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R E S E A R C H A R T I C L E Open Access
Provider initiated tuberculosis case finding
in outpatient departments of health care
facilities in Ghana: yield by screening
strategy and target group
Sally-Ann Ohene
1*
, Frank Bonsu
2
, Nii Nortey Hanson-Nortey
2
, Ardon Toonstra
3
, Adelaide Sackey
2
,
Knut Lonnroth
4
, Mukund Uplekar
4
, Samuel Danso
2
, George Mensah
5
, Felix Afutu
2
, Paul Klatser
6
and Mirjam Bakker
3
Abstract
Background: Meticulous identification and investigation of patients presenting with tuberculosis (TB) suggestive
symptoms rarely happen in crowded outpatient departments (OPDs). Making health providers in OPDs diligently
follow screening procedures may help increase TB case detection. From July 2010 to December 2013, two
symptom based TB screening approaches of varying cough duration were used to screen and test for TB among
general outpatients, PLHIV, diabetics and contacts in Accra, Ghana.
Methods: This study was a retrospective analysis comparing the yield of TB cases using two different screening
approaches, allocated to selected public health facilities. In the first approach, the conventional 2 weeks cough
duration with or without other TB suggestive symptoms was the criterion to test for TB in attendants of 7 general
OPDs. In the second approach the screening criteria cough of >24 hours, as well as a history of at least one of the
following symptoms: fever, weight loss and drenching night sweats were used to screen and test for TB among
attendants of 3 general OPDs, 7 HIV clinics and 2 diabetes clinics. Contact investigation was initiated for index TB
patients. The facilities documented the number of patients verbally screened, with presumptive TB, tested using
smear microscopy and those diagnosed with TB in order to calculate the yield and number needed to screen (NNS)
to find one TB case. Case notification trends in Accra were compared to those of a control area.
Results: In the approach using >24-hour cough, significantly more presumptive TB cases were identified among
outpatients (0.82% versus 0.63%), more were tested (90.1% versus 86.7%), but less smear positive patients were
identified among those tested (8.0% versus 9.4%). Overall, all forms of TB cases identified per 100,000 screened were
significantly higher in the >24-hour cough approach at OPD (92.7 for cough >24 hour versus 82.7 for cough >2
weeks ), and even higher in diabetics (364), among contacts (693) and PLHIV (995). NNS (95% Confidence Interval)
varied from 100 (93-109) for PLHIV, 144 (112-202) for contacts, 275 (197-451) for diabetics and 1144 (1101-1190) for
OPD attendants. About 80% of the TB cases were detected in general OPDs. Despite the intervention, notifications
trends were similar in the intervention and control areas.
Conclusion: The >24-hour cough approach yielded more TB cases though required TB testing for a larger number
of patients. The yield of TB cases per 100,000 population screened was highest among PLHIV, contacts, and
diabetics, but the majority of cases were detected in general OPDs. The intervention had no discernible impact on
general case notification.
Keywords: Tuberculosis, Screening, Case finding, Ghana
* Correspondence: salohene@yahoo.com
1
World Health Organization Country Office, 29 Volta Street Airport, Airport
Residential Area, P.O. Box MB 142 Accra, Ghana
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Ohene et al. BMC Infectious Diseases (2017) 17:739
DOI 10.1186/s12879-017-2843-5
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Ensuring early detection of tuberculosis (TB) cases is
one of the key components of the End TB Strategy [1].
It is estimated by the World Health Organization
(WHO) that there were 10.4 million incident cases of
TB globally in 2015, and 1.8 million deaths due to TB
[2]. Undetected active TB cases, as well as the pool of
persons with latent TB infection which consists of a
third of the human population, serve as an infectious
reservoir for potential new cases, thereby posing a chal-
lenge to TB elimination [3]. Identification of TB cases
usually depends on symptomatic patients voluntarily
reporting to the health facility for diagnosis. Usually a
history of cough for 2 or more weeks, with or without
other TB suggestive symptoms, is the criterion used to
identify people to be tested for TB. However, using this
method may be limited by factors such as patient health
seeking behaviour, health worker alertness and low sen-
sitivity. Some individuals may not have TB suggestive
symptoms at all, or may have less prominent symptoms
that fail to elicit attention for testing for TB. Therefore,
diagnosis of these cases is potentially missed or delayed
with the risk of sub-optimal treatment outcomes, health
sequelae and continued transmission of TB in health fa-
cilities and the general population [4, 5].
Diagnostic delays and low TB case notification pose
important challenges, prompting the need to explore in-
terventions that increase TB case detection. In imple-
menting these interventions, however, it is pertinent that
they are cost effective and targeted at selected risk
groups. Additionally, it is necessary to take into consid-
eration the potential yield of TB cases, benefits, and
harms, as well as the feasibility and costs [4].
