DOI: 10.1111/1471-0528.12997 www.bjog.org Review article Experiences with perinatal death reviews in South Africa the Perinatal Problem Identification Programme: scaling up from programme to province to country NR Rhoda, a D Greenfield, b M Muller, c R Prinsloo, d RC Pattinson, d S Kauchali, a K Kerber e a RMCH Project-Futures Group, University of Cape Town and DFID, Cape Town, South Africa b Neonatal Department, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa c Middelburg Hospital, Mpumalanga Province, South Africa d SA MRC Maternal and Infant Health Care Strategies Unit, Department of Obstetrics and Gynaecology, University of Pretoria, Pretoria, South Africa e Save the Children and School of Public Health, University of the Western Cape, South Africa Correspondence: NR Rhoda, Private Bag X1, Suite 144, Menlo Park 0081, South Africa. Email NRhoda@futuresgroup.com Accepted 27 May 2014. The Perinatal Problem Identification Programme (PPIP) was designed and developed in South Africa as a facility audit tool for perinatal deaths. It has been used by only a few hospitals since the late 1990s, but since the country s commitment to achieve Millennium Development Goal 4 the use of PPIP is now mandatory for all facilities delivering pregnant mothers and caring for newborns. To date 588 sites, representing 73% of the deliveries captured by the District Health Information System for South Africa, provide data to the national database at the Medical Research Council Unit for Maternal and Infant Health Care Strategies in Pretoria. Keywords Neonatal deaths, perinatal audit, perinatal deaths, perinatal review, stillbirths. Please cite this paper as: Rhoda NR, Greenfield D, Muller M, Prinsloo R, Pattinson B, Kauchali S, Kerber K. Experiences with perinatal death reviews in South Africa the Perinatal Problem Identification Programme: scaling up from programme to province to country. BJOG 2014; 121 (Suppl. 4): 160 166. Introduction In South Africa, neonatal deaths account for 30% of the mortality in children under 5 years. 1 In the World Health Organization/United Nations Children s Fund 2012 report Countdown to 2015 South Africa was one of 13 countries globally that had made little progress towards Millennium Development Goal (MDG) 4 since 1990. The country s annual rate of reduction for under-5 mortality was 1.4% between 1990 and 2012. 1 Although progress has increased rapidly over the past 5 years, 2 the decline comes from reducing deaths after the neonatal period. However, the mortality rate in the first month of life remains stagnant according to the most recent Rapid Mortality Surveillance Report. Campaigns such the Campaign for Accelerated Reduction in Maternal, Child and Neonatal Mortality and Morbidity and national initiatives such as the Strategic Plan (2012 16) for Maternal, Newborn Child and Women s Health and Nutrition 3 have concentrated on improving the quality of care for mothers and babies and show the government s commitment to achieving MDG4 and MDG5. Having access to reliable data around the numbers and causes of death is essential for programme planning and monitoring. South Africa s Perinatal Problem Identification Programme (PPIP) is central to tracking and measuring progress through in-depth investigation of the causes and circumstances surrounding deaths occurring at public health facilities. 4 Developed and designed by Dr Johan Coetzee upon request by the Medical Research Council (MRC) Pretoria in the early 1990s, PPIP was primarily developed as a facility-based audit tool to improve quality of care to mothers and babies. The South African public health system at the time was deeply fragmented and segregated and a comprehensive database, centrally managed, was required to address the high mortality of women and babies. PPIP facilitates the collection and analysis of data from maternity and neonatal wards. It does not routinely record information on the neonatal deaths that occur in 160 ª 2014 Royal College of Obstetricians and Gynaecologists
Experiences with perinatal death reviews in RSA the children s wards. Neonatal deaths that occur in children s wards are captured by the Child Health Problem Identification Program (Child PIP), with some provinces linking the two systems. In the early years of PPIP implementation, only two provinces Mpumalanga and the Western Cape made the use of PPIP mandatory at public health facilities. Up until 2009 they contributed 50% of the PPIP data set. The National Department of Health has now made it compulsory for all public health facilities to collect and report data using PPIP. The latest Saving Babies report shows that PPIP has 94% of hospitals (588 sites) contributing data, representing 73% of the deliveries captured by the District Health Information System (DHIS) for the period 2010 11. 5 In 2012, for the first time all 52 districts in South Africa were represented, making PPIP a truly national programme. PPIP has been used as an input to the national and regional cause of death estimates compiled by the Child Health Epidemiology Reference Group. 