SCHOOL OF PUBLIC HEALTH
COLLEGE OF HEALTH SCIENCES
UNIVERSITY OF GHANA
ASSESSMENT OF ADHERENCE TO THE TEST, TREAT AND TRACK (T3)
MALARIA POLICY AT SELECTED HEALTH FACILITIES IN GHANA
BY
CHARLES KYEI
(10805135)
THIS DISSERTATION IS SUBMITTED TO UNIVERSITY OF GHANA, LEGON IN
PARTIAL FULFILMENT FOR THE AWARD OF MASTER OF PUBLIC HEALTH
DEGREE
OCTOBER, 2020
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DECLARATION
I, Charles Kyei, hereby declare that except for the references to the literature and works of
other researchers which has been duly acknowledged, the work in this proposal is the result of
my work put together and that I have never before submitted it to any other tertiary institution
for a study.
CHARLES KYEI
(STUDENT)
……………………………………..
DR AMA POKUAA FENNY
(ACADEMIC SUPERVISOR)
………………………………….
Date: ………………………………….
10th September 2021
Date: ……10th September.2021….
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DEDICATION
I wish to, first of all, dedicate this work to the Almighty God for his protection and guidance
to undertake this study. Secondly, I also dedicate the work to my mother, Madam Akua
Gyesiwaa for conceiving the idea of sending me to school, and finally my wife Madam Patricia
Antwiwaa for the wonderful assistance throughout the programme.
May God richly bless them.
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ACKNOWLEDGEMENT
My first and foremost thanks go to the Almighty God for his guidance to this far. I will like to
give special thanks to my Director, Dr. Kwaku Poku Asante, and the management of the
Kintampo Health Research Centre (KHRC) for the immense support of this programme.
Special thanks go to Mrs. Charlotte Tawiah-Agyemang and Mrs. Stephaney Gyaase of KHRC
for the wonderful assistance during the analysis of this study, and to the entire KHRC staff for
their prayers.
Special acknowledgment also goes to my supervisor, Dr. Ama Pokuaa Fenny of the Institute
of Statistical, Social and Economic Research (ISSER) the University of Ghana, and my head
of department, Dr. Patricia Akweongo, Department of Health Policy Planning and
Management (HPPM), the University of Ghana for their reviews, contributions and the
encouragement in making this study a success.
I would like to give special thanks to Professor Seth Owusu-Agyei, Pro-Vice-Chancellor of the
University of Health and Allied Sciences (UHAS) for the encouragement and motivation to
pursue this programme.
Finally, I would like to acknowledge Secretary Auntie Faustina, and the entire staff of the
Department of Health Policy Planning and Management (HPPM), School of Public Health
(SPH), the University of Ghana for the immense support in making this journey a success.
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List of Abbreviation
Abbreviation Meaning
T3 Test, Treat and Track
WHO World Health Organization
RDT Rapid Diagnostic Test
GMIS Ghana Malaria Indicator Survey
HDSS Health and Demographic Surveillance System
ACT Artemisinin Combination Therapy
CHPS Community-Based Health Planning and Services
KHRC Kintampo Health Research Centre
KHDSS
HDSS
Kintampo Health Demographic Surveillance System
Health Demographic Surveillance System
PPMV Patent and Proprietary Medicine Vendor
OTCMS Over the Counter Medicine Sellers
ERB Ethical Review Board
UG University of Ghana
ISSER Institute of Statistical, Social and Economic Research
NMCP National Malaria Control Programme
LCSA Licensed Chemical Sellers Association
MoH/GHS
mRDTs
Ministry of Health/ Ghana Health Service
Malaria Rapid Diagnostic Tests
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TABLE OF CONTENTS
DECLARATION ................................................................................................................... ii
DEDICATION ...................................................................................................................... iii
ACKNOWLEDGEMENT .................................................................................................... iv
List of Abbreviation ............................................................................................................... v
LIST OF TABLES ................................................................................................................. x
ABSTRACT .......................................................................................................................... xi
CHAPTER ONE .................................................................................................................... 1
INTRODUCTION .................................................................................................................. 1
1.0 Background to the study ................................................................................................... 1
1.1 Problem Statement ........................................................................................................... 3
1.2 Research Questions .......................................................................................................... 5
1.3 General Objective ............................................................................................................. 5
1.4 Specific Objective ............................................................................................................ 5
1.5 Justification ...................................................................................................................... 5
CHAPTER TWO.................................................................................................................... 8
LITERATURE REVIEW ....................................................................................................... 8
2.0 Introduction ...................................................................................................................... 8
2.1 Overview of Test, Treat and Track (T3) Malaria Policy Initiative .................................. 9
2.2 Knowledge of the T3 malaria policy .............................................................................. 11
2.3 Adherence of T3 malaria policy ..................................................................................... 13
2.4 Proportion of malaria cases tested, treated and tracked ................................................. 14
2.5 Practice of T3 malaria policy ......................................................................................... 17
2.6 Conclusion ...................................................................................................................... 19
CHAPTER THREE .............................................................................................................. 20
METHODS........................................................................................................................... 20
3.0 Study design ................................................................................................................... 20
3.1 Study Area ...................................................................................................................... 20
3.2 Target Population ........................................................................................................... 23
3.3 Sample size for the survey ............................................................................................. 23
3.4 Quantitative data collection ............................................................................................ 23
3.5 Inclusion and exclusion criteria...................................................................................... 24
3.5.1 Inclusion criteria .......................................................................................................... 24
3.5.2 Exclusion criteria......................................................................................................... 24
3.6 Quality Control ............................................................................................................... 24
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3.7 Data collection and management ................................................................................... 24
3.8 Study Variables .............................................................................................................. 25
3.8.1 Outcome variable ........................................................................................................ 25
3.8.2 Exposure variable ........................................................................................................ 25
3.9 Explanation to the Conceptual framework ..................................................................... 26
3.11 Data analysis ................................................................................................................ 30
3.12 Ethical consideration .................................................................................................... 30
3.12.1 Benefit and risk ......................................................................................................... 30
3.12.2 Privacy ....................................................................................................................... 31
3.12.3 Informed Consent ...................................................................................................... 31
3.12.4 Voluntary participation ............................................................................................. 31
3.12.5 Conflict of Interest .................................................................................................... 31
3.12.6 Anonymity and confidentiality.................................................................................. 32
3.13 Dissemination ............................................................................................................... 32
CHAPTER FOUR ................................................................................................................ 33
RESULTS............................................................................................................................. 33
4.0 Introduction .................................................................................................................... 33
4.1 Basic characteristics of different health facility levels ................................................... 33
4.2 Facility approach to malaria services ............................................................................. 35
4.3 Knowledge of T3 policy among different health facility levels..................................... 36
4.4 Adherence to treatment of malaria cases among different health facility levels............ 38
4.5 Adherence to tracking of malaria cases among different health facility levels ............. 39
4.6 General adherence to T3 policy among different health facility levels ......................... 40
4.7 Health professionals’ knowledge, adherence and the T3 policy .................................... 41
4.8 Basic characteristics of clients ....................................................................................... 41
4.9 Proportion of clients tested for malaria cases................................................................. 42
4.10 Proportion of treated malaria cases among clients ....................................................... 44
4.11 Proportion of tracked malaria cases among clients ...................................................... 45
4.12 Clients factors associated with proportion that received T3 ........................................ 48
CHAPTER FIVE .................................................................................................................. 49
DISCUSSIONS .................................................................................................................... 49
5.0 Background .................................................................................................................... 49
5.1 Knowledge of testing malaria cases among different health facility levels ................... 50
5.2 Adherence to treatment and tracking of malaria cases at different health facility levels
.............................................................................................................................................. 51
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5.3 Proportion of T3 malaria cases among clients at different facility levels ...................... 53
5.4 Limitations of the study.................................................................................................. 56
CHAPTER SIX .................................................................................................................... 57
CONCLUSIONS AND RECOMMENDATIONS............................................................... 57
6.0 Conclusion ...................................................................................................................... 57
6.1 Recommendations .......................................................................................................... 57
REFERENCES ..................................................................................................................... 59
APPENDICES ...................................................................................................................... 66
Appendix 1 .............................................................................................................................................66
Appendix 2 ............................................................................................................................................69
Appendix 3 ........................................................................................................................... 82
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LIST OF FIGURES
Figure 1 Map of Ghana showing the T3 study districts………………………………. 22
Figure 2 Conceptual framework of the T3 malaria policy………………………….. 26
Figure 3 Distribution of Health Facilities by location…………………………......... 33
Figure 4 Different Health Facility Adherence level………………………………… 40
Figure 5 Total proportion of clients received T3 policy……………………………. 47
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LIST OF TABLES
Table 1. Study variable of interest and definition .................................................................... 28
Table 2: Objective and Outcome measurement ....................................................................... 29
Table 3 Description of basic health facility infrastructure at different levels .......................... 34
Table 4 Description of different facility level approach to malaria services ........................... 35
Table 5 Indicators for assessing knowledge of T3 malaria policy ........................................... 37
Table 6 . Indicators for treatment among different health facility levels................................. 38
Table 7 Indicators of tracking malaria cases among different health facility levels................ 39
Table 8 Relationship between facility adherence and T3 policy ............................................ 41
Table 9 Description of basic demographic of clients.............................................................. 42
Table 10 Indicators of testing malaria cases among clients ..................................................... 43
Table 11 Indicators of treatment of malaria cases among clients ............................................ 44
Table 12. Indicators of tracking clients after treatment .......................................................... 46
Table 13: Association between clients’ demographics, facility type and compliance ............ 48
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ABSTRACT
Background: According to the World Health Organization (WHO) 2012 report, the African
Region carries a disproportionately high share of the global malaria burden. The disease burden
prompted the WHO Global Malaria Programme to initiate the Test, Treat and Track (T3) policy
in 2012, which Ghana adopted to scale up malaria testing, increase treatment with antimalarials
and strengthen the malaria surveillance system. Seven years after the adoption of the policy in
Ghana, it is prudent to assess the adherence towards the T3 malaria policy at different health
facility levels in Ghana.