HIV clinics rank high among the settings for increased
yield of TB cases due to the high risk of TB among
people with HIV [6, 7]. Similarly, studies among dia-
betics have shown that the risk of developing TB is
higher among persons with diabetes compared to non-
diabetics [8, 9]. Contacts of TB cases are another risk
group; data from multiple studies from low and middle
income countries showed pooled prevalence of 3.1% ac-
tive TB in all contacts [10].
Outpatient departments (OPD) of health facilities are
feasible settings for TB symptoms screening [6, 11]. Pa-
tients presenting themselves at the health facility, although
not constituting a specific TB risk group, constitute a
“captive audience”requiring limited logistic arrangements
compared to the labour-intensive case finding methods
employed in non-facility based settings.
The 2007 comprehensive review of the Ghana Na-
tional TB Program (NTP) highlighted low TB case de-
tection as a challenge to TB control in Ghana [12]. With
case detection estimated at 27% for all TB cases and
37% for smear-positive cases in 2008, the National
Tuberculosis Health Sector Strategic Plan for Ghana
(2009-2013) clearly identified TB case detection as one
of the areas for intervention [13]. With support from
WHO and Canadian International Development Agency
(CIDA), the Ghana NTP subsequently implemented a
provider-initiated enhanced TB case finding strategy in
the capital Accra. The selection of Accra for the initia-
tive was because of proximity to facilitate oversight and
monitoring of activities by the national office of the
NTP which is located in Accra. This was done under
programmatic settings among attendants of general out-
patient departments (OPD), HIV clinics, diabetes clinics
and contacts of identified TB cases to augment TB case
detection [14]. Two approaches which used different du-
rations of cough and other TB suggestive symptoms were
used to identify patients for sputum smear testing for TB.
While multiple studies have been published on screen-
ing for TB cases in different settings and countries, there
is very little in the literature on enhanced TB case detec-
tion efforts in Ghana [15, 16]. The first objective of this
paper was to compare the yield of the two different ap-
proaches used in two sets of general OPD clinics in Accra,
with one of the screening approaches using a shorter dur-
ation of cough as well as other TB suggestive symptoms.
The second objective was to compare the yield from the
four groups; namely general outpatients, PLHIV, diabetics
and contacts, using the approach with the shorter dur-
ation of cough and other TB suggestive symptoms. Finally,
as a third objective, case notification trends in Accra were
compared to those of a control area.
Methods
This study is a retrospective analysis comparing the yield
of TB cases using two different approaches to identify
people eligible for TB testing from July of 2010 to De-
cember 2013. The approaches were implemented as part
of an enhanced TB case finding intervention in Accra
Metropolis, the largest city and capital of Ghana, located
in the Greater Accra Region (GAR). The following cri-
teria were used to select public health facilities to partici-
pate in the intervention: availability of TB microscopy
services and functioning DOTS centres, large OPD clien-
tele and capacity to implement the intervention under
programmatic settings which translated into the facility
management indicating ability to implement the interven-
tion activities in the existing setting using the existing
staff. Eleven major public health facilities in Accra, some
having and others not having separate independently-ran
HIV and diabetic clinics in addition to the general OPD
services, fulfilled the criteria and were selected to partici-
pate in the intervention. OPD attendance ranged from
100 per day in the smallest facility to 500 per day in the
largest facility. The intervention was implemented in the
outpatient departments in ten facilities as well as HIV
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clinics and diabetic clinics that were operating in these fa-
cilities, but in the eleventh facility, the intervention was
implemented in only the HIV clinic. These 11 facilities
made up 24% of the 46 TB diagnostic facilities in Accra,
but accounted for approximately 70% of cases reported in
Accra city and 53% of TB cases reported in Greater Accra
Region in 2009. Accra residents as well as the residents of
the neighbouring districts in GAR, who flock into the city
during the day to transact various activities including work
and educational pursuits, patronize these facilities. To facili-
tate ownership and buy-in, management and all health care
staff of the facilities were sensitized about the modalities of
intervention. Standard operating procedures (SOPs) were
developed to guide operations at the facilities and health
care staff in the OPD, consulting rooms, laboratory and TB
DOTS centres who were directly involved in the implemen-
tation of the initiative were trained in their use. Tools that
were produced to track data included registers for contact
tracing, presumptive TB patients, PLHIV screened for TB
and presumptive TB referral forms and screening tool for
the two screening approaches.
Screening methods
In the first approach, assigned to 7 general OPDs, the
history of cough of two or more weeks with or without
other TB suggestive symptoms was elicited from all pa-
tients, regardless of the presenting symptoms, by the at-
tending OPD nurse responsible for taking vital signs. If
the patient affirmed a cough of 2 weeks or more, this
was indicated on the patient’s folder/OPD treatment
card to alert the clinician. The OPD nurse then filled a
sputum request form for the patient, who was then sent
to the laboratory for the first collection of sputum speci-
men. It was ensured that such patients kept their place
in the queue to see the clinician. Subsequently, during
the consultation, the clinician would conduct a thorough
clinical examination to assess for extra-pulmonary TB in
addition to making a diagnosis for the patient’s present-
ing symptoms. The clinician would then refer the patient
to the laboratory for the second sputum smear examin-
ation, even when extra-pulmonary TB was presumed.