6 The data are also being used to assess and triangulate Statistics South Africa s vital registration data. 2 The PPIP audit cycle Identification of the numbers, causes of death and avoidable deaths associated with stillbirths and neonatal deaths enables the identification of critical gaps and decisions to be made on where interventions are needed, such as facility improvement, equipment availability, staffing and staff training. In a meta-analysis of seven before after studies in low- and middle-income countries, perinatal mortality audit was shown to be associated with up to a 30% reduction in perinatal deaths. The consistency of effect suggests that audit may be a useful tool for decreasing mortality and improving quality, but can only be successful if the audit and feedback loop links to action at the point of care. 7 Types of data and process of data entry 1 Data capture of all deliveries, births and perinatal deaths that occur in the delivery and postnatal ward: Each month the total number of deliveries, stillbirths, early neonatal deaths are captured on a standardised data capturing form (DCF) by the facility health worker. These are usually midwives and more recently data capturers appointed to the hospital information system department at every hospital. Basic demographic data, primary obstetric cause of death and final neonatal cause of death are entered with each death. Only the late neonatal deaths that occur in hospital are entered on PPIP but deaths that occur at home or outside the health facility are rarely included or registered by parents, resulting in a significant data and health service delivery gap. The source of deliveries and births is the birth register kept in the labour ward and the early and late neonatal deaths are recorded in the neonatal nursery death book. For late neonatal deaths registers in paediatric wards, emergency and trauma units must also be accessed. 2 Entering and identifying the causes of deaths: Deaths are reviewed at regular minuted perinatal mortality and morbidity (M&M) meetings. These meetings are compulsory for each facility to convene on a regular basis according to the number of deaths that occur. An assigned doctor usually chairs the confidential inquiry into each death and hospital managers, clinicians and midwives attend. The causes of stillbirths and neonatal deaths are first divided into the primary obstetric causes and the final neonatal causes, respectively. For each of these it is then further categorised as an avoidable or unavoidable death. The avoidable deaths are then grouped into patient, medical- personnel- or administrative-related deaths and coded accordingly on the DCF. 3 Avoidable factors linked to each death are identified and discussed: These factors correspond to a code for analysis purposes and are recorded onto the DCF. Avoidable factors are grouped into patient-related, medical personnel-related or administrative-related avoidable factors. Data verification PPIP has a built-in validity check function that should be used once the monthly data have been entered. It minimises the risk of missing data by correlating the monthly data to the detailed perinatal death data. Data verification should happen at facility level before the PPIP data are exported to the provincial office. At provincial level, the provincial maternal, child and women s health (MCWH) co-ordinator must look at the trends and ensure that the second verification occurs before sending it to the national database at the MRC Unit for Maternal and Infant Healthcare Strategies (MRC Unit) in Pretoria. Once the data arrive at the MRC unit, it is impossible to assess validity because of the sheer volume of data being captured. The success of the system rests on the willingness and co-operation of healthcare staff to provide accurate and unbiased reports on the management of the case. A site that is instituting functional PPIP is one that is completing the audit cycle and adhering to the following components: (1) capturing all deliveries, births and perinatal deaths; (2) entering and identifying direct causes of deaths and avoidable factors at regular minuted M&M meetings; (3) instituting management change and policies as a result of meeting findings; and (4) central level providing feedback to the facility on the data received. ª 2014 Royal College of Obstetricians and Gynaecologists 161
