Adherence to the Test, Treat and Track malaria policy among selected health facilities in Ghana: The clients’ perspective

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All malaria suspected conditions are expected to be confirmed by test and treatment initiated with recommended artemisinin-based combination therapy (ACTs) and treatment outcomes monitored over the course of the illness. This study evaluated the adherence to the T3 policy in selected health facilities within three malaria epidemiological zones in Ghana. Methods This crossectional study was conducted in November 2019 involving thirty health facilities comprising one district hospital, one Health Centre and 3 Community Health and Planning Services (CHPS) randomly selected from six districts in the 3 malaria epidemiological zones. In addition, Clients exit interviews were conducted from each facility. Frequency charts highlighted facility characteristics. Factors associated with the test , treat and track defined outcomes were assessed using chi square and multivariable logistic regression models at 5% level of significance and 95% confidence interval. Data were classified according to facility and clients’ perspectives. Results Overall, 590 patients and 30 health facility managers were interviewed from 30 facilities in 6 districts across the three zones. CHPS compounds formed 18 (60.0%) of facilities assessed. Twenty-nine out of 30 health facilities had Rapid Diagnostic Test (RDT) kits and antimalarials. In all, adherence to the T3 policy was 31.9%, whiles 30% of facility managers in the North and Middle zones indicated inadequate training on the T3 policy. The study showed that 90% and 98% of patients were tested and treated respectively for malaria. However only 35% (range 22% − 44%) of patients were tracked according to the T3 policy across all zones. Health facilities in the southern zone of Ghana had almost three-fold increased odds of adhering to the T3 policy compared to the middle zone [aOR = 2.87 (1.7, 4.8): p < 0.001]. Males were more likely not to return to the health facility for review [aOR = 0.6 (0.3, 0.9): p = 0.018]. Conclusion Testing and treating for malaria were high among health facilities in the three epidemiological zones. However, tracking of patients was very low across the zones. Adherence from clients’ perspective was low especially for males, who were more likely to default on health facility return for review, even though facility prescribers informed participants on the need to return for review. The hurdle for one to adhere to the policy was to return to facility for review. Recommendations The National Maria Elimination Program (NMEP) should ensure periodic trainings of health facility staff especially those within the Northern and Middle zones of Ghana and strengthen monitoring and supervision of health facilities to enhance adherence to the T3 policy. The NMEP could also intensify Client sensitization programs especially targeting male clients to help understand the need to return to health facilities for review in line with the T3 policy. There is also the need for implementation research to explore strategies to improve the tracking component of the policy at the client and health facilities levels within the T3 policy framework. Adherence T3 policy Clients’ perspective Facility managers Malaria Epidemiological Zones Ghana Figures Figure 1 Figure 2 Figure 3 Introduction The World Health Organization (WHO) in 2012 introduced the test, treat and track (T3) policy to standardize the process of malaria management in endemic settings. The Test, Treat, and Track (T3) policy, which was introduced in 2012, urges the universal testing of all suspected cases of malaria, regardless of age or endemicity, the treatment of positive test cases with anti-malarial medications of high quality, and the tracking of all patients who have been confirmed and treated for malaria [ 1 ]. Ghana adopted the T3 policy in 2013. The T3 initiative was mainly to ensure accurate diagnosis and treatment of the malaria in Ghana and to reduce pressure on antimalarial medicines by ensuring that only confirmed cases are given treatment. The WHO then recommended the prescription of Artemisinin-based Combination Therapy (ACTs) for those who test positive for malaria [ 2 ]. Prompt and accurate diagnosis and treatment of malaria are essential to reduce disease progression to severe disease and complications [ 3 ]. Implementation of the T3 policy has been challenging for many developing countries for several reasons. Medical supplies for diagnosing and treating malaria frequently run out, and some healthcare professionals have expressed concerns with mistrust of malaria test results, particularly when they are negative (Johansson, 2016). The limited capacity of the health system to provide appropriate care undermines effective adherence to the T3 plan, particularly the tracking component [ 4 ]. It is expected that all treated cases would return for review to determine if they have been cured [ 5 ]. However, the tracking of malaria cases has been inconsistent and occasionally did not occur at all in some health facilities [ 6 ]. The underlying reasons have not been fully elucidated. This study evaluated the adherence to the T3 policy in selected health facilities across the three malaria epidemiological zones in Ghana. Since the WHO launched the T3 policy in 2012, independent evaluations have been conducted in only few districts in Ghana. It is crucial to evaluate and assess the effectiveness of the T3 policy in health facilities across the three malaria epidemiologic zones in Ghana. It is essential that each component of the T3 policy pillars: test , treat and track is fully assessed to understand the main enablers and challenges to achieve optimum outcomes. The evidence from this study provides very vital information for policymakers to decide on the best supportive intervention to the T3 policy. Methods Study Design We conducted a cross sectional study by interviewing health facility managers and conducted exit interviews with patients who had febrile conditions from health facilities in six districts across the three epidemiological zones in Ghana. Study Setting The study was conducted in six Districts/Municipalities; in the three malaria epidemiological zones, the northern savannah zone, the middle/transitional and forest zone, and the coastal savannah zone are Ghana's three malaria epidemiologic zones [ 7 ]. Selected Districts and Epidemioligical Zones No District Zone 1 Mpohor District Coastal Savanna Zone (Southern Zone) 2 Nzema East Municipality Coastal Savanna Zone (Southern Zone) 3 Kintampo North Municipality Middle/transisitonal forest Zone (Middle Zone) 4 Kintampo South District Middle/transisitonal forest Zone (Middle Zone) 5 Jirapa District Northern Savanna Zone (Northern Zone) 6 West Mamprusi Municipalities Northern Savanna Zone (Northern Zone Mpohor District and Nzema East Municipal are both located in the Western North Region. The two districts are largely rural and have a total population of about 147,094, majority of which engage in fishing, agro-processing and mining[ 8 ]. The area is highly malaria endemic and has a doctor-patient ratio of 1:21,461. There are two (2) District hospitals, 5 Health Centers, and 9 CHPS compounds. 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 two districts together cover an area of 7162km 2 , and largely rural with a resident population of approximately 228,631 who are predominantly engaged in subsistence farming [ 8 ]. Public health facilities in the 2 districts include 2 hospitals, 12 health centers/clinics, and 30 Community-based Health Planning and Services (CHPS) compounds; whilst the privately-owned health facilities include 4 clinics, 2 maternity homes, 4 pharmacies, and 86 Over the Counter Medicine Sellers (OTCMS) [ 9 ]). The area has a high perennial incidence of endemic malaria. Jirapa and West Mamprusi Municipalities are located in the north-western part of the Upper West Region and North East Regions respectively. The vegetation of the two municipalities is Guinea Savanna woodland with light under growth and scattered trees. The major economic trees are Shea, Dawadawa, and Baobab species. The area has a combined population of 267,034 [ 8 ]. Malaria ranks highest as a major health problem. Public health facilities in the two municipalities include 2 municipal hospitals, 1 polyclinic, 11 health centers/clinics, and 35 CHPS compounds. Sample Size and sampling method Two districts were purposively selected from each of the 3 zones in the country. In each district, the district hospital, one health centre and 3 CHPS zones were selected, making it 5 health facilities per zone and a total of 30 health facilities across the six districts/municipalities from the 3 zones [ 10 ]. In each of the 30 health facilities, 20 client exit interviews were purposively conducted from each facility, as and when they exit the facility after seeking for heath care, making a total of 600 clients exit interviews. Data collection and management 18 data collectors and 3 supervisors were trained on the objectives of the