The second approach was assigned to 3 general OPDs,
7 HIV clinics - one of which was in a tertiary hospital -
and 2 diabetes clinics, using a similar process. The dif-
ference in the second approach was that the patients
were asked for a history of cough of >24 hours, as well
as a history of any of the following TB suggestive symp-
toms: fever, weight loss, and drenching night sweats. See
Fig. 1 for the diagnostic algorithm. The assignment of
approaches among the clinics was purposely done in
Fig. 1 Algorithm for diagnosing TB among outpatient attendees in 11 health facilities in Accra
Ohene et al. BMC Infectious Diseases (2017) 17:739 Page 3 of 11
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such a way that all the HIV and diabetes clinics used the
second approach, hereafter referred to as >24-hour
cough approach. This was in consideration of improving
identification of TB in those patients who may not have
the typical prolonged cough associated with TB [17].
The main reason for the selection of the three facilities
to implement the >24 hour-cough approach in their
OPD was because they had a relatively larger OPD clien-
tele and it was expected that their laboratories would be
able to handle the potentially larger volume of samples
for sputum examination expected given the criteria of
>24 hours of cough and other TB suggestive symptoms.
While the patient population in the two sets of facilities
was likely similar, it is important to note that the inter-
vention was not implemented as a trial. Therefore, con-
sideration was not given to baseline characteristics of
the patient population at the facilities that could pose as
potential confounding factors. We compared the yield
from the two different approaches used in two sets of
general OPD clinics in Accra and also compared the
yield between the four groups, namely general outpa-
tients, PLHIV, diabetics and contacts using the >24-hour
cough approach.
Contact investigation for TB was not a routine prac-
tice of the facility staff. It was therefore implemented as
one of the case finding interventions with the pool of
people screened being contacts of TB cases, in contrast
to patients attending the respective clinics for the other
groups. Index TB patients from all facilities, with the ex-
ception of one that cited inadequate logistics to carry
out contact investigations, were invited to list their con-
tacts. Depending on the preference of the index patient,
contacts identified were either screened during home
verification of the index patient before treatment initi-
ation, or at the health facility while accompanying the
index patient. The screening approach in use at the facil-
ity of the index patient was employed for the screening
of contacts. Contacts presumed to be TB cases followed
the standard diagnostic algorithm.
At the time of the intervention, Ziehl Nielsen staining
method was used in the diagnosis of TB. A diagnosis of
sputum smear positive TB (SS+ve) was made when at
least one acid-fast bacilli (AFB) was detected in 100
fields in one out of two slides. A diagnosis of smear
negative pulmonary TB was made only after the smear
negative sputum result had been followed up with clin-
ician assessment and chest x-ray with findings consistent
with TB coupled with the clinician decision to treat with
a full course of TB treatment.
Data collection and analyses
The main source of data for these analyses was the Na-
tional Tuberculosis Control Program (NTP) database.
The following data from the participating facilities was
submitted to the NTP by the institutional TB coordin-
ator on a quarterly basis over the period of the interven-
tion: number of people verbally screened at the general
OPD, diabetes clinics, HIV clinics and among contacts
of index TB patients, number of presumptive TB pa-
tients identified among those verbally screened and
number of people tested/evaluated for TB disease among
those identified as presumptive TB patients and number
of people diagnosed with all forms of TB and SS+ve TB.
The data was cross-checked during periodic monitoring
and supervisory support visits to the facilities by the
Accra Metropolis Health Directorate TB team and NTP
staff. The quarterly figures from the two different
screening approaches used in the OPDs were plotted to
show the trend of those screened, identified with TB
suggestive symptoms, tested, and the yield of TB cases
over the period of the intervention. The proportion of
all forms of TB and SS+ve cases among the numbers
screened, the presumptive TB cases and those tested for
TB and the number needed to screen (NNS) to identify
one SS+ve case, as well as all forms of TB for the two
different approaches used in the two sets of general
OPD clinics, HIV clinics, diabetes clinics and contact in-
vestigations were calculated. Two-sample tests of pro-
portion were used to determine the 95% confidence
intervals for these proportions to enable comparison be-
tween the two approaches used in the two sets of gen-
eral OPD clinics in Accra and across the four groups,
namely general outpatients, PLHIV, diabetics and con-
tacts, to identify significant differences. STATA Data
Analysis and Statistical Software version 12 was used for
the analysis. For the third objective of the paper, the
comparison of TB case notification trends at the popula-
tion level, Greater Accra Region (GAR), in which Accra
is located, was assessed as the evaluation population
[18]. Like many major cities, the city of Accra is a con-
gregating hub for residents in surrounding districts who
come into the city daily for a myriad of activities includ-
ing accessing health care in the city’s facilities. A series
of re-demarcation of the districts in GAR has resulted in
some residents originally in the geographic region of
Accra being assigned to new or other districts in Greater
Accra Region, and in some instances residents from the
districts bordering Accra have been reassigned to the
Accra population [19]. The potential of a spill over effect
from the fluid population and the changes in population
figures from the re-demarcation exercise necessitated
the use of a larger evaluation population and geographic
area in order to avoid distortions in the measurements
of intervention effects [18]. Ashanti Region, with similar
characteristics to GAR, was selected as the control
population to compare with GAR. Kumasi, the second
largest city in Ghana, is located in Ashanti Region and
shares a similar profile with Accra city in population,
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human resource for health capacity, health infrastructure
and economic activities. It also has residents commuting
daily from neighbouring districts to the city for various
endeavours, creating the potential for similar spill over
effects [20]. In the same vain, a demarcation exercise in
Ashanti Region resulted in changes in Kumasi’s popula-
tion and geographic spread. In summary, because of the
risk of distortion from the demarcation exercises in
Accra and Kumasi and spillover effect from fluid popula-
tions, we decided to compare notification data from
Greater Accra Region and Ashanti Region instead of
comparing notification data from Accra and Kumasi.
