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Background Antenatal screening is useful for early identification and management of high-risk pregnancies. In low-resource settings, provision of the full complement of tests is limited and diagnostic referrals incure additional costs for pregnant women. We assessed the viability of Bliss4Midwives (B4M) – a point-of-care diagnostic decision support device for decentralized screening of pre-eclampsia, gestational diabetes and anaemia during antenatal care (ANC). Methods The device was piloted in seven health facilities across two districts in Northern Ghana over a ten-month period. Health workers were expected to screen women at each ANC visit till delivery. All screening records from the device were automatically archived digitally and later downloaded. After removing duplicates or invalid entries, descriptive quantitative analysis was carried out with IBM SPSS Statistics (version 23). B4M usage behavior, diagnostic and referral outcome were analyzed. Results Health workers conducted 1323 partial or full antenatal screening on 940 women, resulting in decision support for 835 (88.8%) B4M beneficiaries. Diagnostic referral was eliminated for 708 (84.7%) beneficiaries, with 335 (40.1%) of these from facilities without on-site diagnostic alternatives. Of visits with complete data, 92/559 (16.4%) women were screened in their first trimester, 28/940 (2.9%) had 4+ B4M visits and 107/835 (12.8%) women were recommended for urgent referral to a higher-level facility on the first visit. Follow-up screenings flagged an additional 17 women for urgent referral with 10 cases of repeated alerts in five women. Wide variations between high (9 months use) and low adopting (1.5 months use) facilities were observed, with some similarities in usage trend. Conclusions B4M helped decentralize ANC screening and decrease unnecessary referrals. Project outcomes were influenced by implementation strategy, technical features and behavioural dispositions of users and beneficiaries.
Seven prototype B4M devices were assembled (Figure 1). Each device is composed of three diagnostic and two supportive components. B4M device. 1 – Portable water and heat resistant dustproof case; 2 – Automated blood pressure cuff; 3 – Urinary glucose and protein Chemistrips; 4 – Urisys 1100® Urine Analyzer; 5 – Pronto-7® Rainbow Pulse CO-Oximetry device; 6 – Android tablet with decision support algorithms; 7 – Traffic-signaling alert system; 8 – Unique QR code for easy tracking and recall of patient records; 9 – AC adapter for charging the device. Diagnostic components meet requirements of the Food and Drug Administration or European Standard of Electronic Engineering and conform to standards for developing medical prototypes- ISO 13485 [16]. Diagnostic data were automatically or manually (only hemoglobin) uploaded to the tablet. In addition to updating clinical history and hemoglobin (Hb) results manually, B4M users were expected to input delivery date and outcome as well as summarized notes on their observations or actions. Devices could be locked and transported between locations. Except for the haemoglobinometer that used disposable batteries, a rechargeable lithium battery powered all prototype components. When fully charged, components could operate without electricity for up to seven hours. Consumables (Chemstrip®, disposable batteries, finger sensors) were replenished by the project on request. Other technical details of the device are beyond the scope of this paper. The device was implemented in the Upper East Region (UER) and Northern Region (NR) of Ghana. All intervention sites are predominantly rural and about half of the population is illiterate [17-19]. Five health facilities per region were enrolled, but technical and implementation challenges such as defective devices and transfer of trained staff reduced the total number to seven- four health facilities (facilities A-D) from UER and three facilities (facilities E-G) from NR. Because it was a pilot, B4M was used in addition to the pre-existing paper-based ANC routine and health workers were expected to screen all women who came for ANC at each visit till delivery. Three devices were situated in each region and one device reserved for backup. Facility selection was largely guided by high ANC-load per facility, remote distance from referral hospital and possibility that more women would benefit from the device. Devices were assigned to facilities on a fixed or rotational basis. Higher caseload facilities such as hospitals had a fixed device. Where a facility was too remote for convenient rotation (eg, facility G), it had a fixed device. Each B4M visit ideally involved a systematic step-wise process starting with enrolment of first time beneficiaries using their data and history, followed by presenting complaints, diagnostic screening and referral decision. Client counselling concluded each visit. Based on pre-intervention estimates, 100 pregnant women per health facility were expected to be screened in a year, with 40 women completing at least four ANC visits between early pregnancy and delivery [16]. Twenty-five midwives and community health workers received two-days training on B4M. This included refresher training on managing pregnancy complications and principles of quality ANC. Three field personnel with technical backgrounds, and two program officers (one in each region) were also trained to provide technical support. The Android tablet was programmed to automatically archive all screening records and usage information in a downloadable repository. Such information included: kit number, B4M visit date, B4M visit number and QR code, mother’s name, parity, expected date of delivery, gestational age, delivery date and outcome of delivery, patient history, presenting complaints, diagnostic decisions, action (ie, counseling, testing and treatment) and referral recommendations. The study sample was limited to all women who were screened with the device; therefore excluding those who attended ANC visits during the project period without being screened with B4M. A member of the project team downloaded the repository from each device. Records were de-identified, cleaned and sorted for duplicates or invalid entries (eg, records from training or trial sessions) using Excel. Descriptive quantitative analysis of records archived over a 10-month period (15th June 2016 to 18th April 2017) was carried out using IBM SPSS Statistics (version 23) (IBM Inc, Armonk, NY, USA). Navrongo Health Research Centre Institutional Review Board (Approval ID: NHRCIRB18) and EMGO+ Scientific Committee of the Amsterdam Public Health Institute (Reference Number: WC2017-026), granted study approval. Most information collected in the B4M repository represented data that should also be recorded in the paper-based maternal health record books at each facility. This includes the name, address, parity, age and gestational age of women. Because record books are not necessarily stored securely, they pose a higher privacy risk as anyone could easily access information on ANC attendees. To ensure data protection and privacy, the personal data of women were linked through the anonymised QR code, each with a unique alphanumeric project label (see Figure 1, item 8). Furthermore, each B4M user was assigned a username and password and only personnel with access could assign or scan QR codes, view personal and clinical data and conduct the tests with the device. Prior to assigning QR codes to ANC attendees at their first B4M screening, health workers were trained to enrol pregnant women into the study using a structured information sheet that explained the study procedure, benefits, risks and confidentiality. Women confirmed consent with a signature or thumbprint. The device was introduced as an additional station in the existing ANC workflow and could be locked and securely stored when not in use.
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