study and the studies data collection method. Data was collected using Redcap application. The data collection period spanned over two weeks from 11th November to 29th November 2019. Data Analysis Data were analyzed using Stata 17.0. To assess adherence to the T3 policy from the clients’ perspective, we assessed “Test” by asking whether the client was tested using malaria RDT (mRDT) or microscopy, “Treat” by asking whether the client was prescribed a recommended antimalarial drug and “Track” by asking whether the client was asked to return to the facility for a review and if there was any documented evidence of review. A facility was classified as adherent to the T3 policy if a client responded “Yes” to all the three questions. To assess adherence to the T3 policy at the facility level, “Test” was assessed by asking the facility in-charge whether they performed test for reported feverish conditions, “Treat” was assessed by asking whether the facility prescribed the required antimalarial for confirmed cases and “Track” was assessed by asking whether prescribers inform clients to return to the facility for review after treatment. Tables were used to describe participant background characteristics and chi square test to assess the asssociation between background characteristics and adherence to the T3 policy. Unadjusted and adjusted odds ratios with 95% confidence interval using logistic regression models were used to assess the factors associated with the T3 policy. Results Overall, 590 patients with febrile illness and 30 facility managers were interviewed from 30 facilities in 6 districts across 3 epidemiological zones in Ghana. CHPS compounds formed the majority of the facilities surveyed 18 (60). Twenty-nine out of 30 health facilities had RDT test kits and antimalarials (Table 1). In all, 30% of facility managers in the North and Middle zones indicated that their staff had not been trained adequately on the T3 policy compared to the Southern zone where all staff were reported to be trained. Table 1.0 Background characteristics of health facilities surveyed across the three epidemiological zones in Ghana Indicator North n (%) Middle n (%) South n (%) Total N (%) n = 10 n = 10 n = 10 N = 30 Facility Type CHPS 6(60.0) 6(60.0) 6(60.0) 18(60.0) Health Centre 1(10.0) 2(20.0) 3(30.0) 6(20.0) Hospital 3(30.0) 2(20.0) 1(10.0) 6(20.0) TEST Microscopy services Yes 3(30.0) 3(30.0) 2(20.0) 8 (26.7) No 7(70.0) 7(70.0) 8(80.0) 22 (73.3) Test kits (malaria RDT) Yes 9 (90.0) 10(100.0) 10(100.0) 29(96.7) No 1(10.0) 0(0.0) 0(0.0) 1 (3.3) TREAT Availability of Antimalarial Yes 9(90.0) 10(100.0) 10(100.0) 29 (96.7) No 1(10.0) 0(0.0) 0(0.0) 1(3.3) Training of personnel on T3 Yes 7(70.0) 6(60.0) 10(100.0) 23 (76.7) No 3(30.0) 3(30.0) 0(0.0) 06(20.0) Not Known 0(0.0) 1(10.0) 0(0.0) 1(3.3) TRACK Review after treatment Yes 10(100.0) 10(100.0) 10(100.0) 30(100.0) No 0(0.0) 0(0.0) 0(0.0) 0 (0.0) Figure 2 shows the number of patients and the actual T3 process, one (Test), two (Treat), and three (Track) are the T3s that were performed at the facilities in each zone. This shows that high number of participants went through any of the two of the T3 policy processes. The overall adherence was 31.9%, indicating the number of participants’ who actually had all the three policy requirements. Table 2 ; Association between background characteristics and adherence to the T3 policy from clients exit interviews at health facilities Variables n (%) Client’s Adherence Chi-square Zones Not Adhered Adhered Middle 172(29.2) 135(78.5) 37(21.5) < 0.001 Northern 105(17.8) 70(66.7) 35(33.3) Southern 313(53.1) 197(62.9) 116(37.1) Ownership Government 524(88.8) 364(69.5) 160(30.5) 0.068 CHAG 66(11.2) 38(58.5) 27(41.5) Sex Male 198(33.6) 144(72.7) 54(27.3) 0.089 Female 392(66.4) 258(65.8) 134(34.2) Age 10–29 415(70.3) 288(69.4) 127(30.6) 0.364 30–44 115(19.5) 72(62.6) 43(37.4) 45+ 60(10.2) 42(70.0) 18(30.0) Facility Type CHPS 347(58.8) 224(64.6) 123(35.4) 0.079 Health Centre 135(22.9) 100(74.1) 35(25.9) Hospital 108(18.3) 78(72.2) 30(27.8) Health Staff/Prescriber Community Health Nurse 364(68.4) 226(62.09) 138(37.91) 0.069 Physician Assistant 107(20.1) 77(71.96) 30(28.04) Midwife 53(1.0) 39(73.6) 14(26.4) Other 8(1.5) 7(87.5) 1(12.5) Table 2 shows the association between background characteristics of participants and adherence to the T3 policy. Adherence to T3 policy from Clients’ perspective by epidemiological zone Figure 3 describes the proportions of patients with febrile illness who reported been tested, treated and informed to return for review (tracked) by epidemiological zones. Over all 90%, 98% and 35% of patients indicated being tested, treated and tracked respectively. The track to the T3 policy has the lowest percentages ranging from 22–44% in the respective zones. Factors associated with adherence to the T3 Policy; Clients’ Perspective Table 3 describes the factors associated with adherence to the T3 policy from clients’ perspective. The table shows the influence of factors associated with adherence to the T3 policy on a performance score. Performance was measured as “fail” and “pass” where pass was coded one (1) and fail coded zero (0). A logistic regression model shows a significant relationship between performance and clusters (location) at the crude odds ratio and adjusted odds ratio level. The northern zone is 80 percent odds more likely to pass performance as compared to the middle zone while the southern zone is 2.1 odds more likely to pass performance compared to the middle zone at the crude odds ratio level. Having adjusting for other factors, the facilities in the southern zone has 2.9 increase odds of adhering to the T3 policy compared to the middle zone. Table 3 ; Factors associated with Adherence to the T3 Policy; Clients’ Perspective. Variables Crude OR (95% CI) P-Value Adjusted OR (95% CI) P-Value Cluster/Zone Middle 1 1 < 0.001* North 1.82 (1.1,3.1) < 0.001* 1.74 (0.9,3.3) South 2.15 (1.4,3.3) 2.87 (1.7,4.8) Facility Type CHAG 1 1 0.057 Government 0.60 (0.4,1.0) 0.526 0.5 (0.3,1.0) Sex Female 1 0.018* Male 0.72 (0.4,1.1) 0.090 0.6 (0.4,0.9) Age 15–29 1 0.045* 30–44 1.35 (0.9,2.1) 0.366 1.9 (1.1,3.0) 45+ 0.97 (0.5,1.8) 1.1 (0.6,2.1) Classification of Facility CHPS Compound 1 0.030* Health Centre 0.64 (0.4,1.0) 0.080 0.5 (0.3,0.8) Hospital 0.70 (0.4,1.1) 0.8 (0.4,1.5) Health Staff Community Health Nurse 1 0.088 Medical Physician Assistant 0.64 (0.4,1.0) 0.078 0.9 (0.5,1.8) Midwife 0.59 (0.3,1.1) 0.5 (0.2,0.9) Other 0.23 (0.0,2.0) 0.2 (0.0,1.9) *=significant at 0.05 Males are 40 percent odds less likely to comply with the T3 policy compared to females. Also, persons of ages 30 to 44 years and 45 years and above are 90 percent and 10 percent odds more likely to comply with the T3 compared to individuals within the ages 15 to 29 years. When it comes to the classification types, health centers and hospitals are 50 percent and 20 percent less likely to comply to the T3 policy compared to CHPS compounds respectively. Discussion Our study assessed the adherence to the T3 policy initiated by the WHO for effective malaria diagnosis and management. The findings indicate that the location of the health facility has influence on the entire process of adherence with the policy. Overall, it was evident that the testing and treating components of the policy were high across all the clusters, whiles tracking was low in all the clusters. Results from our study revealed 32% of the patients adhered by completing the three processes of the T3 policy. These findings are consistent with a study conducted in 2020 at the Mfantseman Municipality in the Central Region of Ghana, which found 30% adherence level to the T3 policy among 414 febrile outpatients seen by 18 prescribers[ 11 ] However, the level of adherence observed in this study was below that observed from in a similar study by Agandaa et al in the Bongo District of Ghana, which revealed 42.5% adherence to the T3 policy among 353 children from 28 health facilities. This may be due to the fact that parents are more likely to send their children back for facility reviews because they are vulnerable, compared to adult males who may have refused to return for reviews for unknown reasons. Some studies have shown that public primary health care facilities lack diagnostic kits such as microscopes, and inadequate personnel to use the kits[ 6 ]. Frequent stock out of logistics such as RDTs kits and reagents for microscopy and the absence of qualified staff with malaria testing capacity hinder effective compliance with the components of the T3 policy. A study conducted in Mozambique on diagnostic test kits supply chain revealed 17% of health centers experienced RDT stuck out in any given month. Hence, situation of nonexistence of microscopies, adherence to T3 policy remains a challenge [ 12 ]. The result of this study which showed that more than 70% of the facilities across all zones have no access to microscopy test, which indicates that in terms of RDT stockout, most facilities may not be able to comply with the policy guidelines contrary to the finding of a study among patients in Zambia showing that continues