Effectiveness of an mHealth system on access to eye health services in Kenya: a cluster-randomised controlled trial.

BACKGROUND: There is limited access to eye health services in many low-income and middle-income populations. We aimed to assess the effectiveness in increasing service utilisation of the Peek Community Eye Health (Peek CEH) system, a smartphone-based referral system comprising decision support algorithms (Peek Community Screening app), SMS reminders, and real-time reporting. METHODS: In this cluster-randomised controlled trial of eye health in Kenya, community unit clusters were defined as one health centre and its catchment population. Clusters were randomly allocated (1:1) to receive Peek CEH and referral (intervention group) or standard care via periodic health centre-based outreach clinics and onward referral (control group). Individuals in the intervention group were assessed at home by screeners and those referred were asked to present for triage assessment in a central location. They received regular SMS reminders. In both groups, community sensitisation was done followed by a triage clinic at the cluster health centre 4 weeks after sensitisation. During triage, individuals in both groups were assessed and treated and, if necessary, referred to a specific hospital. Individuals in the intervention group received further SMS reminders. The primary outcome was the mean attendance rate (the number of people per 10 000 population) at triage of those with confirmed eye conditions, as assessed at 4 weeks after sensitisation in the intention-to-treat population. We estimated the intervention effect using a Student's t-test on cluster-level rates. This trial is registered with Pan African Clinical Trial Registry, number 201807329096632. FINDINGS: Between Nov 26, 2018, and June 7, 2019, of the 85 community units in Trans Nzoia County, Kenya, 49 were excluded. We randomly allocated 18 community units each to the intervention group (68 348 individuals) and the control group (60 243 individuals). 9387 individuals from the intervention group and 3070 from the control group attended triage assessment. The mean attendance rate at triage by individuals with eye problems was 1429 (92% CI 1228-1629) in the intervention group and 522 (418-625) in the control group (rate difference 906 per 10 000 [95% CI 689-1124; p<0·0001]). INTERPRETATION: The Peek CEH system increased primary care attendance by people with eye problems compared with standard approaches, indicating the potential of this mobile health package to increase service uptake and guide appropriate task sharing. FUNDING: The Queen Elizabeth Diamond Jubilee Trust and Wellcome Trust.

Smartphone-Guided Algorithms for Use by Community Volunteers to Screen and Refer People With Eye Problems in Trans Nzoia County, Kenya: Development and Validation Study.

BACKGROUND: The provision of eye care services is currently insufficient to meet the requirements of eye care. Many people remain unnecessarily visually impaired or at risk of becoming so because of treatable or preventable eye conditions. A lack of access and awareness of services is, in large part, a key barrier to handle this unmet need. OBJECTIVE: This study aimed to assess whether utilizing novel smartphone-based clinical algorithms can task-shift eye screening to community volunteers (CVs) to accurately identify and refer patients to primary eye care services. In particular, we developed the Peek Community Screening app and assessed its validity in making referral decisions for patients with eye problems. METHODS: We developed a smartphone-based clinical algorithm (the Peek Community Screening app) using age, distance vision, near vision, and pain as referral criteria. We then compared CVs' referral decisions using this app with those made by an experienced ophthalmic clinical officer (OCO), which was the reference standard. The same participants were assessed by a trained CV using the app and by an OCO using standard outreach equipment. The outcome was the proportion of all decisions that were correct when compared with that of the OCO. RESULTS: The required sensitivity and specificity for the Peek Community Screening app were achieved after seven iterations. In the seventh iteration, the OCO identified referable eye problems in 65.9% (378/574) of the participants. CVs correctly identified 344 of 378 (sensitivity 91.0%; 95% CI 87.7%-93.7%) of the cases and correctly identified 153 of 196 (specificity 78.1%; 95% CI 71.6%-83.6%) cases as not having a referable eye problem. The positive predictive value was 88.9% (95% CI 85.3%-91.8%), and the negative predictive value was 81.8% (95% CI 75.5%-87.1%). CONCLUSIONS: Development of such an algorithm is feasible; however, it requires considerable effort and resources. CVs can accurately use the Peek Community Screening app to identify and refer people with eye problems. An iterative design process is necessary to ensure validity in the local context.

Utilization of Secondary Eye Care Services in Western Kenya.

Background: Eye care provision is currently insufficient to meet the population's eye health needs in Kenya. Many people remain unnecessarily visually impaired or at risk of becoming so due to treatable or preventable conditions. A lack of access and awareness of services are key barriers, in large part due to their being too few eye care providers in the health system for this unmet need. Methods: A hospital-based, retrospective analysis of patients who attended Kitale eye unit, Trans Nzoia County, Kenya from 1st January 2013 to 31st December 2015. Age and sex standardized hospital attendance rates by residence, age group, and sex were calculated for Trans Nzoia county and each subcounty. The changing trends in attendance rates were estimated by calculating the difference between base year and last year. Incidence rate ratios for attendance for each age-group, sex, and residence were estimated using a multivariable regression model. Results: 20,695 patients from the county were seen in Kitale Eye Unit in 2013, 2014 and 2015. In that period, 8.3% had either uncorrected refractive error, cataracts or glaucoma, the priority VISION2020 diseases, and 61.0% had allergic or other conjunctivitis or normal eyes, which could potentially be managed at primary eye care. During the study period, overall average annual attendance rate increased from 609 to 792 per 100, 000 population, incidence rate ratio (IRR) 1.30 (95% confidence interval (CI) 1.26-1.35). Attendance rates increased more in females than males (34.7% vs. 25.1%, respectively), IRR 1.07 (1.04-1.10). Attendance rates increased with increasing age, (highest among the elderly compared to the young). We found that in extreme age groups (>75 years and <15years) females were less likely to attend than males and there was reduced utilization from those based furthest from the hospital. Conclusion: Specialist eye services are heavily utilized by people with conditions that could be managed at the primary health care level. Barriers to accessing eye services were distance and gender, especially among the most vulnerable groups (young and the elderly). Integration of primary and secondary eye care services could lower barriers to essential eye care services to the population whilst lowering pressure on the limited specialist services by ensuring more appropriate utilization.

