Forecasting requisite physicians’ density through medical education acceleration strategy towards elimination of workforce deficit in nigeria (2021-2042)

doi:10.21203/rs.3.rs-889328/v1

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Forecasting requisite physicians’ density through medical education acceleration strategy towards elimination of workforce deficit in nigeria (2021-2042)

https://doi.org/10.21203/rs.3.rs-889328/v1

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Background: This paper assessed availability of physicians, supply and demand gap of medical workforce comparatively with the internationally established requisite minimum physicians’ density for Nigeria (2022-2042). It also evaluates the propensity of medical education programme and capability of the Nigerian medical schools to produce sufficient mint medical doctors for effective medical services to population. It also provides projection of estimates of government financing requirement for achieving the targeted number of physicians in the medium to long term.

Methods: Ex-post ‘facto’ quantitative research design and method is employed in the study. Data sets obtained from the relevant Nigerian government’s organisations. Analytical techniques adopted include simple numerical analysis, descriptive statistics, moving average system, demographic estimation methods and projections of future budgetary resource allocation procedures.

Main Finding / Results: Results show that there was a significant deficit in physicians’ density in Nigeria with average annual shortage of 31000. At this range, represents one doctor per 2591 persons as against one-doctor-to-1818 people and shortage of 33000 doctors. Second, the current student enrolment in the range of 3300 to 3600 requires a minimum of 2000300 percent increase in annual students’ enrolment in order to be recording reasonable annual out-turns. With the adoption of a flexible optimum enrolment policy, the result reveals there would be a downward decline in the range of 9%-to-5% in physicians’ shortages which is linked to increase of 250-312%. Thus, Nigeria will be able to produce enough medical doctors and injection to the pool to effectively eliminate physicians’ density deficit in next two decades. Therefore should be replaced with a flexible system. Nigeria would make about one trillion naira savings from medical tourism if Nigeria implements the medical education acceleration strategy as envisage in this paper. Nigeria needs to spend about an average of N313 million annually in next 20 years as against N360 million current spending on foreign medical care (tourism) and with such medical programme funding,

Conclusion: This study provided evidence-based results indicating sub-optimal students’ enrolments and inadequate funding are the root cause of physicians’ density deficit in Nigeria and not necessarily the wage pricing medical labour force. Nigeria is under-producing doctors with about 15000-20000 currently working outside the country. It is illogical that Nigeria’s medical schools have continued to enrol fewer trainees despite a huge deficit of 33000 physicians which implies that about a minimum of 8000-to-10000 for the next two decades in order to clear the shortage or the country will continue to grapple with physicians’ deficit continuously.

Health Economics & Outcomes Research

Health Policy

Physicians requisite density

Medical workforce shortage

population health

labour mobility

accelerated medical education acceleration

Nigeria

Medical education is the pathway of producing doctors and engine room of human health-care services, and sustains human development in economy. Physicians’ medical education, supply and demographic need-based forecasting method consistently applied by countries to gauge physicians’ surplus or shortages over time (1; 2). This approach has guide many countries to implement policy measures to moderate shortage of health workers and Nigerian experience is not significantly different from the trend in other jurisdictions. Paucity of data and lack of empirical studies on physicians’ density in Nigeria particularly scientific health research providing projection of number of physicians to produce in meeting the prescribed minimum ratio of physician to population complicated the situation. Osotimehin (3) explained that health workforce is one of the six components of health system development prescribed in health planning documents but often neglected in developing countries. Tomoko et al (4) opined that there is urgent need to determine the existing number of health workforce before projecting future demand pattern, and prior to designing medical education strategies towards expanding production.

Federal Ministry of Health (FMOH) (2018) (5) reports that there are 74353 registered doctors in its health workforce registry in 2018. Banke-Thomas [6] argues that only about 35000 practising physicians is available in Nigeria; and this gives a ratio of one doctor to 3300 people (0.55 per thousand people of the population. WHO (7) prescribes the minimum ratio of a doctor to population is 39 per 100000; that is, one doctor to 1818 persons and one single doctor to 101108 patients (8; 9). It is estimated that several thousands of Nigerian doctors migrated to foreign countries; which leaves the nation with insufficient number of physicians to effectively healthcare services to 201 million people in 2018, and now increased to 206 million. It is further estimated that Nigeria’s population will reach 400 million by 2050; but currently requires minimum of 111000 doctors for effectively health-care services delivery (6). The existing pool of doctors available in Nigeria is grossly inadequate to provide efficient, cost-effective and equitable healthcare to citizens. It is the same situation in many African countries.