availability of the testing tool has the potential to improve adherence to test results and general malaria case management [ 13 ]. We also found that 30% of the personnel from the North and the Middle zones indicated not being trained on the T3 policy. This could possibly be due to high staff turnover which may have hindered adequate training for new staff. In this study we found that only 35% of patients were tracked according to the T3 policy across all zones. Health facilities in the southern zone of Ghana had almost three-fold increased odds of adhering to the T3 policy relative to their counterparts in the Middle and Northern zones. This may be due to the fact that facilities in the South are mostly well equipped, have more qualified clinical and laboratory staff and located mainly in towns which may be closer to settlement areas thereby making them easily accessible compared to those in the North and the Middle zones where road network and distances to facilities remain a challenge. A study on guiding placement of health facilities in the Bunkpurugu-Yunyoo District in Northern Ghana, confirmed that for malaria case, location of facility has a significant impact on malaria prevalence and care seeking [ 14 ]. The T3 policy discourages presumptive treatment of malaria based on symptoms and signs alone. However, in this study we found that apart from the Northern Zone, the other zones had clients treated for malaria without confirmatory testing. It has been reported that in Kenya, less than 40% of febrile children under five years were tested for malaria whiles in Ghana, 73% of children were presumptively diagnosed and treated for malaria [ 15 ]. In addition, fever from most endemic countries associated with malaria was diagnosed and treated presumptively as malaria [ 6 ]. Even though there is an association between fever and malaria parasitemia, it has been proven that not all patients presenting with fever have malaria parasites and that several other pathogens account for non-malarial fevers even in malaria endemic settings of Ghana [ 16 ]. It is therefore inappropriate to treat feverish conditions with ACTs without confirming diagnosis of malaria with RDT or slide [ 17 ]. Testing for malaria also provides an opportunity for improved diagnoses and better case management [ 6 ]. Comparing the level of adherence of the T3 policy, a study in the Bosomtwi District of Ghana which evaluated compliance level to the T3 policy revealed that 64% of malaria cases were tested before treatment using antimalarials [ 18 ] This finding is relatively lower as compared to what we found in this study, showing 90% and 98% tested and treated cases respectively across the three zones using the required ACTs. Another study on the adherence of the T3 policy on caregivers of children under 10 visiting the Over-the-Counter Medicine Sellers (OTCMS), revealed 56.6% adherence among OTCMS, and indicated that monitoring and supervision of the OTCMS especially in the rural areas would lead to improving adherence of the policy and subsequently scaling up management of malaria events [ 19 ]. The result of the study is high compared to the adherence level revealed by our study. A study on health worker compliance with a “Test and Treat” malaria case management protocol conducted in Papua New Guinea revealed Frequent prescriptions of antimalarials despite negative tests as the most reported barriers to policy compliance [ 20 ]. When compared with our results, facilities in the Middle and the Southern zone provided antimalarials more than the required number of tests performed, meaning that some prescribers from these facilities continue to provide ACTs for the treatment of malaria cases without the required testing which is contrary to the enhancement of the policy. The results from the logistic regressions analysis showed that some facilities in the South are prescribing malaria drugs without testing. The outcome confirms the findings from a qualitative study on malaria case management among prescribers in Ghana, which revealed that; majority of Ghanaian health facilities and CHPS compounds lack laboratories capable of diagnosing malaria, rapid diagnostic tests are mostly implemented at these levels. RDT kits can be hard to come by at health centers without labs and may affect the adherence level [ 21 ]. Limitation There was potential limitation regarding recall bias during exit interview of clients, who may have forgotten about some of the information received at the health facility. The kind of treatment given may not have been accurately provided in the responses. This limitation was minimized by interviewing clients immediately they were discharged from health facilities. Also, healthcare managers may have provided responses solely to please interviewers, which could lead to social desirability bias. However, we verified most of the responses from the facilities to reduce this risk. Limited information on clients’ demographic characteristics like marital status, occupation, religion and wealth quintiles prevented further analysis on some potentially important independent variables. Conclusion Our study showed that testing and treating for malaria was high among health facilities across the three epidemiological zones. However, tracking of patients was very low across the three zones. Adherence from clients’ perspective was low especially for males who were more likely to default facility return for review, even though facility prescribers informed participants on the need to return for review. Training for facilities on the T3 policy was relatively inadequate especially for staff in the Northern and the Middle zones. Recommendations The National Maria Elimination Program (NMEP) should ensure adequate periodic trainings of health facility staff especially those within the Northern and Middle zones of Ghana and strengthen monitoring and supervision of health facilities to enhance adherence to the T3 policy. The NMEP could also intensify Client sensitization programs especially targeting male clients to help them understand the need to return to health facilities for review and also ensure regular supply of test kits in line with the T3 policy. There is also the need for implementation research to explore strategies to improve the tracking component of the policy at the client and health facilities levels within the T3 policy framework. Abbreviations WHO-World Health Organization, CHPS-Community Health and Planning Services, mRDT-Malaria Rapid Diagnostic Test, NMEP-National Malaria Elimination Program, ACT- Artemisinin-based Combination Therapy, T3-Test, Treat and Track, OTCMS- Over the Counter Medicine Sellers RDD-Research and Development Division KHRC-Kintampo Health Research Centre NHRC- Navrongo Health Research Centre DHRC- Dodowa Health Research Centre ARHR-Alliance for Reproductive Health Right ADRRO-Anglican Diocesan Development Relief Organization Declarations Acknowledgement The authors would like to thank the health officials at the municipal and directorate levels, the healthcare institutions where the data were gathered, the patients from the different facilities, the medical staff members who assisted with the data gathering and special acknowledgement to Bill and Melinda Gate Foundation for the training activity. Ethical consideration The research protocol was reviewed and approved by the Kintampo Health Research Centre's Institutional Ethics Committee (KHRC-IEC) KHRCIEC/2014-24. All participants were consented to be part of the study and assured of confidentiality of information. Consent to publish Not applicable Data Availability Information could be provided upon acceptable request Funding This study was funded by COMIC RELIEF and Kintampo Health Research Centre, Ghana. Conflict of Interest Authors declare that they do not have any conlicting inerest Author Contribution CK, CT, KPA, FA, PM, ASNA, JAA, and SBEH were involved in the conception, design, and development of the study proposal. FA, IN, VAA, PM, and AA were responsible for collecting the data. The analysis of the data was performed by CK, SAA, EA, PW, CT, KPA, SG, and RJT. CK, CT, JAA, KPA, MT, WZ, FK, CKK, JO, and SBEH contributed to the interpretation of the results and reviewed the manuscript. 