Stop Malaria Project. Health Facility Assessment Survey Report

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Stop Malaria Project Health Facility Assessment Survey Report September 2011 USAID/JHU Cooperative Agreement No. CA 617-A-00-08-00018-00 1

Table of Contents LIST OF ACRONYMS AND ABBREVIATIONS... 4 EXECUTIVE SUMMARY... 5 1. INTRODUCTION... 8 1.1. BACKGROUND... 8 1.2. STUDY RATIONALE... 10 1.3. STUDY OBJECTIVES... 10 1.4. RESEARCH DESIGN... 11 1.4.1. Study Units and Population... 11 1.4.2. Sample size... 11 1.4.3. Study Procedure... 15 1.4.4. Quality assurance procedures... 17 1.4.5. Field Interviewer Training... 18 1.4.6. Data Processing and Analysis... 18 2. CHARACTERISTICS OF CLIENTS... 19 2.1. INTRODUCTION... 19 2.2. AGE AND SEX OF THE CLIENTS... 19 2.2. RESIDENCE OF RESPONDENTS... 20 2.3. EDUCATION ATTAINMENT... 21 2.4. EXPOSURE TO MASS MEDIA... 23 3. KNOWLEDGE OF MALARIA, AND MANAGEMENT OF FEVER IN PREGNANT WOMEN AND CHILDREN... 26 3.1. KNOWLEDGE OF MALARIA... 26 3.1.1. Knowledge of Causes of Malaria... 26 3.1.2. Exposure to Malaria Treatment Messages... 28 3.1.3. Knowledge of ways to avoid Malaria... 29 3.1.4. Knowledge of Signs of Malaria... 30 3.2. MALARIA PREVENTIVE BEHAVIOR IN CLIENTS... 31 3.2.1 Ownership and Source of Mosquito Nets by Clients... 31 3.3. MALARIA PREVENTIVE AND TREATMENT SEEKING BEHAVIOUR IN CHILDREN UNDER 5 YEARS... 35 3.3.1. Children under 5 who slept under a net the previous night... 35 3.3.2. Prompt malaria treatment for children under 5 years... 37 3.4. MALARIA PREVENTIVE BEHAVIOUR AND CASE MANAGEMENT IN PREGNANT WOMEN... 43 3.4.1. Ownership of Mosquito nets among pregnant women... 43 3.4.2. Pregnant women who slept under a net the previous night... 45 3.4.3. Knowledge of Practices to Avoid Getting Malaria in Pregnant Women... 46 2

3.4. 4.1. Pregnant women in ANC who took IPTp... 48 3.4. 4.2. Pregnant women in ANC who took IPTp under DOT... 49 3.5. PREVALENCE OF DIAGNOSTIC TESTING FOR MALARIA BEFORE TREATMENT... 51 3.6. CLIENTS SATISFACTION LEVELS... 53 3.7. ASSOCIATIONS / CORRELATIONS ON KEY MALARIA OUTCOMES... 54 4. ASSESMENT OF HEALTH FACILITIES... 56 4.1. INTRODUCTION... 56 4.2. STAFFING LEVEL... 56 4.3. OPERATIONAL SERVICES... 58 4.3.1 Source of drinking water at the health facility... 58 4.3.2. Electricity at the health facility... 59 4.3.3. Administrative Operations... 61 4.3.4. Malaria Case Management... 61 4.3.5. Provision of IPT/ANC Services... 63 4.3.5. Administration of IPT under DOT... 64 4.4.1 Availability of medications... 71 4.4.2 Stock outs of medications... 74 4.5. LABORATORY... 77 4.5.1 Ownership of Laboratory Equipment... 78 4.6. COMPETENCE OF HEALTH PROVIDERS TO PROVIDE IPTP SERVICES... 82 4.7 COMPETENCE OF HEALTH PROVIDER TO PROVIDE TO MANAGE A MALARIA CASES IN CHILDREN... 83 APPENDICES... 86 3

LIST OF ACRONYMS AND ABBREVIATIONS ACT ANC BCC HC HFA HMIS IPTp ITN LLIN MDGs MIS MoH NMCP PMI PMP RBM RDT SMP SP USAID WHO Artemisinin-based Combination Therapy Antenatal Care Behaviour Change Communication Health Centre Health Facility Assessment Health Management Information Systems Intermittent Preventive Treatment in pregnancy Insecticide Treated Net Long Lasting Insecticide Treated Net Millennium Development Goals Malaria Indicator Survey Ministry of Health National Malaria Control Program President s Malaria Initiative Performance Monitoring Plan Roll Back Malaria Rapid Diagnostic Testing Stop Malaria Project Sulfadoxine-pyrimethamine United States Agency for International Development World Health Organisation 4

Executive Summary The Stop Malaria Project (SMP) is a project funded by the U.S. President s Malaria Initiative (PMI). SMP is managed by Johns Hopkins University Bloomberg School of Public Health Centre for Communication Programs (CCP), Malaria Consortium (MC), the Infectious Diseases Institute (IDI), and Communication for Development Foundation Uganda (CDFU). SMP is designed to assist the Government of Uganda in reaching the PMI and Roll Back Malaria (RBM) goal of reducing malaria-related mortality by 70% by 2015 (MOP FY 2011), and subsequently contribute to the attainment of the Millennium Development Goals (MDGs). Stop Malaria Project is designed to assist the Government of Uganda, in particular the National Malaria Control Programme (NMCP) and District Health Teams (DHTs), in reaching 85% coverage of children under five years of age and pregnant women with proven preventive and therapeutic malaria interventions, over a period of five years, including: Artemesinin-based Combination Therapy (ACTs), for treatment of uncomplicated malaria, Intermittent Preventive Treatment (IPTp) of malaria in pregnancy, and Long-lasting Insecticide Treated Nets (LLINs). The project activities are implemented in close collaboration with the National Malaria Control Program (NMCP) and district local governments. The project currently covers 34 districts in three regions: (i) Central region covering 21 districts, (ii) Hoima region covering 5 districts and (iii) Teso region covering 8 districts. In July 2011, a cross-sectional Health Facility Assessment (HFA) survey was conducted with the study units including: Public Health facilities in districts targeted by the Stop Malaria Project, Health Providers including Doctors, Clinical Officers, Midwives and Nurses in selected facilities in districts served by the Stop Malaria Project, Clients attending targeted facilities for malaria related services and District officials in selected districts. The HFA survey aimed to assess the effectiveness of various interventions and activities towards achieving the project goals, provide evidence on whether observed changes in outcomes can be attributed to SMP 5