Rhoda Training An MRC appointed PPIP co-ordinator oversees provincial training with a colleague and ensures that the facilities send their data to the central database. They perform yearly provincial workshops where staff are shown how to install the program, how to enter data and fill in the DCF and lastly how to perform data validity checks. These vital checks unfortunately are poorly understood and rarely implemented. Analysis of data Data are analysed at different levels depending upon the human resources available. Since the appointment of the District Clinical Specialist teams in September 2012, one of their main functions is the situational analysis of the hospitals and the district. Some provinces like Western Cape have appointed a neonatologist to co-ordinate PPIP data and perform analysis, Kwazulu Natal have a provincial paediatrician who performs this function for the province, and where no specialist is appointed, as in the Mpumalanga, a provincial team analyses data with the help of the national neonatal care improvement advisor. We wish to chronicle the experience of the two provinces which have been running PPIP the longest Western Cape and Mpumalanga. They have the most comprehensive and complete sets of data. They also provide two very different processes, which might be useful for other sites and settings looking to take up perinatal mortality audit. The Western Cape experience The Western Cape is the southernmost province and has the highest doctor-to-patient ratio in the public sector within South Africa. The majority of the births in the province occur in the Cape Town metropole (75%). The model of perinatal care in the Cape Town metropole is unique in the country, as all low-risk pregnancies are managed by midwives working in Midwife Obstetric Units situated in communities across the peninsula. High-risk mothers or those encountering complications were referred to the secondary and tertiary maternity centres based at Groote Schuur Hospitals (GSH), Tygerberg Hospital and Mowbray Maternity Hospital. As a facility audit tool, PPIP could identify what the gaps in knowledge and skills were in training midwives, which would result in better maternal and perinatal care. The province has been using PPIP as a perinatal audit tool since 2000 comprising 13 years of data. To get all 52 birthing facilities PPIP compliant, Dr Greenfield, a medical officer at GSH, and colleagues had the onerous task of initially collecting and analysing the data in the Peninsula Maternal and Neonatal Service (PMNS). Subsequently, the task involved loading the program on facility PCs, then training the maternity and neonatal nursery staff to not only enter but also interpret their data. Initially this was a paper system with data entered onto the standardised DCF and then entered on PPIP at Groote Schuur. As PPIP was not a mandatory system, it relied upon the work of volunteers and champions. However, when the GSH obstetric department used the perinatal data collected by Dr Greenfield for their own planning and training purposes, he was officially appointed as the PPIP co-ordinator for the PMNS covering half of the metropole. This appointment proved pivotal for the ongoing sustainability of PPIP in the province. With the background of understanding the system, it was then rolled out to all the facilities in the province. The process involved getting people involved, paying monthly visits, assisting with analysis of data, providing feedback to the maternity units and hospital managers. The latter proved to be a huge stumbling block as managers initially refused to come on board. Another round of workshops with managers turned the tide and within three years the province was 100% compliant. It took one day of training but on average 3 6 months before management understood the value of PPIP and up to 3 years before staff members fully appreciated the full benefit that PPIP provided to a facility. It also proved particularly useful as a management tool, as PPIP is able to generate graphs for reports. Upon enquiry when making follow-up visits, this was the most commonly stated reason for why facilities had functional PPIP, it benefited the facility directly to collect the PPIP data. A strategy that helped in rural areas was to appoint the outreach doctor to oversee the PPIP data system and chair the M&M meetings. Likewise, establishing a team of three medical officers to verify data in the urban metropole made the work more doable. A data flow algorithm (Figure 1) assigned designated named people the responsibility along the path of data collection and brought the vital step of accountability to the process. The appointment of a neonatologist as the Provincial Neonatal Specialist in 2008 10, meant that with 8 years of data and established trends, the province could now focus on the quality of the data and plan ahead using the baseline data as a starting point for improving perinatal and neonatal care. A blue print for neonatal care was developed and targeted interventions were planned along the continuum of care over a 3-year period. A steady and sustained decrease in mortality was seen with most recent DHIS data for the financial year 2012/13 showing the Western Cape to have the lowest neonatal mortality rate in the country at 7.1/1000 live births for all weights >500 g. Together with the MCWH provincial co-ordinator, provincial PPIP co-ordination is now institutionalised within 162 ª 2014 Royal College of Obstetricians and Gynaecologists
