MATERNITY DASHBOARD IN TANZANIA

Background to the Problem of Poor Quality of Maternal and Newborn Care 

Globally, quality of health care is high on the agenda of most governments. It is important to pay attention to quality of care (QoC) for the simple reason that the healthcare services will be effective, efficient, acceptable and safe (Nair et al 2014). It is in this context that Tanzania has clearly stated goals of access to quality health care in its key policy documents: the national vision 2025; The NSGRP (MKUKUTA); the Primary Health Development Program (MMAM); and the Tanzania Five Year Development Plan 2011/2012-2015/2016 (URT, 2012; URT 2005a; URT 2005b).

Nevertheless, poor health outcomes have been recorded. For instance, with respect to millennium development goals (MDGs), Tanzania achieved modest reduction of maternal and neonatal deaths (CSIS, 2017). According to the MDGs report, MMR was only minimally reduced from 578 per 100,000 live births in 2004 to 432 per 100,000 live births in 2015 – failing to achieve the set target of reducing MMR to 133 per 100,000 live births by 2015 (URT, 2014).   

Concerns about the quality of health care have been expressed (e.g. Rajkotia, 2007; SEND, 2010). Several studies in resource poor settings report on poor quality of care, either perceived by the patients or objectively measured using medical professional performance indicators (Kowalewski, 2000; Mselle et al 2013; Shama et l 2017). A study by D’Ambruoso et al. (2005) revealed under utilization of maternal health care services due to the perception of poor quality referring to birthing position, fluid intake during delivery, caring actions and health staff attitudes. Also, a study conducted at Muhimbili National Hospital by  Kidanto et al (2009) identified suboptimal care in about 80% of audited cases out of which about 50% were found to be the likely cause of the adverse perinatal outcome. Inadequate maternal and foetal monitoring during labour were the main suboptimal factors.

Interventions to address poor quality have involved advocacy for skilled birth attendance;  availability of skilled personnel and medical supplies; and improvement of infrastructure (Olsen 2009; URT, 2014). Relatively little attention has been put on measurement and evaluation in a maternal and newborn care settings. Monitoring and Evaluation (M&E) experts say “we can only improve things we can measure”. M&E using locally generated data is important for periodic – say monthly –assessment of progress being made and instituting corrective measures rapidly. In fact, the World Health Organization’s Commission on Information and Accountability for Women's and Children's Health has recognized that, in resource-poor settings, health managers do not use local health outcome data for inform quality improvement practice. Conversely, in developed countries a hospital uses local data to develop quality frameworks for measurement and evaluation of maternal and newborn care (Brizuela, 2019).  Such frameworks are referred to as maternity dashboards and have been useful in quality improvement (Crofts et al, 2014). Few developing countries have adapted them. It is against this background that this project intends to implement maternity dashboards for improving quality of services in district hospitals in Tanzania.

 Statement of the Problem: None Use of Local Data for Improvement of Maternal and Newborn Care

In Tanzania, hospital maternal and newborn care data are collected in a manner that is difficult for both front-line staff and managers to identify and deal with local problems quickly enough to prevent further harm. That is, data that are collected – for instance the numbers of births, third degree tears, caesarean sections, maternal deaths, admissions to special care baby units, birth asphyxia, stillbirths and neonatal deaths – are often not used inform service delivery at the health facility where they are generated. Instead, such data are transmitted to the higher administrative offices – in the district, region, and the Ministry of Health, Community Development, Gender, Elderly, and Children. From the Ministry, the data are then transmitted to other national institutions like the National Bureau of Statistics and the international agencies like the World Health Organization (WHO). This pattern of data processing and utilization serves to understand the situation of maternal and newborn health and probably inform national interventions.  Little attention is paid on utilizing the data to inform local prompt response to improve maternal and perinatal outcomes. There is limited or no research evidence on the local system of data utilization for quick improvement of the outcomes. That is, the use of locally collected data to improve maternal and newborn outcomes has not been tested in district hospitals. Therefore, the aim of this project is to develop and implement maternity dashboards in the district Hospitals, obtained in 3 Regions with highest maternal mortality rates.