Method: The study used secondary data from the Coffey International T3 Malaria evaluation
for the analysis. This is a descriptive cross-sectional study using a quantitative method,
conducted in six districts in three regions of Ghana’s three malaria epidemiologic zones: the
northern savannah, the tropical rainforest, and the coastal savannah/mangrove swamps. Data
was collected using a standard questionnaire and analyzed using descriptive statistics and
Pearson’s chi-squared test to determine associations. Data from healthcare providers and client-
exit interviews from 28 health facilities were used for the analysis.
Result: The study assessed 28 health facilities consisting of 16 (57.1%) CHPS, 5 (17.9%)
Government Hospitals and 7 (17.9%) Health Centres. Also, 590 clients from various facilities,
made up of 66.4% females and 33.6% males was interviewed. Overall, the study revealed
98.1% knowledge and 96.4% adherence levels among health facilities. However, the
proportion of total recipients of T3 at the client’s level was 28.0% due to a lower number of
tracking clients to complete the policy guidelines process. The study found a significant
association between age groups of clients and the level of compliance with the policy.
Conclusion: The research revealed higher knowledge and adherence level of the T3 policy at
the facility levels during the survey. However, the study showed that though the percentage of
testing and treating was found to be at a higher level, the number of clients who received the
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three processes (Test, Treat and Tracked) was low (28%). This was due to the inability of a
greater proportion of clients to complete the tracking component of the policy as stipulated in
the implementation guideline. There was an association between the age of clients and
compliance with the T3 policy.
Recommendations: The study recommends that the National Malaria Control Programme
(NMCP) and the GHS undertake measures to train healthcare providers, increase monitoring
and supervision. These two agencies should ensure regular supply of RDTs and Artemisinin
Combination Therapies (ACTs) to promote adherence. Furthermore, there is the need to
undertake further research on the policy implementation processes across the various cascade
of care.
Key words: Adherence, Compliance, RDT, ACT, Malaria, Health facility, Clients.
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CHAPTER ONE
INTRODUCTION
1.0 Background to the study
In 2017, there were an estimated 219 million cases of malaria in 87 countries. The estimated
number of malaria deaths stood at 435 000 (WHO, 2018). The World Health Organization
(WHO) indicated that the African Region alone carries a disproportionately high share of the
global malaria burden. During the same year, the African region was home to 92% of malaria
cases and 93% of malaria deaths (WHO, 2018). In addition to the malaria disease statistics,
approximately 6 million children less than 5 years of age die annually worldwide, and half of
these child deaths occur in Sub Saharan Africa. These deaths are mostly caused by preventable
and treatable diseases like pneumonia, malaria, and diarrhea (Johansson, 2016).
According to Baiden et al, in a study that examines the shift from presumptive treatment to
test-based showed that in Ghana and Kenya, the probability of fever that could be attributed to
malaria was as high as 61% and 67% respectively (Baiden et al., 2014). It has also been reported
that in Kenya, less than 40% of febrile children under five years were tested for malaria and in
Ghana, 73% of children were presumptively diagnosed and treated for malaria (Baiden et al.,
2014). In early 2010, WHO came out with a revised treatment guideline that demanded a shift
from the presumptive diagnosis and treatment to the test-based method of managing diseases.
The practicality of the process was for suspected cases of uncomplicated malaria to be
confirmed with malaria Rapid Diagnostic Tests (mRDTs) or microscopy test before treatment
is initiated with required antimalarial, and for the health care providers to keep surveillance of
the reported cases. This modification was to bring to an end the era of presumptive practice
that spanned several years (Baiden et al., 2014).
The modification has compelled the malaria-endemic countries, donors, and the global malaria
community to scale up diagnostic testing, adhering to treatment measures using recommended
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antimalarial drugs and disease surveillance on tracking malaria reported cases (WHO, 2012).
According to Agandaa et al, 2016, studies have shown that public primary health care facilities
lack diagnostic kits like microscopes and in situations where test kits are available, the
personnel to use the kits are inadequate compared with the high volume of work. Based on this,
in the past, fever from most endemic countries associated with malaria was diagnosed and
treated presumptively as malaria (Agandaa et al, 2016). Besides, clinicians’ adherence to
negative RDT test result among patients was very poor with the claim among health staff that
negative test does not rule out malaria, according to Bisoffi et al, 2011 from a study in Burkina
Faso and Abdelgader 2012, in malaria case management study conducted in Sudan. The test
provides an opportunity for improved diagnoses and better case management (Agandaa et al,
2016). Many countries in malaria-endemic areas have adopted the policy, however, focusing
on the implementation thoroughly has become a challenge due to many factors. In Ghana, 21
percent of children age 6-59 months tested positive for malaria parasites according to
microscopy results, whiles 28 percent of children age 6-59 months were positive for malaria
antigens with RDTs (GMIS, 2016).
In 2012, the WHO initiated a project called T3: Test. Treat and Track, imploring malaria-
endemic countries, donors, and the global malaria community to scale up diagnostic testing,
treatment, and surveillance for malaria (Oteng, Kenu, Bandoh, Nortey, & Afari, 2020). The
Global Initiative was established to provide a mechanism for endemic countries to improve
these three main pillars of malaria prevention and elimination. The T3 strategy, which is one
of the recommended WHO malaria control strategies, emphasizes the main policy messages of
WHO guidelines on diagnostic testing, care, and surveillance, i.e., that every suspected malaria
case should be tested, every confirmed case should be handled with a quality-assured
antimalarial medication, and the disease should be monitored through consistent and accurate
surveillance. In 2013, Ghana introduced this initiative and established guidance for
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implementing the T3 policy by updating the guidance for malaria case management and
educating health professionals on the implementation of the initiative (GMIS, 2016). The
NMCP added to its objectives measures to provide a parasitological diagnosis to all suspected
malaria cases and provide prompt and effective treatment to 100% of confirmed malaria cases
by 2020.
1.1 Problem Statement
Malaria is a principal cause of death for children under five years of age in sub-Saharan Africa.
The disease kills a child every 60 seconds and also poses a threat to pregnant women and their
unborn babies (GMIS, 2016). The implementation of the test-based management of malaria
cases also presented an additional responsibility for clinicians concerning the education of
patients. These are mainly the parents or guardians living in areas where presumptive treatment
was experienced for many years (Baiden et al., 2014). Global malaria treatment policy on
presumptive treatment of malaria whenever there is fever has shifted to treatment with
artemisinin-based combination therapy (ACT), the required antimalarial after a positive test
with microscopy or RDT. A study by Faust et al, 2015 conducted in Senegal assessing drivers
on T3 policy found out that antimalarial usage was not a complete indicator of effective
implementation of the policy but reliance on diagnostic tests is the better measure (Faust et al.,
2015). This is because antimalarial could be provided by a health care provider without a test,
but by relying on physical condition or signs and symptoms of patients, leading to increase in
antimalarial prescription (Rakotonandrasana, Tsukahara, & Yamamoto-Mitani, 2018). The
transition involves shifting from long-standing behavior among health care providers and
patients.
Though it is apparent that rapid diagnostic test for malaria allows improving care, diagnosis,
and improved disease management, the process has not been strictly followed according to the
guidelines by healthcare practitioners (Agandaa et al, 2016). Most of the women of
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reproductive age with their children are currently not going through the test and treat process
at the various facility levels and do not even know the policy which could motivate them to
develop the attitude towards the practicality of the policy guidelines. Adherence to policy
guidelines by both healthcare providers and the response from patients is essential for achieving
the success of the policy, but this has remained a major setback to the policy implementation
(Ezenduka, Okonta, & Esimone, 2014).
According to Agandaa (2016), in terms of health workers, though doctors had good compliance
than the physician assistants or the medical assistants, compliance to the T3 guidelines by
facilities was associated with many challenges that could hinder the smooth implementation of
the policy. Adhering to the policy guidelines would contribute greatly to the achievement of
SDG 3 by eliminating malaria by 2030. Eight years after the introduction of the policy,
gathering data on the extent to which the health facilities adhere to the malaria policy would
help the process of ensuring a successful implementation of the policy.
Seven (7) years after the T3 policy was launched, it is vital to examine and review the policy's
effectiveness in malaria-affected communities. This study aims to play a role in developing
target-focused policies and lobbying that will ensure the elimination of malaria through this
policy. The goal of this study is to contribute to what is already known about the T3 policy and
how health-care facilities comply to its components. It will add to the body of knowledge about
the best practices used by health institutions to guarantee that patients who test positive for
malaria are treated and followed up on to ensure that they do not recur after receiving malaria
treatment.
The study, therefore, examined the adherence of the T3 malaria policy among different levels
of health facilities in six districts in Ghana. Findings will enable policymakers to take decisions
on the appropriate intervention that will ensure a high percentage of adherence to the T3 policy.
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The study tested the hypothesis; different health facility levels adhere to the T3 policy
implementation.
1.2 Research Questions
1. What is the knowledge of the T3 malaria policy among health care professionals at different
health facility levels?
2. What is the level of adherence to T3 malaria policy among the different levels of health
facilities?
3. What is the proportion of patients satisfy with the T3 malaria policy?
1.3 General Objective
The study aims to assess the level of adherence to the T3 malaria policy among the different
levels of health facilities in Ghana.
1.4 Specific Objective
1. To assess the knowledge of the T3 malaria policy among health care professionals at the
health facility level.