Ogunsola (10) submitted that there were only 35,000 working in the country and argued that Nigeria needs no fewer than 237,000 doctors to meet WHO standard requirements for physicians for effective medical service. Olukadiya (11) stated that about 3000 fresh medical students are admitted into Nigeria’s medical schools annually out of well over 120,000 applications with 2.5% success rate in recent years. The level of annual flesh undergraduate medical students are allocated to about 36 full and partially accredited medical schools currently out-turn on the average 2400 to 3000 new doctors annually. The number of physicians relative to the population has persistently ranked well below the global minimum density for several years. Ayetoro (12) observed that patients at the emergency / intensive care sections of public hospital are often stranded and wait long hours even outside hospital wards in their bid to have access to specialists for urgent treatments. Osundina and Opeke (13) explained that patients’ waiting time constitutes perfect measure of hospital effectiveness and indicator of shortages or imbalance in health workforce. They (13) argued patients’ long waiting time in ‘Intensive care Unit (ICU) are incontrovertible evidence that support incidence of shortage of physicians in Nigeria. They maintained that trend continues as long as imbalance in doctor-to-patient and doctor-to-population is not corrected.

With annual out-turn of 3000 physicians, alternative option is to recruit 38000; which will take over 10 years to produce. Demographics on registration and medical workforce exit in Nigeria’s remains underestimated due to unreliable data-base. The Medical and Dental Council of Nigeria (MDCN), NUC and management of medical schools stuck to restrictive admission system, and undependable enrolment / recruitment policy for replenishing medical workforce in sustainable carrying capacity.

There is no visible record of doctors’ unemployment in Nigeria, but increasing trend of doctors migration to other countries, commonly referred as brain-drain (14; 7). Hence, Nigeria stands to benefit economically from mass production physicians since labour market readily exists globally.

The availability of adequate medical workforce is a critical factor affecting effective delivery of health-care services. Several empirical studies have assessed Nigeria’s physicians’ density, for instance, Adebayo et al (9; 6; 7) argue shortage of health workforce, arises supply gap of doctors over time. Physicians’ shortage is directly linked with underfunding of the medical schools. Osotimehin (2) observed that annual budgetary allocation to the health sector is grossly insufficient and affirmed that paucity of reliable information of public spending on undergraduate and residency programmes hinders doctors’ turnout. The combined federal and state budgetary allocation to health sector is 5.5% of the national public expenditure (2). The sub-optimal resources management practices in public health sector and government organizations impact adversely on medical education, physicians’ shortage and population health outcomes.

Physicians’ shortage in African countries is attributed to lack of infrastructure in medical schools to train sufficient doctors (15). Schefler (2) explained that the cause of exodus is owing to inability government of low-income nations to retain doctors to migrate abroad on reasons better career prospects. Relevant authorities of the health sector, medical profession, regulators and management of medical schools are aware of negative impact of brain-drain syndrome on medical workers. Yet, they impose admission quota system which restricts students’ enrolment. The prevailing policy is hindering optimal enrolments of trainee physicians, and compounding doctors’ shortage in Nigeria.

The objective of the research is to establish physicians’ density alongside forecast requisite density comparatively with the internationally prescribed minimum density to population. This involves medical education acceleration strategy to eliminate shortages in next two decades. Specific objectives are, to: determine whether there is surplus / deficit in extant physicians’ density to the population; determine the extent to which new doctors can be produced under the existing admission quota system as injection to the pool to meet the required physicians’ density provide projection of expected optimum annual students’ enrolments that will turn-out sufficient number of new doctors as injection to the pool to eradicate shortages. It also determines savings that accrues from increased production doctors under optimal enrolment strategy. .

The paper provides useful information to government on medical education and health policy makers to guide in health policy formulation, planning and financing of medical training and health systems development and health sector management.

Physicians’ density describes the required minimum ratio or number of physicians to persons in a country. Physicians’ density analysis is primarily concerned with availability, sufficiency or shortage of doctors and it is used in determining number of physicians’ rendering medical services in a country. Adebayo (9) explained that workforce crisis manifest as shortage acute and demographic imbalance in distribution doctors’ in a nation. Data in table 1, illustrates links population, required minimum density and extant density from 2005 to 2020

Table 1:	Number of Physicians, Physicians' Density to Population
		in Nigeria, 2010–2021
Year	Population	REq. Density	Existing Pocs
2005	139,600,000	76,788	48,162
2008	150,270,000	82,657	52,412
2010	158,523,200	87,196	55,960
2012	170,157,060	93,596	62,190
2014	176,405,000	97,032	65,396
2016	185,960,200	102,288	72,000
2018	195,874,690	107,742	76,384
2020	206,139,600	113,388	82,890
Sources:	National Population Commission; Adebayo (9)