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Kyei","email":"data:image/png;base64,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","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":true,"prefix":"","firstName":"Charles","middleName":"","lastName":"Kyei","suffix":""},{"id":445342374,"identity":"4da32107-1baa-46bc-a972-8faff33535a3","order_by":1,"name":"Charlotte Tawiah","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Tawiah","suffix":""},{"id":445342375,"identity":"7c76c7fb-0d88-4e7e-a7d9-667f4e6739e5","order_by":2,"name":"Francis Agbokey","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"","lastName":"Agbokey","suffix":""},{"id":445342376,"identity":"ff44799f-740d-465d-9985-b3a66fa06165","order_by":3,"name":"Japhet Adomako Anim","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Japhet","middleName":"Adomako","lastName":"Anim","suffix":""},{"id":445342377,"identity":"3d5feda0-82f0-424c-9cfc-81258a6ce850","order_by":4,"name":"Mathilda Tivura","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Mathilda","middleName":"","lastName":"Tivura","suffix":""},{"id":445342378,"identity":"bf7eb46a-a702-4e9f-bd63-a644ebef1c58","order_by":5,"name":"Samuel Afari-Asiedu","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Afari-Asiedu","suffix":""},{"id":445342379,"identity":"f80eeb26-c683-43a1-8f0f-741c78305925","order_by":6,"name":"Clifford Kyerematen Kwarteng","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Clifford","middleName":"Kyerematen","lastName":"Kwarteng","suffix":""},{"id":445342380,"identity":"8b165b83-9215-40b2-a377-8c86fa7242f8","order_by":7,"name":"Francis Kornu","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"","lastName":"Kornu","suffix":""},{"id":445342381,"identity":"46c894f1-5d1d-49cd-aea0-f64eb3e58cca","order_by":8,"name":"Joshua Oppong","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Oppong","suffix":""},{"id":445342382,"identity":"b9f36796-b205-4a99-b79b-44ac3b838eee","order_by":9,"name":"Wilfred Zuuri","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Wilfred","middleName":"","lastName":"Zuuri","suffix":""},{"id":445342383,"identity":"c6f09e54-b44d-44c0-aa83-ada469332bd9","order_by":10,"name":"Isaac Nyampong","email":"","orcid":"","institution":"Alliance for Reproductive Health Rights","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Nyampong","suffix":""},{"id":445342384,"identity":"650f9105-da02-4763-afa6-de1d7b8b8634","order_by":11,"name":"Vitalis Atambila Agana","email":"","orcid":"","institution":"Anglican Diocesan Development Relief Organization (ADRRO)","correspondingAuthor":false,"prefix":"","firstName":"Vitalis","middleName":"Atambila","lastName":"Agana","suffix":""},{"id":445342385,"identity":"c3efaa1e-0aa0-44e7-9c9e-abfe36a210bc","order_by":12,"name":"Prince Imoro Awimba","email":"","orcid":"","institution":"Anglican Diocesan Development Relief Organization (ADRRO)","correspondingAuthor":false,"prefix":"","firstName":"Prince","middleName":"Imoro","lastName":"Awimba","suffix":""},{"id":445342386,"identity":"a8842e2f-89f7-4deb-b1eb-eb71ab3f523e","order_by":13,"name":"Annobah-Sarpei Nii Ankonu","email":"","orcid":"","institution":"Alliance for Reproductive Health Rights","correspondingAuthor":false,"prefix":"","firstName":"Annobah-Sarpei","middleName":"Nii","lastName":"Ankonu","suffix":""},{"id":445342387,"identity":"dc446a23-07a2-4bd9-adec-ae4d46733c71","order_by":14,"name":"Elizabeth Awine","email":"","orcid":"","institution":"Dodowa Health Research Centre (DHRC), RDD, GHS","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Awine","suffix":""},{"id":445342388,"identity":"ea9510e9-fe53-4d00-9d3f-93d08e58b6ba","order_by":15,"name":"Paul Welega","email":"","orcid":"","institution":"Navrongo Health Research Centre (NHRC), RDD, GHS","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Welega","suffix":""},{"id":445342389,"identity":"883530dc-5f36-4239-88aa-afbbbfed5ed4","order_by":16,"name":"Stephaney Gyaase","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Stephaney","middleName":"","lastName":"Gyaase","suffix":""},{"id":445342390,"identity":"6548d434-35c2-478f-84d0-beefef34cdef","order_by":17,"name":"Richard Joshua Tetteh","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"Joshua","lastName":"Tetteh","suffix":""},{"id":445342391,"identity":"255ba86e-cde3-45d0-8a0b-07723fa785a3","order_by":18,"name":"Peter Mayers","email":"","orcid":"","institution":"Management Systems International (a Tetra Tech company)","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Mayers","suffix":""},{"id":445342392,"identity":"3fe24a8e-7d86-4b88-b501-4fc565de18da","order_by":19,"name":"Samuel Bernard Ekow Harrison","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Bernard Ekow","lastName":"Harrison","suffix":""},{"id":445342393,"identity":"47f490ea-026c-4f03-baee-4a0502966946","order_by":20,"name":"Kwaku Poku Asante","email":"","orcid":"","institution":"Kintampo Health Research Centre, Ghana Health Service","correspondingAuthor":false,"prefix":"","firstName":"Kwaku","middleName":"Poku","lastName":"Asante","suffix":""}],"badges":[],"createdAt":"2025-03-26 17:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6314427/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6314427/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12936-025-05467-7","type":"published","date":"2025-10-14T15:58:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82130657,"identity":"273e6a8c-870b-4e66-85e8-c21e7d390ce3","added_by":"auto","created_at":"2025-05-07 05:29:10","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88632,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the Districts/Municipalities in the three zones\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6314427/v1/8a5932d5ec1dde8cecc99233.jpg"},{"id":82131592,"identity":"03803921-2ec3-480a-b7c5-ee6cf20d3c7b","added_by":"auto","created_at":"2025-05-07 05:37:10","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34966,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage distribution of patients that adhered to one, two, or all three of the Test, Treat and Track malaria policy\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6314427/v1/b7922080cc3530f256772324.jpg"},{"id":82130658,"identity":"ffa39fee-7f8f-45a7-af39-f23f1df3d575","added_by":"auto","created_at":"2025-05-07 05:29:10","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39626,"visible":true,"origin":"","legend":"\u003cp\u003eProportions of patients with febrile illness who reported been tested, treated and informed to return for review (tracked) by epidemiological zones\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6314427/v1/868f717e197832b1dc68f62b.jpg"},{"id":93956070,"identity":"7f7950d8-983a-47f2-9308-076cc525e34a","added_by":"auto","created_at":"2025-10-20 16:10:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1262955,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6314427/v1/9a71d7e7-0196-4e08-9d92-eeb80d3b0181.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adherence to the Test, Treat and Track malaria policy among selected health facilities in Ghana: The clients’ perspective","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe World Health Organization (WHO) in 2012 introduced the test, treat and track (T3) policy to standardize the process of malaria management in endemic settings. The Test, Treat, and Track (T3) policy, which was introduced in 2012, urges the universal testing of all suspected cases of malaria, regardless of age or endemicity, the treatment of positive test cases with anti-malarial medications of high quality, and the tracking of all patients who have been confirmed and treated for malaria [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Ghana adopted the T3 policy in 2013. The T3 initiative was mainly to ensure accurate diagnosis and treatment of the malaria in Ghana and to reduce pressure on antimalarial medicines by ensuring that only confirmed cases are given treatment. The WHO then recommended the prescription of Artemisinin-based Combination Therapy (ACTs) for those who test positive for malaria [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Prompt and accurate diagnosis and treatment of malaria are essential to reduce disease progression to severe disease and complications [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImplementation of the T3 policy has been challenging for many developing countries for several reasons. Medical supplies for diagnosing and treating malaria frequently run out, and some healthcare professionals have expressed concerns with mistrust of malaria test results, particularly when they are negative (Johansson, 2016). The limited capacity of the health system to provide appropriate care undermines effective adherence to the T3 plan, particularly the tracking component [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is expected that all treated cases would return for review to determine if they have been cured [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the tracking of malaria cases has been inconsistent and occasionally did not occur at all in some health facilities [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The underlying reasons have not been fully elucidated. This study evaluated the adherence to the T3 policy in selected health facilities across the three malaria epidemiological zones in Ghana.\u003c/p\u003e \u003cp\u003eSince the WHO launched the T3 policy in 2012, independent evaluations have been conducted in only few districts in Ghana. It is crucial to evaluate and assess the effectiveness of the T3 policy in health facilities across the three malaria epidemiologic zones in Ghana. It is essential that each component of the T3 policy pillars: \u003cem\u003etest\u003c/em\u003e, \u003cem\u003etreat\u003c/em\u003e and \u003cem\u003etrack\u003c/em\u003e is fully assessed to understand the main enablers and challenges to achieve optimum outcomes. The evidence from this study provides very vital information for policymakers to decide on the best supportive intervention to the T3 policy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eWe conducted a cross sectional study by interviewing health facility managers and conducted exit interviews with patients who had febrile conditions from health facilities in six districts across the three epidemiological zones in Ghana.