025 a remarkable
achievement. The actual number of doctors trained may
be even higher than the model predicts, since we assumed
a steady rate of 1,580 students enrolling every year after
2015, the capacity of programs approved by the Tanzania
Commission for Universities for the 2015/2016 academic
year (10). New medical schools continue to open and
existing schools continue to expand enrollment. Thus, the
number of students enrolling in and graduating from
medical schools between 2016 and 2025 may escalate well
beyond the number used in the model.
The model demonstrates that there are massive losses
in the deployment of those trained. We estimate that of
those who will graduate medical school between 2016 and
2025, 6,400 will be lost to clinical practice, representing
a loss of 50%. Even more serious, in rural areas the
physician-to-population ratio will improve very little over
the next decade and will only reach 0.55 by 2025. The
model predicts that the ratio of doctors to population in
urban areas will reach 2.6 per 10,000 population five
times higher than the ratio for rural areas.
We identified several key points in which those setting
out to become doctors are lost to clinical practice. The
first is before students graduate. There are no definitive
figures for the numbers of students entering Tanzanian
medical schools who do not graduate as doctors, but
Leon et al. demonstrate low motivation on entering and
leaving medical school (11). If the figure is as high as the
10% we estimate in the model, then 1,370 of the 13,700
students who enter medical school from 2011 to 2020 will
never practice medicine. Strategies to improve gradua-
tion rates would include admission policies that require
potential candidates to write statements of purpose or be
assessed through a pre-admissions interview, two policies
that are not currently implemented at Tanzanian medi-
cal schools (25, 42, 43). Although medical schools in
Tanzania are some of the strongest in their region, they
are often challenged by a lack of staff, equipment, and
facilities while being overwhelmed by too many students
(38, 44). Mshana and Pemba suggest that policies focused
on improving the curriculum, especially competency-
based curricula, as well as upgrading equipment, will
assist educational institutions (37).
The second key LP is when a qualified doctor no
longer practices clinically. This can occur at any point in
their careers when they become unemployed or move to a
non-clinical or administrative job. Some graduates never
actually practice medicine, perhaps because they have
lost motivation and sought another type of employment
or because they were unable to find a job (11, 45). We
estimated that 41% of all medical school graduates
between 2016 and 2025 will be lost to clinical practice
in Tanzania for these reasons by 2025. A major concern is
the number of graduates who cannot find employment
immediately after graduating (15). The inequity between
graduating physicians and available clinical positions may
be due to poor coordination between different ministries
Alex J. Goodell et al.
8
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responsible for provisioning and funding these different
sectors (46). We demonstrate that Tanzania could reach
an acceptable physician-to-population ratio earlier by
scaling up the employment of recent graduates in public
positions. This is consistent with the suggestions of
Sirili et al., who argue that large portions of doctors in
Tanzania are lost in the transition from medical school to
employment (15).
The third key LP concerns qualified doctors choosing
to practice abroad. Indeed, 2452% of Tanzanian-trained
doctors worked abroad according to studies published
in 2006 and 2008 (2, 47). Major reasons for poor job
satisfaction and emigration include low pay, poor work
opportunities and environment, and lack of access to
training and advancement opportunities (4850). We
estimated that 1.6% of clinically active doctors leave the
country each year, based on evidence of the number of
Tanzanian-trained doctors working abroad. In the model,
9% of all medical school graduates between 2016 and
2025 will go overseas by 2025, demonstrating that this is
not the same scale of problem as internal migration from
clinical practice.
The fourth and fifth key LPs relate to choices that
doctors make to work in urban rather than rural areas.
We demonstrate that if this loss could be prevented, the
rural ratio of doctors per 10,000 population could reach
1.5 per 10,000 by 2020. Researchers in Ethiopia, Rwanda,
Ghana, and the United States have found that improve-
ments in infrastructure (including equipment), supportive
management, study leave, and pay can increase students’
willingness to accept a rural posting by 11-fold and main-
tain a 5-year retention of 90%, especially when benefits
are packaged in bundles (30, 5052). We explored the
development of a rural fellowship for some medical stu-
dents to encourage them to work in rural areas. Although
we cannot predict the overall success of such an inter-
vention, we are able to show the changes in numbers
working in rural areas for different success rates.