2. To examine the adherence of T3 malaria policy among District hospitals, Health Centres and
CHPS compounds.
3. To find the proportion of community members (clients) satisfy with the T3 malaria policy.
1.5 Justification
Malaria has been identified as a major disease burden in the World with morbidity and
mortality rates of countries in Sub-Saharan Africa being the highest. The WHO has been
monitoring the prevalence of the disease and has initiated policy guidelines aimed at combating
the disease burden. A review of literature indicates that the practice of the test and treat case
management has not been strictly followed by health facilities. Currently, many countries have
adopted the case management guidelines but the implementation at the various health care
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facility levels concerning adherence or compliance has been a challenge to the successful
implementation of the policy. According to the Ghana Malaria Indicator Survey, 2016, only
54% of women who reported experiencing malaria provided a blood sample for malaria testing
to confirm the diagnosis (Prah, 2019).
There has been a mixed effect on the use of RDTs by health facilities and evidence has shown
that consistently not using the test or ignoring the test results do not lead to effective targeting
of ACTs. For effective results, evidence of proper diagnosis is required for the success of the
T3 implementation (Burchett et al., 2017). Since the WHO initiated the T3 policy in 2012,
there have been independent evaluations carried out in selected districts, however, this study
seeks to comprehensively evaluate the T3 policy in selected districts in each of the three
epidemiological zones in Ghana to assess the adherence to the guidelines which will support
WHO effort to reduce the disease burden. The NMCP’s recent strategic plan is to reduce
malaria burden by 75% by 2020, however, data to establish the relationship of variables to
support planning decisions and future assessments remains a challenge, due to inadequate
research conducted in this area in Ghana (Awine, Malm, Bart-Plange, & Silal, 2017).
The main purpose of the study is to obtain information on the T3 strategy's effectiveness at
health facilities; persuade stakeholders to overcome gaps in the T3 policy's implementation;
and guarantee that authorities hold duty bearers accountable for the delivery of malaria
services. Prioritizing the T3 policy of malaria case management at all facility levels especially
the outlying community level is key to the attainment of the sustainable development goals.
Although several studies have determined the adherence and compliance of the T3 policy, not
much has been done in terms of assessing the T3 policy in general among health facilities levels
and client perspective. The study is therefore designed to explore the adherence towards the
implementation of the T3 policy usage among different health facilities and clients in six
districts. The three regions where the six districts of the study are located and the NMCP can
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use the outcomes of the study as a baseline to inform policy interventions relevant to enhance
the process to increase adherence
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CHAPTER TWO
LITERATURE REVIEW
2.0 Introduction
Malaria is the world’s most dangerous and most common infectious disease found primarily
on the continent of Africa. In 2016, 90% of malaria infection and 91% of disease-related deaths
occurred in Africa (Sanofi, 2018). The WHO in an attempt to eradicate malaria targeted
universal coverage with long-lasting insecticidal nets and other essential malaria control
interventions by the end of 2010 (WHO, 2012). Distribution of more than 290 million nets in
Africa between 2008 and 2010, made significant progress towards achieving the target of
universal bed net coverage for at-risk population groups (WHO, 2012). Indoor residual
spraying, another highly cost-effective control intervention, also contributed significantly and
scaled up, helping to cut malaria cases and deaths in high-transmission areas (WHO, 2012).
To achieve universal coverage with diagnostic testing and antimalarial treatment, as well as
strengthen the malaria surveillance systems, the WHO recommended diagnostic testing,
treatment, and surveillance, as well as updating existing malaria control and elimination
strategies (WHO, 2012).
Malaria is one of the most proven fatal diseases in humans and some of the measures needed
to combat the deadly disease are early detection and precise diagnoses which enhances the
eradication process. The main aim for which the WHO provided the T3 treatment guidelines
was to ensure that only actual malaria cases are treated with a required antimalarial drug to
prevent misdiagnoses and overdiagnoses, and to further discourage the adherence to
presumptive treatment. A cross-sectional study among Ghanaian prescribers by Prah et al
seeking to evaluate the level of knowledge of prescribers on rapid diagnostic test revealed that
about 73% of the participants had good knowledge on the diagnosis, 84% used malaria test kits
in diagnosis, and only 9% relied on the test results for treatment (Prah, 2019). The study
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concluded that though the project depicted high awareness from prescribers, significant
numbers did not use the test results for all suspected cases.
The WHO recommended the testing and treatment of malaria cases as a strategy, by way of
using RDT for all suspected cases to support the accurate diagnosis of malaria infections.
However, prescribers continue to treat patients based on presumptive measures and clinical
symptoms without confirmation and also issue antimalarial to patients without adequate tests
to confirm cases before the treatment (Graz, 2011). The diagnostic test is relevant to help
confirm and count the number of malaria cases in order to assess the percentage of the
population being diagnosed with the disease. Therefore, in order to differentiate other diseases
from malaria and subsequent treatment with the required antimalarial drugs, there is the need
to adhere to the T3 guidelines.
2.1 Overview of Test, Treat and Track (T3) Malaria Policy Initiative
The WHO launched the malaria treatment guidelines for the management of malaria cases, by
advising the disease-endemic countries, donor agencies, and the malaria community to enhance
the testing, treatment, and surveillance of malaria. The process was to support the endemic
communities to strengthen these three parameters of malaria control and prevention (WHO,
2012). The early diagnosis and accurate surveillance of malaria cases were acclaimed to be an
important step towards the management of the disease. However, inaccurate diagnoses of
malaria cases have a dire consequence on malaria morbidity and mortality.
It is evident that parasite based diagnostic testing enhance and improve the overall management
of malaria cases, especially by identifying those who do not have the malaria disease and
therefore would not need antimalarial drugs (WHO, 2018). According to WHO report 2012,
investments in malaria prevention and control over the past decade have created unmatched
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momentum and protected more than a million lives. Malaria mortality rates have been reduced
by over a quarter globally and by one third in the WHO African Region (WHO, 2012).
A study reported that malaria diagnosis and treatment in the past years was based on clinical
signs and symptoms. Most fevers were often diagnosed as malaria and treated with
Chloroquine without pre-testing to confirm the diagnosis. As a result, there were inappropriate
diagnoses and the treatment contributed to the malaria parasites building resistance to the
Chloroquine drug which was the ‘first-line drug’ for the treatment of uncomplicated malaria
and this further increased the economic burden contributed by the disease (Agandaa et al,
2016). Prescribers’ motivation to patients resulted in high uptake of RDT especially in private
facilities which were more of working for profit but also ensuring that they get sufficient clients
(Burchett et al., 2017).
The treatment of malaria across the world has changed from just the signs and symptoms being
mainly fever to a more specific treatment after a positive laboratory-based diagnosis (Faust et
al., 2015). According to WHO, the focus is to get every suspected malaria case tested, treated,
and using timely and accurate surveillance to track the disease to set forth a new approach to
bring a near-zero malaria death in endemic countries (WHO, 2012). The WHO policy
recommended diagnostic testing for every suspected malaria case, treatment for every
confirmed case with quality-assured antimalarial medicine, and surveillance. For some time
now, malaria prevention and control have seen massive investments which have saved millions
of lives. Despite these, malaria still occurs in over 99 countries so governments need to
prioritize the malaria issue (WHO, 2012). During these periods of malaria infections, if the
necessary support for improving the T3 initiative is not forthcoming, there will be a gap in
strengthening the T3 strategy to conquer malaria. Hence, if endemic countries get the needed
support, they will be moving towards achieving the health-related Sustainable Development
Goals.
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2.2 Knowledge of the T3 malaria policy
Many people visit health facilities as well as licensed chemical sellers reporting fever with the
mindset of acquiring malaria drugs for treatment without being tested but rather based on signs
and symptoms. In Ghana, a study found that generally, people do not adopt a single treatment
pattern for uncomplicated malaria. While some patients visit health facilities immediately they
feel unwell, others visit drug stores to purchase any drug they deem appropriate for the disease
suspected or mention their health condition to the vendor who then decides on which drug is
most appropriate (Ansah, Gyapong, Narh-Bana, Bart-Plange, & Whitty, 2016).
A study conducted at HO showed that the level of adherence to the test of fever cases, negative
test results, and tracking of malaria cases had major problems that need attention (Kankpetinge
et al., 2016). From the study, general adherence to the T3 strategy was not encouraging so the
study recommended that the Ministry of Health/ Ghana Health Service (MOH/GHS) ensure
adequate and sustained supply of RDTs and ACTs to both public and private health facilities.
The study by Kankpetinge et al, 2016 revealed that 58.8% of the observed cases of fever were
tested and diagnosed for malaria before treatment, whiles 41. 5% of the cases were not tested
for malaria parasites. The study also confirmed that clinicians are likely to overlook the malaria
negative result after testing and continue to prescribe antimalarial drugs to cases that are not
malaria illnesses. The WHO in collaboration with other agencies should develop diagnostic
tools and guidelines for non-malarial fevers and incorporate them into malaria case
management (Kankpetinge et al., 2016). The study recommended that the GHS and the Ho
MHD sensitize clinicians on the relevance of the T3 strategy, especially mandatory testing and
adherence to negative test results, tracking of malaria cases, and the use of antibiotics in malaria
treatment. More research should be conducted to determine the sensitivity and specificity of
RDTs especially after it has been stored for some time at the health facilities.
