Study setting and design
This was a cross sectional study carried out in selected public and private not for profit HCFs in the GKMA from January to March 2019. The GKMA includes the districts of Kampala, Wakiso and Mukono whose HCFs serve over 14% of Uganda’s population (7). In this study, we considered HCFs at level III or above since these have a core mandate to deliver Maternal, New-born and Child Health (MNCH) services. The study was restricted to public and private not for profit HCFs because these offer affordable MNCH services to majority of the population in the GKMA. In Uganda, the health care system is organised into a four-tier system (i.e., hospitals, health centres of levels IV, III and II) (8). Level II HCs have a catchment population of about 5,000 people and only provide outpatient care and community outreach services. Level III HCs with a catchment population of about 20,000 people provide basic preventive, promotive, laboratory and curative services. They have limited inpatient capacity mainly maternity and general patient wards. Level IV HCs (catchment population 100,000) provide outpatient and inpatient services, maternity, children and adults’ wards, laboratory and blood transfusion services as well as an operating theatre. General hospitals (catchment population 500,000) provide preventive, promotive, curative, maternity, and inpatient health services and surgery, blood transfusion, laboratory, and medical imaging services. In this study, we considered HCFs at level of HCIII or above since these have a core mandate to deliver MNCH services.
Sample Size And Sampling Procedure
We sampled 60 out of 105 HCFs in the GKMA. This proportion was considered representative enough as per the criteria described by Ramsey and Hewitt (9). In the sampling, we included all public hospitals and HC IVs since these provide MNCH services to majority of the population. High volume private not for profit (PNFP) hospitals and HC IVs were also purposively selected. Purposive selection was done for public and PNFP HC IIIs with large catchment population.
Data Collection And Measurement Of Study Variables
Data collection was conducted using the validated WASH Conditions (WASHCon) tool on the Commcare mobile data collection platform. The tool, developed by the Centre for Global Safe Water, Sanitation, and Hygiene (CGSW) at Emory University has been used to evaluate WASH conditions within HCFs in low- and middle-income countries including Uganda (10). The WASHCon tool relies on data collected through surveys, observational checklists and water quality testing. Data collection was done using mobile devices. The data was then uploaded into pre-programmed dashboards via a cellular or wireless internet network (not required during data collection). The WASHCon tool has been previously used in a number of studies (11, 12)
For this study, the outcome of the WASHCon tool was WASH status which was categorized as basic, limited or unimproved/no service similar to the JMP WASH service ladders (10). Based on WASHCon indicators, WASH status is a composite variable generated from five variables (water supply status, sanitation status, environmental cleanliness, hand hygiene status and waste management status). In order to establish the water supply status, data was collected on source and accessibility, quantity and quality of water. Sanitation status was assessed by collecting data on accessibility to toilet facilities, quantity of toilets and existence of the infrastructure, while for hand hygiene data was collected on availability of hand hygiene services and availability of associated supplies. Assessment of the status of environmental cleanliness was based on availability of cleaning supplies, cleaning practices and frequency, and facility hygiene. In order to establish the status of healthcare waste management, data was collected on segregation, treatment and disposal of healthcare waste. These five constituent variables were also independently categorized as basic, limited or unimproved/no service. The independent variables included ownership and level of HCF.
Using the WASHCon dashboard, evaluation scores were calculated on a scale of 1–3 for each of the WASH domains, as well as an overall score that is an average of all the domains. The scores were determined based on the responses to the survey questions, observation checklists, and water quality testing results (appendix 1). These scores were further categorized into basic, limited or improved/ no service. HCFs that scored between 2.8 to 3.0 were classified as basic, and were considered to meet the minimum WASH in HCF requirements or were on track to meet them; HCFs that scored between 1.9 to 2.7 were classified as limited, and were considered to have made some progress towards meeting minimum WASH in HCFs but were not on track to meet them; while HCFs that scored between 1.0 to 1.8 were classified as having no service or unimproved. Such facilities were considered to have made little or no progress towards achieving the minimum WASH in HCFs requirements (10) (Table 1)
Table 1
Definitions of WASH status indicators (domains)
Domains (Indicators) | Service level |
Basic | Limited | Unimproved / No Service |
Water supply in HCFs | Water from an improved source is available on premises | Water from an improved source is available off premises; or an improved source is onsite, but no water is available | Unprotected dug well or spring, surface water, or no water source |
Sanitation in HCFs | Improved facilities are usable, separated for patients and staff, separated for women, provide menstrual hygiene facilities, and meet the needs of people with limited mobility | Improved sanitation facilities are present but are not usable or do not meet the needs of specific groups (staff, women, people with limited mobility) | Pit latrines without a slab or platform, hanging latrines, or no toilets or latrines at the facility |
Hand hygiene in HCFs | Hand hygiene materials, either a basin with water and soap or alcohol hand rub, are available at points of care and toilet | Hand hygiene station at either point of care or toilets, but not both | Hand hygiene stations are absent, or present but with no soap or water |
Healthcare waste status in HCFs | Waste is safely segregated into at least 3 bins in the consultation area, and sharps and infectious waste are safely treated and disposed of | Waste is segregated but not disposed of safely, or bins are in place but not used effectively | Waste is not segregated or safely treated and disposed of |
Adapted from the JMP service ladders for monitoring WASH in HCF in the SDGs
Quality control
Prior to data collection, study enumerators received training on the use of the WASHCon tool, quality control and research ethics. The observations and interviews were conducted by trained enumerators who had a minimum of a Bachelor’s degree in Environmental Health Science; Nursing; or Social Sciences. All the study enumerators were supervised to ensure quality control.
Water Quality Assessment
In order to determine the water supply status of HCFs, microbial water quality tests were conducted. At each HCF, observations were done to establish the type of water source and availability of water. Observations were followed by collection of duplicate water samples from the maternity ward. Maternity wards were prioritised due to an elevated risk of transmission of HAIs compared to other patient care areas (13). Water samples were collected using Whirl-Pak bags of 100 mls (with sodium thiosulfate to halt chlorine action in chlorinated supplies) and stored on ice until laboratory analysis. All samples were analysed within four hours from the time of collection. Water was tested for faecal coliform, i.e. E. coli using the membrane filtration method (14). Chromocult agar was used for culturing E-Coli at 37 °C for 24 hours. Colonies of E-coli (i.e. dark blue to violet in colour) were counted and results recorded per 100 ml of sample.
Data Management And Analysis
The data obtained using the WASHCon Commcare app, preinstalled on a mobile device were uploaded onto a server managed by Makerere University School of Public Health and Emory University CGSW. Forms were synchronized daily by each enumerator. The investigators had access to preliminary results through a pre-programmed dashboard.
Analysis was performed using Stata version 14 (StataCorp, Texas) and R 3.5.2. Descriptive statistics such as frequencies and proportions were used to summarize quantitative categorical data. Continuous data was expressed as means and standard deviations. Classification of WASH status and its five domains into basic, limited and unimproved/no service was guided by the scoring tool shown in appendix 1. Fishers exact tests were used to establish any statistically significant difference in WASH status based on ownership and level of HCF. Fishers exact test was preferred over chi-square tests due to low expected counts in some categories.