Experiences with perinatal death reviews in RSA Figure 1. Flow of data in PPIP. the Western Cape and meetings are held quarterly. This forum known as the Provincial Perinatal Morbidity and Mortality Committee reports directly to National Department of Health (NDOH) via the Ministerial Committee on National Perinatal Mortality and Morbidity Committee (NaPeMMCo) (Figure 2). The Mpumalanga experience Mpumalanga is one of the poorest and most rural provinces in the northeast of South Africa. Though situated close to the rich Gauteng and populated Kwazulu Natal it lacks human resources to staff its ª 2014 Royal College of Obstetricians and Gynaecologists 163
Rhoda Figure 2. NaPeMMCo relationships. health facilities. However, it is the only province with 100% of its facilities entering PPIP data and has the smallest gap between DHIS and PPIP data. Remarkably, all this was achieved with the support of a voluntary team led by midwife Marie Muller while still working full time at a district hospital. The provincial PPIP co-ordination function was officially assigned to her in June 2008. Hospital visits Marie covers 28 hospitals and 45 community health centres and performs hospital visits every 3 months. Each facility has an appointed PPIP co-ordinator and together they painstakingly go through all the folders for maternal and perinatal deaths from the antenatal care booking cards to the neonatal nursery records. Verification and validity checks are performed on the data; mistakes are identified in clinical folders, clinical coding is checked and monthly perinatal M&M meeting minutes are randomly requested. M&M meetings are compulsory for all staff involved in maternal and perinatal care to attend and Marie only attends if it coincides with a planned visit. The facility M&M meeting minutes and attendance register are sent to the district offices, who relay it to the provincial MCWH co-ordinator. Once the data are verified the results, analysis and discussion on facilities data is then entered into with the facilities PPIP data set. In January and February of each year, all provincial facility data undergo intense scrutiny before the submission of the previous year s data to the national PPIP database at the MRC in Pretoria. 164 ª 2014 Royal College of Obstetricians and Gynaecologists
Experiences with perinatal death reviews in RSA Marie also provides guidance to the facility perinatal co-ordinators to drive the PPIP process, identifies the gaps to achieve set targets and assists them in making data-driven recommendations to the hospital management. For example, if the facility data show that the fresh stillbirths have increased over a period of time then she will recommend that the facility unit managers step up the Essential Steps to Managing Obstetric Emergencies (ESMOE) training to improve the intrapartum care of mothers in labour. Similarly, if the final neonatal cause of deaths is coded as immaturity as a result of hyaline membrane disease, the use of continuous positive airway pressure (CPAP) should be planned for and if already installed then Marie checks that the equipment is functional and that protocols for the management is of hyaline membrane disease are available on the neonatal ward. Her follow-up visits thereafter will include specific attention to these recommendations. It takes on average 3 years for the facility to function independently to understand and engage with their own data without her support an arduous though rewarding journey. Feedback to the facility staff is a vital and highly anticipated consequence of her visit. To date, 80% of the PPIP data sets in the hospitals in Mpumalanga are entirely midwife and MCWH driven. Despite excellent data collection, this has not translated to a rapid reduction in the perinatal deaths within the province. Collecting numbers alone is not sufficient to reduce mortality, there have to be solutions that link to action and follow through. However, good-quality surveillance data is the first stage in the pre-implementation phase of change (Figure 3). Strengths As a facility-based tool, its primary strength lies in the fact that it allows the end user to interact with their own data in real time. Analysis is performed monthly. Astute and involved unit and hospital managers can use the perinatal data to effect change within a short period of time. Built in validation checks improve the quality of the data entered. Serves as a comparative data set to the DHIS total births and deaths. The quantitative gap can be recorded and tracked to improve data capturing. Blame-free, no-fault environment allows staff to be self-critical and provides an opportunity for group learning with potential for locally identified and implemented solutions. Challenges PPIP was not mandatory in South Africa until 2012, and the data chain was dependent upon champions who are passionate and data driven. Reliance upon champions has an inherent weakness because it depends upon one or two people to run and motivate others and there is no back-up system should these champions leave the facility. In order for PPIP to be effective and sustainable it has to be compulsory and become institutionalised within the existing MCWH programmes at hospitals. Not everyone entering data into PPIP understands its importance. Data capturers with no clinical background compromise the quality of the data and therefore the validity checks must be stringently performed after each monthly data entry to minimise errors. Auditing alone does not necessarily imply that there will be a reduction in deaths. It requires a functional PPIP system that has constant monitoring and evaluation with the feedback loop in place as per the audit cycle (Figure 4). Figure 3. Stages of change. Figure 4. The audit cycle. ª 2014 Royal College of Obstetricians and Gynaecologists 165
