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Objective: This study analyzed cost of implementing computer-assisted Clinical Decision Support System (CDSS) in selected health care centres in Ghana. Methods: A descriptive cross sectional study was conducted in the Kassena-Nankana district (KND). CDSS was deployed in selected health centres in KND as an intervention to manage patients attending antenatal clinics and the labour ward. The CDSS users were mainly nurses who were trained. Activities and associated costs involved in the implementation of CDSS (pre-intervention and intervention) were collected for the period between 2009-2013 from the provider perspective. The ingredients approach was used for the cost analysis. Costs were grouped into personnel, trainings, overheads (recurrent costs) and equipment costs (capital cost). We calculated cost without annualizing capital cost to represent financial cost and cost with annualizing capital costs to represent economic cost. Results: Twenty-two trained CDSS users (at least 2 users per health centre) participated in the study. Between April 2012 and March 2013, users managed 5,595 antenatal clients and 872 labour clients using the CDSS. We observed a decrease in the proportion of complications during delivery (pre-intervention 10.74% versus post-intervention 9.64%) and a reduction in the number of maternal deaths (pre-intervention 4 deaths versus post-intervention 1 death). The overall financial cost of CDSS implementation was US$ 23,316, approximately US$1,060 per CDSS user trained. Of the total cost of implementation, 48% (US$11,272) was pre-intervention cost and intervention cost was 52% (US$12,044). Equipment costs accounted for the largest proportion of financial cost: 34% (US$7,917). When economic cost was considered, total cost of implementation was US$17,128-lower than the financial cost by 26.5%. Conclusions: The study provides useful information in the implementation of CDSS at health facilities to enhance health workers’ adherence to practice guidelines and taking accurate decisions to improve maternal health care. © 2014 Dalaba et al.
The study was approved by the ethics committee of the University of Heidelberg (S-173/2008) and the Institutional Review Board of the Navrongo Health Research Centre in Ghana (NHRCIRB 085). The study was done in the Kassena-Nankana District of northern Ghana. The district is located in the northeastern corner of the country bordering Burkina Faso, and occupies an area of about 1,675 square kilometres. As in many parts of the savanna zone of Ghana, poverty is endemic in this district. Due to the erratic nature of rainfall and deteriorating soil quality, harvests are often poor and seasonal food shortages are not unusual. The KND has a population of 150,000 with females constituting 53% [20]. The district has a district hospital located in Navrongo that serves as a referral point for the Kassena-Nankana district, the Builsa district and neighboring towns in Burkina Faso. There are six main health centers, and two community clinics jointly run by the Catholic Diocesan Development Office and the District Health Administration that provide services to the communities. There is one private clinic and 27 functional Community-based Health Planning and Services (CHPS) compounds with resident Community Health Officers (CHOs) offering doorstep services [21]. A descriptive cross sectional study was conducted in the Kassena-Nankana district. The study captured data from October 2009 to March 2013. Costs were collected from the programme/provider perspective. All information on activities involved in the implementation of the computer-assisted CDSS and associated costs were collected. These activities included training of computer-assisted CDSS users, buying equipment such as laptops and monitoring and supervision of computer-assisted CDSS users. Computer-assisted CDSS software development costs were not collected and therefore not included in the analysis. The study is part of a wider project assessing the quality of maternal and prenatal care (QUALMAT-Quality of prenatal and maternal care: bridging the know-do gap) using a computer-assisted CDSS. The QUALMAT research project started in 2009 as collaboration between six partners- Centre de Recherche en Santé de Nouna (Burkina Faso), Ghent University (Belgium), Heidelberg University (Germany), Karolinska Institute (Sweden), Muhimbili University of Health and Allied Sciences (Tanzania), and Navrongo Health Research Centre (NHRC, Ghana). The computer-assisted CDSS is being tested in the six health care centres in the Kassena-Nankana district. Each health centre has at least a nurse, a midwife, and a medical assistant and provides outpatient services and normal deliveries. With regards to maternal health care, the Ghana health service policy stipulates that all health facilities are to use the reproductive health guideline “ National Safe Motherhood Service Protocol (2008)” [19] and the WHO guideline ‘Pregnancy, Childbirth, Postpartum and Newborn Care (PCPNC); A Guide for Essential Practice” [7]. Maternal health care is free of charge for all women accessing care in all public health facilities (including the selected health centres). The maternity services that are provided free of charge include antenatal care, childbirth, caesarean section, management of emergency obstetric conditions, and postnatal care [22]. The selected health centres have basic infrastructure such as utilities (electricity and water) equipment and medical supplies [21]. These health centres are within 2 hours drive to the district hospital where patients can be referred to [6]. Future users (midwives), medical experts and Information Technology (IT) specialists jointly developed the computer-assisted Clinical Decision Support System (CDSS) within the project and the system was subsequently adapted to the country specifics of Tanzania, Burkina Faso and Ghana. The Ghana computer-assisted CDSS is based on Ghana’s reproductive health guideline “ National Safe Motherhood Service Protocol (2008)” [19] and the WHO guideline ‘Pregnancy, Childbirth, Postpartum and Newborn Care (PCPNC); A Guide for Essential Practice” [7] and then accustomed to the study health centres [6]. These guidelines have algorithms for decision-making and management of conditions at all levels of care and for all the stages of