promoted interventions and identify gaps and challenges that inhibit the success of the project and identify possible solutions and remedies. The survey indicated that 3 in 4 of all respondents were knowledgeable that malaria is caused by mosquitoes. On the contrary, 1 in 3 respondents wrongly cited drinking unboiled water whereas 12 percent and 7 percent cited eating mangoes and maize respectively as the causes for malaria. Approximately 9 in 10 (86 percent) of all clients reported that they had been exposed to malaria treatment messages with the radio and health providers (nurse, doctors etc.) the most cited sources of messages with 59 percent and 54 percent respectively. In the sample, knowledge of at least one way to avoid malaria was nearly universal (97%) with sleeping under a mosquito net cited by 90 percent of all respondents. Of all respondents in the survey, 4 in 5 (79%) of all respondents reported to own any mosquito and 3 in 5 (64%) owned an ITN. Forty-four percent of clients who owned a mosquito net reported that they got their mosquito nets from household distributions, 35 percent from the ANC clinic and 20 percent bought them from the market. Of equal interest, respondents from Hoima (76%) and Central (63%) regions were more likely to own any mosquito net compared to their counterparts from the Teso region (53%). Current use of mosquito nets was ascertained by asking use of a mosquito net the night before the survey. Seventy-one percent of respondents slept under any mosquito net of which 64 percent were ITNs. Pregnant women (82%) were more likely than children under five (75%) to have slept under any mosquito net the night before the survey but both groups were better than the 71 percent in the general population. Concerning prompt seeking of malaria treatment, 59% of the care takers were knowledgeable about seeking malaria treatment within 24 hours. However, 29 percent of caretakers of children below 5 years actually sought treatment for the child on the same day after the onset of fever, 32 percent on the next day and 18 percent two days after. Male care takers (34%) were more likely to seek treatment on the same day of fever onset compared to female care takers (28%). In addition to prompt treatment, 82% of respondents were knowledgeable that malaria should be treated with ACTs. 6

Malaria treatment is based on taking good history of the patient, doing a thorough physical and clinical examination and guiding the patients on how to recover well. Results showed that 90% of the providers asked for the child s age before treatment but less than 32% described signs which should prompt care takers to take their children to a health facility. Also, only 9% of the sick children presented to a health facility were referred to another facility. Notably, a higher percentage of male care takers had their children s temperature and weight measured and almost all were asked for the child s age (98%) compared to 89% of female care takers. 7

1. INTRODUCTION 1.1. Background The Stop Malaria Project (SMP) is a project funded by the U.S. President s Malaria Initiative (PMI). SMP is managed by Johns Hopkins University Bloomberg School of Public Health Centre for Communication Programs (CCP), Malaria Consortium (MC), the Infectious Diseases Institute (IDI), and Communication for Development Foundation Uganda (CDFU). SMP is designed to assist the Government of Uganda in reaching the PMI and Roll Back Malaria (RBM) goal of reducing malaria-related mortality by 70% by 2015 (MOP FY 2011), and subsequently contribute to the attainment of the Millennium Development Goals (MDGs). Stop Malaria Project is designed to assist the Government of Uganda, in particular the National Malaria Control Programme (NMCP) and District Health Teams (DHTs), in reaching 85% coverage of children under five years of age and pregnant women with proven preventive and therapeutic malaria interventions, over a period of five years, including: Artemesinin-based Combination Therapy (ACTs), for treatment of uncomplicated malaria, Intermittent Preventive Treatment (IPTp) of malaria in pregnancy, and Long-lasting Insecticide Treated Nets (LLINs). The project activities are implemented in close collaboration with the National Malaria Control Program (NMCP) and district local governments. The project currently covers 34 districts in three regions: (i) Central region covering 21 districts, (ii) Hoima region covering 5 districts and (iii) Teso region covering 8 districts. Activity implementation during the FY 2010/2011 was based on the results framework below: The framework provides a foundation for the project results, and activities that contributed to the results. 8