Correspondence demand for trainees into Nigeria’s medical schools indicate that over 120,000 applicants sought admission and 3000 students were admitted with 2.5% acceptance rate in past decade (11). Trend in population linked-doctors demand and supply to requisite physicians’ density-demand for medical education provides glimpse shortfall. The requests and actual enrolments illustrates unsatisfied trainees enrolment which translates supply of doctors to population need and pointer of root causes of shortages, but not necessarily the price of labour

Projection of physicians’ density commence with ascertainment of existing physicians, students’ enrolment, and attrition rate and are built into forecasting future out-turns. Annual rate of exit of physicians arising from emigration are captured as out-flows from the pool (16; 17; 18). The requisite physicians’ density and rolling annual density for next two decades, in comparison with existing physicians’ workforce, estimates of additional annual out-turns; existing and projected estimates of students’ annual enrolments under extant quota system and flexible expected optimal students’ enrolment are covariates of the third objectives. These variables link medical education / with production and supply of doctors and gauges whether subsisting quota admission system could satisfy Nigeria’s future requisite workforce; and ensure efficient health-care delivery (19; 20; 16; 17; 18).

Human capital is defined as expenditures incurred in education, training, and medical services are investments in human capital (21). It contributes in improving health conditions of the society, raise persons income and or earnings, and person’s appreciation in knowledge, expertise, and literacy over a life-time (22; 23; 24). Arrow (25) explained that health human capital investment involves vocational training of physicians, licensure and registration to practice medicine. Arrow further argued that certification in medicine of the doctors and registration by national bodies represent barrier to entry into the health-care industry and monopoly for medical practitioners in provision of medical services. Without this mode of training, the orthodox medical services cannot be legitimately be rendered and based on these premises Arrow elucidated that there is no substitutionability of medical certification. Furthermore, Department of Health [20] states that the commonest health policy for improving medical schools performance is increased funding.

2.2 Nigeria’s Medical Education System, Regulation and Structure

Medical education system in Nigeria is anchored on British medical education and applies to other British former colonies. Nigeria’s medical school system admits predominantly secondary school graduates with requisite credit passes in core science subjects into undergraduate programmes. The programme in general medicine (MBBS) is structured in the UK’s curriculum and runs for minimum of five or six years, depending on entry qualification(s) of registrants’ with additional one-year internship in clinical practice and health care delivery management.

FMOH in collaboration with MDCN regulate the practice of medicine, dentistry and alternative medicine in Nigeria. Nigerian universities are categorised into three based ownership structure, notably; Federal, State and private Universities. Medical education leading to the award of Bachelor in Medicine and Surgery (MB BS) has been structured into two stages, pre-basic medicine course / basic medical programme and clinical studies (11; 27; 28). On successful completion of qualifying examinations and internship, graduate physicians proceed to one-year youth service; making up eight years cycle prior to career employment.

Quota admission system is adopted in Nigeria; and latest report of National Universities Commission [29] indicates that there are 82 NUC approved medical schools, but MDCN accreditation determines the institutions that their graduates are registerable for license. MDCN [30] provides list of 32 fully accredited and six partially accredited medical schools presently. MDCN‘s comprehensive list of fully and partially accredited institutions is available in its web-site. The aggregate admission quota and actual enrolment of medical undergraduates hovered from 2780 in 2007 to 3510 in 2020 academic session(s) (11; 30). There were more than 100,000 candidates seeking admission to medical schools annually in Nigeria annually (27; 11). Distribution of enrolment indicates that University of Ibadan Medical School gets highest allotment of 180; followed by other federal medical schools with 150; some other get 100 whilst the remainders get only 50 slots.

2.3 Theory of medical workforce, density, imbalance; medical education and financing

Theory of physicians-side and population demographic need-based demand gap model with requisite minimum density theory as invoked in (2; 17; 16) is the core theoretical framework guiding this sub-theme. Zurn et al (31). Theory of medical workforce imbalance assesses consequences of lower quality and productivity of health services, closure of hospitals’ ward, increasing wait time, diversion of emergency department patients, reduced number of staff beds, or under-utilization of trained individuals (31). A shortage/surplus is result of disequilibrium between demand and supply for labour, and imbalance in health workforce has featured regularly discussed by researchers and policy makers.

Modern–optimum plant size theory is the framework underpinning production (supply of doctors) and demand function and establish locus of points of the optimum capacity (32). This theory links students’ enrolment and cohort out-turns, facilitate estimation of expected optimum annual intake of medical trainees, injections as well as forecasting of requisite density of physicians to population towards elimination of current and future shortages. This sub-theory is augmented with health-care spending frontier as proxy for government expenditure in medical education in our context. It dwells extensively on enrolment of medical students, new doctors’ inflows, foreign trained doctors / employment of foreigners, availability of sufficient physicians to meet WHO’s minimum ratio to population and sundry issues. Medical workforce availability, demographic density forecasting and supply constitutes the mainframes of health human capital theory (2).