Quarterly notification rates (for all forms of TB and
smear positive TB) per 100,000 population were plotted
using Microsoft Excel 2010, using figures obtained from
the NTP and Ghana Statistical Service for the period
2008 to 2013 for the 2 regions. A linear-trend line was
drawn through the quarterly historical TB notification
data during the baseline (the first quarter of 2008 up to
the second quarter of 2010) to project TB notification
expected during the intervention period for Greater
Accra Region and for Ashanti Region. A linear-trend line
was also drawn through the actual TB notification data
during the intervention period (third quarter 2010 to
fourth quarter 2013) for each region. The graphs showed
how the two linear-trend lines compared to each other
in the intervention area Greater Accra and in the control
area Ashanti Region.
Ethical consideration
Ethical clearance for the study was obtained from the
Ghana Ministry of Health Research Division Ethical Review
Board. Permission was also sought from the NTP and the
participating facilities to use the data for the study. The data
used in the analyses did not involve personal identifiers, but
confidentiality was nevertheless maintained.
Results
During the implementation period, out of the reported
2,954,057 persons screened in the various clinics in par-
ticipating facilities, approximately 1 out of 100 (24,562)
were identified as having symptoms suggestive of TB
(Table 1). About 90% (21,890) of these presumptive TB
cases were tested for TB. Among these 21,890 pre-
sumed TB cases tested, 84.3% were from OPD, 11.9%
from the HIV clinic, 2.0% from the diabetes clinic and
1.7% from contacts investigation. Overall, 3,162 TB pa-
tients (all forms) were identified, with 79.7% from the
OPD, 18% from the HIV clinic, 0.8% from the diabetic
clinic, and 1.5% from the contact investigation. Among
the TB patients, 57.9% (1,833) were sputum smear
positive.
Quarterly variations
The TB cases detected ranged from 170.8 per 100,000
screened in the fourth quarter of 2010 to 73.8 per
100,000 in the fourth quarter of 2012. Figure 2 shows
the trend of the number of people verbally screened,
identified as presumptive TB, tested for TB, and diag-
nosed with TB by quarter, from the third quarter of 2010
to the last quarter of 2013 for the two different screen-
ing approaches from the OPD clinics. While fluctuations
were observed in these parameters over the period, there
was no clear-cut pattern over the course of time. Linear-
trends lines for the respective graphs showed that while
there was an increasing trend among those verbally
screened over the course of the intervention, a decreas-
ing trend was generally identified for the number of pre-
sumptive TB cases identified and for numbers tested.
Yield from clinics
A comparison of the 2 approaches used in the general
OPD setting showed that in the >24 hour-cough ap-
proach, significantly more presumptive TB cases were
identified among general outpatients (0.82% versus 0.63%,
p=0.0000). Also, more patients were tested (90.1% versus
86.7%, p=0.0000) and fewer smear positive patients were
identified among those tested (8.0% versus 9.4%, p<0.007)
(Table 1). Overall, the rate of TB cases (all forms) identi-
fied among the outpatients screened was higher in the
>24 hour-cough approach (92.7 per 100,000 versus 82.7
per 100,000, p=0.004). More patients needed to be
screened to identify one TB patient in the 2-week cough
approach (NNS=1209, 95% confidence interval (95%CI)
1145 - 1280) compared to the >24 hour-cough approach
(NNS=1079, 95%CI 1022 - 1142). The differences between
the 2 approaches in all of the above-mentioned indicators
were statistically significant. However, the proportion of
SS+ve TB diagnosed among all forms of TB did not differ
between the two approaches.