Strategic Objective 8: Improving Human Capacity Critical Assumptions Program Objectives 3.1.1: Reduce Malaria Mortality Availability of Funds IR1: IR2: Malaria diagnosis and treatment improved NMCP IR3: Capacity Strengthened IR 1.1: Malaria related policies and guidelines operationalized IR 1.2: Access to IPTp increased IR 1.2.1: Services providers knowledg e and skills for IPTP improved. Program Activities to affect the Results - IR 1.2.2 Community Knowledge and perceptions of IPTp and LLIN IR 1.3: Access to LLINS increased IR 2.1 Malaria diagnostic treatment and referral services improved Program Activities to affect the Results - IR 2.2 Increased access to ACTS (Not doing it this year) IR 2.3 Communit y knowledg, e, perceptio ns and behaviors of febrile illness - IR 3.1 Technical resources and skills of M & E sub-unit increased IR 3.2 Collection, processing and use of data from districts and implementing partners Program Activities to affect the Results. IR.1.1: 1. Provide TA for the malaria program review 2. Develop and Adapt LLIN guidelines and manual for ANC distribution 3. Print and dissemination of policy documents IR 1.2. 1. Procure and distribute IPTp commodities - : for IPTp DOTs (jerry cans, cups) for HCII and additional replacements at other levels of the health system 2. Collaborate with SURE to track SP stock on a monthly and quarterly basis in 34 3. Print and distribute ANC cards to HFs IR 1.2.1 1. In collaboration with STRIDES, conduct health facility based IPTp orientation for new staff and HCII health workers in integrated with LLIN/ANC. 2. Print and distribute counselling guides, gestational wheels - for HCII and additional replacements at other levels of the health system IR1.2.2 1. Orientation of Health Assistants in malaria prevention and treatment 2. Support radio talk shows and Secure radio properties for creating community awareness on ANC LLIN distribution and IPTP uptake 3. Support school outreaches IR 2.1 1. Conduct TOT orientation in the - management of un-complicated and severe malaria, and the clinical audit approach for training at the hospital and HCIV levels, and pre-referral training for HCIII and HCIIs 2. Provide financial and technical support to district teams to carry out clinical audits at hospitals and HC IVs in order to build capacity of facility staff 3. Print job aids on management of uncomplicated and severe malaria 4. Print and distribute clinical audit manuals to health centre IVs and hospitals 5. Print and distribute (during support supervision) referral forms to HCIIIs and HCIIs 6. In collaboration with SURE project track stocks of ACTs in health facilities 7. Carry out external quality assessments in conjunction with CPHL 8. Conduct on- site re-orientation to improve microscopy skills of laboratory personnel for the public and private sector 9. Reprint and distribute Malaria laboratory diagnostic charts to all functional laboratories IR2.3 1. Orientation of Health Assistants in malaria treatment IR 3.1 1. Continue to Second an M & E Specialist to the NMCP M & E Subunit 2. Support and provide technical assistance in the development of the NMCP M&E plan 2010-2015 3. Provide technical assistance in proposal development for GFATM Round 7 phase II LLIN distributions 4. Provide Technical Assistance in the development and printing of the NMCP strategic plan, national malaria communication strategy, print and disseminate in the 34 districts 5. Support information sharing through NMCP quarterly and annual reports IR 3.2 1. Organize and financially support quarterly national level RBM coordination meetings 2. Link RC-MoH to NMCP database 3. Consolidate and analyze data from the districts 4. Orient Malaria, HMIS FPs and biostatisticians at district, records staff at hospitals and HCIVs in reviewed HMIS tools and data quality assessment, utilization and management Crossing cutting program activities 1. Conduct Quarterly Support supervision to districts and health facilities( JHU, Malaria Consortium, IDI, CDFU) 2. Conduct IEC/BCC mass media campaign to increase LLIN usage and IPTp uptake( JHU, Malaria Consortium, IDI, CDFU) 9

1.2. Study rationale Malaria remains one of the most important diseases in Uganda, causing significant morbidity, mortality, and economic loss. Children under age 5 and pregnant women are disproportionately affected. Hospital records suggest that malaria is responsible for 30 to 50 percent of outpatient visits, 15 to 20 percent of admissions, and 9 to 14 percent of inpatient deaths (2009, Uganda, Malaria Indicator Survey). Further, Uganda ranks 6th worldwide in number of malaria cases and 3rd in number of malaria deaths (World Health Organization, 2008). The overall malaria-specific mortality is estimated to be between 70,000 and 100,000 child deaths annually in Uganda, a death toll that far exceeds that for HIV/AIDS (Lynch et al., 2005). The Government of Uganda through the Uganda National Malaria Control Program (NMCP) is working with the Stop Malaria Project and other partners to reduce deaths due to malaria. The SMP activities are designed to meet three intermediate results namely: (ii) to improve and implement malaria prevention programs in support of the national malaria strategy; (ii) to improve and implement malaria diagnosis and treatment activities in support of the national malaria strategy; and (iii) to strengthen the NMCP capacity to monitor and evaluate interventions. The Health Facility Assessment (HFA) survey was based on a set of benchmarks and targets for a set of performance indicators and targets for FY 2011 which are prescribed in the project performance monitoring plan (PMP). In order to assess progress in achieving the project s objectives and targets, the HFA survey was conducted so that findings could be compared with a set of benchmarks. 1.3. Study objectives SMP focuses on pregnant women and children under five years. The facility survey therefore sought to assess the capacity of targeted facilities to provide prevention, diagnosis and treatment of malaria for these populations. Specific objectives include: To assess the availability of commodities, equipment, human resources, supplies and systems necessary to provide adequate malaria prevention, diagnosis and treatment in targeted facilities; To assess the quality of client-provider interactions; 10

To assess the knowledge, attitudes and practices of health workers regarding the prevention, diagnosis and treatment of malaria; To assess the level of client satisfaction and overall facility experience among antenatal counseling (ANC) clients as well as clients seeking malaria services for children under 5 years. To identify gaps and challenges that inhibit the success of the project and identify possible solutions and remedies To provide recommendations for developing, refining and prioritizing the project s interventions for public health facilities in relation to prevention and treatment of malaria. 1.4. Research Design 1.4.1. Study Units and Population The study had the following study units and populations: a. Public Health facilities supported by the Stop Malaria Project; b. Health providers including Doctors, Clinical Officers, Midwives, Nurses and laboratory staff in selected facilities supported by the Stop Malaria Project; c. ANC clients as well clients visiting the Outpatient department (OPD) to receive malaria care for children under-5 years. 1.4.2. Sample size The sections below discuss the sample size for each study unit and population: I. Public health facilities The SMP project targets public health and nonprofit facilities in 34 districts in Uganda. The project supports a total of 1145 facilities including health Center IIs, Health Center IIIs, Health Center IVs and hospitals. This survey included 235 facilities. This sample size was calculated using 11