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Setting\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in six Districts/Municipalities; in the three malaria epidemiological zones, the northern savannah zone, the middle/transitional and forest zone, and the coastal savannah zone are Ghana's three malaria epidemiologic zones [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eSelected Districts and Epidemioligical Zones\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistrict\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZone\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMpohor District\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoastal Savanna Zone (Southern Zone)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNzema East Municipality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoastal Savanna Zone (Southern Zone)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKintampo North Municipality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMiddle/transisitonal forest Zone (Middle Zone)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKintampo South District\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMiddle/transisitonal forest Zone (Middle Zone)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJirapa District\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorthern Savanna Zone (Northern Zone)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWest Mamprusi Municipalities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorthern Savanna Zone (Northern Zone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMpohor District and Nzema East Municipal are both located in the Western North Region. The two districts are largely rural and have a total population of about 147,094, majority of which engage in fishing, agro-processing and mining[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The area is highly malaria endemic and has a doctor-patient ratio of 1:21,461. There are two (2) District hospitals, 5 Health Centers, and 9 CHPS compounds.\u003c/p\u003e \u003cp\u003eThe Kintampo North Municipality and Kintampo South District are located within the forest-savannah transitional ecological zone in the Bono East region of Ghana. The two districts together cover an area of 7162km\u003csup\u003e2\u003c/sup\u003e, and largely rural with a resident population of approximately 228,631 who are predominantly engaged in subsistence farming [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Public health facilities in the 2 districts include 2 hospitals, 12 health centers/clinics, and 30 Community-based Health Planning and Services (CHPS) compounds; whilst the privately-owned health facilities include 4 clinics, 2 maternity homes, 4 pharmacies, and 86 Over the Counter Medicine Sellers (OTCMS) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]). The area has a high perennial incidence of endemic malaria.\u003c/p\u003e \u003cp\u003eJirapa and West Mamprusi Municipalities are located in the north-western part of the Upper West Region and North East Regions respectively. The vegetation of the two municipalities is Guinea Savanna woodland with light under growth and scattered trees. The major economic trees are Shea, Dawadawa, and Baobab species. The area has a combined population of 267,034 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Malaria ranks highest as a major health problem. Public health facilities in the two municipalities include 2 municipal hospitals, 1 polyclinic, 11 health centers/clinics, and 35 CHPS compounds.\u003c/p\u003e \n\u003ch3\u003eSample Size and sampling method\u003c/h3\u003e\n\u003cp\u003eTwo districts were purposively selected from each of the 3 zones in the country. In each district, the district hospital, one health centre and 3 CHPS zones were selected, making it 5 health facilities per zone and a total of 30 health facilities across the six districts/municipalities from the 3 zones [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In each of the 30 health facilities, 20 client exit interviews were purposively conducted from each facility, as and when they exit the facility after seeking for heath care, making a total of 600 clients exit interviews.\u003c/p\u003e\n\u003ch3\u003eData collection and management\u003c/h3\u003e\n\u003cp\u003e18 data collectors and 3 supervisors were trained on the objectives of the study and the studies data collection method. Data was collected using Redcap application. The data collection period spanned over two weeks from 11th November to 29th November 2019.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using Stata 17.0. To assess adherence to the T3 policy from the clients\u0026rsquo; perspective, we assessed \u0026ldquo;Test\u0026rdquo; by asking whether the client was tested using malaria RDT (mRDT) or microscopy, \u0026ldquo;Treat\u0026rdquo; by asking whether the client was prescribed a recommended antimalarial drug and \u0026ldquo;Track\u0026rdquo; by asking whether the client was asked to return to the facility for a review and if there was any documented evidence of review. A facility was classified as adherent to the T3 policy if a client responded \u0026ldquo;Yes\u0026rdquo; to all the three questions. To assess adherence to the T3 policy at the facility level, \u0026ldquo;Test\u0026rdquo; was assessed by asking the facility in-charge whether they performed test for reported feverish conditions, \u0026ldquo;Treat\u0026rdquo; was assessed by asking whether the facility prescribed the required antimalarial for confirmed cases and \u0026ldquo;Track\u0026rdquo; was assessed by asking whether prescribers inform clients to return to the facility for review after treatment.\u003c/p\u003e \u003cp\u003eTables were used to describe participant background characteristics and chi square test to assess the asssociation between background characteristics and adherence to the T3 policy. Unadjusted and adjusted odds ratios with 95% confidence interval using logistic regression models were used to assess the factors associated with the T3 policy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, 590 patients with febrile illness and 30 facility managers were interviewed from 30 facilities in 6 districts across 3 epidemiological zones in Ghana. CHPS compounds formed the majority of the facilities surveyed 18 (60). Twenty-nine out of 30 health facilities had RDT test kits and antimalarials (Table\u0026nbsp;1). In all, 30% of facility managers in the North and Middle zones indicated that their staff had not been trained adequately on the T3 policy compared to the Southern zone where all staff were reported to be trained.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1.0\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBackground characteristics of health facilities surveyed across the three epidemiological zones in Ghana\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18(60.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Centre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(20.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(20.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTEST\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMicroscopy services\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (26.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (73.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest kits (malaria RDT)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29(96.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (3.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTREAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAvailability of Antimalarial\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (96.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(3.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTraining of personnel on T3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (76.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e06(20.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Known\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(3.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTRACK\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReview after treatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30(100.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the number of patients and the actual T3 process, one (Test), two (Treat), and three (Track) are the T3s that were performed at the facilities in each zone. This shows that high number of participants went through any of the two of the T3 policy processes. The overall adherence was 31.9%, indicating the number of participants\u0026rsquo; who actually had all the three policy requirements.