Approximately 7% of those verbally screened in the
diabetes clinic and contacts of index patients were iden-
tified as presumptive TB cases compared to about 5% in
the HIV clinic. In the various groups, over 80% of people
identified to be presumptive TB cases were tested. How-
ever, the HIV clinic had the highest proportion of pre-
sumptive TB cases being tested for TB (94.9%), as well
as the highest proportion of those tested being diag-
nosed with TB (21.8%). HIV clinic attendees had the
lowest proportion of cases confirmed with sputum
smear microscopy (36%). Rates of TB among those
screened were also highest among the HIV patients (995
per 100,000), followed by contact investigation (693 per
100,000). Consequently, the number of people needed to
screen (NNS) to identify one TB case was lowest at100
for HIV patients, followed by contacts at 144.
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Evaluation versus control area
Both projected TB notification and the actual TB notifica-
tion for all forms of TB and smear positive TB during the
intervention period showed a downward trend in Greater
Accra Region (Figs. 3 and 4). However, the actual notifica-
tion data for smear positive TB cases was less than the
projection using the historical data. For Ashanti Region,
the control region, projected notification data for all forms
of TB and smear positive TB using historical data for the
projection also showed a downward trend. However, while
actual notification data for smear positive TB during the
intervention period was similar to the figures projected
from historical data, more TB cases (all forms) were re-
ported in Ashanti Region compared to the projected data.
In other words, over the period of the intervention, more
TB cases (all forms) were identified among the control
population (Ashanti Region), while fewer SS+ve cases
were identified in the intervention population (Greater
Accra Region) compared to projected figures using histor-
ical data.
Discussion
Various TB case finding strategies across different popula-
tion groups globally have been implemented as a means of
Table 1 Results from TB case finding activities in clinics in Accra Metropolis from July 2010 to December 2013
OPD HIV Diabetes Contacts Total
Indicators 2-week cough >24-hour cough Total >24-hour
cough
>24-hour cough Total Total
Number of facilities 7 3 10 7 2 10
(A) Number of people screened 1,522,297 1,360,846 2,883,143 57,265 6,866 6,783 2,954,057
(B) Number of presumptive TB
patients identified
9,648 11,211 20,859 2,751 495 457 24562
(C) Number of people
tested/evaluated for TB disease
8,358 10,100 18,458 2,610 441 381 21890
(D) Number of people diagnosed
with all forms of TB
1,259 1,261 2,520 570 25 47 3162
(E) Number of people diagnosed
with SS+ TB
787 803 1590 205 14 24 1833
% presumptive TB cases among
those screened (B/A)
0.63% 0.82% 0.72% 4.80% 7.21% 6.74% 0.83%
95%CI (0.62-0.65) (0.81-0.84) (0.71-0.73) (4.63-5.00) (6.60-7.82) (6.14-7.33)
% people tested for TB among
presumptive TB patients (C/B)
86.6% 90.1% 88.5% 94.9% 89.1% 83.4% 89.1%
95%CI (86.0-87.3) (89.5-90.6) (88.1-88.9) (94.1-95.7) (86.3-91.8) (80.0-86.8)
% SS+ TB patients among those
tested (E/C)
9.4% 8.0% 8.6% 7.9% 3.2% 6.3% 8.4%
95%CI (8.8-10.0) (7.4-8.5) (8.2-9.0) (6.8-8.9) (1.5-4.8) (3.9-8.7)
patients with all forms of TB among
those screened (D/A) per 100,000
82.7 92.7 87.4 995.4 364.1 692.9 107.0
95%CI (78.1-87.3) (87.6-97.8) (84.0-90.8) (914.1-1076.7) (221.6-506.6) (495.5-890.3)
SS+TB patients among those
screened (E/A) per 100,000
51.7 59.0 55.1 358.0 203.9 353.8 62.1
95%CI (48.1-55.3) (54.9-63.1) (52.4-57.9) (309.1-406.9) (97.2-310.6) (212.5-495.1)
% SS+ve TB patients among total
number of TB patients (E/D)
62.5% 63.7% 63.1% 36.0% 56.0% 51.1% 58.0%
95%CI (59.8-65.2) (61.0-66.3) (61.2-65.0) (32.0-40.0) (36.5-75.5) (36.8-65.4)
Number Needed to Screen to find
one TB patient all forms (NNS1) (A/D)
1209 1079 1144 100 275 144 934
95%CI (1145-1280) (1022-1142) (1101-1190) (93-109) (197-451) (112-202)
Number Needed to Screen to find
one SS+TB patient (NNS2) (A/E)
1934 1695 1813 279 490 283 1612
95%CI (1808-2080) (1584-1821) (1727-1908) (246-324) (322-1029) (202-471)
>2-week cough –screening approach using a history of cough of 2 or more weeks with or without other TB symptoms; >24-hour cough –screening approach
using a history of cough of >24 hours as well a history of any of the following symptoms fever, weight loss and drenching night sweats. 95% CI –95%
Confidence intervals
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diagnosing undetected TB cases that would otherwise be
difficult to identify relying only on symptomatic patients
reporting to the health facility for diagnosis [21]. The yield
of TB cases is affected by several factors including the
screening and diagnostic methods, setting and the popula-
tion being screened, which could range from those consid-
ered to be at high risk for TB to the general population.