pregnancy, delivery and postpartum period [2]. The QUALMAT computer-assisted CDSS translates these decision-making trees into computer-based algorithms to be carefully followed by health care providers. The computer-assisted CDSS supports routine antenatal care and care during delivery and up to 24 hours after delivery. It is developed using 3 main principles: (i) Guidance through routine actions in maternal and perinatal care is provided by checklist to safeguard comprehensive history taking; (ii) Integration of clinical data to detect situations of concern by algorithms which then suggest diagnoses or alert the user about dangerous situations that need attention; (iii) Electronic partograph for observation of the progress of delivery up to 24 hours after delivery. Detailed description on the development of the computer-assisted CDSS and how it works are presented elsewhere [6]. Two software release candidates were piloted and feedback incorporated to produce a final version that was then used for implementation. The final version of the computer-assisted CDSS software was implemented and authorized for use in patient care in the six health centres in April 2012. A form was designed for the project coordinator to document all activities and associated costs (quantities and unit costs) that occurred during the CDSS implementation. In addition, the project had a financial manager who kept records on all expenditure made on the project. Information on the activities and costs were therefore retrieved from both the project coordinator and the financial manager. We collated information on trainings, meetings, management, monitoring and supervision as well as logistics and transportation involved in the computer-assisted CDSS implementation (Table 1). Data on both quantities and unit costs of resources consumed were gathered for the period October 2009 to April 2013. For the effects of the CDSS, we collected pre-intervention data to capture 12 months (April 2011 to March 2012) of information on maternal health routine services before computer-assisted CDSS implementation and the post-intervention captured 12 months (April 2012 to March 2013) of data after computer-assisted CDSS implementation. The health centres have books that there record maternal health services provided. We therefore reviewed these books or registers at the health centres and collected data on the number of antenatal consultations, labour cases, deliveries, referrals (due to complications) during ANC visits as well as labour referrals (due to complications). We also collected information on maternal mortality that occurred at the study health centres during the study period. The data were entered, cleaned and analyzed using excel. An ingredients approach where quantities of the resources are multiplied by their unit prices was used to calculate costs. Costs were categorized into personnel, trainings, overheads costs (representing recurrent costs) and equipment costs (representing capital cost). Costs of implementation were further grouped into two phases. The first phase was referred to as the pre-intervention phase. This first phase was defined as all activities and associated costs that occurred before computer-assisted CDSS was commenced for patient care (October 2009 to March 2012 period). The second phase was referred to as the intervention phase and included all the activities and associated costs incurred during the 12 months period of actual use of computer-assisted CDSS for patient care (April 2012 to March 2013). The cost of implementation was calculated by adding the pre-intervention costs and intervention costs. We calculated cost without annualizing capital cost to represent financial cost of the implementation and cost with annualizing capital costs to allow differential timing of capital costs to represent economic cost. Capital costs (resources with lifespan greater than 1 year) such as equipment (laptops, tables are chairs) were annualized using discount rate of 3% and a useful life of 5 years, consistent with economic evaluation guidelines [23], [24]. Personnel costs were calculated by summing the cost incurred on staff involved in the computer-assisted CDSS intervention during the 12 months period of actual use of computer-assisted CDSS for patient care. The two main staff that were involved were a technical Officer and computer-assisted CDSS users. A technical officer with knowledge in information technology (IT) provided trainings and technical support to the computer-assisted CDSS users. The officer visited the computer-assisted CDSS users fortnightly to monitor and supervise them. The technical officer also downloaded data captured in the computer-assisted CDSS and updated antivirus during the monitoring visits. In addition, whenever a computer-assisted CDSS user moves (transfer, study leave), the officer trains a new user to continue the use of the computer-assisted CDSS. Based on the time spent monitoring, supervising and training the computer-assisted CDSS users (45% of time spent on CDSS activities) and the monthly pay for staff in technical officer category (US$1,000), an agreed amount of US$250 was paid per month to the technical officer. The total cost of the technical officer was therefore calculated by multiplying number of months worked by the monthly allowance. Not all staff at the health centres were trained to use the CDSS. At least two nurses were trained in each health centre. Each health centre had at least one midwife. All the midwives in the health centres were trained. In addition to the midwives (main CDSS users), some community health nurses (CHN) were trained to support the midwives. These additional nurses were selected in consultation with the in-charges of the study health centres. The basic criteria for selection of these additional nurses for the training were based on their involvement in the provision of antenatal care and delivery in the health centre. Whenever a midwife was transferred or on annual leave or left for further studies, a new person was trained on time for replacement. The staff that were not selected and trained to use the CDSS carried out their normal duties. CDSS users and non-users both abided by the normal work regulations (both start and close work same time). In order not to disrupt the normal duties of the selected CDSS users, training sessions were