www.sega2.org.za/lib/download.php?doc_id=190%20&%20doc_url=190.doc
Prof. Y Veriava, Principal Investigator
Dr. D Connelly Sevilla, Lead Researcher
RN A Jordan, S Roberts, and J Tsotetsi, Research Team
Asst Profs Mary Bachman and Sydney Rosen, Consultants (Boston
University)
Health Economics Research Office (HERO)
Wits Health Consortium, University of the Witwatersrand
Tel: 011 276-8888 (HERO office)
Email:
dsevillag@yahoo.com
Technical assistance from the
Joint Economics Aids and Poverty Programme (JEAPP)
November 1, 2005
Much has been written
about the burden placed on the health sector in South Africa by
HIV/AIDS. Most of this work focuses on the increased demand for
health services created by AIDS and the costs of providing
hospital care to HIV-infected patients. Little has been
published about the impact of HIV/AIDS on
nurses, doctors, and the
other trained professionals who are responsible for keeping
increasingly over-burdened public healthcare facilities
functioning. Little is known about the contribution of AIDS to
the high attrition of healthcare personnel, the impact of
HIV/AIDS on healthcare worker labour productivity, or the actual
financial and human capital costs of the disease to the public
health system.
To
help fill this gap in knowledge, a research team from
Helen Joseph Hospital and Coronation Hospital
in Johannesburg, working through the Health Economics Research
Office at the University of the Witwatersrand (HERO) and with
technical assistance from the Joint
Economics Aids and Poverty Programme (JEAPP) and Boston
University’s Center for International Health and Development (CIHD),
analyzed the impact of HIV/AIDS on health care personnel at
these two sites.
The
overall objective of this study was to describe and analyze the
impact of HIV on professional-level health care workers in order
to assist the National Department of Health, provincial health
departments, hospitals, training institutions, and other public
sector agencies to develop more effective strategies for
maintaining productivity and managing costs in the public health
system. To achieve this general objective, we collected and
analysed data in four specific areas: 1) levels of termination
and replacement of nurses; 2) reasons for termination among
nurses; 3) HIV prevalence in the workforce; and 4) costs of
HIV/AIDS in the nursing workforce. Our analysis focused on the
nursing workforce, for which we had the most complete data
sets.
We
obtained retrospective data from the Gauteng Shared Services
Centre (GSSC) database on all healthcare professionals at our
two study sites who left employment for any reason between 2001
and 2004 and all healthcare professionals who were appointed in
that period. Results for professional and staff nurses are
shown in Table 1. Although attrition
(terminations) of nurses was fairly constant over the period
studied, rates of hiring (replacement) declined substantially.
As a result, the two hospitals had approximately 100 fewer
nurses at the end of 2004 than at the beginning of 2001. Most
nurses who left service (83%) had fewer than five years of
service. A very small proportion (5%) of those terminating
service did so due to death or ill health, suggesting that
nurses’ own illness due to HIV infection is not a major
contributor to overall attrition.
|
Year |
Total no. nurses at beginning of period |
No. nurses leaving during period* |
No. nurses hired during period† |
Annual attrition rate (% of total) (b/a) |
Annual hiring rate (% of total)
(c/a) |
Hiring/ attrition ratio
(e/d) |
|
|
a |
b |
c |
d |
e |
f |
|
2001 |
760 |
45 |
210 |
7.5 |
28.6 |
3.68 |
|
2002 |
868 |
86 |
62 |
9.9 |
7.1 |
0.72 |
|
2003 |
843 |
52 |
19 |
6.2 |
2.2 |
0.37 |
|
2004 |
810 |
43 |
1 |
9.1 |
0.2 |
0.05 |
*Attrition data were truncated for 2001 (starting 3/16) and 2004
(ending 7/31). Rates for these years have been annualised.
†Hiring
data were truncated for 2004 (ending 7/31). Rate for 2004 has
been annualised.
III. Reasons
for Termination among Nurses
To understand why
attrition among nurses is relatively high (particularly among
younger staff), we conducted exit interviews of all terminating
staff over a 12-month period and held more than 34 focus group
discussions involving approximately 100 current staff on reasons
for staff termination.
Rankings of reasons for termination by both focus group
participants and exit interview participants are shown in Table
2. Among focus group participants, the reasons offered for
nurse resignations were largely related to compensation and
administrative/managerial issues. HIV/AIDS played a role in
aggravating working conditions, however. Three quarters of
nurses included an HIV-related reason among the top ten reasons
for nurse resignations, and nearly half placed an HIV-related
reason among their top five.