This study adopts ex-post ‘facto’ research design.

3.1 Data Sources, Focal Institution and Collection

This is Nigeria’s specific study of medical workforce, physicians’ density, medical education system, requisite doctors’ density to population. Secondary data-sets were extracted from published government’s reports and include: Departments of Medicine of selected federal universities, MD CN, NBS, National Population Commission (NPC), NUC, FMOH, NBS, and empirical studies.

3.2 Theoretical Framework of the Models

Demographic forecasting of physicians’ density to population-linked demand and need-based supply of physicians (2; 18) and modern optimum plant theory (32) is eclectics of theories supporting models of this study. The combination of physicians-side and population demographic need-based demand gap model with requisite minimum density theory as invoked in (2; 17;16;8) is the core theoretical foundation supporting the projection of inflows of physicians in meeting the internationally prescribed threshold of minimum ratio of 1: 1818 persons of the national population. The modern–optimum plant theory is the framework underpinning production (supply of new doctors) and demand function (request for admission into medicine) Dirks cited in Ahmed, (30). A socially optimum plant size of medical schools at any given time resides within the range of student enrolments which results in lowest cost unit and doctors’ cohort annual outturn.

The estimation of medical education productivity relies on supply and demand gap model and has been frequently used forecasting of density of medical workforce here. The medical workforce data with students enrolment and out-turns trends, facilitates building of physicians projection model. This reckons on current stock of licensed physicians, current inflow of new physicians and recruited foreign doctors, net of withdrawals including emigration as outflows in comparison to the required minimum ratio in determining shortage(s) or surplus at a given time (2). Scheffler-Dal Poz’s model captures aggregate public and private annual investment expenditure on medical education in producing and providing requisite number of physicians in cost-effective and efficient health care delivery. Optimum plant size theory by extension students’ enrolment and productivity facilitates estimation of expected annual intake of trainees as well as forecasting of requisite density of physicians to population towards elimination of shortages (32; 2).

3.2.1 Model variables and descriptions

Models and variables definition and description are given in Table 2.

Table 2

Variable Description and definitions
Acronym	Variable Description	Definition
Species of Socioeconomic Returns Models Employed
SCIR ₍₁₎	Social Capacity Impact Rate (surplus / deficit)	Social Capacity Impact Rate (SCIR) is measure of sufficiency or shortage (imbalance) in medical workforce.
SESR ₍₂₎	Socio-economic Sustainability Rate (based on existing rigid quota admission)	Socio-economic sustainability rate (SESR₁) gauges extent to which current students’ enrolment relative to optimum intakes to turn out newly licensed physicians towards reducing shortages and meeting can minimum density of physicians on a rolling bases in due course.
SESR ₍₃₎	Socio-economic Sustainability Rate (based on existing rigid quota admission)	Socio-economic sustainability rate (SESR₁) gauges extent to which current medical students’ enrolment relative to optimum intakes to turn out newly licensed physicians towards reducing shortages and meeting can minimum density of physicians on a rolling bases in next two decades
NHFS ₍₄₎	Federal Government of Nigeria’s National Health Expenditure Savings	FGN’s projected national savings arising from the lower amount to be expended as government’s subvention spending on medical education acceleration strategy against the cumulative annual expenditure on foreign medical treatment (medical tourism) using $1 billion spends in 2017 as benchmark.
Macroeconomic aggregates used as model variables
PDSS	Physicians’ Density Shortages or Sufficiency (Imbalances)	Physicians’ sufficiency or deficit is a measure of ratio of surplus number of available physicians (or shortage) to the internationally prescribed minimum doctors’ density to population. It is the established demographic measure of imbalance in medical workforce in the economy
PMSE	Prior – subsisting Medical Students’ Annual Enrolment	This represents the subsisting medical students’ annual enrolment which is used as measure of the relationship of current annual medical students’ enrolment with the projection of optimum annual intakes needed to in producing out-turns to meet population need-based requisite physicians density
FMSE	Forecast Optimum-Medical Students’ Annual Enrolment	This is expected optimum future medical students’ annual enrolment projection is the measure of the relationship of current annual medical students’ enrolment with the projection of optimum annual intakes needed to in producing out-turns to meet population need-based requisite physicians’ density
AFFP	Aggregate-to-Annual Financial Estimates and Financing Arrangement Projections	AFFP refer to the total annual expenditure and aggregated financial estimates and financing arrangements of the individual participants and institutions / government to contribute in medical education annually. Financing arrangement shows the scheme of jointly contribution of funds between households and the state in the envisaged strategy
PIME	Private Investment Medical Expenditure i	Private investment expenditure (_PIME) in medical education is the amount expended by a physician during medical studies for acquisition of MB.BS degree and license to practice medicine in Nigeria.
GSME	Government Medical Subvention Expenditure	FGN’s subvention expenditure on medical education is the total expenditure by the medical institution directly and indirectly in the education and training of medical doctors.
Source: The Author’s Compilation (2018; 2019; 2020).