organized on days and times that were most convenient to the CDSS users. For the period, 22 computer-assisted CDSS users were trained (16 midwives, and 6 nurses). The government of Ghana pays on average US$626 per month to a midwife, and US$ 404 per month to a community health nurse. We did not include these salary costs in our personnel cost, since this cost was already incurred by the government and the focus was on additional costs. However, in order to motivate the computer-assisted CDSS users to use the system, a token (allowance) of US$31 was given per month to each CDSS user. Cost of computer-assisted CDSS users was therefore calculated by multiplying the number of months worked by the computer-assisted CDSS users by the monthly allowance. Training costs included all cost incurred during the various training sessions. For the period, a total of six major meetings/training sessions were held. The first meeting was a one day stakeholder meeting, in which the directors of health services, district public health nurses, midwives and other key stakeholders participated. During the meeting, the computer-assisted CDSS concept was discussed and approval and support by the stakeholders were established. Five training sessions for the computer-assisted CDSS users were held. Each training session lasted two days. The training sessions were facilitated by a technical officer and four support staff (medical officer, midwife and two research officers). The computer-assisted CDSS users were first introduced to basic computer training sessions, as most of them were using computers for the first time. Further specific trainings on computer-assisted CDSS usage (2 trainings: pre-intervention period) and refresher trainings (2 trainings: intervention period) took place. These training workshops aimed to help users understand the algorithm, the algorithm stages and the decision stages of the programme. During the training workshops, demonstrations and hands-on training took place. In addition, each participant was asked to enter an initial and follow- up visit using a simulated patient material. The computer-assisted CDSS users were also taught how to access and use technical support on the software. Participants of these trainings were each paid an allowance of US$11 per training day for their time. This is a standard amount paid by the Ghana Health Service to health workers who participate in trainings of this kind. The cost of training was calculated by summing all the allowances for participants, facilitator and support staff per training session and other expenditure made during the training sessions. Transportation costs were calculated as hired costs (US$0.45 per km) per vehicle rented for visiting the health centres for monitoring and supervision. The total cost for transportation was therefore calculated by multiplying the kilometre covered by the cost per kilometre. Equipment costs included all the equipment bought for the computer-assisted CDSS implementation and the associated costs. Six dell laptop computers (specification: 2 GB RAM, 250 GB hard disk drive, Duo core) were purchased and the computer-assisted CDSS software was installed on each of them. These laptops were distributed to each of the six health centres. One additional laptop was bought and the software installed on it, and it served as a backup laptop. In addition, six computer tables and chairs were bought and distributed to the six computer-assisted CDSS health facilities to support computer-assisted CDSS users’ work. The total equipment cost was calculated by multiplying the unit cost of items by the quantities. Further analysis was done where laptops, chairs, tables were categorized as capital cost and were annualized using discount rate of 3%, and a useful life of 5 years to determine the economic cost. Other costs (overheads) including stationary, repairs of computers and other costs incurred in the computer-assisted CDSS implementation were obtained and calculated by multiplying the unit cost of the items by their quantities. Average cost of training a computer-assisted CDSS user was calculated by dividing the total cost of computer-assisted CDSS implementation by the number of computer-assisted CDSS users trained during the entire study. Computer-assisted CDSS cost per woman managed was calculated by dividing the total cost of implementation by the total number of women managed using computer-assisted CDSS. One-way sensitivity analysis was conducted to determine whether changes in variables such as discount rate and life expectancy of equipment will change the economic costs of CDSS implementation significantly. Accordingly, we varied the discount rate from 3% to 5% and 10% as well as the life span for equipment from 5 years to 10 years. Given that the aim of this analysis was to provide the cost of the computer-assisted CDSS implementation, which would be of use to health providers/policy makers considering the use of computer-assisted CDSS within health centres, we did not include health centre specific costs such as actual salaries of computer-assisted CDSS users (midwives and CHNs), capital costs (such as buildings of the health centres) in the analysis as these were already costs incurred by the health centres. Only additional costs not already borne by the health centres were included. In addition, cost of developing the CDSS software, research cost such as cost of conducting cross sectional surveys and qualitative studies and other costs not related to computer-assisted CDSS implementation were not included. Costs results are presented by: pre-intervention cost (cost from October 2009 to March 2012); intervention representing the cost incurred over the course of the one year intervention (from April 2012 to March 2013); and cost of implementation representing overall cost (pre-intervention plus intervention cost). Costs were also presented by health centres. The personnel, training, and overhead costs were allocating to the various health centres based on the number of staff trained per health centre. Transportation cost allocation was based on the distance from the research centre to the health centres. All costs were collected in local currency, Ghana cedis (GH) but results are presented in US dollars (US$). We used the average exchange rate for 2012 (1US$ = GH1.8).
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