Yamane s formula for sample size calculation--equation 1 Equation 1 n 0 = N 1 + N(e) 2 where n 0 is the sample size, N (equal to 1145 supported health facilities) is the population size and e (equal to 5%) is the level of precision. Using equation 1, we get a required sample size of 296 health facilities. But because our sampling frame of public health facilities is finite (1145 targeted public health facilities), we adjust for finite populations using a correction factor formula suggested by Yamane (equation 2) Equation 2 n 0 n= 1 + n 0-1 N Given that districts vary in size and the number of facilities targeted vary, we did not not select an equal number of facilities in each district. On the contrary, the number of facilities selected for the study was proportional to the number of facilities supported in that district. As an example, a district representing one fifth of all supported facilities also represented one fifth of facilities in the survey. Selection of facilities within each district took into account the following factors; a) inclusion of all types of facilities (i.e Health Center IIs, Health Center IIIs, Health Center IVs, and hospitals); b) the proportion of each type of facility among the supported districts. Therefore, given that most districts have one or two hospitals and a relatively small number of health Center IVs, at least one hospital and one health Center IV from each district was included in the sample. Health Center IIIs and Health Center IIs were selected proportional to their representation in the SMP supported facilities list in each district. We randomly selected health providers, and clients from these facilities as discussed below. 12

II. Health Service providers Health service providers participated in 3 data collection activities; 1) Facility audit; 2) Health provider knowledge, attitude and practice assessment and 3) the client provider observations. We included in the sample, 940 health providers comprising of 235 facility managers, 235 laboratory workers and 470 other health workers who were assessed for their knowledge and attitudes. We discuss below the numbers and selection of health workers for each of the above activities. a) Facility Audit: The facility audit sought to assess the facility s capacity to diagnose and treat malaria. For each one of the public health facilities, we interviewed the facility manager or their designee as well as the most senior health worker involved in the delivery of laboratory services (a lab technologist or other person) or their designee. These two were selected purposively because of their positions. Therefore 235 facility managers (or their designees) and 235 laboratory workers were interviewed from the 235 selected facilities. b) Health provider, knowledge, attitude and practice assessment: At each facility, 2 health providers; one health provider from the ANC clinic and one health provider from the OPD were randomly selected to participate in the knowledge, attitude and practice assessment, for a total of 470 providers/interviews. Because some facilities did not provide ANC services, research staff compensated for ANC providers at the next facility, i.e. more than one ANC provider could be interviewed at the next facility if there was none at the previously visited facility. c) Client Provider observations: In addition to the knowledge and attitude interviews mentioned above, the two health providers (the ANC provider and the OPD provider) were each observed providing services to 2 clients. The observations of the ANC provider were solely conducted by a research assistant. One of the observations of the OPD clients was conducted by a research assistant and the other by a mystery client (details provided below). Therefore, we observed a total of 3 real clients. There were 940 observations. These observations included 705 real clients and 235 mystery client observations. Health providers who agreed to be observed had to agree to be interviewed. In some facilities more than 3 observations were conducted if observations were carried over from a previously visited 13

facility that did not have ANC services and ANC providers. However, the overall number of observations did not exceed 940. III. Service Clients Service clients were involved in two data collection activities: i) the Client-provider observations; and ii) the exit interviews. Five exit interviews at each facility were targeted. Three of the five clients at each facility were observed and interviewed while the remaining 2 were only interviewed. Therefore, a total of 1175 interviews were to be conducted. Clients who agreed to be observed also had to agree to be interviewed. Because some facilities did not have ANC services, interviews and observations at facilities without ANC were carried over to the next visited facility with ANC services. The study targeted to observe three real clients at each facility. Among the clients served by the ANC provider, interviewers randomly selected and observed interactions involving 2 pregnant women. One client seen by the OPD health worker was randomly selected for observation. In each facility, an additional observation of the OPD health worker was made by a mystery client or a trained individual posing as a client. The latter involved somebody who acted as a caretaker of a child complaining of malaria related symptoms. In some cases, these mystery clients were recruited from the facility (i.e caretakers of children waiting to receive malaria services while in others mystery clients were recruited from the community). The difference between the mystery clients and other clients included in the study was that the mystery client was coached on how they should act in the examination room and helped the research assistant to complete the observation tool once the consultation was complete. Unlike the other observations, the research assistant was not in the room during consultations involving the mystery client. Mystery clients are commonly used in observations of client provider interactions. They ensure that health providers do not adjust their behavior because they are being observed. In this study, they provided an opportunity to observe the client provider interactions as they would occur with a typical client. Research assistants assisted the mystery client to complete the client-provider observation tool after the consultation. Mystery clients were oriented on their task and advised to decline any 14

medication provided during the consultation. This was necessary since they did not need the medication as they were not real clients but individuals who were acting to be sick. 1.4.3. Study Procedure The sections below provide a detailed description of the study procedures. a) General study design and methods. We used a cross sectional survey design. Quantitative research methods were employed to assess the quality of malaria care and treatment in the targeted facilities. b) Data Collection The study targeted health facilities, and services providers at 235 facilities. ANC pregnant women and caretakers of children under 5 years seeking care and treatment for malaria at these facilities also were included. Survey activities were carried out in 34 districts in three regions: (i) Central region: Buikwe, Bukomansimbi, Butambala, Buvuma, Gomba, Kalungu, Kayunga, Kiboga, Kyankwanzi, Luweero, Lwengo, Masaka, Mityana, Mpigi, Mubende, Mukono, Nakaseke, Nakasongola, Rakai, Sembabule, and Wakiso (ii) Hoima region: Buliisa, Hoima, Kibaale, Kiryandongo, and Masindi (iii) Teso region: Amuria, Bukedea, Kaberamaido, Katakwi, Kumi, Ngora, Serere and Soroti. The study collected data on the following; a) Malaria related commodities, equipment, human resources and systems available in each facility; b) Knowledge, attitudes, skills of health professionals providing malaria treatment; c) Quality of the client provider interaction/consultations; d) Satisfaction with services and general experience of ANC clients and caretakers of children below five years complaining of malaria symptoms; The study used a combination of tools to collect the above data. These tools included: a facility audit questionnaire; 15