Rhoda Quality implementation of the audit cycle is not addressed by PPIP software and is of grave concern because it is an important aspect of any audit process. In the Western Cape model this is exemplified by the appointment of specialists and subspecialists to strengthen the analysis of the data and spearhead the implementation phase. They are also pivotal in budget planning for specific interventions to target the high impact factors, e.g. roll out of CPAP to district hospitals to reduce neonatal deaths. Both the type of person and the number of people entering data affects the quality. Data capturers may not detect errors. In some smaller facilities, one appointed PPIP person might perform the jobs of persons 2 to 5 on Figure 1; bigger hospitals are more likely to have seven people involved as per the diagram. Naturally the fewer people, and the more trained they are in what PPIP does, the better the quality of the data. Opportunities In our growing technologically advanced world with increasing access to computers and mobile devices, PPIP provides a user-friendly platform with minimum requirements for installation. If adequately supported in its initial phase of roll out, it can facilitate the rapid expansion of data collection, analysis and review. As demonstrated, it can be entirely midwife-run and is poised for adaptation and expansion within the country and beyond. Conclusions In order for PPIP to succeed as a quality improvement tool as well as a monitoring tool it has to be a functional data system where data are complete, verified, analysed and fed up to higher levels of management, so that both health workers and administrators can change policies and practices. The system requires leaders to champion the process, especially ensuring a no-blame environment for ascertaining avoidable factors associated with perinatal deaths. Installing the programme with appropriate training, support and guidance will save the lives of South Africa s mothers and babies. Disclosure of interests NR is the current chairperson of the National Perinatal Mortality and Morbidity (NaPeMMCo) Ministerial committee. Our task is to look at the national perinatal data set and advise the Minister of Health accordingly. Date of appointment February 2012. The tenure is for 3 calendar years. In addition my current job is as the Neonatal Care Improvement Advisor within the DIFID-funded RMCH programme (July 2013 to June 2015). None of the other contributory co-authors have any conflict of interest. Details of ethics approval None was required. Funding No funding was received. Acknowledgements Dave Greenfield, Marie Muller, Johan Coetzee, Roz Prinsloo and Prof Robert Pattinson were consulted to verify the details for the following: Dave Greenfield PMNS details; Marie Muller Mpumalanga experience; Johan Coetzee PPIP developer; Roz Prinsloo national training and data verification. Kate Kerber and Shuaib Kauchali have also provided editorial assistance. Lastly, thank you to all the staff in the maternity and neonatal wards across the country, who are dedicated to making PPIP function optimally. & References 1 UNICEF, WHO, The World Bank, United Nations. Levels and Trends in Child Mortality: Report 2013. New York, NY: UNICEF, 2013. 2 Kerber KJ, Lawn JE, Johnson LF, Mahy M, Dorrington RE, Phillips H, et al. South African child deaths 1990 2011: have HIV services reversed the trend enough to meet Millennium Development Goal 4? AIDS 2013;27:2637 48. 3 National Department of Health. Strategic Plan (2012 2016) for Maternal, Newborn Child and Women s Health (MNCWH) and Nutrition. Pretoria: National Department of Health, 2012. 4 National Perinatal Mortality and Morbidity Committee (NaPeMMCo). NaPeMMCo Interim Report 2010 2011. Pretoria: NaPeMMCo, 2012. 5 Pattinson RC. Saving Babies: 2010 2011 Interim Report. Pretoria: Medical Research Council; 2012. 6 Liu L, Johnson HL, Cousens S, Perin J, Scott S, Lawn JE, et al. Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000. Lancet 2012;379:2151 61. 7 Pattinson R, Kerber K, Waiswa P, Day LT, Mussell F, Asiruddin SK, et al. Perinatal mortality audit: counting, accountability, and overcoming challenges in scaling up in low- and middle-income countries. Int J Gynaecol Obstet 2009;107(Suppl 1):S113 21, S121 2. 166 ª 2014 Royal College of Obstetricians and Gynaecologists