Description of Maternity Dashboard [The Solution]

The ‘Maternity Dashboard’ is a clinical performance and governance score card which enables a hospital to monitor various pre-selected parameters at a regular interval.  Local [Hospital] goals and targets for improving mutually agreed parameters are set and monitored (Chandraharan and Arulkumaran, 2016). It is used to monitor performance against the standards agreed locally for the maternity unit on a monthly basis. It follows the principles of a car dashboard, which provides contemporary information about the amount of fuel in the tank, speed, state of the battery, temperature of the engine, so that appropriate action can be taken before the car breaks down (for example, refuelling when the fuel gauge is on ‘low’ rather than stalling on the motorway with an empty fuel tank). Similarly, the Maternity Dashboard will provide contemporary information about resources and clinical activity as reflected in - maternal deaths, birth asphyxia, stillbirths and neonatal deaths – thus enabling early identification of deviation from the set goals.

Individual maternity units should set local goals for each of the parameters monitored, as well as upper and lower thresholds. The set goals are entered into a computer resulting a tool [dashboard] that presents a health facility’s clinical data graphically using a traffic-light coding system to alert front-line staff about changes in the frequency of clinical outcomes. It provides rapid feedback on local outcomes in an accessible form and enables problems to be detected early. In the context of maternity care, the traffic light system works as follows:

● Green: when the goals are met (that is, within the lower threshold)

● Amber: when the goals are not met (that is, above the lower threshold but still within the upper threshold). If a parameter is in amber, it indicates that action is needed if one is to avoid entering the red

zone.

● Red: when the upper threshold is breached. If a parameter enters the red zone then immediate action is needed from the highest level to maintain safety and to restore quality.

 Significance of the project:

This project seeks to document evidence on utilization of data for improvement of services at the very health facility where data are generated. Data collection, analysis and local use of the same are essential to improving health outcomes in maternal care units. To hold district hospitals accountable toward that direction, maternity dashboards - which have been found to be useful tools elsewhere – will be tested in the context of Tanzania. It is envisaged that maternity dashboards will equip hospitals with a simple method for maintaining and monitoring clinical quality. In essence, this study underscores the importance of measurement and evaluation in a health care setting. 

Our solution is targeting pregnant women and newborns. Currently, there is limited local [Hospital level] use of data by Hospital Administrators for the reduction of maternal and neonatal mortality. The setting of targets and weekly review of the Maternity Dashboard will enable the Hospital Administrators to closely monitor the quality of care and institute corrective measures.    

Me and My Team are Professors and Lecturers at a leading Health Training University in Tanzania. As academicians, we teach, research, and provide care to women and children. Therefore, we are very well informed about problems of poor quality of maternal and newborn care; high level of maternal and neonatal mortality; and limited and target-less use of data by Hospital Administrators for reduction of mortality. 

Currently, Tanzania has general health dashboards [aggregated data at the district, regional, and National levels]. We need funds to develop and implement Hospital and maternity-specific dashboards.

Our solution provides a significantly improved approach to data use for the reduction of maternal and neonatal mortality. This is because it has 3 main components:

1. Strengthening governance:

    We understand that strong clinical governance is key to the utilization of  data for quality improvement

2. Goal and Target setting.   

    Unlike the usual practice in Tanzania where a broad goal of reduction of maternal and neonatal mortality is set without specific indicator targets; our solution will involve setting the target for the overall goal and specific targets for the selected indicators. Setting the targets will facilitate the measurement of the progress, and we know that a Hospital can only improve what it can measure. 

3. Local maternity dashboard: 

    Developing and implementing the Hospital's Maternity Department specific will encourage local use of data and monitoring of outcome indicators.     

Goal 1 (for the next year): Maternity dashboard-driven improvement of maternal and newborn health

This will be achieved through the following mechanisms: 

i) Strengthening clinical governance - through training and sensitizing managers of maternity services to understand the critical role of governance in setting outcome targets and ensuring that information gained through the maternity dashboard is utilized to improve performance toward meeting the target.       

ii) Strengthening ICT infrastructure - through orienting existing ICT staff and procuring state-of-the-art computers in which the dashboard will be developed.

iii) Strengthening human resource for maternal and newborn care - through short-term training and sensitization to inculcate the culture of striving to meet the set outcome targets. This will eventually enhance staff accountability.      