Peek Community Eye Health - mHealth system to increase access and efficiency of eye health services in Trans Nzoia County, Kenya: study protocol for a cluster randomised controlled trial.

BACKGROUND: Globally, eye care provision is currently insufficient to meet the requirement for eye care services. Lack of access and awareness are key barriers to specialist services; in addition, specialist services are over-utilised by people with conditions that could be managed in the community or primary care. In combination, these lead to a large unmet need for eye health provision. We have developed a validated smartphone-based screening algorithm (Peek Community Screening App). The application (App) is part of the Peek Community Eye Health system (Peek CEH) that enables Community Volunteers (CV) to make referral decisions about patients with eye problems. It generates referrals, automated short messages service (SMS) notifications to patients or guardians and has a program dashboard for visualising service delivery. We hypothesise that a greater proportion of people with eye problems will be identified using the Peek CEH system and that there will be increased uptake of referrals, compared to those identified and referred using the current community screening approaches. STUDY DESIGN: A single masked, cluster randomised controlled trial design will be used. The unit of randomisation will be the 'community unit', defined as a dispensary or health centre with its catchment population. The community units will be allocated to receive either the intervention (Peek CEH system) or the current care (periodic health centre-based outreach clinics with onward referral for further treatment). In both arms, a triage clinic will be held at the link health facility four weeks from sensitisation, where attendance will be ascertained. During triage, participants will be assessed and treated and, if necessary, referred onwards to Kitale Eye Unit. DISCUSSION: We aim to evaluate a M-health system (Peek CEH) geared towards reducing avoidable blindness through early identification and improved adherence to referral for those with eye problems and reducing demand at secondary care for conditions that can be managed effectively at primary care level. TRIAL REGISTRATION: The Pan African Clinical Trials Registry (PACTR), 201807329096632 . Registered on 8 June 2018.

Smartphone-based screening for visual impairment in Kenyan school children: a cluster randomised controlled trial.

BACKGROUND: Childhood visual impairment is a major public health concern that requires effective screening and early intervention. We investigated the effectiveness of Peek school eye health, a smartphone-based sight test and referral system (comprising Peek Acuity test, sight simulation referral cards, and short message service [SMS] reminders), versus standard care (Snellen's Tumbling-E card and written referral). METHODS: We initially compared the performance of both the Snellen Tumbling-E card and the Peek Acuity test to a standard backlit EDTRS LogMAR visual acuity test chart. We did a cluster randomised controlled trial to compare the Peek school eye health system with standard school screening care, delivered by school teachers. Schools in Trans Nzoia County, Kenya, were eligible if they did not have an active screening programme already in place. Schools were randomly allocated (1:1) to either the Peek school eye health screening and referral programmes (Peek group) or the standard care screening and referral programme (standard group). In both groups, teachers tested vision of children in years 1-8. Pupils with visual impairment (defined as vision less than 6/12 in either eye) were referred to hospital for treatment. Referred children from the standard group received a written hospital referral letter. Participants and their teachers in the Peek group were shown their simulated sight on a smartphone and given a printout of this simulation with the same hospital details as the standard referral letter to present to their parent or guardian. They also received regular SMS reminders to attend the hospital. The primary outcome was the proportion of referred children who reported to hospital within 8 weeks of referral. Primary analysis was by intention to treat, with the intervention effect estimated using odds ratios. This trial is registered with Pan African Clinical Trial Registry, number PACTR201503001049236. FINDINGS: Sensitivity was similar for the Peek test and the standard test (77% [95% CI 64·8-86·5] vs 75% [63·1-85·2]). Specificity was lower for the Peek test than the standard test (91% [95% CI 89·3-92·1] vs 97·4% [96·6-98·1]). Trial recruitment occurred between March 2, 2015, and March 13, 2015. Of the 295 eligible public primary schools in Trans Nzoia County, 50 schools were randomly selected and assigned to either the Peek group (n=25) or the standard group (n=25). 10 579 children were assessed for visual impairment in the Peek group and 10 284 children in the standard group. Visual impairment was identified in 531 (5%) of 10 579 children in the Peek group and 366 (4%) of 10 284 children in the standard care group. The proportion of pupils identified as having visual impairment who attended their hospital referral was significantly higher in the Peek group (285 [54%] of 531) than in the standard group (82 [22%] of 366; odds ratio 7·35 [95% CI 3·49-15·47]; p<0·0001). INTERPRETATION: The Peek school eye health system increased adherence to hospital referral for visual impairment assessment compared with the standard approach among school children. This indicates the potential of this technology package to improve uptake of services and provide real-time visibility of health service delivery to help target resources. FUNDING: Seeing is Believing, Operation Eyesight Universal, Queen Elizabeth Diamond Jubilee Trust, and Wellcome Trust.