a service provider questionnaire; a client-provider observation checklist; a client exit interview questionnaire; The tools adopted questions from tools used in the Uganda service provision assessment as well as other tools used in Uganda and other African countries to assess the quality of malaria care. We describe below each of the tools used in the HFA. The facility audit questionnaire: This questionnaire included close ended questions that were posed to the facility manager (or their designee) and the most senior laboratory health worker or their designees. The questionnaire assessed whether the facility had the commodities, equipment, staff and systems needed to provide quality malaria prevention, testing and treatment services. The questionnaire was administered by a trained research assistant and took not more than one and half hours. The research assistant was responsible for making observations at the facility to confirm responses provided by the facility manager. Another 45 minutes could be used to make these observations around the facility. The facility audit questionnaire included the following sections: (See Attachments) Information on person participating in the facility audit Information on provided services and quality assurance Provision of intermittent preventive treatment of malaria and antenatal services Laboratory equipment and staff Commodities and supplies including MOH policies and guidelines related to malaria Malaria related behavior change communication HMIS and other data recording systems The Health Service Provider questionnaire: This questionnaire was used to assess knowledge, attitudes and skills of health providers at each facility. The questionnaire also included questions on received training and supervision. Administering the service provider questionnaire was conducted by a trained research assistant and would not last more than one hour. (See Attachments) Client-Provider observation checklist/tool: The client observation checklist was used to assess the quality of the client-provider interaction/consultations. This tool assessed whether 16

the provider was following ministry of health and other clinical procedures. The tool included specific items for ANC mothers as well as consultations involving children complaining of malaria or malaria related symptoms. SMP used two types of individuals to collect data on the quality of the client-provider interaction. The first type of individual included a trained research assistant who observed client-provider interactions with a real client. SMP recruited research assistants who had a medical background for these observations. The second set of individual included a mystery client, or a trained individual who acted and presented him/herself as a client to the provider. The guide had the following sections (See Attachments) Observation of ANC process Observation of consultation involving children suspected of having malaria Diagnosis and treatment of childhood malaria Exit Interview questionnaire: The exit interview questionnaire was used to assess the level of satisfaction and overall experience of clients with provided services. This questionnaire was administered at the end of the client s visit. Administration of this questionnaire did not last more than one hour. The Health provider selection worksheets: The study also included a listing worksheet for selection of health providers at the health facility. The lists included only the first name and last initial of the potential respondent and were destroyed once all individuals had been interviewed. Two separate lists were generated. The first included ANC workers at the facility on the day of the facility visit and the second, health providers in the OPD clinic that day. One ANC and one OPD health worker from each facility were selected. The facility manager or their designee was responsible for assisting the team in listing the providers. 1.4.4. Quality assurance procedures Supervision and guidance to the field teams was provided by team leaders, quality controllers and the study coordinator. They ensured a regular progress of data collection in all the study districts. The following quality control procedures were put in place to ensure the collection of high quality data: 17

1.4.5. Field Interviewer Training Training of interviewers, which was conducted at the Kati-Kati hotel in Kampala, consisted of a combination of classroom training and practical experience. Before each training session, interviewers were required to study their manual carefully along with the questionnaire. Interviewers were also given the opportunity to ask questions at any time to avoid mistakes during field work. Additionally, each interviewer was given a copy of the Questionnaire and the Interviewer s Training Manual for easy reference and guidance during field work. During the training, the questionnaire sections, questions, and instructions were discussed in detail. Interviewers participated in demonstration interviews that were conducted in front of the class as examples of the interviewing process. They practiced reading the questionnaire to each other several times. They also participated in role playing in which they practiced by interviewing another trainee. After interviewer training, additional specialized training was provided on the specific duties of appointed supervisors and quality controllers. This ensured that all teams followed a uniform set of procedures and also it enabled the supervisors and quality controllers to learn - how to check the fieldwork and edit completed questionnaires. 1.4.6. Data Processing and Analysis The design of data entry screens started shortly after the questionnaire review process. The microsoft. Visual FoxPro software was used to develop data entry screens and this was fitted with the range and consistency checks. Data entry clerks were selected from among the trainees who participated in the field interviewer training. Because they had participated in the interviewer s training, they were very familiar with the household questionnaire which made it easier for them to enter data quickly and with minimal data entry errors. Data analysis was then performed using Stata 11 (StataCorp 2009) software which was used to manage the dataset by running consistency checks, clean the data. Ms. Excel was also used to produce graphs for visual display in the HFA report. 18

Percent (%) of interviews Number of interviews 2. CHARACTERISTICS OF CLIENTS 2.1. Introduction This chapter assesses responses from clients captured using the exit interview questionnaire. This questionnaire; which was administered at the end of the client s visit was used to assess the level of satisfaction and overall experience of clients with provided services. In total, 1,104 clients found at health facilities were interviewed. As shown in the Figure 1 below, more than a third of the clients were from HC IIIs (36%), followed by HC IVs with 29 percent, HC IIs contributed 23 percent and only 13 percent of the clients were got from hospitals. 40 Distribution of Exit Clients by type of facility, N=1,104 36% 500 30 29% 400 20 13% 23% 300 200 10 100 0 Hospital HC IV HC III HC II 0 Fig. 2.1 Distribution of exit clients by type of facility 2.2. Age and Sex of the Clients Table 2.1 shows distribution of clients by background characteristics. The age distribution of clients was categorized into 5 year age groups generated from the questions on age (in complete years) and gender of the respondent categorized into male or female. As seen from the table, more than 9 in 10 (93%) clients interviewed were female due to the high health seeking behaviour of females relative to males. More than half (59%) of the clients were females in the age range of 20 to 30 years. A few clients were under 15 years (0.5%) and over 50 years of age (2%). Hence, in most of the analyses in this report, we concentrated on the age range 15 49 years to avoid the problem with small numbers. 19

