2.3 Hontelez
2.3 Hontelez
2.3 Hontelez
RESEARCH
Open Access
Abstract
Background: Although access to life-saving treatment for patients infected with HIV in South Africa has improved
substantially since 2004, treating all eligible patients (universal access) remains elusive. As the prices of antiretroviral
drugs have dropped over the past years, availability of human resources may now be the most important barrier to
achieving universal access to HIV treatment in Africa. We quantify the number of HIV health workers (HHWs)
required to be added to the current HIV workforce to achieve universal access to HIV treatment in South Africa,
under different eligibility criteria.
Methods: We performed a time and motion study in three HIV clinics in a rural, primary care-based HIV treatment
program in KwaZulu-Natal, South Africa, to estimate the average time per patient visit for doctors, nurses, and
counselors. We estimated the additional number of HHWs needed to achieve universal access to HIV treatment
within one year.
Results: For universal access to HIV treatment for all patients with a CD4 cell count of 350 cells/l, an additional
2,200 nurses, 3,800 counselors, and 300 doctors would be required, at additional annual salary cost of 929 million
South African rand (ZAR), equivalent to US$ 141 million. For universal treatment (treatment as prevention), an
additional 6,000 nurses, 11,000 counselors, and 800 doctors would be required, at an additional annual salary cost
of ZAR 2.6 billion (US$ 400 million).
Conclusions: Universal access to HIV treatment for patients with a CD4 cell count of 350 cells/l in South Africa may
be affordable, but the number of HHWs available for HIV treatment will need to be substantially increased. Treatment
as prevention strategies will require considerable additional financial and human resources commitments.
Keywords: Human resources for health, HIV, South Africa, Antiretroviral treatment
Introduction
With about 22.5 million people living with HIV [1], the
disease remains one of the most important health problems in sub-Saharan Africa (SSA). Antiretroviral therapy (ART) significantly improves the survival and quality
of life of people infected with HIV [2-4]. In June 2011,
the United Nations General Assembly High Level Meeting on AIDS adopted a political declaration of achieving
* Correspondence: tbarnighausen@africacentre.ac.za
1
Africa Centre for Health and Population Studies, University of KwaZulu-Natal,
Mtubatuba, South Africa
6
Department of Global Health and Population, Harvard School of Public
Health, Boston, USA
Full list of author information is available at the end of the article
2012 Hontelez et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Methods
Ethics approval
We obtained consent for this study from the local Department of Health. This study received ethics approval
from the Biomedical Research Ethics Committee of the
University of KwaZulu-Natal (ethics certificate number
BF109/09). Written consent was obtained from all
HHWs observed.
Data collection
Page 2 of 12
between the local Department of Health and a Wellcome Trust-funded research center based in the community (the Africa Centre for Health and Population
Studies, University of KwaZulu-Natal) [20]. HIV treatment is delivered within the program through 17 PHC
HIV clinics and one district hospital. The professional
nurses and trained HIV counselors perform tasks exclusively related to HIV treatment and care. Doctors visit
clinics on a scheduled rotation (usually one weekly visit
per clinic) to start new patients on ART and to review
cases of treatment failure, drug toxicity, and other complications. The Hlabisa sub-district has a total population of 228,000 and an adult HIV prevalence of 28%
[21]. ART uptake in the area is high, and by June 2011,
nearly 17,000 people had been initiated on ART [22].
We randomly selected three PHC HIV clinics (clinics
A to C) within the treatment program for observation. A
single observer was then randomly assigned to a different HHW (in one of the three categories: doctor, nurse,
or treatment counselor) on different, randomly assigned
calendar days within the observation period. No HHW
was observed more than once. Activities were timed and
recorded for each separate patient contact, and subsequently entered into a spreadsheet (Excel; Microsoft
Corp., Redmond, WA, USA). Data were collected by a
single observer trained in quantitative and qualitative
data collection, and the observer was closely supervised
by three doctors and two professional nurses. The observer was given written instructions on how to keep and
record time for different types of tasks, and was trained
in two stages. The initial stage involved observing the
work days of different HHWs without recording any
tasks, in order to allow the observer to become familiar
with the work routine. Next, a pilot study was conducted
in which tasks were observed and recorded, and subsequently coded. The pilot data were checked for errors or
inconsistencies, and the study protocol was improved,
based on the pilot findings. During the final data collection, data were continuously entered and checked by the
supervising doctors.