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After the introduction and modification of the malaria prevention treatment policy, there is
considerable compliance on the use of ACT, which are first-line treatment for malaria endemic
countries (Ezenduka et al., 2014). However, malaria confirmation process is associated with
limited use of laboratory diagnoses due to over-reliance on presumptive treatment other than
diagnostic treatment, absence of routine evidence on malaria treatment, and co-medication to
direct effective implementation of the guidelines. There is the risk of developing parasite
resistance and unsuccessful treatment, thereby undermining the motive of the malaria treatment
policy. A wide scope for improved diagnosis and treatment measures exist to promote the
efficiency of malaria case management at some facilities (Ezenduka et al., 2014). From the
research studied, treatment practices varied notably between the two public health facilities, in
terms of patients’ characteristics. The p-value shows significance in many of the variables,
indicating differences in prescribing practices of doctors between the facilities. These
differences highlight the variation in prescribing cultures between similar facilities across the
country, suggesting differences in the dissemination of anti-malaria training information. The
differences may also point to the levels of exposure to malaria treatment practices
The study showed a significant relationship in many variables depicting differences in practices
of doctors between facilities. There were differences in variation in prescribing cultures in
many similar facilities across the country, showing differences in training information on
malaria treatment practices. The use of RDT by the Licensed Chemical Sellers Association
(LCSA) is largely accurate and acceptable to community members. However, potential
challenges associated with large-scale deployment need to be addressed.
According to Asibong et al. (2019), knowledge score during the survey indicated that
knowledge of malaria amongst Primary healthcare workers was poor, while acceptance of
RDTs amongst Primary healthcare workers was fair, this reflected in the overall knowledge
score of RDTs which was also fair. The study recommended the need for regular training and
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retraining of health workers at the PHC level and Government agencies and Donors to ensure
the continuous availability of ITNs, RDTs, and ACTs in Public Health facilities to promote
adherence in the implementation process of the policy.
In terms of knowledge on the test and treat policy, a study conducted on Healthcare providers
in Ethiopia showed that 69.3% of the total prescribers had ever seen the diagnostic test for
malaria infections, 55.2% knew how to read the test results after performing the test to clients
(Argaw, 2015). In furtherance to this study was the highlights of health information to patients
or caregivers which recorded 97% out of the 264 clients interviewed. The success of the T3
policy depends largely on the compliance to the policy at the facility level which is supposed
to be implemented through knowledge and actualization of the practice. However, according
to the study, 92% of the prescribers interviewed confirmed usage of microscopy diagnostic
kids in confirming cases showing a higher level of patronage in line with the WHO guidelines,
while only 15% resorted to the use of RDTs in confirming malaria infections. A study in West
Kenya conducted among Healthcare providers and dispensers found 93% of higher knowledge
levels exhibited, which indicated that they used RDTs and microscopy in confirmed malaria
cases, and also described the signs and symptoms to affirm the national treatment guideline
(Riley et al., 2018). Another study by Oladipo assessing knowledge among Patent Proprietary
Medicine Vendors (PPMVs) on malaria testing and treatment showed that their knowledge on
the antimalarial was very poor, below 20% knew the national antimalarial policy in 2011 and
even less than 5% had seen the document (Oladepo et al., 2019). To increase participation for
the universal adherence to the policy there is the need to involve all the various stakeholders in
the process to achieve the set target.
2.3 Adherence of T3 malaria policy
The attitude of community members towards a policy determines the success or failure of the
policy. A research conducted among primary health care workers using a self-administered
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questionnaire showed that only 2.6% of them had a good rating when determining the
acceptability rating of RDT using the acceptability score, however, none of the respondents
had good knowledge of malaria RDT usage (Asibong et al., 2019). In another study conducted
in the North-Eastern part of Tanzania among village health workers, it reported that most health
workers thought that RDTs put unnecessary pressure on standard procedures and claimed that
they needed more personnel to perform the tests (Mushi et al., 2016). In that survey, most
respondents agreed that RDTs were often available at their workplace, and usage rates are high,
but some health workers said the RDTs were unreliable. This is parallel to the suggestion in a
study in Enugu, Nigeria which detailed that they do not trust the results despite the fact that
RDTs have been found to have a sensitivity of 90.6% and a specificity of 95.9% in Nigeria
(Uzochukwu et al, 2010). In a study conducted in the South-Eastern part of Nigeria, Health
Care Providers and community members both recognized malaria RDTs as an important step
to correct treatment, though, it was also reported that there were concerns as to the reliability
of test results with symptoms being deemed more important than test results (Uzochukwu et
al, 2010). It has been noted that health workers still treat for malaria even when RDT result is
negative, due to reasons such as lack of finances to conduct microscopy by patients, which is
supported by a study carried out in Zanzibar. In a prospective cohort trial in Uganda on malaria
treatment restricted to confirmed laboratory cases, 0.8% of blood smear-negative patients who
were not given antimalarial drugs developed clinical malaria over 7 days of follow-up and all
13 were detected by the health facility and treated (Njama-Meya et al., 2007). Similar findings
were seen in Tanzania were 0.5% of RDT-negative patients developed malaria within 7 days
(Asibong et al., 2019).
2.4 Proportion of malaria cases tested, treated, and tracked
Statistics from NMCP indicate that in Ghana, the percentage of positive malaria cases using
microscopy reduced from 30 percent in 2015 to 26.4 percent in 2016 whiles RDTs also
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increased from 33 percent in 2015 to 34.3 percent and an overall increase in malaria testing
rate from 73.6 percent in 2015 to 77.3 percent in 2016 (NMCP, 2016). The availability of
quality malaria RDTs has led to an improvement in access to testing increasing the proportion
of cases tested across the world. Despite the advances made in the rate of testing for malaria
cases due to the increase in RDTs, many children do not still receive the diagnostic test and by
giving antimalarial drugs to these children will prolong their illnesses and increased the risk
(UNICEF/WHO, 2015). It is therefore prudent to adhere to the test and treatment guidelines to
enhance the success of fighting the menace. A compliance study among prescribers in both
Ghana and Uganda also showed about 71.8% of the patients were recommended for malaria
(laboratory) testing using RDT in public health facilities in Ghana, and 80% of patients in
Uganda also testing for malaria cases (Ampadu et al., 2019).
A study by Ezenduka 2014 that assessed adherence to treatment guidelines for uncomplicated
malaria at two public health facilities in Nigeria found that, out of the 2171 patients who had
been treated for uncomplicated malaria, only 49% were sent for laboratory confirmation of
malaria, out of which 45% tested positive. 51 percent of the prescriptions were based on
presumptive treatment. 58 percent of negative slide results received antimalarial drugs
(Ezenduka et al., 2014). Even when the results were negative, prescribers still presumed that
the patients were having malaria based on the symptoms they presented and went ahead to give
antimalarial medicines to them.
In evaluating the knowledge of the T3 policy, a study by Faust 2015 assessing the drivers of
full adoption of the Test and Treat Policy revealed that though national policies in Senegal have
already spread across the malaria-endemic areas, adherence to policy implementation is still
limited (Faust et al., 2015). This study indicates that prescribers do not comply fully with all
the components of the T3 policy strategy. There are two main components of the case
management strategy: accurate case identification through testing and effective treatment with
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ACTs (Hamer et al., 2007). Though effective drugs are available, thousands of people in high
-risk areas still cannot have easy access to required treatment (WHO, 2012). This is an
indication that people still do not have access to recommended drugs and there is the need to
evaluate the implementation process to address the challenges confronting the operations of
the guidelines.
In 2010, over 181 million ACT drugs were distributed throughout the world in the public sector,
increasing from 158 million in 2009. ACT use was estimated to get to 287 million courses in
2011, which was an increase of 30 percent compared to 2010 due to discounted sales in the
private sector (WHO, 2012). Active surveillance for malaria cases involves health workers
searching for malaria infections at community and household levels in populations that are seen
to be at high-risk. Improved reporting on malaria cases and deaths give an idea of people and
places most affected to inform the decision as to where resources are needed most and also
enable policymakers to take appropriate decisions in malaria prevention and control programs
(WHO, 2012). From the case management policy, malaria cases must be documented properly
so that age groups affected and the death cases from malaria ascertained. However, this process
has not been very effective in most health facilities especially the licensed chemical sellers who
are very close to the community and served as the first point of call, when one is not well.
Another study on the accuracy and perception of test-based malaria case management which
used the mixed method on both clients and licensed chemical sellers found out that test-based
management of suspected malaria cases at the licensed chemical shops was widely accepted as
an effective method of improving diagnoses for malaria treatment though there are few
challenges in the implementation. This finding adds to the rising evidence in the resource-
constrained countries, including Ethiopia, Senegal, Sudan, and Uganda where the test-based
management of malaria using RDT by non-health professionals has proven to be an innovative
strategy in malaria diagnoses and treatment (Kwarteng et al, 2019)
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2.5 Practice of T3 malaria policy
The NMCP in Ghana recommends strategically that all suspected malaria cases are confirmed
in agreement with the T3 policy guidelines (GMIS, 2016). Diagnosing malaria in the early
stage and applying the right treatment is very paramount in morbidity and mortality reduction.
Several factors like accessibility, patient gender, attitude among others influence the health-
seeking behavior of patients. Evaluating the attitude and practice of community members
regarding the diagnosis and treatment of malaria contribute to the efficient control of the
disease and supports the process of selecting an appropriate intervention, to obtain full
participation from participants.
A cross-sectional study among Ghanaian prescribers in two different regions in Ghana
(Western and Central) assessed the knowledge, attitude, and practice of 100 prescribers at four
different facilities to know the various factors affecting prescribers’ decisions on using RDTs
in the process of prescription. From the study, respondents had good knowledge of about 73%
of the total sample of 100 prescribers, and the routine use of malaria testing as 84 %, only 9 %
relied completely on malaria test results for treatment (Prah, 2019). The study depicted that
though about 90 percent of the participants were aware of the malaria test and diagnostic
guidelines, and the only handful was using the feedback from the test results (Prah, 2019). The
factors accounting for the barriers in the implementation of the WHO malaria treatment
guidelines by prescribers were found to be coming from both the health worker level and the
health systems-related, which could be potentially redressed.