Table 2.1: Background characteristics of clients interviewed. Percent of Percent of Number Background Characteristics women all respondents Overall 93.2 100.0 1104 Age i (years) < 15 0.4 0.5 6 15-19 8.3 9.0 99 20-24 27.8 27.6 305 25-29 31.5 30.0 331 30-34 19.7 19.2 212 35-39 6.3 6.3 70 40-44 1.0 1.4 15 45-49 1.0 1.0 11 50+ 2.2 2.2 24 Missing 1.9 2.8 31 Education ii None 5.1 5.3 59 Primary 55.3 54.3 599 Secondary+ 25.0 24.8 274 Missing 14.6 15.6 172 Region Central 72.3 71.5 789 East 13.7 14.2 157 West 13.9 14.3 158 Note: Education: refers to highest level of education attained, The Eastern region is also referred to Teso region and the West is referred to as Hoima region. 2.2. Residence of Respondents Table 2.1 also shows the distribution of clients categorized into three SMP geographical areas of operation; Central, East also referred to Teso region and the West referred to as Hoima. To obtain the geographical distribution, we sub-divided the districts into 3 clusters as follows: (i) Central region: Buikwe, Bukomansimbi, Butambala, Buvuma, Gomba, Kalungu, Kayunga, Kiboga, Kyankwanzi, Luweero, Lwengo, Masaka, Mityana, Mpigi, Mubende, Mukono, Nakaseke, Nakasongola, Rakai, Sembabule, and Wakiso (ii) Hoima region: Buliisa, Hoima, Kibaale, Kiryandongo, and Masindi and (iii) Teso region: Amuria, Bukedea, Kaberamaido, Katakwi, Kumi, Ngora, Serere and Soroti. 20

Results indicate that most of the respondents were from the central region with 72% of the respondents. This was followed by respondents from Hoima and Teso regions each contributing 14 percent of the clients. Owing the fact that majority of respondents in the sample were female, the distribution of female clients by region and gender is not different from the overall sample distribution (See table 2.1). 2.3. Education attainment Education affects many aspects of life including health behaviour for individual and the people they care for. Studies have also shown that educated people are more likely to be knowledgeable and practice preventative behaviour against killer diseases such as malaria. In the HFA survey, data was collected on the highest level of education attained by clients and categorized at analysis into three: No education, Primary and Secondary and above. As shown in table 2.1 above, 5 percent of clients attained no education at all, 54 percent of the participants attained primary education and 24 percent) attained secondary education or higher. Uncategorized responses on highest level of education attained, shown in table 2.2, were used establish differences in education attained by age group and region of residence. In Figure 2.2, the highest level of education attained is represented graphically by health facility where 1=None, 2=Some Primary, 3=Completed Primary, 4=O level, 5=A level and 6=University/Tertially. The median education level attained was primary and this was similar across the four types of health facilities that contributed the clients being assessed. 21

1 2 3 4 5 6 Highest Level of Education Attained, by Health Facility Hospital HC IV HC III HC II Fig 2.1: Highest level of education attained, by health facility. Generally, the overall education levels in the sample were low. Participants from the central were more likely to be educated with 6.8 percent reporting that they completed secondary level or above compared to their counterparts from the West (3.2%) and East (1%). Table 2.2: Uncategorized highest education level attained by characteristics of clients interviewed. Background Characteristics Highest level of schooling Number None Some Completed Some Completed More Number Primary Primary Secondary Secondary than Secondary Overall 17.7 42.9 13.1 19.7 5.4 1.2 1104 Age(years) 15-19 7.4 43.2 13.7 32.6 3.2 0.0 99 20-24 16.7 39.9 13.7 24.2 4.4 1.0 305 25-29 16.7 42.7 14.9 18.0 6.2 1.6 331 30-34 22.4 37.8 11.9 18.9 7.0 2.0 212 35-39 16.4 58.2 10.5 6.0 9.0 0.0 70 40-44 20.0 53.3 13.3 13.3 0.0 0.0 15 45-49 27.3 72.7 0.0 0.0 0.0 0.0 11 Region Central 14.8 42.0 13.6 21.5 6.8 1.4 789 East 20.4 56.3 8.5 12.7 0.7 1.4 157 West 28.9 35.3 14.7 18.0 3.2 0.0 158 22

Percent (%) of Clients Notes: 61 respondents outside the 15-49 age range were not grouped 2.4. Exposure to mass media Exposure to mass media is essential in increasing people s knowledge about health and their communication about health issues, which eventually affects their perceptions and health behaviours. In the HFA survey, exposure to media was assessed by asking clients who had visited the health facilities how often they read a newspaper or magazine, listen to radio or watch television. The possible responses to media exposure were: almost every day, at least once a week, less than once a week, and not at all. Table 2.3 and figure 2.2 below summarize percentages of clients who mentioned that they were exposed to the three media sources at least once a week by background characteristics. 100 Respondents who Listen to Radio, Watch TV or Read Newspaper atleast once a week by Age group, N=1,104 92 90 89 95 91 86 91 91 80 60 40 20 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 All Age group Fig 2.2: Proportions, by age group, exposed to three the sources at least once in a week As seen in table 2.3, the radio, by far, is the most popular media source with close to 9 in 10 clients (88%) reporting listening in at least once in a week. Although listenorship to radio was above 82 percent across all age groups, it was lower in the older clients at 86 percent and 82 percent among those aged 40-44 and 45-49 years respectively. The radio was followed by readership of newspapers or magazine with 28 percent. Clients in the 45-49 year age group were more likely to read a newspaper atleast one a week with 36 percent, followed by those aged 25-29 and 30-34 years each with 31 percent. Lastly, TV watching at least once in a week 23

Percent (%) of clients was reported by 26 percent. Participants in the 45-49 year age group were more likely to watch TV atleast once a week (36 percent) followed by those aged 25-29 years (30 percent) and 30-34 years (28 percent). Generally, slightly over 9 in 10 (91%) clients reported exposure to at least one of the three media sources at least once in a week. By education status, higher levels of education increased one s chances of exposure to any of the three media source. Also, clients from health facilities in the Central region were more likely to be exposed (94%) media sources, followed by those from the West (88%) and then the East with 81 percent. 100 Percent of clients that were exposed to the media sources atleast once in a week 88 91 80 60 40 28 26 20 0 Radio Newspapers TV One of the 3 Fig 2.3: Overall proportions exposed to radio, TV and Newspapers at least once in a week 24

