Correction: Analyzing data from the digital healthcare exchange platform for surveillance of antibiotic prescriptions in primary care in urban Kenya: A mixed-methods study.

[This corrects the article DOI: 10.1371/journal.pone.0222651.].

Implementation of an international standardized set of outcome indicators in pregnancy and childbirth in Kenya: Utilizing mobile technology to collect patient-reported outcomes.

BACKGROUND: Limited data exist on health outcomes during pregnancy and childbirth in low- and middle-income countries. This is a pilot of an innovative data collection tool using mobile technology to collect patient-reported outcome measures (PROMs) selected from the International Consortium of Health Outcomes Measurement (ICHOM) Pregnancy and Childbirth Standard Set in Nairobi, Kenya. METHODS: Pregnant women in the third trimester were recruited at three primary care facilities in Nairobi and followed prospectively throughout delivery and until six weeks postpartum. PROMs were collected via mobile surveys at three antenatal and two postnatal time points. Outcomes included incontinence, dyspareunia, mental health, breastfeeding and satisfaction with care. Hospitals reported morbidity and mortality. Descriptive statistics on maternal and child outcomes, survey completion and follow-up rates were calculated. RESULTS: In six months, 204 women were recruited: 50% of women returned for a second ante-natal care visit, 50% delivered at referral hospitals and 51% completed the postnatal visit. The completion rates for the five PROM surveys were highest at the first antenatal care visit (92%) and lowest in the postnatal care visit (38%). Data on depression, dyspareunia, fecal and urinary incontinence were successfully collected during the antenatal and postnatal period. At six weeks postpartum, 86% of women breastfeed exclusively. Most women that completed the survey were very satisfied with antenatal care (66%), delivery care (51%), and post-natal care (60%). CONCLUSION: We have demonstrated that it is feasible to use mobile technology to follow women throughout pregnancy, track their attendance to pre-natal and post-natal care visits and obtain data on PROM. This study demonstrates the potential of mobile technology to collect PROM in a low-resource setting. The data provide insight into the quality of maternal care services provided and will be used to identify and address gaps in access and provision of high quality care to pregnant women.

Analyzing data from the digital healthcare exchange platform for surveillance of antibiotic prescriptions in primary care in urban Kenya: A mixed-methods study.

BACKGROUND: Knowledge of antibiotic prescription practices in low- and middle-income countries is limited due to a lack of adequate surveillance systems. OBJECTIVE: To assess the prescription of antibiotics for the treatment of acute respiratory tract infections (ARIs) in primary care. METHOD: An explanatory sequential mixed-methods study was conducted in 4 private not-for-profit outreach clinics located in slum areas in Nairobi, Kenya. Claims data of patients who received healthcare between April 1 and December 27, 2016 were collected in real-time through a mobile telephone-based healthcare data and payment exchange platform (branded as M-TIBA). These data were used to calculate the percentage of ARIs for which antibiotics were prescribed. In-depth interviews were conducted among 12 clinicians and 17 patients to explain the quantitative results. RESULTS: A total of 49,098 individuals were registered onto the platform, which allowed them to access healthcare at the study clinics through M-TIBA. For 36,210 clinic visits by 21,913 patients, 45,706 diagnoses and 85,484 medication prescriptions were recorded. ARIs were the most common diagnoses (17,739; 38.8%), and antibiotics were the most frequently prescribed medications (21,870; 25.6%). For 78.5% (95% CI: 77.9%, 79.1%) of ARI diagnoses, antibiotics were prescribed, most commonly amoxicillin (45%; 95% CI: 44.1%, 45.8%). These relatively high levels of prescription were explained by high patient load, clinician and patient perceptions that clinicians should prescribe, lack of access to laboratory tests, offloading near-expiry drugs, absence of policy and surveillance, and the use of treatment guidelines that are not up-to-date. Clinicians in contrast reported to strictly follow the Kenyan treatment guidelines. CONCLUSION: This study showed successful quantification of antibiotic prescription and the prescribing pattern using real-world data collected through M-TIBA in private not-for-profit clinics in Nairobi.