A study found out that in practice some prescribers mostly do rely on symptoms relatively to
RDT results and prescribe according to the patient symptoms. The study revealed that RDT
has not been effectively used with regards to the dispensaries and identifying reasons
accounting for acceptance and adherence by prescribers to the results may support to improve
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the strategy aimed at effective implementation of cost-effective and accurate diagnostic tool
(David, n.d.).
The test and the treatment of malaria infections using the recommended guideline is associated
with implementation and adherence challenges. The major challenge at the CHPS compounds
were frequent RDT stock-outs. The CHPS compounds were mostly affected because RDT was
the only diagnostic tool available for testing. Health Centers also mentioned a lack of diagnostic
facilities such as microscopy as a major challenge (Agandaa et al, 2016).
A study that looked at the challenges and the perception of the access to test and treat malaria
policy acknowledged that some people did not participate in the Mass testing, treatment, and
tracking (MTTT) activities because of misconceptions and rumors spread in the community
(Ndong et al., 2019). One reason for their refusal to participate was the perception that health
workers were infecting people. They believed that epilepsy was being introduced into the blood
of the person through the needle prick and that some of the volunteers were spiritualists. From
the study, some community members did not like the medicine because they experienced side
effects such as stomach upset, dizziness, or headache after taking the medicine (Ndong et al.,
2019).
The over-treatment of uncomplicated malaria using ACT as a prescription for patients under
presumptive diagnoses was higher (30.6%) among patients who presented feverish conditions
as signs of malaria, with those showing various symptoms other than fever going for 17.2%.
Some of these invalid practices were found relative to other research on health professionals.
Apart from malaria control progress made over the years, case management, and unsuitable
treatment remains a challenge for health systems of many malaria-endemic countries
(Kwarteng et al, 2019). This initiative of the WHO is obviously a positive attempt to improve
case management by ensuring adherence to the T3 guidelines as per the treatment protocols of
each WHO member state.
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A study conducted in Bongo in the Upper East Region of Ghana revealed that frequent RDT
stock-outs (39.3%) as the major challenge followed by lack of diagnostic (35.7%) with the least
being frequent ACTs stock-outs (3.6%). RDT shortage was key at the CHPS level, lack of
diagnostic facilities was a major challenge at the Health Centre level whilst the District
Hospital, however, did not have any challenge (Agandaa et al, 2016). A study in Western
Uganda reported that few prescribers raised concerns about RDT negative test that later proved
to be smear-positive (Altaras et al., 2016). A study found out that the individual or caregiver
confidence of the test may have influenced whether the individual who is sick and tested for
malaria would adhere to the test result. In other words, there were several places of evidence
from the study that suggested that the testing and the treatment decisions were made largely by
the health worker. Additionally, regardless of the test status, the study reported that about 84
percent of individuals were given ACT at the health facility or pharmacy.
2.6 Conclusion
Chapter two summarized the literature examined to address the research questions. The
literature reviewed included: a general description of the malaria test, treatment, and follow-
up, T3 policy initiative; the proportion of malaria patients tested, treated, and monitored;
compliance; awareness of the malaria test, treatment, and follow-up policy; attitudes towards
the malaria test, treatment, and monitoring policy; implementation of the test, treatment, and
follow-up of malaria policies and facility issues relating to adherence to the T3 programme.
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CHAPTER THREE
METHODS
3.0 Study design
The study used secondary data from the Coffey International study “Ghana’s implementation
of the Test, Treat and Track Policy for Malaria” for the analysis. The parent study was a
descriptive cross-sectional study using mixed methods. However, this study used the
descriptive cross-sectional study data with quantitative methods. The quantitative method used
surveys and other available service delivery data to provide quantitative estimates of the desired
outcomes of the project. The method was used to collect information on T3 malaria policy
implementation among service providers at the health facilities and clients exit interviews.
3.1 Study Area
The study was conducted in six districts: Nzema East Municipality, Mpohor District, Kintampo
North Municipality, Kintampo South District, Jirapa Municipality, and Mamprusi Municipality
across three Regions in Ghana – Western North Region, Bono East Region, and Upper East
Region. Selected districts were those districts where malaria interventions funded by Comic
Relief had its intervention programmes undertaken. Also, Ghana has 3 malaria epidemiologic
zones: the northern savannah, the tropical rainforest, and the coastal savannah/mangrove
swamps (Owusu, Brown, Grobusch, & Mens, 2017). The six districts were carefully selected
to represent each of the 3 malaria epidemiologic zones.
Mpohor District and Nzema East Municipal are both located in the Western North region. The
two largely rural districts have a total population of about 130,000, the majority of whom
engage in fishing, agro-processing, and mining. The area which is highly endemic in malaria
has a doctor-patient ratio of 1:21461 has 2 district hospitals, 5 health Centres, and 9 CHPS
compounds by way of public health facilities. Key issues or challenges of the districts include
poor road network, poor health infrastructure, inadequate potable water, poor drainage system,
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inadequate educational infrastructure, inadequate market structure, inadequate services the
high number of poor and vulnerable groups, and low agricultural production.
The Kintampo north municipality and Kintampo south district are located within the forest-
savannah transitional ecological zone in the Bono East region of Ghana. The 2 districts cover
an area of 7162km2, which is largely rural with a resident population of approximately 160,
000 who are predominantly practicing subsistence farming. Public health facilities in the 2
districts include 2 hospitals, 12 health centres/clinics, and 30 Community-based Health
Planning and Services (CHPS) compounds; whilst the privately-owned health facilities
included 4 clinics, 2 maternity homes, 4 pharmacies, and 86 Over the OTCMS (Afari-Asiedu
et al., 2018).
Jirapa and West Mamprusi Municipalities are located in the northwestern part of the Upper
West region and North East regions respectively. The vegetation of the 2 municipalities is
Guinea Savanna woodland with light undergrowth and scattered trees. The major economic
trees are shea, dawadawa, and baobab species. The population for the 2010 population census
is approximately 138,000 (GSS, 2012). The main economic activities engaged in by the people
are farming, livestock rearing, and fishing. Malaria ranks tops as a major health problem.
Public health facilities in the 2 districts include 2 hospitals, 1 polyclinic, 11 health
centres/clinics, and 35 CHPS compounds.
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Figure 1 Map of Ghana showing the T3 study districts
Source: Coffey International T3 malaria evaluation, 2019.
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3.2 Target Population
The study was conducted using health facilities. Specifically, health care providers working in
government health facilities were interviewed to determine their knowledge and adherence to
the T3 policy. Also, community members (client) exit interviews were conducted and gathered
evidence on client perspectives on the malaria T3 policy. The focus was on clients who have
had an episode of malaria and have received treatment at different health facility level i.e.,
Hospitals, Health Centres and CHPS.
3.3 Sample size for the survey
Thirty (30) health facilities were assessed across the three regions. In each of the selected
districts, the government hospital, a health Centre and three (3) CHPS compounds providing
malaria services were visited, and readiness to provide malaria services and their adherence to
the T3 policy were assessed. Twenty (20) client-exit interviews were conducted in each of the
five facilities per district, thus in total, in each district, 100 client-exit interviews were to be
undertaken. The total for six districts was 600 client-based interviews. However, in all 590 out
of the targeted 600 clients were actually interviewed for the study.
3.4 Quantitative data collection
In each district, five health facilities were studied. The five health facilities comprised of 3
CHPS compounds, 1 health Centre, and 1 district hospital. The data collection period was
spanned for over two weeks. Face to face interviews using structured questionnaire was used
to collect information on knowledge and adherence to the T3 policy among service providers
and clients. The clients were interviewed as they exited the facility after treatment. The
proportion of client interviews per district was 100. The data collectors and supervisors were
trained on the objectives of the study, data collection tool, and mode of data collection. To
ensure the quality of data, three days of training were given to both the data collectors and
supervisors on the objectives of the study, data collection tool and mode of data collection.
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3.5 Inclusion and exclusion criteria
3.5.1 Inclusion criteria
1. Eligible patients willing to be consented into the study
2. All health care providers working in facilities in the selected districts.
3. Clients who have had an episode of malaria and have received treatment at the selected
health facility.
3.5.2 Exclusion criteria
1. Excluded from the analysis all non-health workers
2. Clients from non-selected health facilities.
3. Clients without an episode of malaria during the survey.
3.6 Quality Control
To ensure the quality of data, the questionnaire was pre-tested on 10% of the sample size at
different health facilities across the same district and their respective clients. The result of the
pre-test was analyzed and necessary modifications were made before the actual data collection.
The completed questionnaires were submitted to the data managers. The data managers kept
the questionnaires and transcribed materials in a cabinet under lock and key. The site
investigators, data managers were responsible for the safety of the questionnaires to avoid a
third party from having access to it.
3.7 Data collection and management
Data were collected electronically using Cosmos Version 1.6 data collecting App. This was a
platform for data collection, analysis, mapping, and reports. It works on Windows and Android
mobile phones. Electronic data files were stored on a cloud-based secured platform hosted by
Coffey International. In addition to this, individual sites also hosted their respective site data
on their local servers. The data stored on this secured server were encrypted so it can only be
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accessed by those with the correct encryption key. The encryption key was only available to
members of the immediate research team who analyzed the data. All hard copies of data sheets
were kept in a locked file cabinet that was accessed by the programme managers. For the
purposes of this study, data collected for variables like facility approach to malaria services,
awareness of T3 policy, access to training on T3 policy, client’s treatment information and
tracking records were extracted for the analysis.
3.8 Study Variables
3.8.1 Outcome variable
The specific outcome of interest is the adherence to the T3 policy. Adherence to the policy in
the study refers to accepting and using the three processes of testing, treating, and an indication
of tracking of cases treated at the facilities.