Table 2.3: Percentage of respondents who were exposed to specific media on a weekly basis, by background characteristics. Listens to radio at least once a week Reads a newspaper or magazine Watches TV at least once a week One of the three at least once a week Number Background Characteristics at least once a week Overall 87.8 27.9 26.3 90.8 1104 Gender Male 88.1 33.3 19.7 92.5 76 Female 87.5 30.0 26.5 90.5 1028 Age iii (years) 15-19 89.9 29.5 24.7 91.9 99 20-24 86.6 22.8 23.1 90.1 305 25-29 87.2 30.9 30.1 89.4 331 30-34 90.0 30.5 28.2 94.8 212 35-39 87.1 25.4 26.1 91.4 70 40-44 85.7 23.1 7.1 80.0 15 45-49 81.8 36.4 36.4 90.9 11 Education iv None 69.5 42.9 17.0 74.6 59 Primary 86.9 19.7 22.2 90.7 599 Secondary+ 94.5 44.6 39.9 96.4 274 Region Central 91.6 30.2 30.1 93.5 789 East 73.7 20.2 17.5 80.8 157 West 83.5 22.5 16.7 88.0 158 25

3. KNOWLEDGE OF MALARIA, AND MANAGEMENT OF FEVER IN PREGNANT WOMEN AND CHILDREN 3.1. Knowledge of Malaria 3.1.1. Knowledge of Causes of Malaria Public health research has showed that knowledge and exposure to malaria messages is paramount to the effectiveness of malaria interventions. In the HFA survey, respondents knowledge on the causes of malaria was ascertained by asking them how malaria spreads and all answers were recorded. As shown in table 3.1, approximately three-fourths (74%) of all respondents were aware that malaria is spread through mosquito bites. About one third (33%) of clients wrongly thought that malaria is spread by drinking unboiled water, 12 percent and 7 percent thought that it is spread by eating mangoes and maize respectively. The distribution of knowledge on spread of malaria by background characteristics of clients can be seen from the table 3.1 below. Table 3.1: Percent distribution of knowledge of causes of malaria Background Characteristic Mosquitoes Drinking unboiled water Eating Maize Eating mangoes Eating mixed food during harvest Bathing in cold water Other Does not Know any Number Overall 74.0 33.4 7.4 12.3 2.9 2.1 4.5 1.8 767 Gender Male 75.0 41.7 6.3 20.8 2.1 0.0 4.3 2.1 53 Female 73.7 33.9 8.2 12.4 3.3 2.2 4.7 2.0 714 Age (years) 15-19 70.8 29.9 1.5 9.1 0.0 6.1 1.6 6.0 73 20-24 79.1 28.7 4.2 8.4 0.9 0.5 3.9 1.9 224 25-29 69.7 37.3 10.0 15.7 4.8 2.6 6.4 0.9 243 30-34 75.6 36.1 11.7 13.6 2.6 1.3 2.8 1.3 156 35-39 76.7 38.2 0.0 14.6 3.6 3.6 2.0 1.8 51 40-44 80.0 30.8 23.1 7.7 7.7 0.0 0.0 0.0 11 45-49 55.6 0.0 12.5 12.5 0.0 0.0 25.0 12.5 8 Education None 85.0 20.0 5.0 7.5 0.0 2.5 4.9 2.5 49 Primary 75.5 32.2 8.0 11.9 2.1 1.4 5.7 2.6 493 Secondary+ 72.9 38.2 4.3 11.4 3.2 3.2 1.1 0.5 225 Region Central 71.7 36.3 9.5 13.9 3.0 2.4 6.3 1.2 548 East 88.8 12.1 0.9 1.7 0.0 2.6 0.9 1.7 109 West 71.8 40.3 5.4 14.9 4.7 0.7 1.4 4.1 110 26

Several districts including Bukomansimbi, Buvuma, Kalungu, Masaka, Nakaseke, Nakasongola, Bukedea, Kaberamaido had all respondents correctly mentioning mosquitoes as the cause for malaria. On the contrary, high proportions from Buvuma, Gomba, Kiboga, Kyankwanzi and Luweero, Mukono Buliisa and Kibaale mentioned other causes not mosquitoes as can be seen from the table below. Table 3.2: Knowledge of causes of Malaria District Mosquitoes Drinking unboiled water Eating Maize Eating mangoes Eating mixed food during harvest Bathing in cold water Other Does not Know any Overall, n=767 74.0 33.4 7.4 12.3 2.9 2.1 4.5 1.8 Central Region BUIKWE 93.5 19.4 3.2 16.1 3.2 6.5 6.5 0.0 BUKOMANSIMBI 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 BUTAMBALA 95.0 0.0 0.0 42.9 0.0 0.0 0.0 0.0 BUVUMA 100.0 42.9 14.3 28.6 0.0 0.0 0.0 0.0 GOMBA 66.7 27.8 27.8 38.9 0.0 0.0 0.0 0.0 KALUNGU 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 KAYUNGA 83.3 11.8 5.9 11.8 0.0 11.8 5.9 0.0 KIBOGA 66.7 57.1 4.8 19.0 0.0 0.0 22.2 4.8 KYANKWANZI 57.9 36.8 10.5 26.3 5.3 5.3 16.7 5.3 LUWEERO 32.8 74.2 11.5 6.7 10.0 1.6 0.0 0.0 LWENGO 88.2 20.0 11.1 0.0 0.0 0.0 0.0 0.0 MASAKA 96.6 50.0 4.8 9.1 0.0 0.0 0.0 0.0 MITYANA 73.1 37.0 7.4 23.1 0.0 0.0 0.0 0.0 MPIGI 68.8 24.0 20.0 20.0 0.0 0.0 4.0 0.0 MUBENDE 73.3 11.1 0.0 0.0 2.2 2.2 18.6 2.2 MUKONO 44.7 48.7 7.7 10.3 2.6 5.3 5.1 2.6 NAKASEKE 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 NAKASONGOLA 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 RAKAI 81.5 15.7 7.8 5.9 0.0 0.0 14.3 0.0 SEMBABULE 90.0 25.0 0.0 5.0 0.0 0.0 5.0 0.0 WAKISO 62.9 43.5 16.5 20.0 5.9 3.5 1.2 2.4 Sub total 71.7 36.3 9.5 13.9 3.0 2.4 6.3 1.2 Teso Region AMURIA 90.9 18.2 0.0 0.0 0.0 9.1 0.0 0.0 BUKEDEA 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 KABERAMAIDO 100.0 23.1 0.0 0.0 0.0 0.0 7.7 0.0 KATAKWI 90.9 13.6 0.0 0.0 0.0 4.5 0.0 0.0 KUMI 72.7 9.1 0.0 9.1 0.0 0.0 0.0 0.0 NGORA 80.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 SERERE 92.0 8.0 0.0 4.0 0.0 4.0 0.0 0.0 SOROTI 84.2 15.8 5.3 0.0 0.0 0.0 0.0 10.5 Sub total 88.8 12.1 0.9 1.7 0.0 2.6 0.9 1.7 Hoima Region 27