Focus group discussions
inevitably involved only nurses who have not (yet)
terminated service. To explore reasons for leaving among those
who had decided to resign, we conducted exit interviews with
approximately 90% (n=72) of nurses who handed in their
resignations between March and August 2004. Those leaving
service were primarily African (62%) and female (90%). A
majority (63%) stated that they were the primary wage-earner in
the family. More than three quarters of participants reported
that they already had a new job, suggesting substantial “pull”
from other employers, in addition to work dissatisfaction
internally (“push”). Of those with a new job, 48% planned to
work in the private sector, and 37% planned to work elsewhere in
the public sector. Exit interview participants were also asked
in a separate question about the influence of HIV on their
decision to leave, and 30% stated that HIV had at least somewhat
affected their decision to leave.
|
Reason |
Ranking by participants of: |
|
|
EI |
FG |
|
Insufficient salary. |
1 |
1 |
|
Excessive work burden/too many patients. |
2 |
2 |
|
No career development/professional development. |
|
3 |
|
Managerial/supervisory incompetence and
unresponsiveness. |
3 |
4 |
|
Family reasons or family member relocating |
4 |
not ranked |
|
Poor work environment |
5 |
not ranked |
|
Difficult and inflexible work schedule. |
6 |
5 |
|
Insufficient benefits |
7 |
not ranked |
|
Insufficient hospital equipment, infrastructure,
medicine. |
not ranked |
6 |
|
Strained interpersonal relationships at work. |
not ranked |
7 |
|
Better working conditions overseas or in private sector. |
not ranked |
8 |
|
No recognition of the harshness of the nature of the
work. |
not ranked |
9 |
|
Stress/depression from increased HIV among patients
(burnout). |
8 |
10 |
|
Insufficient training in HIV management. |
not ranked |
11 |
|
No grief counselling/ emotional support for staff. |
not ranked |
12 |
|
Fear of occupational exposure to HIV through needle
pricks. |
not ranked |
13 |
|
Socially and economically vulnerable patients are very
demanding. |
not ranked |
14 |
|
Demoralizing/frustrating caring for AIDS patients. |
not ranked |
15 |
IV. HIV
Prevalence in the Workforce
We conducted a
voluntary, anonymous, unlinked sero-prevalence survey of all
healthcare workers at our study sites. To protect the anonymity
of the survey, participants were not given their test results.
Instead, they were referred to a VCT and ARV treatment clinics
on and off site. Significant
groundwork aimed at obtaining support for the survey from
workers, unions, hospital management and staff was conducted
prior to the testing through meetings, focus groups, social
events, and written informational posters and handouts.
Participants chose whether to give a blood or an oral fluid
sample, and along with either sample, we recorded the age, sex,
race, and job level of each participant and ran CD4 counts on
all blood samples. Participants were given a T-shirt as a gift
for their participation and potential discomfort during the
survey.
Results are summarized
in Tables 3 and 4.
|
Variable |
Present on testing days (no.) |
Tested (no.) |
Response rate (%) |
HIV positive (no.) |
Prevalence (%) |
|
Overall |
1,613 |
1,444 |
89.5% |
171 |
11.8% |
|
Job category* |
|
|
|
|
|
|
Allied staff |
278 |
247 |
88.8% |
14 |
5.7% |
|
Nurses |
708 |
644 |
91.0% |
88 |
13.7% |
|
Student nurses |
66 |
65 |
98.5% |
9 |
13.8% |
|
General assistants |
561 |
488 |
87.0% |
60 |
12.3% |
|
Gender |
|
|
|
|
|
|
Female |
|
1315 |
|
158 |
12.0% |
|
Male |
|
178 |
|
14 |
7.9% |
|
Age |
|
|
|
|
|
|
18-24 |
|
105 |
|
7 |
6.7% |
|
25-34 |
|
327 |
|
52 |
15.9% |
|
35-44 |
|
530 |
|
69 |
13.0% |
|
45-54 |
|
393 |
|
40 |
10.2% |
|
55+ |
|
138 |
|
4 |
2.9% |
*Participation by medical doctors was not sufficient to generate
valid results, and medical doctors are therefore not included in
the job category results. Medical doctors are included in the
results by gender and age, however.
|
CD4 cell count |
Number of persons |
Percent of total |
|
<=200 |
14 |
18.9% |
|
201-350 |
21 |
28.4% |
|
351-500 |
13 |
17.6% |
|
>500 |
26 |
35.1% |
|
Total |
74 |
100% |
|
Overall mean=451; SD=286; | | 