This project has revealed areas for future research.
Creating the model demonstrated to us the dearth of
recent information available not only about the number
of Tanzanian graduates but also about what happens to
them after they graduate (53). Some efforts have been
made to track health professionals in Tanzania by
MUHAS, Sikika, and the MoHSW (35, 45, 53), but we
could not find reliable information to populate many
parameters in the model. The new human resources for
health information system implemented by the MoHSW
will help tracking of all cadres of health care workers
(35), but its data must feed into human resource and
education policy decisions to ensure its utility.
Another key area for future research is into determin-
ing the factors for physician employment. Discrete-choice
experiments completed with Tanzania’s clinical officers
and outside of Tanzania prove that these investigations
are fruitful (50, 51, 54). They should be replicated for phy-
sicians and recent medical school graduates in Tanzania.
Conclusions
To our knowledge, this is the first model exclusively
focusing on the education and employment of physicians
in Tanzania. While the model highlights the need for
more information on medical school graduates, it pro-
vides useful insights into the attrition of doctors trained
in Tanzania. The model suggests that upwards of 56% of
medical students enrolled between 2011 and 2020 will not
be practicing medicine in 2025. In light of these findings,
Tanzanian policy makers would be well served to increase
the health system’s capacity to absorb additional gradu-
ating students and improve physician working conditions,
especially in rural areas. Without these efforts, the goals
laid out in Tanzania’s Development Vision 2025 may be
jeopardized.
Tanzania is not alone in these challenges: 22 other
nations in Africa have physician-to-population ratios
under the minimum recommendation of one per 10,000
(9). Most of these nations are increasing enrollment at
established schools and witnessing the development of
new (largely private) medical schools (55). The pathways
through medical education and graduate employment
and the LPs that we describe are similar in these settings.
Without targeted interventions, we anticipate that other
African countries will face similar challenges in employ-
ing their increasing number of graduates. The dearth of
data available for the model highlights the need to collect
information that will inform the development of inter-
ventions to make the best use of this emerging physician
workforce.
Authors’ contributions
JK, EK, EEK, and SM conceptualized the model. AG
and JK developed the model. AG and SM wrote the first
draft of manuscript. AG, JK, SN, EK, EEK, and SM
contributed to the writing of the manuscript. AG, SN,
EK, and EEK collected the data. AG, JK, SN, EK, EEK,
and SM read and met the ICMJE criteria for authorship.
AG, JK, SN, EK, EEK, and SM agree with the manu-
script results and conclusions.
Acknowledgements
We thank Dr. Rose Mpembeni, Dr. Joyce Masalu, Professor
Leshabari Melkizedeck, and Professor Tom Hall for their contribu-
tions to the development of the model. We thank Mohamed
Mustafa for assistance with manuscript preparation.
Conflict of interest and funding
Funding was provided by the Bill & Melinda Gates
Foundation for the MUHAS-UCSF Academic Learning
Project.
Modeling solutions to Tanzania’s physician workforce challenge
Citation: Glob Health Action 2016, 9: 31597 - http://dx.doi.org/10.3402/gha.v9.31597 9
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Ethics and consent
This study was not human subject research.
Paper context
Tanzania is challenged with one of the world’s lowest
physician-to-population ratios. In response, universities
have rapidly scaled up admissions. We built a model to
track medical students and physicians from 1990 to 2025.
The model predicts enormous attrition from clinical prac-
tice, especially from rural areas. Interventions such as
increasing the number of public positions available to recent
graduates and developing rural-focused training fellowships
may avert this attrition and help Tanzania reach acceptable
physician-to-population ratios nationwide.
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