BULIISA 37.5 50.0 0.0 25.0 12.5 0.0 14.3 0.0 HOIMA 76.3 23.7 13.6 13.6 6.8 0.0 0.0 6.8 KIBAALE 64.9 56.1 0.0 14.0 1.8 0.0 0.0 3.5 KIRYANDONGO 81.8 36.4 0.0 9.1 9.1 10.0 9.1 0.0 MASINDI 92.9 42.9 0.0 23.1 0.0 0.0 0.0 0.0 Sub total 71.8 40.3 5.4 14.9 4.7 0.7 1.4 4.1 3.1.2. Exposure to Malaria Treatment Messages In the HFA, exposure to malaria treatment messages was ascertained by asking clients if they had heard of any malaria prevention and treatment messages. As shown in table 3.2, about 86 percent of all clients reported that they had been exposed to malaria treatment messages. The radio and health providers (nurse, doctors etc.) were cited by majority of the clients with 59 percent and 54 percent respectively. These were followed by community leaders (22%), health assistants or community health workers (21%), family or friends (7%) and other sources such as phone messages, TV and posters with 5 percent. Exposure to malaria treatment messages increased with high levels of education. As shown in table 3.2, clients with no education that were exposed to these messages were 64 percent, followed by those at primary level with 84 percent and those with secondary levels or above with 93 percent. Also, clients from the Western (90%) and the Eastern (88%) regions were more likely to be exposed to malaria treatment messages than their counterparts from the central region (83%). For distribution of exposure to malaria treatment messages by other background information, please refer to the table 3.2. Table 3.3: Percent distribution of exposure to malaria messages Background Characteristic Percent exposed to malaria treatment messages Overall Number Radio Health Provider (Nurse, Doctor etc) Health Assistant / Community health worker Community leader Family or Friends Other Number Exposed Overall 85.5 728 59.2 53.5 21.3 22.3 7.0 4.6 623 Gender Male 86.3 50 61.5 50.0 23.7 15.8 10.8 0.0 43 Female 85.5 678 59.0 53.7 21.1 22.8 6.8 5.0 579 Age (years) 15-19 78.7 69 53.1 57.7 16.3 22.9 6.1 4.0 54 20-24 82.0 213 62.5 47.5 16.1 19.8 4.3 3.6 174 25-29 87.0 231 58.4 53.6 23.8 21.5 8.2 5.7 201 30-34 94.1 148 60.1 58.7 25.4 22.1 7.8 4.4 139 28

35-39 86.3 49 60.0 50.0 21.7 29.6 7.1 6.7 42 40-44 84.6 10 63.6 45.5 16.7 18.2 0.0 0.0 9 45-49 75.0 8 66.7 50.0 0.0 16.7 0.0 0.0 6 Education None 64.3 46 51.7 48.3 24.1 14.3 7.4 17.9 30 Primary 84.4 468 60.6 50.5 18.1 21.4 3.3 2.6 395 Secondary+ 92.9 214 62.0 56.8 28.7 2.7 7.6 7.9 199 Region Central 83.4 520 58.8 49.6 20.7 24.0 3.8 4.3 434 East 88.5 104 57.6 50.0 11.3 11.5 1.0 6.1 92 West 89.7 104 62.4 66.7 29.6 23.0 17.2 3.7 93 Note: Percentages may add to more than 100.0 due to multiple responses 3.1.3. Knowledge of ways to avoid Malaria The best ways to avoid getting malaria is by taking precautionary measures to eliminate mosquitoes from areas around the home. In order to assess knowledge of clients on the ways to protect themselves or their family members from catching malaria, each client was asked for their opinion and all responses were recorded. The responses given are summarized in table 3.3 below. Overall knowledge of at least one way to avoid malaria was universal (97%) in the sample. Sleeping under a mosquito net received the most responses (89%), followed by clearing bushes around the house (26%), use of insect repellents and anti-mosquito coils with 22 percent and getting rid of stagnant water with 20 percent. The clients region of residence and highest education level attained did not cause differences in knowledge of ways to avoid malaria. However, older clients between 40 to 49 years were more likely to be knowledgeable than their younger counterparts. For distribution of knowledge by other background characteristics, please refer to table 3.3 below. Table 3.4: Percent distribution of knowledge of ways to avoid malaria Background Percent who Use Clear Use insect Get rid Spray Use Use Other Number Characteristic mention atleast one way to avoid malaria Mosquito nets bushes around the house repellent/antimosquito coils of stagnant water house periodically aerosol insect killer mosquito screens in the house ways Overall 97.1 89.2 26.1 21.8 19.8 4.7 2.7 2.1 4.9 867 Gender Male 98.3 85.2 33.3 16.0 16.7 6.3 4.1 4.2 10.4 59 Female 97.1 89.4 26.5 22.2 20.3 4.1 2.7 1.7 4.7 808 Age (years) 29