Goal 2 (for the next 5 years): Significant reduction of maternal and perinatal mortality.

This will be achieved through sustained implementation of mechanisms (i)-(iii) outlined under Goal1 above. 

Morbidity Indicators:

Percentage of women who gave birth preterm (i.e. before 37 weeks’ gestation)

Caesarean section rate

Assisted delivery rate

Percentage of women with a third- or fourth-degree perineal tear

Percentage of women who had a postpartum haemorrhage >500 mL

Percentage of women with eclampsia

Percentage of neonates with an Apgar score <7 at 5 minutes

Percentage of neonates admitted to the special care baby unit

Mortality indicators:

Percentage of women who died

Percentage of women who died

Percentage of avoidable maternal deaths

Percentage of maternal deaths due to the third delay (i.e. delay in receiving adequate treatment

at a health facility)

Percentage of maternal deaths that occurred in women not scheduled for antenatal care

Percentage of maternal deaths secondary to:

• postpartum haemorrhage

• pregnancy-induced hypertension or eclampsia

• sepsis

• ectopic pregnancy

• abortion

• placenta praevia

• placental abruption

• retrovirus infection

• anaesthetic complications

Total stillbirth rate

Fresh stillbirth rate

Macerated stillbirth rate

Perinatal mortality rate

This project rests on 3 pillars, namely: Clinical governance, ICT infrastructure, and human resource for health. Much as the three pillars are interlinked, Clinical governance drives the process. Thus, in this project managers of maternity services will be empowered through training and sensitization to enable them to understand the critical role of governance in setting outcome targets and ensuring that information gained through the maternity dashboard is utilized to improve performance toward meeting the target. Getting involvement and understanding of managers of maternity services is the first and critical step.        

A supportive Management will collaboratively strengthen ICT infrastructure - by procuring state-of-the-art computers in which the maternity dashboard will be developed; and orienting existing ICT staff so they can take part in the development and management of the maternity dashboard.

Again, supportive Management will collaboratively strengthen human resource for maternal and newborn care - through short-term training and sensitization - so they can respond appropriately to the signals displayed in the maternity dashboard. Additionally, the short-term training and sensitization together with sustained supportive supervision will lead to the inculcation of the culture of striving to meet the set outcome targets. Finally, staff accountability will be enhanced.

We will use software that will enable the analysis of data about the selected maternal and newborn health parameters. That is, the individual maternity units will set local goals for each of the parameters to be monitored, as well as upper and lower thresholds. The set goals will be entered into a computer resulting in a tool [dashboard] that will present a health facility’s clinical data graphically using a traffic-light coding system to alert front-line staff about changes in the frequency of clinical outcomes. It will provide rapid feedback on local outcomes in an accessible form and enables problems to be detected early. In the context of maternity care, the traffic light system will work as follows:

● Green: when the goals are met (that is, within the lower threshold)

● Amber: when the goals are not met (that is, above the lower threshold but still within the upper threshold). If a parameter is in amber, it indicates that action is needed if one is to avoid entering the red zone.

● Red: when the upper threshold is breached. If a parameter enters the red zone then immediate action is needed from the highest level to maintain safety and restore quality.

Midwives who are responsible for taking care of women before, during, and after childbirth will collect data and enter them into the maternity dashboard.

One midwife will on daily basis be assigned to enter data for the selected outcome indicators into the maternity dashboard. 

Since the Management will occupy a central position in the implementation of the solution, data collection and feeding of data into the maternity dashboard will be integrated into the Hospital's routine duties. Therefore, there will not be a separate incentive for implementing the solution, thereby facilitating the sustainability of the solution during and after the project period.     

Implementation of the maternity dashboard will be participatory from the design to implementation. The Hospital Management will be involved to facilitate the establishment of the dashboard. The Solution team will have representation of both females and males.   

This is a non-monetary profit project. The solution will enable the selected Hospitals to utilize locally generated data to drive improvement of maternal and newborn care and eventually contribute to the reduction of maternal and perinatal mortality.   

Firstly, the initial money to fund this project will come from this project's grant.

Secondly, since the project will be implemented in government-owned hospitals, implementation of the Solution will be included in the annual budgets of the respective Hospitals.  

1. Sida grant for supporting health system research, worth SEK 2 Million.