The Ghana NTP implemented a TB case finding interven-
tion across four different groups: OPD attendants, PLHIV,
diabetics, and contacts of TB cases. Among the OPD at-
tendants, two screening approaches, which differed on
duration of cough, were used. As expected, more people
with presumptive TB were identified and tested for TB
among the OPD clinics using the >24 hour-cough screen-
ing approach, and comparatively fewer numbers of people
needed to be screened to detect one TB case (all forms).
Across the four groups, the number that needed to be
screened to identify a TB case was lowest among PLHIV
and highest among the OPD attendants. Despite
implementing this initiative, the decreasing trend in the
TB notification for all forms of TB noted in the preceding
two years before the start of the intervention continued. A
similar phenomenon was noted in the control population.
Screening by using more sensitive methods results in
an increase in the pool of presumptive TB cases from
which actual cases can be identified, because the net is
cast wider. This is, however, at the expense of specificity
[22]. It was therefore not surprising that our study
showed that compared to the OPD attendees with cough
of 2 weeks or more, the OPD attendants with a shorter
duration of cough yielded a higher proportion of candi-
dates for TB testing but a lower proportion of TB cases
among those tested. Yet our overall yield of 0.72% of
OPD attendees identified as presumptive TB cases to be
tested for TB was quite low when compared to the 2.6%
to 3.5% range found in studies on the yield of potential
TB cases among OPD attendees in Tanzania and Kenya
[23–25]. There could be a number of reasons for this
Fig. 2 Number of people verbally screened for TB, identified as presumptive TB, tested for TB, diagnosed with all forms of TB and diagnosed with
sputum positive TB identified by the quarter from third quarter 2010 to fourth quarter 2013 for 2-week cough and >24-hour cough approaches
in Accra Metropolis facilities
Ohene et al. BMC Infectious Diseases (2017) 17:739 Page 7 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
marked difference. For one, different screening criteria
were used. For another, unlike strictly supervised study
settings with screening conducted over shorter periods
of time our screening occurred over a period of three
and a half years and under programmatic settings with
inherent challenges. It is therefore possible that the yield
could have been higher since under the programmatic
conditions, there may have been gaps in following all
steps in the algorithm possibly contributing to missed
opportunities to screen all patients to ensure that all
presumptive cases identified underwent sputum smear
microscopy.
Fig. 3 Quarterly notification rates of all TB cases for Greater Accra and Ashanti Regions with linear-trend lines from 2008 to 2013. Q: Quarter, GA-
AT: Greater Accra all TB cases, AS-AT: Ashanti all TB cases. Baseline trend –refers to the linear-trend line drawn to project TB notification expected
during the intervention period for both regions using quarterly historical TB notification data from Greater Accra and Ashanti Regions during the
baseline period (first quarter of 2008 up to the second quarter of 2010) before the intervention started. Intervention trend –refers to the linear-trend
line drawn through the actual TB notification data from Greater Accra Region during the intervention period (third quarter 2010 to fourth quarter
2013). Control trend –refers to the linear-trend line drawn through the actual TB notification data from Ashanti Region during the period (third quarter
2010 to fourth quarter 2013)
Fig. 4 Quarterly notification rates for sputum smear positive cases for Greater Accra (GA) and Ashanti (AS) Regions with linear-trend lines from
2008 to 2013. Q: Quarter, GA-SS: Greater Accra sputum smear positive cases, AS-SS: Ashanti sputum smear positive cases. Baseline trend –refers
to the linear-trend line drawn to project TB notification expected during the intervention period for both regions using quarterly historical TB
notification data from Greater Accra and Ashanti Regions during the baseline period (first quarter of 2008 up to the second quarter of 2010)
before the intervention started. Intervention trend –refers to the linear-trend line drawn through the actual TB notification data from Greater
Accra Region during the intervention period (third quarter 2010 to fourth quarter 2013). Control trend –refers to the linear-trend line drawn
through the actual TB notification data from Ashanti Region during the period (third quarter 2010 to fourth quarter 2013)
Ohene et al. BMC Infectious Diseases (2017) 17:739 Page 8 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Given the higher risk of TB among PLHIV and dia-
betics and by using the screening criteria of cough of
any duration and at least one TB suggestive symptom,
we found higher proportions of presumptive TB cases
among the attendees in the HIV and DM clinics than in
the OPD [7, 8]. It was noted that presumptive TB cases
among PLHIV had the highest rate of testing for TB.
This is indicative of good adherence to the set guide-
lines, requiring PLHIV with symptoms suggestive of TB
to be investigated [26].