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e; Association between background characteristics and adherence to the T3 policy from clients exit interviews at health facilities\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eClient\u0026rsquo;s Adherence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZones\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Adhered\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdhered\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172(29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e135(78.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37(21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105(17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35(33.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e313(53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e197(62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116(37.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOwnership\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e524(88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e364(69.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160(30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38(58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27(41.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e198(33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e144(72.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54(27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e392(66.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e258(65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e134(34.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e415(70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e288(69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e127(30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115(19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72(62.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(37.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60(10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42(70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18(30.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e347(58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e224(64.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e123(35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Centre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e135(22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100(74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35(25.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108(18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78(72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30(27.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth Staff/Prescriber\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity Health Nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e364(68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226(62.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e138(37.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysician Assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107(20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77(71.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30(28.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53(1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39(73.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14(26.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7(87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1(12.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the association between background characteristics of participants and adherence to the T3 policy.\u003c/p\u003e\n\u003ch3\u003eAdherence to T3 policy from Clients’ perspective by epidemiological zone\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e describes the proportions of patients with febrile illness who reported been tested, treated and informed to return for review (tracked) by epidemiological zones. Over all 90%, 98% and 35% of patients indicated being tested, treated and tracked respectively. The track to the T3 policy has the lowest percentages ranging from 22\u0026ndash;44% in the respective zones.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with adherence to the T3 Policy; Clients\u0026rsquo; Perspective\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e describes the factors associated with adherence to the T3 policy from clients\u0026rsquo; perspective. The table shows the influence of factors associated with adherence to the T3 policy on a performance score. Performance was measured as \u0026ldquo;fail\u0026rdquo; and \u0026ldquo;pass\u0026rdquo; where pass was coded one (1) and fail coded zero (0). A logistic regression model shows a significant relationship between performance and clusters (location) at the crude odds ratio and adjusted odds ratio level. The northern zone is 80 percent odds more likely to pass performance as compared to the middle zone while the southern zone is 2.1 odds more likely to pass performance compared to the middle zone at the crude odds ratio level. Having adjusting for other factors, the facilities in the southern zone has 2.9 increase odds of adhering to the T3 policy compared to the middle zone.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e; Factors associated with Adherence to the T3 Policy; Clients\u0026rsquo; Perspective.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster/Zone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.82 (1.1,3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.74 (0.9,3.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15 (1.4,3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.87 (1.7,4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.4,1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (0.3,1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.018*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72 (0.4,1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (0.4,0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35 (0.9,2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9 (1.1,3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.5,1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.6,2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClassification of Facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHPS Compound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.030*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Centre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.64 (0.4,1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (0.3,0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70 (0.4,1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (0.4,1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth Staff\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity Health Nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Physician Assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.64 (0.4,1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9 (0.5,1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59 (0.3,1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (0.2,0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23 (0.0,2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2 (0.0,1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*=significant at 0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMales are 40 percent odds less likely to comply with the T3 policy compared to females. Also, persons of ages 30 to 44 years and 45 years and above are 90 percent and 10 percent odds more likely to comply with the T3 compared to individuals within the ages 15 to 29 years. When it comes to the classification types, health centers and hospitals are 50 percent and 20 percent less likely to comply to the T3 policy compared to CHPS compounds respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study assessed the adherence to the T3 policy initiated by the WHO for effective malaria diagnosis and management. The findings indicate that the location of the health facility has influence on the entire process of adherence with the policy. Overall, it was evident that the testing and treating components of the policy were high across all the clusters, whiles tracking was low in all the clusters. Results from our study revealed 32% of the patients adhered by completing the three processes of the T3 policy. These findings are consistent with a study conducted in 2020 at the Mfantseman Municipality in the Central Region of Ghana, which found 30% adherence level to the T3 policy among 414 febrile outpatients seen by 18 prescribers[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] However, the level of adherence observed in this study was below that observed from in a similar study by Agandaa et al in the Bongo District of Ghana, which revealed 42.5% adherence to the T3 policy among 353 children from 28 health facilities. This may be due to the fact that parents are more likely to send their children back for facility reviews because they are vulnerable, compared to adult males who may have refused to return for reviews for unknown reasons.