3.8.2 Exposure variable
The key exposure variables are the indicators of adherence, comprising of different facility
level characteristics with regards Hospitals, Health Centres and CHPS, infrastructure and
approach to malaria services and the background of clients, including age and sex, and the
availability and access to RDTs and awareness of malaria T3 policy as well as the interplay of
follow-up and practice.
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Figure 2 Conceptual framework of the T3 malaria policy
-
Source: Adapted from Boadu et al, 2016
3.9 Explanation to the Conceptual framework
Several factors influence the decision of a health facility and community members to adhere to
a policy, by testing before treatment of feverish conditions as provided by the WHO T3 policy
guidelines. For this study, the factors influencing health facility and client’s adherence to the
T3 policy have been grouped into health facility level factors and patients' or client’s factors.
Health facility factors comprised of facility infrastructures like access to water and toilet
facilities and designated phone and availability of services which includes the availability of
RDTs or microscopy, while the patient factor includes access, awareness, knowledge. The
study dwells on the concept of the effect of inadequate facility resources on service provision
which can influence the outcome of an intervention programme (Amoakoh-Coleman et al.,
2016).
Age
Sex
Awareness
Access
Facility factors
Facility type
Infrastructure
Staffing
Operations
Adherence
To T3 policy
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Demographic variables like sex, age, level of the facility, location of the facility whether urban
or rural also play a major role in ensuring the success of a particular policy. Other factors such
as mode of operation of services for testing with RDTs and other services to support a particular
intervention could also influence the process. Beyond these factors, the adherence to the policy
may largely depend on whether the beneficiaries of the policy know, a positive attitude, and
are willing to practice during policy implementation. According to Abor et al. (2011), the
utilization of maternal health services and intensity of use of antenatal services was influenced
by several variables including the age of mother, education of mother, ethnicity, economic
status, geographic location, and religious affiliation. Also, according to Ansah et al. (2016),
demographic characteristics and socio-economic status are among the factors influencing the
choice of health-seeking for acute fever in Ghana. Malaria diagnosis and treatment
encompasses an interplay of factors from both clients and health facility levels. Availability
of guidelines and the level of care at the primary health care is significantly associated with the
adherence to the T3 malaria policy (Sciences, 2018).
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Table 1. Study variable of interest and definition
TERM DEFINITION
Study participant
Healthcare provider
Compliance
A person selected as part of the study
Health worker delivering service by prescription at the facility
Patient who has been tested, treated and given information for review
Client Patient who has had episode of malaria and had visited health facility
Challenges Factors hindering opportunity to access the T3 policy at the facility
Knowledge Being aware and responsive to the test, treat and track policy
Practice Received test, treat and tracked
T3 policy Testing, treating and tracking of suspected malaria cases
Adherence Compliance to the T3 malaria policy processes
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Table 2: Objective and Outcome measurement
Objective Outcome Measure How to measure
To assess the
knowledge of the T3
malaria policy
among health
facilities.
Knowledge
of testing
before
treatment
Estimating the
percentage of
facilities having
knowledge on
T3
Fraction of Health facilities with
knowledge on testing, treating
and tracking for malaria cases
Use Fishers exact test to
determine the relationship
between Knowledge and T3
policy.
To assess the
adherence of T3
malaria policy
among facility
levels.
Adherence of
T3 policy
among
facilities
Calculating the
percentage of
facilities
adhering to the
T3 policy
Fraction the proportion of Health
facilities adhering to testing,
treating and tracking of malaria
cases.
Use Fishers exact test to
determine the relationship
between Adherence and T3
policy
To find out the
percentage of clients
who were satisfied
with the T3 malaria
policy process.
Practice of
testing before
treating
malaria case
Calculating the
proportion of
Clients went
through the T3
policy steps
Proportion of respondents who
are tested, treated and tracked
were computed. Use Pearson’s
chi2 to determine an association
between clients demographic and
the proportion of clients received
T3
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3.11 Data analysis
Data were analyzed using Stata version 14.0. Tabulations were done to evaluate the
characteristics of the health facilities and the clients who visited the facilities. Descriptive
statistics were used in explaining all the indicators relating to the outcome of the study
Categorical variables were expressed as frequencies and percentages. The health facility levels,
the facility type, the operation of the facility, and other variables were presented using tables
and graphs. Fisher’s exact test was used to determine the relationship between knowledge,
adherence, and T3 policy. Similarly, Pearson’s chi-squared test was also run to determine the
association between clients’ demographics, facility type, and compliance to T3 policy.
3.12 Ethical consideration
The protocol for the parent study was assessed within the Kintampo Health Research Centre’s
Scientific Review Committee (KHRC SRC). Ethical approval was obtained from the Kintampo
Health Research Centre Institutional Ethics Committee (KHRC-IEC), Kintampo. The study
protocol, data collection tools, and consent forms were presented to these bodies for review
and approval. Data collection tools included structured questionnaire. A list of all participants
and identifier codes were securely stored on a cloud-based platform hosted by Coffey
International in the UK. On completion of the research, all data were secured on a central server
hosted by Coffey International for a minimum of 10 years. Data access was limited to
authorized team members only. Levels of access to the study data were established before data
collection to minimize version control challenges.
3.12.1 Benefit and risk
The study was reported to have had minimal risk; the questionnaires completed by participants
were not sensitive. There were no direct benefits, however, the findings were expected to
contribute to understanding the level of adherence to the T3 policy by study participants. No
compensation was to be paid to participants.
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3.12.2 Privacy
The researchers ensured that the interviews were conducted in a secured place free from the
interaction of other ongoing activities and privacy. The participation in the interviews was
made voluntary with a free will to participants. Participants were given the additional option to
opt-out at any point of the interview without any implications of their decision.
3.12.3 Informed Consent
Participants who agreed to be part of the study were made to sign or thumbprint a consent form
as an indication of their willingness to participate. The consent forms were read and explained
to participants who cannot read, in the presence of an impartial witness. In situations where the
respondent was not physically present, interviews were conducted via telephone. The purpose
of the study, the benefits, and rights of the participants, and the procedure involved were
explained to all participants.
3.12.4 Voluntary participation
Participating in the study was entirely voluntary and participants were also at liberty to
withdraw from the study at any stage of the participation. Participants were assured of
confidentiality and voluntary informed consent was obtained from all participants, by signing
a consent form, except in situations where the respondent was not physically present and was
interviewed via phone.
3.12.5 Conflict of Interest
Study participants were informed that the principal investigators do not have any commercial
interest in the outcome of the study.
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3.12.6 Anonymity and confidentiality
All information provided by the respondents was kept confidential and data were locked in a
cabinet and on computers protected by passwords. The name and identity of the respondent
was not recorded for the purposes of the study. The information provided was only to be
identified by a code number and treated with strict confidentiality. Respondents’ name was not
to be mentioned in any part of the report of this study.
3.13 Dissemination
The findings of the study would be communicated to the GHS and the communities within the
study area. Findings of this study will be publicized through stakeholder engagement,
publication in scientific journals (of international repute), policy briefs and presentations at
national conferences.
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CHAPTER FOUR
RESULTS
4.0 Introduction
This section presents an analysis of the study outcomes. The descriptive statistics presented are
in line with the study objectives and outcome.
Figure 3 Distribution of Health Facilities by location
The above figure shows that all the CHPS compounds (100.0%) were in the rural area, whiles
the Government Hospital had 3 out of 5 facilities in the urban areas.
4.1 Basic characteristics of different health facility levels
The study examined the availability of basic health facility infrastructure that supports the
delivery of effective service to clients. Among them was access to designated phones,
availability of water, and access to toilet facilities.
0
16
00
2
3
1
5
11
23
4
PER I-U R BA N R U R A L U R BA N
TYPE OF HEALTH FACILITY BY TYPE OF
RESIDENCE
CHPS Gov. Hospital Health Centre Total
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Table 3 Description of basic health facility infrastructure at different levels
Indicator
CHPS
n (%)
Gov. Hospital
n (%)
Health Centre
n (%)
Total
n (%)
Number of Facilities
16 (57.1) 5 (17.9) 7 (25.0) 28 (100)
Designated Phone
No 11 (68.7) 1 (20.0) 5 (71.4) 17 (60.7)
Yes 5 (31.3) 4 (80.0) 2 (28.6) 11 (39.3)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
Water Availability
No 6 (37.50) 0 (0.0) 0 (0.00) 6 (21.4)
Yes 10 (62.50) 5 (100.0) 7 (100.0) 22 (78.6)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
Toilet Facility
No 4 (25.0) 0 (0.0) 1 (14.3) 5 (17.9)
Yes 12 (75.0) 5 (100.0) 6 (85.7) 23 (82.1)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
A total of 28 health facilities were examined at three different levels. The CHPS compound
constituted the majority with a total number of 16 (57.14%), whiles Government Hospital was
the least with a total number of 5 (17.86%) facilities in addition to 7 Health Centres
representing 17.86% of the total facilities examined. Table 3 above depicts various amenities
of the three levels of facilities. Most of the health facilities assessed had basic amenities such
as phones and water. Apart from phones, more than 50% of facilities had basic amenities such
as water and toilet facilities. The Government Hospitals had higher, 80.0% designated phones
with only 20.0% not having a phone assigned for service delivery. With the Health Centres,
the number of facilities without designated phones was high with 71.4% not having access to
phones. On availability of water at the various facility levels, 6 out of the 16 CHPS compound
facilities did not have access to water. Both the Government Hospitals and the Health Centres
had water available, to enhance service delivery. With the availability of toilet facilities, CHPS
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compounds had 4 (25%) of the facilities not having access to toilet, but Health Centres and
Government Hospitals had higher accessibility to water with 85.71% and 100% respectively.