Two investigators independently coded the recorded
activities into pre-defined categories: 1) direct patient
contact (talking to patient; writing; writing and talking;
venepuncture; physical examination; dispensing medication); 2) indirect patient contact (discussing clinical or
work-related issues with other HHWs; performing workrelated paperwork or administration; contacting health
workers in other healthcare facilities, such as hospitals,
for patient referral); and 3) other (breaks; idle time; unaccounted time). Categories (1) and (2) are times allocated to perform tasks within the job description of the
particular HHW, while category (3) contains breaks and
idle time. It is important to note that breaks and idle
time do not necessarily imply wasted or unproductive
time. Breaks may serve an important purpose in allowing the HHW to maintain productivity when performing
tasks in categories (1) and (2). The final assignment of
category codes was determined in discussion between
the two investigators and, when conflicting assignments
could not be resolved, through discussion with a third
investigator.
Data analysis
Page 3 of 12
populations might operate below their full capacity because of limited ART patient load, owing to the low
population density in remote and rural areas. In fact, the
clinics in which ART was initially rolled out were more
likely to have been located in more densely populated,
urban areas, and thus are more likely to operate at capacity. Thus, as the program is scaled up, the fixed costs
per patient may increase, implying diseconomies of
scale. The running costs per patient may also increase
with scale, as the health-system efforts required to motivate patients to begin and continue taking ART may be
lower for patients who accessed the ART program at
earlier stages of the scale-up than for those who accessed
the program at later stages. We thus assessed two scenarios to measure the scale effects: one assuming increasing returns to scale, the other assuming decreasing
returns to scale. In both cases, we assumed that the scale
effects followed an exponential distribution. The equations were:
patients per HHW = EXP(0.03858 F)
and
patients per HHW = EXP(0.03858 F),
for economies and diseconomies of scale, respectively,
where F = a constant number of patients per HHW
across scale. In addition, we examined the sensitivity of
our results to changes in the average time per patient
and duration of work day by using the times and durations of either the least efficient or the most efficient
clinic in our estimations.
Finally, we performed a scenario analysis on the effect
of alternative models of delivering ART on the HHW:patient ratio and overall salary costs. Nurse-initiated treatment has been allowed in South Africa in recent years
[24]; therefore, we performed an additional analysis in
which nurses were assumed to perform all initiations, at
the same productivity level as doctors [18]. In addition,
we assumed the following alternative delivery models: i)
decreased frequency of routine clinic visits (once every
2, 3, or 4 months); and ii) decreased frequency of nurseattended routine clinic visits (once every 2, 3, or 4
months).
Results
Table 1 gives an overview of the baseline characteristics
of the time and motion data. In total, thirteen HHWs
(six nurses, four counselors, and three doctors) were
observed over the period 12 August to 1 September
2009. The total number of patient visits observed was
334. An average work day lasted 6.3 hours, and the average duration of work days differed significantly between
the busiest and least rural clinic (clinic B) and the least
busy and most rural clinic (clinic C) in our sample (7.3
versus 4.9 hours; P = 0.01). The observed HHW with
the shortest observed work-day duration was a counselor
Page 4 of 12
By clinic
Clinic A Clinic B
Clinic C
4
Observation days, n
13
Observation period
12 August to
1 September
19 to 26 12 to 18 27 August to
August August 1 September
HHWs observed, n
Nurse
Counselor
Doctor
Total patients
observed, n
334
115
120
99
5.2
7.3
4.9
6.3
Nurse
7.1
5.2
7.3
5.3
Counselor
5.8
5.3
6.7
5.8
Doctor
5.4
5.1
7.7
3.4
86
87
76
83
Nurse
83
84
83
82
Counselor
74
87
82
20
Doctor
92
91
94
89
Overall
10
Nurse
13
Indirect patient
contactb
Counselor
13
44
Doctor
14
Nurse
12
Counselor
13
10
36
Doctor
Otherc
Overall
12
(9 to 14)
14
11
10
(9 to 18) (8 to 13) (5 to 16)
Nurse
10
(6 to 13)
12
12
7
(6 to 18) (7 to 17) (1 to 12)
Counselor
14
(9 to 19)
15
8
43
(7 to 23) (5 to 11) (2 to 83)
Doctor
13
(9 to 16)
15
15
9
(2 to 27) (11 to 18) (7 to 11)
Page 5 of 12
in clinic C, who spent only 20% of the work day on direct patient contact; this counselor used 44% of the work
day to perform administrative work and 36% on breaks
and idle time. This time distribution was probably due
to the fact that the patient load in this rural clinic was
relatively low. There were no significant differences in
the time per patient between the three clinics (P = 0.47)
or between the different HHWs (P = 0.24). On average,
a nurse-visit took 10 minutes (95% CI 6 to 13 minutes),
a counselor-visit 14 minutes (95% CI 9 to 19 minutes),
and a doctor-visit 13 minutes (95% CI 9 to 16 minutes).