The following assumptions were incorporated in development of the models and analyses:

Table 3

Significant assumptions applied in models development
Significant Assumptions Incorporated in Model Development and Analysis
1	4 percent students’ attrition rate
2	A rate of 1 percent for premature losses and 1.5 percent for emigration for exit of physicians
3	A rate of 1 percent for premature losses and 1.5 percent for emigration for exit of physicians
4	The unit total annual medical education expenditure in Nigeria and this amount has been used as the estimates of static annual of N5 million is applied evenly for the next two decades; with 50 percent lump-sum financing expected to be provided by the State’s treasury
5	Standard retirement age put at 65-to-70 or maximum of 40 years of active service.
6	Public fund used in fund medical education is assumed to be raised from tax revenue, donor funds or project loans from international financial institution without interest, thus interest charges not used.
7	The total medical education expenditure (cost outlay) for the MBBS in medicine degree is six standard years, whereas the seventh (7th ) representing the internship period apparently does not attract additional social cost per se as it provides newly graduated doctors the necessary exposures to practical experience.
8	Average age of medical students at entry is 17/18; average doctor’s age is 25
9	Nigeria’s average annual medical bills/spending via medical tourism is N360 billion ($1 billion) (33)
Source: Authors Compilation (2021).

3.3 Model Specification and Development

The model specifications are provided within this sub-section.

Research Questions:

What is the magnitude of imbalance between extant density of physicians to population and prescribed minimum physicians’ density to population?

To what extent can the Nigerian medical schools produce enough doctors needed to achieve the requisite density of physicians to population based on extant quota system?

To what extent can the Nigerian medical schools produce enough medical doctors needed to achieve the requisite density to population under a flexible system?

(4) Would it be prudent for the Nigerian government to dispense substantial amount of funds on medical tourism, rather than medical education subvention spending?

Formulated hypotheses:

Ho₁: There is no significant difference in the ratio of variation between the actual and the prescribed minimum physicians’ densities to population (on revolving basis) in Nigeria.

Ho₂: There is no significant variation between annual out-turns of mint doctors and requisite physicians’ density based on the prevailing annual students’ enrolment quota system.

Ho₃: There is no significant variation between annual out-turns of mint doctors and requisite physicians’ density based on implementation of flexible-optimum annual students’ enrolment quota system.

Ho₄: There will be no significant difference between future total annual foreign medical spending and the future total public spending tantamount to national savings of the envisage medical education strategy.

(1) Social capacity impact rate (workforce imbalance-surplus and deficit)

This model measures the extent to the available medical workforce contributes to population health outcomes and human development. The model’s equation function is specified as:

SCIR = Pdgv = a + b+ (B₁Cu-dens + B₂ prespys-dens + B_3…+ B_n + u) = 0, 1, 2, or -1, 2, (3.3.1)

(2) Prior enrolment capacity sustainability

This model assesses the extent to which current (actual) medical student enrolment contributes positively in pre-censual density of physicians to population (34; 35). The model’s equation function is expressed as:

PESR₍₁₎ = Mdsv = f₁[(Curr-dens–Mdats)] + B₂[(presphys-den–Pysxt)] + B_n+u) = 0, 1, 2…. (3.3.2)

(3) Sustainability level (enrolment-extrapolation population) optimum capacity

This model assesses the extent to which the forecast–expected optimum student enrolment comparative to the requisite physicians’ density to the pre-censual population estimates in next two decades. The equation functions developed to derive imbalance in medical students’ enrolment towards proactive reduction or eliminating deficit is expressed as follows:

SESR₍₃₎ = f[((pres-phy-dns-Currdens)-(CuMdstE)/1] ……………………… (3.3.3)

(4) Medical education acceleration programme financing estimation/arrangement

This model utilises the aggregate financing projection, particularly estimates of government’s funding comparatively with Nigeria’s average annual expenditure on foreign medical care to measure fiscal gain (savings) accruable from implementing medical acceleration strategy. This model development leans on the computable variation between government subvention expenditure on medical education and the nation’s foreign medical expense in deriving implicit financial gain or extra burden accruing from physicians’ training scheme in next two decades. Foreign medical expense is anchored on Vanguard newspaper [33] which reported that the Nigerian Health of Minister to have stated that Nigeria spent about $1 billion (N360 billion) on settlement of foreign medical expenses of Nigerian alone as such public and private medical expenditure. The system equation function for this model is given as:

NHFS₍₄₎ = f1 [(Total Gsme- FxmedSpnd) / FxmedSpnd )}/. FxmedSpnd = 0, 1, 2, … (3.3.4)

3.4. Operationalisation of Test Statistics

This is anchored on mixture of confirmatory and exploratory data analyses / estimation methods. Results derived in the models is subjected to ‘Absolute Percentage Error (APE) (36) test; a modified version of ‘mean absolute percentage error (MAPE). This approach is applied in deriving social capacity impact rate of workforce imbalance and social sustainability range for medical schools on resource utilization (38) at 5%. This was applied to determine .whether current enrolments capacity falls within optimum enrolment range to eliminate shortage or otherwise. The significance limit is adopted for models at 5% level as acceptance and rejection conditions as parameters to test the results. If the APE yields 0 or 95% (lies within 5% significance level), then the derived economic rate of return is valid but rejected, if otherwise.

Decision rule: if a 5% is also adopted as minimum cut-off acceptance criterion in the models.

4.1 Data Presentation

Descriptive statistics for medical workforce demographics, existing density and requisite density to population, subsisting students enrolments with out-turns, and forecast future optimum enrolments with out-turns (34; 35) and financial aggregates used in analyses are presented in tables 4a to 4d in the appendices (in the data analyses attachment). The longitudinal data-sets are the sources and bases for both the demographics and financial aggregates used and reflected in the descriptive statistics and analyses results.

Descriptive statistics, unit root and co-integration evaluation tests are presented in tables 5a to 5d.

Table 5: Descriptive Statistics: Demographics of Medical Workforce; Student Enrolments, Out-turns, Population and Requisite Physicians’ Densities

Variables	Count	Co-efficient	Std Error	T-Stats	Mean	Min	Max
RecPhy_dens	21	0.487326	0.025363	143.2217	152,584	118,859	188,388
RPhy_dens	21	0.991861	0.006564	151.1159	114,336	85,600	147,040
PhysDens_deficit	21	0,987874	0.007179	137.6048	38,247	33,259	41,338
RecMdsA_ens	21	0.139678	0.023286	133.2486	3.524	3.000	4,000
OptMds_ens	21	0.359197	0.012798	129.2115	11,702	6,000	12,500
ExtMintPhy-Inj	21	0.171671	0.127984	134.1350	3,057	2,304	3,840
OptMintPhys-Inj	21	0.369775	0.241818	153.2137	10,952	2,304	12,200

Source: Author’s computation using E-views 9.0 (Adjustments: once and three)

The outcome of data evaluation tests are given in tables 5b; 5c and 5d in the appendix. Results of diagnostic tests given in table 5b show that the series were integrated of order zero 1(0). The series not integrated in first order were normalised in order(s) of 1(1). Whilst the outcome of ‘Trace and Maximum Eigen’ statistics as provided in tables 5c and 5d respectively indicate that the co-integrating variables fitted well at 5% level in the model. Therefore, we considered the relevant demographics and financial variables to have medium to long-run relationship.

4.2 Results

Results are presented in table 5.

Table 6: Results (in tabulation)

Models	Calc Range	Specified Range	Test Decision
Physicians’ Density Imbalance	31 %	5 %	H_A1
Simulated Density Imbalance (Extant enrolment)	28/34 %	5 %	H_A2
Projected Optimal Density (Flexible enrolment)	9-5%	5 % (NA)	Ho₃
Gsme-National Savings (Health Spend/Invest)	13 %	5 %	H_A4

Source: Authors’ computation (2020; 2021)

(1) Result of first objective yields annual average of 31 % deficits of required minimum density to population. Supplementary regression analysis produces: R= 29% and R-squared of 5.5 percent. Based the results, we adopted H_A1; and concludes that there is significant adverse deviation between existing workforce and requisite physicians’ density to population.

(2) Result of model two yields demand-to-supply deficit of 200-250%. This signifies significant gap in supply and demand gap vis-à-vis shortage of physicians if the extant rigid admission policy is retained. Supplementary regression analysis result yields: R= 36% and R-squared of 6, and implies prevalence of physicians’ density deficit under the existing rigid quota admission system. Hence, alternative hypothesis is adopted. It supports that Nigeria should increase students’ annual enrolment to minimum of 250 % (from 3510–3600 in 2020/2021) in order to produce enough physicians to reduce shortage.

(3) The result yields a downward decline in the range of 9%-to-5% in physicians’ shortages. This is linked to increase of 250-312%. Supplementary regression analysis yields: R = 38% and R² = 6%. This demonstrates that Nigeria under the forecast optimum future medical students’ enrolment under a flexible admission policy. Thus, null hypothesis is accepted. Hence the study concludes that with implementation of flexible admission quota policy and enhanced annual enrolments will produce sufficient doctors to eliminate physicians’ shortages within next two decades.