In our study the proportion with sputum smear positive
results of those tested from the OPD (8.6%) fell within the
range of what was found in two studies from Tanzania
(6.1%) and Ethiopia (13.5%) [27, 28]. The variation could
be due to the differences in settings (a tertiary facility in
Tanzania and 5 public and private health facilities in
Ethiopia) and the different durations of data collection.
The rate of sputum smear positive results among PLHIV
patients tested for TB was similar to what was found in
the study by Seni and colleagues in Tanzania [27].
The proportion of sputum smear positive TB cases
among all forms of TB varies in different reports and
may be related to the population studied, the setting, the
sensitivity of the diagnostic method and microscopy
quality assurance issues [29–35]. Consequently the di-
verse circumstances and populations studied contribute
to the range of 31.6% to 77% found in studies from dif-
ferent parts of the world [29–35]. The proportion of SS
+ve TB among the various categories of patients in our
study fell within this range. The finding of the PLHIV
TB patients having relatively lower prevalence of SS+ve
positive is not out of place, since this falls in line with
studies reporting higher prevalence of sputum smear
negative TB in PLHIV [36–38].
The ranking of the number of TB cases identified per
100,000 populations of the various groups in our study
resonates with what others have found, with OPD at-
tendees having the lowest and PLHIV the highest and
more than 10 times the figure for the OPD attendees [9,
39]. Overall, slightly more TB cases (all forms) were
identified among the outpatients screened in the >24
hour-cough approach (92.7 per 100,000 outpatients ver-
sus 82.7/100,000). Although the difference was signifi-
cant, it is important to consider the implications of the
increased burden on the laboratory having to test so
many presumptive TB patients. The numbers needed to
screen to find one TB patient (NNS) for all the categor-
ies of patients was in sync with what one would find in a
low to moderate TB incidence country like Ghana [15].
The discovery that the case finding intervention did
not demonstrate an increase in TB case notification in
the intervention population compared to the comparator
and even showed a downward trend compared to histor-
ical data was unexpected. It is possible that the number
of extra cases was too small to see an effect. Another
possibility is that some of the TB patients detected dur-
ing the program would otherwise also have been de-
tected though perhaps a bit later. It is also important to
note that the intervention was facility-based and used
symptoms screening to identify potential TB cases for
testing, which also limited its ability to identify TB pa-
tients not exhibiting these TB suggestive symptoms and
those not accessing the facilities for care. Prevalence sur-
veys have demonstrated that 50% or more of those with
bacteriologically confirmed TB may not have symptoms
commonly used to presume TB [4, 40]. Considering that
the 2013 TB prevalence survey in Ghana showed an esti-
mated TB prevalence of 290 cases per 100,000 which
was more than quadruple the WHO estimate at the time
of the project, a lot more needs to be done to improve
case finding among the general population and groups
at high risk of contracting TB including miners, PLHIV
and diabetics, prisoners and contacts of TB patients. [41,
42] Some of these key groups may also not access health
care regularly and therefore may not be reached in inter-
ventions such as these which are facility based. As reiter-
ated by the End TB Strategy, it is imperative to ensure
universal access to early and accurate diagnosis of TB
which among others includes education to trigger care
seeking among those with symptoms suggestive of TB
and screening among high risk groups. [42] In employ-
ing these active and enhanced case finding methods,
there is a need to scale up the use of more sensitive
diagnostic methods beyond sputum smear microscopy
that include new molecular diagnostics and employ add-
itional screening tools beyond symptom screening such
as chest X-ray to identify other forms of TB including
extra-pulmonary and bacteriologically negative forms as
well as TB in children [21, 42].
Since the projection from the baseline historical data
indicated a downward trend similar to the decreasing
TB case notification nationally over the intervention
years, it is also possible that there might be some under-
lying programmatic constraints contributing to fewer
cases being detected [41]. This could be a subject for
further investigation. Contrary to study settings in which
there is meticulous supervision, monitoring and mea-
sures put in place to ensure adherence to protocols, this
intervention was implemented under programmatic
conditions.
There are some limitations to this study. Since it was a
retrospective assessment of an intervention that was not
implemented under rigorous trial conditions, some ele-
ments of bias, such as the assignment of the screening
approach to the facilities, could have been introduced in
the execution of the intervention. Secondly, validation of
the diagnosis of TB cases was not possible. Finally, the
study did not explore the possible events and prevailing
Ohene et al. BMC Infectious Diseases (2017) 17:739 Page 9 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
circumstances that may have affected the outcomes and
thrown light on some of the findings, such as suspension
of OPD services that occurred as a result of industrial
actions by health workers or shortage of diagnostic re-
agents during the intervention period. Despite these
drawbacks, to our knowledge this study is the first in
Ghana to assess the yield of TB cases from symptomatic
screening of different categories of patients. Further
study building on the finding of this paper should ex-
plore treatment enrolment and outcomes of the TB
cases identified from the different settings.
Conclusion
In this study the screening approach using a shorter dur-
ation of cough (>24 hours) had a somewhat better yield
of TB cases and appears feasible for implementation.