Estimates of ART coverage under different eligibility
criteria are shown in Table 2. As of 2009, nearly 1 million people were on HIV treatment in South Africa [1].
Universal access to ART for HIV-infected people with
CD4 cell counts of 350 cells/l would require an additional 1.6 million initiations (a total of 2.6 million
Receiving ART, n
Point
estimate
Low
estimate
High
estimate
971,566
NA
NA
Needing ART, n
CD4 200
1,700,000
1,500,000
2,000,000
1,925,000
1,750,000
2,200,000
CD4 350
2,600,000
2,500,000
2,800,000
CD4 500c
4,100,000
3,950,000
4,340,000
5,600,000
5,400,000
5,900,000
Coverage,%
CD4 200
56
65
48
50
56
44
CD4 350
37
39
35
CD4 500c
24
25
22
17
18
16
728,434
528,434
1,028,434
952,444
778,444
1,228,444
CD4 350
1,628,434
1,528,434
1,828,434
CD4 500c
3,128,434
2,978,434
3,368,434
4,628,434
4,428,434
4,928,434
ART, antiretroviral therapy; CD4, CD4 cell count (expressed in cells/l;); NA, not
applicable.
a
Source: WHO Towards Universal Access report 2010 [23].
b
We assumed 25% of those with CD4 cell counts of 200 to 350 l to be
eligible because of pregnancy or co-infection with tuberculosis.
c
Number of people estimated to be between those eligible at 350 cells/l or
lower and those eligible under the strategy of ART for all HIV-infected people.
Page 6 of 12
Table 3 Human resources needs and salary costs for initiating all those eligible for antiretroviral therapy (ART) and
maintaining them on ART for one year, under different treatment strategies
Human resources needs
Costs
Proportion of
Total salary
current HIV
costs, in
million ZAR) sector budget,
% (95% CI)a
(95% CI)
Counselor
FTEs
1,000
(95% CI)
Doctormonths
1,000
(95% CI)
Doctor
FTEs
1,000
(95% CI)
2 (1 to 2)
12 (8 to 16)
15 (10 to 20)
2 (1 to 3)
15 (10 to 20)
CD4 350
26 (18 to 35)
3 (2 to 4)
26 (18 to 35)
CD4 500
51 (34 to67)
6 (5 to 8)
51 (34 to67)
Nursemonths
1,000
(95% CI)
Nurse
FTEs
1,000
(95% CI)
CD4 200
12 (8 to 16)
Counselor
months
1,000
(95% CI)
Point estimateb
6.2 (4.2 to 8.2) 129 (79 to 179) 10.7 (6.6 to 14.9) 9 (7 to 12) 0.8 (0.6 to 1.0) 74 (50 to 99)
74 (50 to 99)
High estimateb
CD4 200
17 (11 to 22)
2 (1 to 3)
17 (11 to 22)
20 (13 to 26)
3 (2 to 3)
20 (13 to 26)
CD4 350
30 (20 to 39)
4 (3 to 5)
30 (20 to 39)
CD4 500
54 (37 to 72)
7 (5 to 9)
54 (37 to 72)
All HIV-positive people 80 (54 to 106) 6.6 (4.5 to 8.8) 137 (84 to 191) 11.4 (7.0 to 15.9) 10(7 to 13) 0.8 (0.6 to 1.1) 80 (54 to 106) 80 (54 to 106)
Low estimateb
CD4 200
9 (6 to 11)
1 (1 to 1)
9 (6 to 11)
13 (8 to 17)
2 (2 to 3)
13 (8 to 17)
CD4 350
25 (17 to 33)
3 (2 to 4)
25 (17 to 33)
CD4 500
48 (32 to 64)
6 (4 to 8)
48 (32 to 64)
6.0 (4.0 to 7.9) 123 (75 to 171) 10.3 (6.2 to 14.3) 9 (6 to 12) 0.8 (0.5 to 1.0) 72 (48 to 95)
72 (48 to 95)
CD4, CD4 cell count (expressed as cells/l); FTE, full-time equivalent; ZAR = South African rand.