(4) The expected national fiscal savings is 13 percent on aggregate foreign medical-care spending. This exceeds the 5% minimum social rate of returns on social capital projects in developing countries; therefore H_A4 is accepted as a significant positivity. This signifies that the macroeconomic benefit of government investment in fast-track medical education scheme appears higher than health expenditure on medical tourism.

4.4 Discussions

The first result established significant density deficit of annual average of 31000 is in tandem with findings in Omoluabi (8; 39; 40; 41). Nigeria will continue to experience shortages of medical doctors into unforeseeable future if remedial policy action is not taken henceforth. This result also signifies that Nigeria risks great danger in the event of national or global health emergencies. Dearth of statistical data contributed to this problem requires that government should set-up task-force to conduct enumeration of doctors in Nigeria by 2020 (42; 8; 42).

(2) The extant admission quota system, restrictive students’ enrolments is tantamount to under-utilization of existing physical infrastructure and schools and constitutes a major source of demand-supply-gap. Sub-optimal enrolments and out-turn is a systemic health system problem, is more of time-bomb waiting to explode. The subsisting admissions and enrolment policy implies that the medical schools are unlikely to produce up to 60000 in next 20 years and far below the number needed to off-set medical work force deficit as established in the first objective. With this level of restrictive quota enrolment system Nigeria will not produce enough doctors to satisfy the prescriptive physician density to population.

(3) To reverse the trend of shortages, Nigeria should increase in students’ enrolment from 3000 to 6000 upwards in first three years as from 2022 to 2024; thereafter, increase enrolments further from 7200-8000; then, up to 9600–11000 and reaching its peak of 12500 in the 18^th year of the scheme. Results of second and third objectives demonstrate that the subsisting admission enrolment system is ineffective in producing enough additional doctors into the pool (production ineffectiveness). It is inappropriate for Nigeria with over 206 million (2020) and about 211 million in 2021 with NUC’s approved 83 Universities Department of Medicine and 38 fully and partially accredited medical schools by MDCN produce fewer doctors annually (38). Accelerated medical education system advocated here is similar to the approach in Timor and Leslie and related plans as previous proposed and implemented (19; 20; 18).

There are notable physicians’ training programmes that have already attracted technical assistance from foreign universities to some countries in Africa. New York University’s medical school brazes the trail by implementing tuition-free medical training recently (43; 44). This was possible through some pre-planned fund-raising from where the medical school generated $6 million fund from grant NYU utilised in development of an ultra-modern medical school infrastructure that enabled it to provide tuition free (43; 44) in its reputable medical programme. Nigeria’s medical schools should ‘up their game(s)’; intensify research effort, and innovative in order to attract grants to support their activities. The macroeconomic benefit accruing from the fast-rack medical training scheme include development of sustainable medical capacity with improved health infrastructure thereby reduce over-reliance on foreign medical treatments and achieve savings (45; 46; 47; 48; 43).

5.1 Conclusion

This study provided evidence-based results indicating sub-optimal students’ enrolments and inadequate funding are the root cause of physicians’ density deficit in Nigeria and not necessarily the wage pricing medical labour force. It is illogical that Nigeria’s medical schools have continued to enrol fewer trainees despite a huge deficit of 33000 physicians which implies that about a minimum of 8000-to-10000 for the next two decades in order to clear the shortage or the country will continue to grapple with physicians’ deficit continuously. Our findings are in tandem with prior empirical evidence attests the fact that Nigeria is under-producing doctors with about 15000–20000 currently working outside the country (42). The adoption of accelerated medical education scheme will bring lasting solution to the shortage of health workers in the economy. Financing arrangement can be sourced from taxation, securing of project-tied loan or concessionary fund from international institutions and donations

This policy action will conserve government spending which are likely to be expended on recruiting of expatriates’ doctors to meet population demographic need-based demand arising from deficit in medical workforce. By the time Nigeria produce enough doctors above its health-care needs, she becomes a major physicians exporting country like Mexico Cuba, India, Thailand and Philippines (34). A significant portion of increased annual out-turns of physicians will readily serve as doctors exports to other countries; generate substantial foreign currencies remittance. Nothing in our health planning can be better than this strategy and the best time is to “act now”. .

5.2 Recommendation

Government, medical profession, medical schools’ management and policy-makers should implement upward review of admission quota to facilitate increase in enrolment

Government is advised to enhance health sector budgets and extra budgetary allocation for financing the proposed medical education expansion project or increase subvention spending to medical students and provide student loan scheme, revive tertiary education loans, to make credit facilities available to students to pursue studies in medicine.