\u003c/p\u003e \u003cp\u003eSome studies have shown that public primary health care facilities lack diagnostic kits such as microscopes, and inadequate personnel to use the kits[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Frequent stock out of logistics such as RDTs kits and reagents for microscopy and the absence of qualified staff with malaria testing capacity hinder effective compliance with the components of the T3 policy. A study conducted in Mozambique on diagnostic test kits supply chain revealed 17% of health centers experienced RDT stuck out in any given month. Hence, situation of nonexistence of microscopies, adherence to T3 policy remains a challenge [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The result of this study which showed that more than 70% of the facilities across all zones have no access to microscopy test, which indicates that in terms of RDT stockout, most facilities may not be able to comply with the policy guidelines contrary to the finding of a study among patients in Zambia showing that continues availability of the testing tool has the potential to improve adherence to test results and general malaria case management [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. We also found that 30% of the personnel from the North and the Middle zones indicated not being trained on the T3 policy. This could possibly be due to high staff turnover which may have hindered adequate training for new staff.\u003c/p\u003e \u003cp\u003eIn this study we found that only 35% of patients were tracked according to the T3 policy across all zones. Health facilities in the southern zone of Ghana had almost three-fold increased odds of adhering to the T3 policy relative to their counterparts in the Middle and Northern zones. This may be due to the fact that facilities in the South are mostly well equipped, have more qualified clinical and laboratory staff and located mainly in towns which may be closer to settlement areas thereby making them easily accessible compared to those in the North and the Middle zones where road network and distances to facilities remain a challenge. A study on guiding placement of health facilities in the Bunkpurugu-Yunyoo District in Northern Ghana, confirmed that for malaria case, location of facility has a significant impact on malaria prevalence and care seeking [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe T3 policy discourages presumptive treatment of malaria based on symptoms and signs alone. However, in this study we found that apart from the Northern Zone, the other zones had clients treated for malaria without confirmatory testing. It has been reported that in Kenya, less than 40% of febrile children under five years were tested for malaria whiles in Ghana, 73% of children were presumptively diagnosed and treated for malaria [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In addition, fever from most endemic countries associated with malaria was diagnosed and treated presumptively as malaria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Even though there is an association between fever and malaria parasitemia, it has been proven that not all patients presenting with fever have malaria parasites and that several other pathogens account for non-malarial fevers even in malaria endemic settings of Ghana [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. It is therefore inappropriate to treat feverish conditions with ACTs without confirming diagnosis of malaria with RDT or slide [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Testing for malaria also provides an opportunity for improved diagnoses and better case management [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComparing the level of adherence of the T3 policy, a study in the Bosomtwi District of Ghana which evaluated compliance level to the T3 policy revealed that 64% of malaria cases were tested before treatment using antimalarials [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] This finding is relatively lower as compared to what we found in this study, showing 90% and 98% tested and treated cases respectively across the three zones using the required ACTs. Another study on the adherence of the T3 policy on caregivers of children under 10 visiting the Over-the-Counter Medicine Sellers (OTCMS), revealed 56.6% adherence among OTCMS, and indicated that monitoring and supervision of the OTCMS especially in the rural areas would lead to improving adherence of the policy and subsequently scaling up management of malaria events [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The result of the study is high compared to the adherence level revealed by our study.\u003c/p\u003e \u003cp\u003eA study on health worker compliance with a \u0026ldquo;Test and Treat\u0026rdquo; malaria case management protocol conducted in Papua New Guinea revealed Frequent prescriptions of antimalarials despite negative tests as the most reported barriers to policy compliance [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. When compared with our results, facilities in the Middle and the Southern zone provided antimalarials more than the required number of tests performed, meaning that some prescribers from these facilities continue to provide ACTs for the treatment of malaria cases without the required testing which is contrary to the enhancement of the policy. The results from the logistic regressions analysis showed that some facilities in the South are prescribing malaria drugs without testing. The outcome confirms the findings from a qualitative study on malaria case management among prescribers in Ghana, which revealed that; majority of Ghanaian health facilities and CHPS compounds lack laboratories capable of diagnosing malaria, rapid diagnostic tests are mostly implemented at these levels. RDT kits can be hard to come by at health centers without labs and may affect the adherence level [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitation\u003c/h2\u003e \u003cp\u003eThere was potential limitation regarding recall bias during exit interview of clients, who may have forgotten about some of the information received at the health facility. The kind of treatment given may not have been accurately provided in the responses. This limitation was minimized by interviewing clients immediately they were discharged from health facilities. Also, healthcare managers may have provided responses solely to please interviewers, which could lead to social desirability bias. However, we verified most of the responses from the facilities to reduce this risk. Limited information on clients\u0026rsquo; demographic characteristics like marital status, occupation, religion and wealth quintiles prevented further analysis on some potentially important independent variables.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study showed that testing and treating for malaria was high among health facilities across the three epidemiological zones. However, tracking of patients was very low across the three zones. Adherence from clients\u0026rsquo; perspective was low especially for males who were more likely to default facility return for review, even though facility prescribers informed participants on the need to return for review. Training for facilities on the T3 policy was relatively inadequate especially for staff in the Northern and the Middle zones.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRecommendations\u003c/strong\u003e \u003cp\u003eThe National Maria Elimination Program (NMEP) should ensure adequate periodic trainings of health facility staff especially those within the Northern and Middle zones of Ghana and strengthen monitoring and supervision of health facilities to enhance adherence to the T3 policy. The NMEP could also intensify Client sensitization programs especially targeting male clients to help them understand the need to return to health facilities for review and also ensure regular supply of test kits in line with the T3 policy. There is also the need for implementation research to explore strategies to improve the tracking component of the policy at the client and health facilities levels within the T3 policy framework.