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Background: Ultrasound for gestational age (GA) assessment is not routinely available in resource-constrained settings, particularly in rural and remote locations. The TraCer device combines a handheld wireless ultrasound probe and a tablet with artificial intelligence (AI)-enabled software that obtains GA from videos of the fetal head by automated measurements of the fetal transcerebellar diameter and head circumference. Objective: The aim of this study was to assess the perceptions of pregnant women, their families, and health care workers regarding the feasibility and acceptability of the TraCer device in an appropriate setting. Methods: A descriptive study using qualitative methods was conducted in two public health facilities in Kilifi county in coastal Kenya prior to introduction of the new technology. Study participants were shown a video role-play of the use of TraCer at a typical antenatal clinic visit. Data were collected through 6 focus group discussions (N=52) and 18 in-depth interviews. Results: Overall, TraCer was found to be highly acceptable to women, their families, and health care workers, and its implementation at health care facilities was considered to be feasible. Its introduction was predicted to reduce anxiety regarding fetal well-being, increase antenatal care attendance, increase confidence by women in their care providers, as well as save time and cost by reducing unnecessary referrals. TraCer was felt to increase the self-image of health care workers and reduce time spent providing antenatal care. Some participants expressed hesitancy toward the new technology, indicating the need to test its performance over time before full acceptance by some users. The preferred cadre of health care professionals to use the device were antenatal clinic nurses. Important implementation considerations included adequate staff training and the need to ensure sustainability and consistency of the service. Misconceptions were common, with a tendency to overestimate the diagnostic capability, and expectations that it would provide complete reassurance of fetal and maternal well-being and not primarily the GA. Conclusions: This study shows a positive attitude toward TraCer and highlights the potential role of this innovation that uses AI-enabled automation to assess GA. Clarity of messaging about the tool and its role in pregnancy is essential to address misconceptions and prevent misuse. Further research on clinical validation and related usability and safety evaluations are recommended.
A cross-sectional, descriptive, qualitative study was conducted in two public health facilities in Kilifi county in coastal Kenya. The two health facilities are the rural Rabai Health Centre (primary care facility) and the larger, urban Mariakani Sub-county Hospital (secondary care facility). Both facilities would later participate in the PRECISE (Pregnancy Care Integrating Translational Science, Everywhere) pregnancy cohort study [20]. At the time of data collection, enrollment to the PRECISE cohort had not yet started. ANC, routine delivery care, and emergency care for pregnancy complications are provided primarily by nurses/nurse-midwives with support by clinical officers (nonphysician clinicians) at both facilities. At Mariakani Hospital, doctors and an obstetrician/gynecologist provide specialist services for high-risk pregnancies. Ultrasound services are not available routinely, but can be undertaken at Mariakani Hospital (and other private facilities) upon referral for pregnancy complications or uncertainties regarding GA. We sought to enroll two main groups of participants: (1) HCWs directly involved in the provision of services for pregnant women, as well as managers and health administrators; and (2) community members, represented by pregnant women participating in ANC and their family members (partners, as well as the pregnant woman’s parents and parents-in-law). HCWs were purposely sampled to cover providers at the ANC clinic, maternity, outpatient, and radiology (including ultrasound) departments. Health administrators were also purposely sampled to ensure inclusion of facility and subcounty managers overseeing reproductive health services. Pregnant women were approached by research assistants when they presented for routine ANC, and participating women could invite their partners or parents. Data were collected between March and May 2019 by two Kenyan researchers: a social scientist (PMM) and a maternal health researcher and obstetrician (AK), who were assisted by two trained local research assistants who took notes during the sessions. Researchers were familiar with the local setting and the Kenyan health care system, and were fluent in both English and Swahili. The research assistants were also fluent in Mijikenda. None of the data collectors were involved in the participants’ clinical care; however, some HCWs had previous interactions with the two researchers as part of PRECISE study preparations. In-depth interviews (IDIs) with HCWs and focus group discussions (FGDs) with pregnant women and their families were conducted in person in private areas of the health facility, away from the clinical areas. We developed a semistructured interview guide, which was piloted on two HCWs at Rabai Health Centre and revised prior to the subsequent interviews. The topic guide began with simple assessment of prior exposure to computers, smartphones, and obstetric ultrasound, followed by a discussion on existing methods of assessing GA and the potential value to pregnant women and HCWs. The study was started before clinical implementation of TraCer. A video demonstrating its use during routine ANC was shown to participants. The 5-minute video, recorded at one of the facilities in Swahili, showed a nurse using TraCer with a pregnant woman who was unsure of her LMP. In the video, the nurse shows the mother the image of the fetal heartbeat and the head of the baby on the tablet screen, reports the GA, and then gives a date for the next clinic visit. Participants were encouraged to voice their thoughts and ask any questions during and immediately after watching the video. Participants were asked what they liked or disliked about TraCer as seen in the video, whether TraCer could be introduced to their health facility, how confident they would be in its findings, any outcomes (positive or negative) they expected with its introduction, the type of provider they thought could use TraCer, and whether they would recommend it to other pregnant women and health facilities. IDIs were conducted in the participants’ language of choice. HCWs preferred English, whereas pregnant women and their families preferred Swahili. All sessions were audio-recorded with permission and field notes were taken during each session. After each IDI and FGD, the research team debriefed to update field notes, discussed revisions and additional probes to the topic guide, and assessed data saturation. All recordings were transcribed verbatim in the language of the interview and translated to English (where applicable) by research assistants. A sample of transcripts was compared with the recordings to ensure accuracy. NVivo 12 (QSR International, Melbourne, Australia) was used to manage the transcripts, and to facilitate coding and collaborative data analysis. The data analysis team comprised three Kenyan researchers familiar with the study site and local languages (AK, PMM, GMM), including two who had participated in the data collection (AK, PMM) and two experienced Canadian social scientists (MWK, MV). The data analysis team first familiarized themselves with the transcripts. Employing a directed content analysis approach [21], the coding framework was developed deductively from the research question based on pre-existing definitions of acceptability and feasibility [22] that were modified to fit our study. Acceptability was assessed according to the perceptions of the appropriateness of TraCer to participant needs, preferences, and sociocultural norms, along with factors that would influence willingness to use the device. Feasibility was assessed according to perceptions on whether TraCer could be implemented in the study health facilities and factors required for its successful implementation. Major themes and subthemes were explored related to acceptability and feasibility. The coding framework (see Multimedia Appendix 1) was tested on three transcripts to refine and ensure agreement between coders. Transcripts were then divided between coders for analysis. Emergent common and divergent patterns of responses between participants were explored through discussion within the team. Factors that were considered included differences in the site characteristics (urban vs rural, level of facility, access to ultrasound), HCW characteristics (skill level/cadre and prior experience of ultrasound), and community member characteristics (age, gender). The study obtained ethical approval from Aga Khan University Institutional Ethical Research Committee (2018_REC_47), King’s College London (Ref HR-17/18-7855), and University of British Columbia (H18-02828). All participants provided individual written informed consent prior to research activities. Confidentiality and safe storage of the data were ensured through deidentification of transcripts and electronic storage in password-protected devices accessible only to members of the research team.