4.2 Facility approach to malaria services
The study assessed the mode of service delivery at the various health facilities in terms of the
availability of flyers for displaying malaria messages, availability of guidelines and protocol
for malaria care, the presence of functional laboratory for microscopy and mRDT, performing
checks for hemoglobin, and finally whether facilities perform microscopy services.
Table 4 Description of different facility level approach to malaria services
Indicators
CHPS n
(%)
Gov.
Hospital n
(%)
Health
Centre n
(%)
Total N (%)
Does health facility display
availability of malaria services?
No 0 (0.0) 0 (0.0) 1 (14.3) 1 (3.6)
Yes 16 (100.0) 5 (100.0) 6 (85.7) 27 (96.4)
Availability of guidelines and
protocol for malaria care
No 1 (6.3) 0 (0.0) 0 (0.0) 1 (3.6)
Yes 15 (93.7) 5 (100.0) 7 (100.0) 27 (96.4)
Functioning laboratory for
malaria microscopy
No 16 (100.0) 0 (0.0) 6 (85.7) 22 (78.6)
Yes 0 (0.0) 5 (100.0) 1 (14.3) 6 (21.4)
Availability of kits for malaria
testing
No 1 (6.3) 0 (0.0) 0 (0.0) 1 (3.6)
Yes 15 (93.7) 5 (100.0) 7 (100.0) 27 (96.4)
Check for hemoglobin for
patients
No 10 (62.5) 0 (0.0) 2 (28.6) 12 (42.9)
Yes 6 (37.5) 5 (100.0) 5 (71.4) 16 (57.1)
Facility performs microscopy
services for malaria
No 16 (100.0) 0 (0.0) 6 (85.7) 22 (78.6)
Yes 0 (0.0) 5 (100.0) 1 (14.3) 6 (21.4)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
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The analysis of the approach to malaria services of the various facilities with regards to the
three different health facility levels is shown in Table 4 above. It would be seen that all of the
16 CHPS and the 5 Government Hospitals surveyed displayed the availability of malaria
services. However, there was only 1 out of the 7 Health Centres that did not display the
information at the facility. In asking for the availability of guidelines and protocol for malaria
care, the study found that all (100%) of both the Government Hospitals and Health Centres
guidelines and protocol for malaria services, whiles only 6.3% of the CHPS had no guideline
and protocol for malaria care. Apart from the Government Hospitals which had all 5
functioning laboratories to test for malaria cases, the table 4 shows that all the 16 CHPS
compounds did not have functioning laboratory and so do not perform any microscopy test and
about 6 of the Health Centres do not also have laboratory and therefore do not also perform
microscopy test. Government Hospital showed 100% available functional laboratories for
testing and confirming cases. In all, less than 30% of the facilities had a functional laboratory
for microscopy testing services and actually, none were found at the CHPS level. The study
enquired about staff with RDT training in the participating facilities, out of which only 37.5%
out of the 16 CHPS compound facilities confirmed having no RDT training, with the
Government Hospital and the Health Centres having 100% training on RDTs. In all, 96.4% of
the facilities had available kits for malaria testing and 62.5% of CHPS compounds do not check
for hemoglobin in the process of care. However, all 5 Government Hospitals surveyed, and 5
out of the 7 Health Centres checked for hemoglobin. The Health Centres had only 28.6% using
microscopy for testing malaria cases.
4.3 Knowledge of T3 policy among different health facility levels
To assess the knowledge of facilities on the T3 malaria policy, participating facility
professionals were asked whether they are aware of the policy implementation, whether they
have received training on the policy and how they confirm malaria cases.
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Table 5 Indicators for assessing knowledge of T3 malaria policy
Indicator
CHPS n
(%)
Gov.
Hospital n
(%)
Health
Centre n
(%)
Total N
(%)
Awareness of the T3 policy
No 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Yes 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
Have you received training on
T3 policy
No 6 (37.5) 0 (0.0) 0 (0.0) 6 (21.4)
Yes 10 (62.5) 5 (100.0) 7 (100.0) 22 (78.6)
How facility confirm malaria
cases
Microscopy 0 (0.0) 1 (20.0) 0 (0.0) 1 (3.6)
RDTs 16 (100.0) 4 (80.0) 7 (100.0) 27 (96.4)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
In testing and confirming results for malaria cases, the facilities showed a good knowledge of
the policy by all the three facilities, as depicted in table 5. The facility respondents were asked
if they were aware of the T3 malaria policy, to which all 16 CHPS, 5 Government Hospital,
and the 7 Health Centres confirmed awareness, indicating a higher rate of awareness in all the
facilities. It is significant to note that almost all three facilities indicated that they were aware
of the T3 malaria policy guidelines. On the question of whether the health workers have
received training on T3 malaria, 6 out of 16 CHPS compounds indicated they have not received
training, while higher percentages were recorded at 100% Government Hospitals and 100%
Health Centres for having been trained on the T3 policy. A higher number of facilities
indicated using RDTs when asked on how facilities confirm malaria cases. Both the CHPS and
the Health Centre confirmed 100% usage of RDTs, while 20.0% of the Government Hospitals
use microscopy to test and confirm the case. The outcome of the assessment showed a higher
proportion of knowledge among all facilities based on the indicators measured.
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4.4 Adherence to treatment of malaria cases among different health facility levels
The various health facility level adherence to the treatment using T3 guidelines was measured
using the availability of medications and indication of whether the facility had had stock-outs
for more than 72 hours, which might influence service delivery with regards to treatment.
Table 6 . Indicators for treatment among different health facility levels
Indicators CHPS n (%)
Gov.
Hospital n
(%)
Health
Centre n
(%)
Total N (%)
Availability of medicines
Artemether Lumefantrine 3 (20.0) 3 (60.0) 0 (0.0) 6 (22.2)
Artesunate Amodiaquine 11 (73.3) 0 (00.0) 6 (85.7) 17 (63.0)
Quinine 1 (6.7) 2 ((40.0) 1 (14.3) 4 (14.8)
Total 15 (100.0) 5 (100.0) 7 (100.0) 27 (100.0)
Has the HF had any stock
out for more than 72 hours
No 10 (62.5) 4 (80.0) 6 (65.7) 20 (71.4)
Yes 6 (37.5) 1 (20.0) 1 (14.3) 8 (28.6)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28(100.0)
Table 6. above shows that CHPS compounds had higher usage (73.3%) of Artesunate-
Amodiaquine as preferred medication, and 60.0% of the Government Hospital also used
Artemether Lumefantrine. From the study, though artesunate-amodiaquine was the highest
ACT used among the total facilities, there was none available at the Government hospitals at
the time of assessment. The study further revealed that all three facilities had some usage of
quinine which is recommended for the second line of treatment aside from the ACTs, with
Government Hospital having the highest use of 40.0% of the facilities. As shown in table 6,
except for one CHPS compound, the rest of the 27 facilities used some type of antimalarial for
the treatment of malaria cases. The analysis showed that 6 CHPS compounds had stock out for
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more than 72 hours and in all the facilities, 8 out of the total 28 facilities had stock out for more
than 72 hours.
4.5 Adherence to tracking of malaria cases among different health facility levels
In measuring the adherence to tracking of malaria cases by various facilities, the study looked
at the type of emergency transport which could be used to facilitate the tracking process and
staff responsible for tracking malaria cases.
Table 7 Indicators of tracking malaria cases among different health facility levels
Indicators CHPS n (%)
Gov.
Hospital n
(%)
Health
Centre n
(%)
Total N (%)
Types of emergency
transport
Ambulance 0 (0.0) 3 (60.0) 0 (0.0) 3 (10.7)
Motorbikes 5 (31.3) 1 (20.0) 2 (28.6) 8 (28.6)
Other 0 (0.0) 1 (20.0) 0 (0.0) 1 (3.6)
Private vehicle 2 (12.5) 0 (0.0) 0 (0.0) 2 (7.1)
Taxis 9 (56.3) 0 (0.0) 5 (71.4) 14 (50.0)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
Responsibility for tracking
cases
Community Health nurse 9 (56.3) 1 (20.0) 3 (42.9) 13 (46.4)
Doctor 0 (0.0) 1 (20.0) 0 (0.0) 1 (3.6)
Health Assistant Clinical 1 (6.3) 0 (0.0) 2 (28.6) 3 (10.7)
Medical Physician Assistant 0 (0.0) 2 (20.0) 1 (14.2) 3 (10.7)
Midwife 3 (18.8) 0 (0.0) 0 (0.0) 3 (10.7)
Nurse RGN 2 (12.5) 1 (20.0) 1 (14.3) 4 (14.3)
Other 1 (6.23) 0 (0.0) 0 (0.0) 1 (3.6)
Total 16 (100.0) 5 (100.0) 7 (100.0) 28 (100.0)
Considering the transportation system that can be relied on to support tracking of malaria cases
by facilities, more than half of the CHPS compounds (9 out of 16) and Health Centres (5 out
of 7) representing 56.3% and 71.4% respectively use taxis as emergency transport. In terms of
ambulance service, the Government Hospitals were the only health facilities with access to this
service with 3 out of the 5 government hospitals surveyed. In all cases, various facilities had
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some option of emergency transportation for service delivery, with the CHPS and the Health
Centres relying on motorbikes as the second option with 31.3% and 28.6% respectively, while
12.5% of CHPS facilities also use private vehicles as the third option. Table 7 showed that
responsibility for tracking cases relying on community health nurses were higher 9 out of the
16 CHPS, with Health Centres also relying mostly on the same category of staff with 3 out of
7 facilities. Apart from the community health nurses, CHPS depended on the Registered
Nurses, whiles the Health Centres also depended on the Health Assistants as the second
category of staff responsible for the tracking of cases. In the Government hospitals, the data
showed that Medical Physician Assistants dominated with 2 out of 5 facilities studied. Doctors,
Registered Nurses, and Physician Assistants were not much involved with the responsibility
for tracking cases with low percentages from the various facilities with 3.6%, 14.3%, and 10.7
respectively.
