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Background: Young people aged 10-24 years are a vulnerable group with poor health service access relative to other populations. Recent South African initiatives, the She Conquers campaign, the Integrated School Health Policy and the Adolescent & Youth Health Policy, include a focus on improving the breadth and quality of youth-friendly health service delivery. However, in some settings the provision and impact of scaled-up youth friendly health services has been limited indicating a gap between policy and implementation. In this study we reviewed existing sources of data on health service utilisation to answer the following question: ‘What health conditions do young people present with and what services do they receive at public health clinics, mobile clinics and school health services?’ Methods: We conducted a retrospective register review in three purposively selected primary healthcare clinics (PHCC), one mobile clinic, and one school health team in Hlabisa and Mtubatuba sub-districts of uMkhanyakude District, KwaZulu-Natal, South Africa. The focus was service utilisation for any reason by 10-24 year olds. We also conducted descriptive analysis of pre-existing data on service utilisation by young people available from the District Health Information System for all 17 PHCC in the study sub-districts. Results: Three quarters of 4121 recorded young person visits in the register review were by females, and 40% of all young person visits were by females aged 20-24 years. The most common presenting conditions were HIV-related, antenatal care, family planning, general non-specific complaints and respiratory problems (excluding TB). There were relatively few recorded consultations for other common conditions affecting young people such as mental health and nutritional problems. Antibiotics, antiretrovirals, contraceptives, vitamins/supplements, and analgesics were most commonly provided. Routine health registers recorded limited information, were often incomplete and/or inconsistent, and age was not routinely recorded. Conclusions: Measuring morbidity and service provision are fundamental to informing policy and promoting responsive health systems. Efforts should be intensified to improve the quality and completeness of health registers, with attention to the documentation of important, and currently poorly documented, young people’s health issues such as mental health and nutrition.
In 2017, the mixed methods ‘Health Services for Young People’ study was conducted in uMkhanyakude, one of the poorest districts in KwaZulu-Natal [13]. The district has high unemployment and low literacy rates, limited access to piped water and electricity, and poor road infrastructure [14]. In 2012, the provincial HIV prevalence in KwaZulu-Natal was estimated to be the highest in the country at 16.9% [15]. PHCC provide a comprehensive package of health care services, however, a focus on HIV services in more recent years has meant that other essential primary health care services such as non-communicable diseases, maternal health, nutrition and health promotion have been less well implemented. The provision of mental health, oral and eye health and rehabilitation is especially limited [16]. We report here on the quantitative component of the study. The qualitative component of the study has been reported elsewhere [17]. Quantitative data collection and analysis was made-up of two parts: We reviewed paper registers in three purposively selected PHCC, one mobile clinic, and one school health team in Hlabisa and Mtubatuba sub-districts of uMkhanyakude to assess clinic attendance for any reason by males and females aged 10–24 years. During the register review, trained study nurses extracted relevant data from each clinic’s paper registers and entered the data into pre-programmed REDCap forms on tablets. Study nurses were encouraged to record the completeness and consistency of the data within each register. Hlabisa and Mtubatuba sub-districts have a total of 17 PHCC: three urban, three semi-urban and eleven rural. The study clinics were selected from those with whom the Africa Health Research Institute (AHRI) Population Intervention Programme (PIP) already had established regular collaboration [18, 19]. Clinics were purposively selected to be broadly representative of the medium and small semi-urban and rural clinics in the study area. Clinic 1 was a medium semi-urban clinic; clinic 2 was a medium rural clinic; and clinic 3 was a small rural clinic. One of the two mobile clinic teams operational in Mtubatuba sub-district was purposively selected to participate in the register review, as was one of the two sub-district school health teams. In each study clinic, two study nurses aimed to review the following main registers (Table (Table11): Registers and data sources reviewed Daily clinic ‘pink’ registers (May 15, July 15, Sep 15, Nov 15, Jan 16 , Mar 16) PHCC comprehensive tick register (May-Sept 16) Integrated School Health Programme Daily Register (Jul 15, Sep 15, Nov 15, Jan 16, Mar 16, May 16) District Health Information System (May-Sep 16) Registers used by clinic staff to record the age, gender of the clients, the presenting condition, and the treatment given. The daily clinic register review took place between January and March 2017 with registers reviewed for 6 months of a one-year period (May 2015, July 2015, September 2015, November 2015, January 2016, March 2016). This was the most recent period prior to the April 2016 replacement of the daily clinic registers with the PHCC comprehensive tick register. Daily clinic register review in clinic 1 was not possible as the daily clinic registers had been moved to the district hospital (Hlabisa) for filing. Following piloting, the study nurses reviewed the conditions being recorded and grouped them into 38 categories. Similarly, 33 categories were created for treatment and services provided (Additional file 1: Table S1). Since April 2016, these registers have been used to record attendances for select conditions and treatments. Tick register data were extracted over 4 days between February and April 2017 for the months May–September 2016. Age was not recorded on these registers so to estimate the attendance of YP, study nurses extracted data where one of the following was ticked: Family planning acceptor < 18 years, Diabetes client < 18 years new, Mental health client < 18 years, Td dose at 12 years, ANC 1st visit < 18 yrs. Other disease or service specific registers that were present in the clinics such as TB, ART and delivery registers were not consulted. The school health team (SHT) comprises two nurses who provide periodic services at schools. They conduct screening of learners in grade 8 (approximately aged 14 years) and grade 10 (approximately aged 16 years) and provide advice, treatment (primarily analgesics) and referrals for screened students and for other learners who present to the nurses. The SHT had their own register to record the occurrence of health screenings and immunizations. Multiple conditions and/or treatments could be ticked. The school health register recorded the gender of the learner, the reason for seeing the nurse and the treatment given. Age was not recorded. Study nurses extracted data where the register indicated that the learner received one of the following services delivered to learners in our target age range: grade 8 screening, grade 10 screening and tetanus vaccination at age 12. The school health registers were reviewed for: July 2015, September 2015, November 2015, January 2016, March 2016, May 2016. During these months the school health team provided services in 7 schools. In order to get a better understanding of whether the patterns of health service utilisation observed in our three study clinics were broadly representative of utilisation patterns observed across the district, we conducted secondary analysis of data from one additional source (Table Table11). We analysed District Health Information System (DHIS) adolescent health indicators for the 17 PHCC in Mtubatuba and Hlabisa sub-districts for the period May 2016–September 2016. The DHIS database did not contain detailed information on treatment and services provided according to age and gender. PHCC-level DHIS data was a summary of the comprehensive tick register data that PHCC submitted monthly to the district. At each PHCC a weekly tally sheet was available for collating daily/weekly totals and a monthly summary sheet was used for submission to the sub-district/district [20]. We analysed routine health facility and school health data to describe the health conditions that young people presented with and the services that they received. The data were described according to age group, gender, and clinic. In bivariate analysis, chi-squared tests were used to compare the observed proportions against the null hypothesis of equal distribution of outcomes across categories e.g. equal number of clinic attendances by males and females. Comprehensive tick register data and DHIS data were compared to assess internal consistency. For each of the target months, we reviewed the comprehensive tick registers and manually counted up the number of ticks each month each of the target adolescent health indicators. We then compared this tick register monthly total to the monthly total as recorded in the DHIS.