\u003c/p\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eWHO-World Health Organization,\u003c/p\u003e\n\u003cp\u003eCHPS-Community Health and Planning Services,\u003c/p\u003e\n\u003cp\u003emRDT-Malaria Rapid Diagnostic Test,\u003c/p\u003e\n\u003cp\u003eNMEP-National Malaria Elimination Program,\u003c/p\u003e\n\u003cp\u003eACT-\u0026nbsp;Artemisinin-based Combination Therapy,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eT3-Test, Treat and Track,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOTCMS- Over the\u0026nbsp;Counter Medicine Sellers\u003c/p\u003e\n\u003cp\u003eRDD-Research and Development Division\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKHRC-Kintampo Health Research Centre\u003c/p\u003e\n\u003cp\u003eNHRC- Navrongo Health Research Centre\u003c/p\u003e\n\u003cp\u003eDHRC- Dodowa Health Research Centre\u003c/p\u003e\n\u003cp\u003eARHR-Alliance for Reproductive Health Right\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eADRRO-Anglican Diocesan Development Relief Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the health officials at the municipal and directorate levels, the healthcare institutions where the data were gathered, the patients from the different facilities, the medical staff members who assisted with the data gathering and special acknowledgement to Bill and Melinda Gate Foundation for the training activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research protocol was reviewed and approved by the Kintampo Health Research Centre's Institutional Ethics Committee (KHRC-IEC) KHRCIEC/2014-24. All participants were consented to be part of the study and assured of confidentiality of information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformation could be provided upon acceptable request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by COMIC RELIEF and Kintampo Health Research Centre, Ghana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare that they do not have any conlicting inerest\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCK, CT, KPA, FA, PM, ASNA, JAA, and SBEH were involved in the conception, design, and development of the study proposal. FA, IN, VAA, PM, and AA were responsible for collecting the data. The analysis of the data was performed by CK, SAA, EA, PW, CT, KPA, SG, and RJT. CK, CT, JAA, KPA, MT, WZ, FK, CKK, JO, and SBEH contributed to the interpretation of the results and reviewed the manuscript. All authors have read and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKolekang AS, et al. Challenges with adherence to the \u0026lsquo;test, treat, and track\u0026rsquo; malaria case management guideline among prescribers in Ghana. Malar J. Dec. 2022;21(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12936-022-04365-6\u003c/span\u003e\u003cspan address=\"10.1186/s12936-022-04365-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKwarteng A, et al. 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Improved adherence to test, treat, and track (T3) malaria strategy among Over-the-Counter Medicine Sellers (OTCMS) through interventions implemented in selected rural communities of Fanteakwa North district, Ghana. Malar J. Dec. 2022;21(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12936-022-04338-9\u003c/span\u003e\u003cspan address=\"10.1186/s12936-022-04338-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePulford J, Smith I, Mueller I, Siba PM, Hetzel MW. Health worker compliance with a \u0026lsquo;test and treat\u0026rsquo; malaria case management protocol in Papua New Guinea. PLoS ONE. Jul. 2016;11(7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0158780\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0158780\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolekang AS, et al. Challenges with adherence to the \u0026lsquo;test, treat, and track\u0026rsquo; malaria case management guideline among prescribers in Ghana. Malar J. Dec. 2022;21(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12936-022-04365-6\u003c/span\u003e\u003cspan address=\"10.1186/s12936-022-04365-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adherence, T3 policy, Clients’ perspective, Facility managers, Malaria Epidemiological Zones, Ghana","lastPublishedDoi":"10.21203/rs.3.rs-6314427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6314427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe World Health Organization in 2012 introduced the test, treat and track (T3) policy to standardize the process of malaria management in endemic settings. All malaria suspected conditions are expected to be confirmed by test and treatment initiated with recommended artemisinin-based combination therapy (ACTs) and treatment outcomes monitored over the course of the illness. This study evaluated the adherence to the T3 policy in selected health facilities within three malaria epidemiological zones in Ghana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis crossectional study was conducted in November 2019 involving thirty health facilities comprising one district hospital, one Health Centre and 3 Community Health and Planning Services (CHPS) randomly selected from six districts in the 3 malaria epidemiological zones. In addition, Clients exit interviews were conducted from each facility. Frequency charts highlighted facility characteristics. Factors associated with the \u003cem\u003etest\u003c/em\u003e, \u003cem\u003etreat\u003c/em\u003e and \u003cem\u003etrack\u003c/em\u003e defined outcomes were assessed using chi square and multivariable logistic regression models at 5% level of significance and 95% confidence interval. Data were classified according to facility and clients’ perspectives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 590 patients and 30 health facility managers were interviewed from 30 facilities in 6 districts across the three zones. CHPS compounds formed 18 (60.0%) of facilities assessed. Twenty-nine out of 30 health facilities had Rapid Diagnostic Test (RDT) kits and antimalarials. In all, adherence to the T3 policy was 31.9%, whiles 30% of facility managers in the North and Middle zones indicated inadequate training on the T3 policy. The study showed that 90% and 98% of patients were tested and treated respectively for malaria. However only 35% (range 22% − 44%) of patients were tracked according to the T3 policy across all zones. Health facilities in the southern zone of Ghana had almost three-fold increased odds of adhering to the T3 policy compared to the middle zone [aOR = 2.87 (1.7, 4.8): p \u0026lt; 0.001]. Males were more likely not to return to the health facility for review [aOR = 0.6 (0.3, 0.9): p = 0.018].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTesting and treating for malaria were high among health facilities in the three epidemiological zones. However, tracking of patients was very low across the zones. Adherence from clients’ perspective was low especially for males, who were more likely to default on health facility return for review, even though facility prescribers informed participants on the need to return for review. The hurdle for one to adhere to the policy was to return to facility for review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe National Maria Elimination Program (NMEP) should ensure periodic trainings of health facility staff especially those within the Northern and Middle zones of Ghana and strengthen monitoring and supervision of health facilities to enhance adherence to the T3 policy. The NMEP could also intensify Client sensitization programs especially targeting male clients to help understand the need to return to health facilities for review in line with the T3 policy. There is also the need for implementation research to explore strategies to improve the tracking component of the policy at the client and health facilities levels within the T3 policy framework.\u003c/p\u003e","manuscriptTitle":"Adherence to the Test, Treat and Track malaria policy among selected health facilities in Ghana: The clients’ perspective","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 05:29:05","doi":"10.21203/rs.3.rs-6314427/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-20T13:04:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-18T08:40:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-13T18:29:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"285787259634866807818844515807567315266","date":"2025-04-05T09:15:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"97704853008841103532294787387303650885","date":"2025-04-05T08:22:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314034816921834142200986560437973626431","date":"2025-04-05T08:09:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"301306622938963756168339834950716988405","date":"2025-04-04T15:06:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-04T08:01:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10065574523333361889980109600628691669","date":"2025-04-03T08:03:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80874382026801047070736566190424670092","date":"2025-04-03T05:07:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-03T04:47:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-27T07:37:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-27T07:36:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2025-03-26T16:57:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f262b1af-9e3e-4e53-805b-d63e9fa8b193","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:04:15+00:00","versionOfRecord":{"articleIdentity":"rs-6314427","link":"https://doi.org/10.1186/s12936-025-05467-7","journal":{"identity":"malaria-journal","isVorOnly":false,"title":"Malaria Journal"},"publishedOn":"2025-10-14 15:58:18","publishedOnDateReadable":"October 14th, 2025"},"versionCreatedAt":"2025-05-07 05:29:05","video":"","vorDoi":"10.1186/s12936-025-05467-7","vorDoiUrl":"https://doi.org/10.1186/s12936-025-05467-7","workflowStages":[]},"version":"v1","identity":"rs-6314427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6314427","identity":"rs-6314427","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}