The increased workload on the laboratory, however, war-
rants further study to assess whether this is outweighed
by the higher number of TB cases identified. This study
reiterated that the yield of TB cases was highest among
PLHIV, contacts of TB patients and diabetics screened
but the vast majority of cases were detected in general
OPDs. Though in Ghana screening of PLHIV for TB is
being implemented to an appreciable extent in HIV
clinics, it is important to ensure that it is being done sys-
tematically. Screening of contacts of TB cases and dia-
betics has been virtually non-existent. Since it is already
a policy in Ghana to undertake home verification of TB
cases before the initiation of treatment, tagging along
screening of the contacts of the TB cases during these
home visits could facilitate the identification of potential
cases in this high risk group. Greater collaboration be-
tween the NTP and the Non-Communicable Disease
Control Program could facilitate the introduction of TB
screening in all diabetes clinics. When considering a TB
screening program, it is essential to simultaneously look
at the overall health system functions and enhance cap-
acity to facilitate early detection. This would involve en-
suring that more sensitive screening and diagnostic tools
such as chest X-rays (CXR) and Gene Xpert (GXP) are
available where needed throughout the system. The
NTP is rolling out programs to further improve case de-
tection among risk groups and including the deployment
of GXPs and the launch of a digital X-ray project in
health facilities [41]. Considering that the study could
not demonstrate any impact on overall case notification,
further research is needed to assess the impact of the
introduction of these initiatives which use more sensitive
methods for screening and diagnosis of TB on yield and
notification.
While the study could not demonstrate any impact on
overall case notification, in view of the significant pool
of TB cases yet to be diagnosed sole reliance on identify-
ing TB among patients presenting with TB suggestive
symptoms or those accessing care at health facilities may
limit timely diagnosis creating the conditions for disease
transmission and worse outcomes.
Abbreviations
AS: Ashanti; CIDA: Canadian International Development Agency; CXR: Chest
X-ray; DM: Diabetes mellitus; ECF: Enhanced case finding; GA: Greater Accra;
GXP: Gene Xpert; HIV: Human Immuno-deficiency Virus; NNS: Number
needed to screen; NTP: National Tuberculosis Control Program; OPD: Out-
patient department; PLHIV: Persons living with HIV; SS+ve: Sputum smear
positive; TB: Tuberculosis; WHO: World Health Organization
Acknowledgements
The authors wish to thank the staff and patients of Korle Bu Teaching
Hospital, Ridge Hospital, Achimota Hospital, Legon Hospital, Maamobi
Hospital, Princess Marie Louie Hospital, La General Hospital, Kaneshie
Polyclinic, Mamprobi Polyclinic, Ussher Polyclinic, Dansoman Polyclinic for
their wonderful support and cooperation in making this report possible.
Thanks also go to Dr. Salah Ottmani and Dr. Jacob Creswell for the
tremendous support in facilitating the implementation of the TB case finding
initiative in Ghana. Profound appreciation goes to the Canadian International
Development Agency for funding the intervention. SAO, KL and MU are
WHO staff members. The authors alone are responsible for the views
expressed in this publication and they do not necessarily represent the
decisions or policies of WHO.
Ethical approval and consent to participate
Ethical clearance for the study was obtained from the Ghana Ministry of
Health Research Division Ethical Review Board. There was no contact with
individual patients so consent to participate is not applicable.
Funding
The TB case-finding intervention in the health facilities in Accra Metropolis
was funded by Canadian International Development Agency with technical
support from WHO. There was, however, no funding allocated to support
these analyses.
Availability of data and materials
The data for this study is available at the Ghana National TB Control Program
and not accessible online. The data may be made available upon written
request to the NTP through the authors, provided the request complies with
the Ethical Review Board guidelines.
Authors’contributions
SAO conceptualized and drafted the paper. AS, SD, GM, FA, AT and SAO
helped to collect the data. SAO, AT and MB undertook the statistical analysis.
FB, NNHN, PK, MB, MU, KL and SAO contributed to the evaluation design
and revising drafts of the paper. All authors approved the manuscript.
Consent for publication
Not applicable
Competing interests
The authors declare that they have no competing interests.
Publisher’sNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
1
World Health Organization Country Office, 29 Volta Street Airport, Airport
Residential Area, P.O. Box MB 142 Accra, Ghana.
2
National Tuberculosis
Control Program, Accra, Ghana.
3
KIT Health, Royal Tropical Institute (KIT),
Amsterdam, The Netherlands.
4
Global TB Programme, WHO, Geneva,
Switzerland.
5
Ghana Health Service, Accra, Ghana.
6
Department of Global
Health, Academic Medical Centre, Amsterdam Institute of Global Health and
Development, Amsterdam, The Netherlands.
Ohene et al. BMC Infectious Diseases (2017) 17:739 Page 10 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Received: 14 August 2016 Accepted: 21 November 2017
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