a
Current total expenditure: estimate of the total amount spent on preventing and treating HIV in South Africa in 2009 (ZAR 14 billion) [66].
b
For the calculations of the point, high, and low estimates, we used the point, high, and low estimates of the number of people living with HIV in South Africa
published in the most recent UNAIDS world AIDS report [66].
Discussion
In this study, we estimated for the first time the number
of additional HHWs needed to achieve universal access
to HIV treatment in South Africa, using data from a
time and motion study. We found that universal access
to ART at CD4 cell counts of 350 cells/l will require
South Africa to commit a further 2,200 nurses, 3,800
counselors, and 300 doctors to HIV treatment, at a cost
of ZAR 929 million (US$ 141 million) in salaries. We
found an average HHW:patient ratio of 0.2 per 1,000
patients for doctors (for performing all ART initiations),
Page 7 of 12
Table 4 Sensitivity analysis of human resources needs and salary costs for initiating all those eligible for antiretroviral
therapy (ART) and maintaining them on ART for one year, under different treatment strategies
Human resources needs
Nursemonths
1,000
(95% CI)
NurseFTEs
1,000
(95% CI)
Counselormonths
1,000
(95% CI)
Costs
Doctormonths
1,000
(95% CI)
Counselor
FTEs
1,000
(95% CI)
Doctor
FTEs
1,000
(95% CI)
Total salary
costs in
million ZAR
(95% CI)
Proportion of
current HIV
sector budget,
% (95% CI)a
10 (7 to 13)
17 (10 to 24)
1 (1 to 1)
2 (2 to 3)
CD4 350
13 (9 to 17)
(TB or pregnant);
CD4 200
(all other
HIV-infected
people)
22 (14 to 31)
1 (1 to 2)
3 (2 to 4)
CD4 350
38 (23 to 53)
2 (2 to 3)
CD4 500
73 (45 to 101)
4 (3 to 6)
All HIV-positive
people
63 (42 to 84) 5.2 (3.5 to 7.0) 108 (66 to 150) 9.0 (5.5 to 12.5)
6 (5 to 8)
5 (4 to 7)
10 (7 to 14)
28 (17 to 38)
2 (2 to 3)
4 (3 to 5)
CD4 350
19 (13 to 26) 1.6 (1.1 to 2.2)
(TB or pregnant);
CD4 200
(all other
HIV-infected
people)
36 (22 to 50)
3 (2 to 4)
5 (3 to 7)
CD4 350
62 (38 to 86)
6 (4 to 7)
9 (6 to 12)
CD4 500
63 (43 to 85) 5.3 (3.6 to 7.1) 118 (72 to 165) 9.9 (6.0 to 13.7) 11 (8 to 14) 0.9 (0.6 to 1.1) 2,401 (1,584 to 3,218) 17 (11 to 23)
All HIV-positive
people
94 (63 to 126) 7.9 (5.3 to 10.5) 175 (107 to 243) 14.6 (8.9 to 20.3) 16 (11 to 20) 1.3 (0.9 to 1.7) 3,552 (2,344 to 4,762) 25 (17 to 34)
20 (12 to 27)
1 (1 to 2)
3 (2 to 4)
CD4 350
15 (10 to 20) 1.2 (0.8 to 1.6)
(TB or pregnant);
CD4 200
(all other
HIV-infected
people)
11 (8 to 15)
26 (16 to 36)
2 (1 to 3)
4 (2 to 5)
CD4 350
43 (26 to 59)
3 (2 to 4)
CD4 500
77 (47 to 107)
6 (4 to 7)
All HIV-positive
people
62 (42 to 82) 5.2 (3.5 to 6.9) 107 (65 to 149) 8.9 (5.5 to 12.4)
6 (4 to 8)
11 (7 to 15)
CD4 = CD4 cell count (expressed as cells/l); FTE, full-time equivalent; ZAR = South African rand.