4.6 General adherence to T3 policy among different health facility levels
After assessing the various indicators influencing adherence of health facility professionals to
implement the T3 policy, the data gathered revealed that almost all the facilities adhered to the
T3 policy with a higher proportion.
Figure 4 Different Health Facility Adherence level
15
5
7
27
1 0 0 1
CHPS GOV. HOSPITAL HEALTH CENTRE TOTAL
T3 ADHERENCE VERSUS NON ADHERENCE BY
TYPE OF FACILITY
Adhere Not Adhere
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The general adherence level from the facility perspective as shown in figure 5 above revealed
a high adherence of 100% each from both the Government Hospitals and the Health Centres
respectively. This was based on indicators, awareness, and access to training of health
professionals. Apart from one CHPS compounds, the rest of the facilities surveyed representing
27 (96.4%) out of the 28 facilities, showed a high level of adherence from all the indicators
measured.
4.7 Health professionals’ knowledge, adherence and the T3 policy
Table 8 Relationship between facility adherence and T3 policy
Variable
Facility adherence to T3 policy Fisher’s
exact p-value Not Adhere (%) Adhere (%)
Facility type 1.000
CHPS 1 (100.0) 15 (55.6)
Gov. Hospital 0 (0.0) 5 (18.5)
Health Centre 0 (0.0) 7 (25.9)
Total 1 (100.0) 27 (100.0)
The research revealed that there was no relationship between facility types and adherence to
the T3 policy, (p = 1.000) as per the Fisher’s exact test. From Table 8, only one facility
responded not complying with all the three processes of the T3 guidelines. Awareness of T3
among facility level was 27 out of the 28 health facilities, so there was no relationship between
the facility type and knowledge.
4.8 Basic characteristics of clients
The study conducted 590 client-based exit interviews from the three facility levels. Out of the
total participants, 347 (58.8%) were from CHPS compounds, 128 (21.7%) were from the
Government Hospital and 115 (19.5%) from the Health Centres, as displayed in table 9. The
clients recruited into the study were distributed across the six districts, Jirapa had 105 (17.8%),
West Mamprusi 104 (17.6%), Kintampo North and South had 83 (14.1%) and 89 (15.1%)
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respectively, whiles Mpohor East and Nzema constitute 104 (17.6%) and 105 (17.8%
respectively. The ages of clients assessed were categorized into five groupings with the CHPS
compound recording the highest of 154 (44.4%) in the age category of 0-10 years. A greater
proportion 392 (66.4%) out of the 590 clients in all the three facilities were female as shown
in table 9 below.
Table 9 Description of basic demographic of clients
Indicators CHPS n (%)
Gov. Hospital
n (%)
Health
Centre n (%)
Total n (%)
Total Clients 347 (58.8) 128 (21.7) 115 (19.5) 590 (100)
Districts
Jirapa 62 (17.9) 27 (21.1) 16 (13.9) 105 (17.8)
Kintampo North 43 (12.4) 20 (15.6) 20 (17.4) 83 (14.1)
Kintampo South 49 (14.1) 20 (15.6) 20 (17.4) 89 (15.1)
Mpohor East 65 (18.8) 0 (0.0) 39 (33.9) 104 (17.6)
Nzema 65 (18.7) 20 (15.6) 20 (17.9) 105 (17.8)
West Mamprusi 63 (18.2) 41 (32.0) 0 (0.0) 104 (17.6)
Total 347 (100) 128 (100) 115 (100) 590 (100)
Ages in years
0-10 154 (44.4) 42 (33.3) 16 (13.9) 212 (35.9)
11-19 46 (13.3) 14 (11.1) 19 (16.5) 79 (13.4)
20-29 61 (17.6) 31 (24.6) 30 (26.1) 122 (20.7)
30-39 39 (11.2) 22 (17.5) 28 (24.4) 89 (15.1)
40+ 47 (13.5) 17 (13.5) 22 (19.1) 86 (14.6)
Total 347 (100) 126 (100) 115 (100) 590 (100)
Sex
Female 230 (66.3) 79 (61.7) 83 (72.2) 392 (66.4)
Male 117 (33.7) 49 (38.3) 32 (27.8) 198 (33.6)
Total 347 (100) 128 (100) 115 (100) 590 (100)
4.9 Proportion of clients tested for malaria cases
The testing of cases was measured with indicators enquiring from the participants whether an
exam or test was performed after visiting the facility, asking for whether temperature, lab test,
and tepid sponging were performed for the clients. In assessing the knowledge of the process,
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clients were asked if they were aware of the testing process and whether the results of the test
performed were explained to them.
Table 10 Indicators of testing malaria cases among clients
Indicators CHPS n (%)
Gov. Hospital
n (%)
Health
Centre n (%)
Total n (%)
Did they perform any
exams, procedures or
tests?
No 14 (4.0) 18 (14.1) 5 (4.4) 37 (6.3)
Yes 333 (96.0) 110 (85.9) 110 (95.7) 553 (93.7)
Total 347 (100) 128 (100) 115 (100) 590 (100)
Temperature taken,
Lab Test, Tepid
sponging
Temperature taken 15 (4.6) 19 (17.3) 3 (2.7) 37 (6.8)
Lab Test 7 (2.2) 0 (0.0) 12 (10.9) 19 (3.5)
Tepid sponging 2 (0.6) 1 (0.9) 3 (2.7) 6 (1.1)
RDT 299 (92.6) 90 (81.8) 92 (83.6) 481 (88.6)
Total 323 (100) 110 (100) 110 (100) 543 (100)
Were results
explained?
No 52 (15.6) 27 (24.6) 11 (10.0) 90 (16.3)
Yes 281 (94.4) 83 (75.5) 99 (90.0) 463 (83.7)
Total 333 (100) 110 (100) 115 (100) 553 (100)
Aware you must be
tested for malaria
before treatment
No 25 (7.2) 28 (21.9) 21 (18.3) 74 (12.5)
Yes 322 (92.8) 100 (78.1) 94 (81.7) 516 (87.5)
Total 347 (100) 128 (100) 115 (100) 590 (100)
As shown in table 10, Clients' responses to whether the exams, procedures, or tests were
performed showed that all facilities performed these processes with higher proportions in
CHPS 333 (96.0%), Government Hospital 110 (85.9%), and the Health Centre 110 (95.7%).
The overall proportion indicated 93.7% of the facilities performed these processes, out of 590
clients. A high proportion of facilities adhered to the use of RDTs in confirming cases. Over
86.6% of the facilities used RDTs, with 6.8% of these facilities taking temperature. Lab test
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accounted for 3.5% of the total 543 facilities adhering to the process. Awareness of testing
before treatment by clients was high with 92.8% in CHPS, 78.1% in Government Hospitals,
and 81.7% in the Health Centres. In all, 87% of clients were aware they must be tested before
treatment.
4.10 Proportion of treated malaria cases among clients
Treatment of malaria cases using the T3 process was measured by asking clients about the
possible prescription of antimalarial and the type of antimalarial prescribed.
Table 11 Indicators of treatment of malaria cases among clients
Indicators CHPS n (%)
Gov. Hospital
n (%)
Health
Centre n (%)
Total n (%)
Were you prescribed
any antimalarial
medicine
No 6 (1.7) 5 (3.9) 0 (0.0) 11 (1.9)
Yes 341 (98.3) 123 (96.1) 115 (100) 579 (98.1)
Total 347 (100) 128 (100) 115 (100) 590 (100)
What antimalarial
were prescribed to
you?
Arsuamoon 26 (7.6) 8 (6.5) 0 (0.0) 34 (5.9)
Camoquine plus 16 (4.7) 2 (1.6) 0 (0.0) 18 (3.1)
Chloroquine 0 (0.0) 1 (0.8) 0 (0.0) 1 (0.2)
Coarsucam 2 (0.6) 3 ((2.4) 0 (0.0) 5 (0.9)
Coartem 40 (11.7) 30 (24.4) 11 (9.6) 81 (14.0)
Don't Know 20 (5.9) 7 (5.7) 0 (0.0) 27 (4.7)
Duocotexcin 0 (0.0) 1 (0.8) 0 (0.0) 1 (0.2)
Gunate 2 (0.6) 2 (1.6) 6 (5.2) 10 (1.7)
Herbal medicine 0 (0.0) 1 (0.8) 1 (0.9) 2 (0.4)
Lonart 91 (26.7) 34 (27.6) 53 (46.1) 178 (30.7)
Lumarterm 68 (19.9) 13(10.6) 17 (14.8) 98 (16.9)
Other 22 (6.5) 9 (7.3) 0 (0.00%) 31 (5.4)
Palaxin 0 (0.0) 0 (0.0) 1 (0.87%) 1 (0.2)
Quinine 2 (0.6) 1 (0.08) 0 (0.0) 3 (0.5)
Wintrhop 52 (15.3) 11 (8.9) 26 (22.6) 89 (15.4)
Total 341 (100.0) 123 (100.0) 115 (100.0) 579 (100.0)
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In table 11, Above 90% of antimalarials were prescribed to clients who visited at each level of
the health facility. The study revealed that 98% of the health facilities were treated with
antimalarial, most of clients were provided with Lonart, followed by Lumarterm and Wintrhop,
and only 0.2% were treated with Chloroquine.
4.11 Proportion of tracked malaria cases among clients
Adherence to tracking of malaria cases on clients who visited the various facilities was
examined through provider follow-ups after treatment of malaria, actual tracking after
medication, the staff responsible for the follow-up, and how the tracking was done.
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Table 12. Indicators o