BackgroundAccess to quality hypertension care is often poor in sub-Saharan Africa. Some community pharmacies offer hypertension monitoring services, with and without involvement of medical doctors. To directly connect pharmacy staff and cardiologists a care model including a mobile application (mHealth) for remote patient monitoring was implemented and pilot tested in Lagos, Nigeria. Pharmacists provided blood pressure measurements and counselling. Cardiologists enrolled patients in the pilot program and remotely monitored them, for which patients paid a monthly fee. We evaluated the feasibility of this care model at five private community pharmacies. Outcome measures were retention in care, blood pressure change, quality of care, and patients’ and healthcare providers’ satisfaction with the care model.MethodsPatients participated in the care model’s pilot at one of the five pharmacies for approximately 6–8 months from February 2016. We conducted structured patient interviews and blood pressure measurements at pilot entry and exit, and used exports of the mHealth-application, in-depth interviews and focus group discussions with patients, pharmacists and cardiologists.ResultsOf 336 enrolled patients, 236 (72%) were interviewed at pilot entry and exit. According to the mHealth data 71% returned to the pharmacy after enrollment, with 3.3 months (IQR: 2.2–5.4) median duration of activity in the mHealth-application. Patients self-reported more visits than recorded in the mHealth data. Pharmacists mentioned use of paper records, understaffing, the application not being user-friendly, and patients’ unwillingness to pay as reasons for underreporting. Mean systolic blood pressure decreased 9.9 mmHg (SD: 18). Blood pressure on target increased from 24 to 56% and an additional 10% had an improved blood pressure at endline, however this was not associated with duration of mHealth activity. Patients were satisfied because of accessibility, attention, adherence and information provision.ConclusionPatients, pharmacists and cardiologists adopted the care model, albeit with gaps in mHealth data. Most patients were satisfied, and their mean blood pressure significantly reduced. Usage of the mHealth application, pharmacy incentives, and a modified financing model are opportunities for improvement. In addition, costs of implementation and availability of involved healthcare providers need to be investigated before such a care model can be further implemented.Electronic supplementary materialThe online version of this article (10.1186/s12913-018-3740-3) contains supplementary material, which is available to authorized users.

BackgroundSouth Africa has a large burden of rifampicin-resistant tuberculosis (RR-TB), with 18,734 patients diagnosed in 2014. The number of diagnosed patients has increased substantially with the introduction of the Xpert MTB/RIF test, used for tuberculosis (TB) diagnosis for all patients with presumptive TB. Routine aggregate data suggest a large treatment gap (pre-treatment loss to follow-up) between the numbers of patients with laboratory-confirmed RR-TB and those reported to have started second-line treatment. We aimed to assess the impact of Xpert MTB/RIF implementation on the delay to treatment initiation and loss to follow-up before second-line treatment for RR-TB across South Africa.Methods and findingsA nationwide retrospective cohort study was conducted to assess second-line treatment initiation and treatment delay among laboratory-diagnosed RR-TB patients. Cohorts, including approximately 300 sequentially diagnosed RR-TB patients per South African province, were drawn from the years 2011 and 2013, i.e., before and after Xpert implementation. Patients with prior laboratory RR-TB diagnoses within 6 mo and currently treated patients were excluded. Treatment initiation was determined through data linkage with national and local treatment registers, medical record review, interviews with health care staff, and direct contact with patients or household members. Additional laboratory data were used to track cases. National estimates of the percentage of patients who initiated treatment and time to treatment were weighted to account for the sampling design.There were 2,508 and 2,528 eligible patients in the 2011 and 2013 cohorts, respectively; 92% were newly diagnosed with RR-TB (no prior RR-TB diagnoses). Nationally, among the 2,340 and 2,311 new RR-TB patients in the 2011 and 2013 cohorts, 55% (95% CI 53%–57%) and 63% (95% CI 61%–65%), respectively, started treatment within 6 mo of laboratory receipt of their diagnostic specimen (p < 0.001). However, in 2013, there was no difference in the percentage of patients who initiated treatment at 6 mo between the 1,368 new RR-TB patients diagnosed by Xpert (62%, 95% CI 59%–65%) and the 943 diagnosed by other methods (64%, 95% CI 61%–67%) (p = 0.39). The median time to treatment decreased from 44 d (interquartile range [IQR] 20–69) in 2011 to 22 d (IQR 2–43) in 2013 (p < 0.001). In 2013, across the nine provinces, there were substantial variations in both treatment initiation (range 51%–73% by 6 mo) and median time to treatment (range 15–36 d, n = 1,450), and only 53% of the 1,448 new RR-TB patients who received treatment were recorded in the national RR-TB register.This retrospective study is limited by the lack of information to assess reasons for non-initiation of treatment, particularly pre-treatment mortality data. Other limitations include the use of names and dates of birth to locate patient-level data, potentially resulting in missed treatment initiation among some patients.ConclusionsIn 2013, there was a large treatment gap for RR-TB in South Africa that v...

BackgroundTargeted global efforts to improve survival of young adults need information on mortality trends; contributions from health and demographic surveillance system (HDSS) are required.Methods and FindingsThis study aimed to explore changing trends in deaths among adolescents (15–19 years) and young adults (20–24 years), using census and verbal autopsy data in rural western Kenya using a HDSS. Mid-year population estimates were used to generate all-cause mortality rates per 100,000 population by age and gender, by communicable (CD) and non-communicable disease (NCD) causes. Linear trends from 2003 to 2009 were examined. In 2003, all-cause mortality rates of adolescents and young adults were 403 and 1,613 per 100,000 population, respectively, among females; and 217 and 716 per 100,000, respectively, among males. CD mortality rates among females and males 15–24 years were 500 and 191 per 100,000 (relative risk [RR] 2.6; 95% confidence intervals [CI] 1.7–4.0; p<0.001). NCD mortality rates in same aged females and males were similar (141 and 128 per 100,000, respectively; p = 0.76). By 2009, young adult female all-cause mortality rates fell 53% (χ2 for linear trend 30.4; p<0.001) and 61.5% among adolescent females (χ2 for linear trend 11.9; p<0.001). No significant CD mortality reductions occurred among males or for NCD mortality in either gender. By 2009, all-cause, CD, and NCD mortality rates were not significantly different between males and females, and among males, injuries equalled HIV as the top cause of death.ConclusionsThis study found significant reductions in adolescent and young adult female mortality rates, evidencing the effects of targeted public health programmes, however, all-cause and CD mortality rates among females remain alarmingly high. These data underscore the need to strengthen programmes and target strategies to reach both males and females, and to promote NCD as well as CD initiatives to reduce the mortality burden amongst both gender.