The underlying number of patients needing treatment are based on the WHO-reported ART treatment coverage in South Africa [23] and UNAIDS-reported point
estimate of the total number of people infected with HIV [66], see Table 2.
a
Current total expenditure: estimate of the total amount spent on preventing and treating HIV in South Africa in 2009 (ZAR 14 billion) [66].
and 1.2 per 1,000 patients for nurses and 2.1 per 1,000
patients for counselors (for performing initiations of eligible people and maintaining them on treatment).
It is interesting to compare our empirical findings
from this time and motion study with estimates based
on other sources of information. Based on reports of the
total numbers of health workers and patients in HIV
treatment programs, Hirschhorn et al. estimated that in
2004 the number of doctors and nurses required to treat
1,000 HIV-infected people were 12 and 27,
Page 8 of 12
without major changes to national health worker production and retention. However, recruiting the required
additional 2,200 nurses fully devoted to HIV care may
prove to be a greater challenge, given that the total of all
professional nurses who graduated from nursing schools
in South Africa in 2011 was only about 5,600 [39].
It is therefore vital to increase efforts to expand the
health worker pool for HIV in South Africa by increasing training and retention, considering reinstatement of
retired health workers, or increasing HHW productivity,
in particular to achieve universal coverage at more
relaxed eligibility criteria [37]. Currently, public-sector
HHWs are paid a salary on a monthly basis and, additionally, receive contributions to health and retirement
pension insurance, as well as a rural allowance for service in under-served areas. Alternative models of contracting and incentivizing HHWs, such as performancebased payment, might improve productivity. However,
such new models might also lead to inefficiencies (for
example, transaction costs for monitoring performance),
and unintended behavioral consequences (for example,
decreased quantity and quality of care for services not
included in the performance-based payment scheme)
[40]. It is possible that transferring public-sector patients
on ART to the private sector for routine follow-up and
monitoring, as has been done effectively in Botswana
and Mexico [41,42], might increase the pool of available
HHWs. At the same time, of course, this strategy might
increase the human resources costs per individual on
ART, because health worker salaries in the private sector
in South Africa are higher than those in the public sector. Health worker interventions, such as shifting tasks
from more to less skilled health workers [43] and integration of ART delivery into the general primary care
services [44] should also be considered as means to free
up human resources for HIV treatment. Integration
might improve productivity, if it either increases capacity
Table 5 Effect of alternative models of antiretroviral therapy (ART) delivery on the HIV health worker-to-patient ratio
and overall salary costs for universal access to HIV treatment in South Africa
Scenario
Overall reduction
in salary costs, %
Nurses
Counselors
Doctors
NA
Every 2 months
36
Every 3 months
50
Every 4 months
57
Baseline
Decrease visit frequency to:
24
Every 3 months
33
Every 4 months
38
Nurse-initiated treatment
NA
NA = not applicable.
Page 9 of 12
Page 10 of 12
Conclusion
We provide policy-relevant estimates of the number of
HHWs needed and associated salary costs for scaling up
HIV treatment to achieve universal access under different treatment eligibility criteria and delivery models in
South Africa. We show that, in terms of HHWs required
for scaling up ART to universal access at CD4 cell count
of 350 cells/l seems achievable in the present context,
Page 11 of 12
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