Government should undertake technical inventory of extant facility and provide immediate funds for expansion in physical health infrastructure, modern equipment, facilities and faculty members are required for proper take-off of the proposed plan.

Nigeria advised to enrol minimum of 6000 to 7500 students’ annually enrolment rate whilst retaining existing 6-year MBBS degree programme, with options for degree level entrants as in the United Kingdom. The ministry of health and medical schools are advised ensure that accurate data on health budgets, actual spends and costs invested on medical programmes properly rendered henceforth.

FMOH - Federal Ministry of Health, Nigeria

FGN - Federal Government of Nigeria

ICU - Intensive Care Unit

MBBS - Bachelor of Medicine, Bachelor of Surgery (Professional Degree)

M.D - Doctor of Medicine (Degree)

MDCN - Medical & Dental Council of Nigeria (Professional Regulatory Board)

NBS - National Bureau of Statistics, Nigeria

NPC - National Population Commission,

NUC - National Universities Commission,

NYU - New York University (Medical School)

WHO - World Health Organisation

Key Points for Decision Makers

The expansion in admission of medical students and the production of Nigerian Medical Schools to increase physicians supply and reduce / eliminate shortages
Lowering financial barriers to medical education for economically disadvantaged prospects
Improvement of Nigeria’s Health System Infrastructure for efficient healthcare delivery

Acknowledgements

The authors acknowledge the acceptance of the Conference Paper by the ATPS Network and the presentation of the maiden version of the study at ATPS Silver Jubilee Anniversary Conference in Nairobi, on October 31^st 2019.

Contributions

CEA and HEI jointly conceptualised the design and development of the study. HEI provided direction on the structure, overall literature improvement and policy perspective. CEA handled data gathering and performed routine analysis. The entire text was independently reviewed and approved by each of the authors.

The authors hereby declare that this paper is not submitted to other Journal and not under consideration elsewhere.

Ethical Approval and Consent to Participate

Not Applicable. However, the research protocol was approved by the University of Benin Teaching Hospital and Nnamdi Azikiwe Teaching Hospital Health Research Review Ethics (Committees HREC) respectively, but no consent is required because ex-post ‘Facto’ data were employed. (The devices where the softcopies are stored got lost and will be inserted on recovery of the affected data - before the completion of peer review of the paper)

Consent for Publication

Not Applicable

Data Accessibility:

The data-sets employed and analysed in the current study are predominantly secondary demographic data available in the Nigerian National Bureau of Statistics repository, http://www.nigeriastat.gov.ng/index/; FMOH and MDCN web-site / sources; and Vanguard Newspaper’s publication on the reference date on Nigeria’s medical tourism spend in 2017. However, these data-set were further processed in deriving the condensed computations and reported results can be obtained on request.

Compliance to Ethical Standards

Ethical Standards: This paper employs publicly available secondary data in Nigeria, which to the best of the authors’ knowledge do not require ethical approvals for their use.

Economic Evaluation Reporting Standards: This standard is duly followed. Cost minimisation analysis (CMA) or effectiveness analysis (CEA) which compares the consequences of compared interventions are required to be equivalent, and only relative costs are compared is followed in line with CHEERS .

Conflict of Interest: Not Applicable. The authors have no conflict of interest to declare.

Funding

The author did not receive research grant from third parties or any source to be disclosed.

Open Access: This article (if accepted and published) can be distributed under the terms of the Creative Commons Attribution-Non-commercial 4.0 International License (http://creativecommons.org/by.ne/4.0/), which permits any non-commercial use, distribution and reproduction in any medium, provided appropriate credit is given to the original authors and source, provide a link in the Creative Commons License and indicate if changes were made.

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Forecasting requisite physicians’ density through medical education acceleration strategy towards elimination of workforce deficit in nigeria (2021-2042)

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Abstract

1.0 Introduction

2.0 Review Of Literature

2.2 Nigeria’s Medical Education System, Regulation and Structure

2.3 Theory of medical workforce, density, imbalance; medical education and financing

3.0 Methodology

3.1 Data Sources, Focal Institution and Collection

3.2 Theoretical Framework of the Models

3.2.1 Model variables and descriptions

3.3 Model Specification and Development

(1) Social capacity impact rate (workforce imbalance-surplus and deficit)

(2) Prior enrolment capacity sustainability

(3) Sustainability level (enrolment-extrapolation population) optimum capacity

(4) Medical education acceleration programme financing estimation/arrangement

3.4. Operationalisation of Test Statistics

4.0 Analysis And Results

5.0 Conclusions And Recommendations

5.1 Conclusion

5.2 Recommendation

Abbreviations

Declarations

References

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