Increasing Vision Center Service Utilization

The Global Action Plan for Universal Eye Health emphasizes the importance of providing basic eyecare to all individuals, \& the communities they constitute, at affordable rates. In India, PEC is delivered through two main mechanisms. Transient screening camps and permanent facilities- vision centers (VCs) with catchment areas of roughly 50,000 people, located in rural areas \& urban slums \& accessible by public transport. They refract, diagnose \& treat minor eye conditions \& refer cases needing further care to their nearest base hospital. The literature on barriers to PEC in India is limited but points to lack of knowledge about eye diseases, detrimental social stigmas, low priority being accorded to eye problems, gender discrimination, unaffordability, lack of perceived need as well as immobility \& dependence on escorts. These barriers potentially affect the operational sustainability of VCs-in large part by the number of walk-in patients. Our organization is a network of eye care delivery mechanisms based on the pyramidal model; spread across north India. 36 VCs (9 urban \& 27 rural) are under operation; raising awareness, providing refraction, recognition \& referral services to their catchment population \& increasing contact of those in need of services. For the majority of people, these are the first point of contact when accessing or attempting to access eye care services. Developing trust \& high referrals to these VCs, from the entire catchment population they service, is essential for the overall sustainability of these centers \& to increase the ambit of PEC delivery. This protocol aims to study the effect of an intervention combining door-to-door screening with regular awareness activities in the catchment population on the service utilization at VCs.

Study Design \& Process: Randomized experimental intervention, in which four VCs are selected: two each in the intervention \& control arms (one each from a particular operational area). Our organization has 6 secondary centers (SCs), of which 4 are located in the state of Uttar Pradesh, namely, Meerut, Mathura, Saharanpur \& Kheri. These regions have a total of 23 VCs operating in rural \& semi-urban areas, together serving around 1 million people. Of these 4 SCs, 2 were selected (Vrindavan in Mathura district \& Mohammadi in Kheri district) for this study based on feasibility \& the demographic profile of their catchment population. The Vrindavan region has 8 VCs delivering eyecare services in its' semi-urban areas while the Mohammadi region has 6 VCs (5 rural \& 1 semi-urban). Most of these VCs have been operational for over 3 years. However, the previous year's data indicated that 80% of VCs as sub-optimal in performance. The sub-optimal VCs were listed. From a total of 10 VCs (5 in each region, meeting the inclusion/exclusion criteria), 2 were randomly selected from each: one each for the control \& intervention arms. The VCs in the 2 blocks of the Mathura district were located at Chhata \& Raya, respectively, while the 2 VCs from 2 blocks of Kheri district were located at Mitauli \& Pashgaon. Due to the nature of the study, it was impossible to mask the field staff to the intervention.

Inclusion/Exclusion Criteria: The regional team gathered detailed information regarding all VCs operating in the Vrindavan \& Mohammadi region. VCs were included based on the following criteria:

Low performance (walk-in OPD ≤ 10/day) Duration of operation >1 year Presence of 1 VC in each arm from selected VCs VCs with a walk-in OPD greater than 10 per day \& those in operation for less than one year were excluded.

Study Setting: Mathura district has a population of about 2.5 million, 70% resident in rural areas. Kheri district has a population of 4 million- 88% residents in rural areas. Chhata block, in Mathura, has 81 villages with 30 within 10km of the VC. These 30 have a combined population of 70,000. On the other hand, Raya block has 124 villages with 90 within 10km of the VC, having a combined population of 130,000. In Kheri, the Mitauli block has 138 villages with 75 within 10km of the VC. The combined population is around 111,000. Pashgaon block has 230 villages with 85 within 10km of the VC, a population of around 110,000.

Sample Size: Average OPD attendance at the intervention VCs is 7/day, at present. The investigators expect to achieve 14 after the intervention, failing which, the intervention will not be considered a success. Therefore, the primary objective of the statistical analysis should be to estimate the average attendance, post-intervention, with extreme precision which leads us to assess if the investigators have been able to achieve the target (14 per day on average). The investigators set the confidence interval ±1 for the post-intervention sample mean (the narrowest possible confidence interval in this case). To check if at least 20 per day on average has been achieved, the investigators expect a sample mean of at least 21 (i.e. the confidence interval will be 20-22). The investigators assume that the probability of the confidence interval is 95%, \& the daily OPD attendance has a Poisson distribution. Thus, the investigators expect that the post-intervention daily attendance has a Poisson distribution with a mean of at least 21. It implies that the variance of the distribution also equals 21 (or more), \& the investigators want to estimate the mean with a 95% confidence interval of ±1. It requires a minimum sample size of 81 days.

The investigators have used the following formula to calculate the sample size:

Sample Size= 〖1.96〗^2/d^2 x variance of the distribution Where 1.96 is the 97.5 percentile point of the standard normal distribution, d is the length of the confidence interval (on one side of the estimate). d=1 \& variance=21 give sample size=81. The investigators had put a target of 20 in the pre-COVID time but due to the pandemic, the investigators have revised our desired target to 14 per day to consider the intervention a success. The investigators have persisted with the additional days in the sample size (instead of 58 days for a target of 14) to be able to estimate up to 14 per day OPD with precision.

Intervention arm: The intervention will include door-to-door screening \& awareness generation in 8-12 villages surrounding the intervention VC. The VC team will be trained in using the PEEK acuity20 application for measuring visual acuity \& using the data collection software (Taraka) on android platforms. A list of surrounding villages (within 10km) will be prepared by the Vision Centre Coordinator \& the VC attendant. The Vision Centre Coordinator will meet the village leader to take permission for the door-to-door intervention survey to be carried out in the village. After having received the necessary permissions, a priority list of survey villages would be prepared to initiate the intervention. In the intervention villages, the VC attendant will go from door to door. During the screening, if any house is locked or family members are not available, the attendant will attempt to contact those missing at least 3 times. The attendant will explain the intervention \& obtain consent for participation in the survey. Household or family members, who are unwilling or not interested to participate in the survey, will also be recorded separately. After obtaining consent, the attendant will communicate regarding the need for eye care in general \& share the IEC material. For each family member above 5 years of age, the visual acuity of each eye will be taken \& recorded using the PEEK application on a smartphone. Demographic data, ocular complaints \& information regarding any previous eye check-up would be also be recorded in the android application. Any person with a visual acuity <6/12 (cut-off) or other eye issues would be counseled \& referred for a comprehensive examination to the vision center. A referral slip will be provided to referred patients along with a reason for referral. Referred patients' records will be available to the Vision Technician (optometrist) through the software. Patients reporting to the VC for a comprehensive check-up \& treatment, due to the door-to-door intervention will be recorded in the vision center management software (VCMS). Any patient requiring surgical treatment or further care will be referred to the respective secondary center.

Control Arm: The control arm VC will continue its routine awareness activities \& health talk sessions in the community. The VC attendant will prepare a monthly activity plan \& organize activities in the surrounding 8-10 villages. Persons with eye issues will be recorded \& referred to the VC for further evaluation \& treatment. Patients reporting to the VC will be registered in the VCMS. For surgical interventions or further care, patients will be referred to the respective SC. The activities will be the same in both the arms \& will also be standardized in the same manner. Only their mode \& reach will be different.

Project Timelines: The study period will be 12 months. Two months will be spent preparing the study intervention \& obtaining approvals, three months will be needed for pre-intervention work i.e. training the team, field preparation, finalizing a data collection format \& IEC development, four months for the intervention \& data collection. After data collection, the remaining three months will be used for data analysis \& writing.

Data Collection \& Variables: Both electronic \& manual data collection for both arms. Intervention arm-field level data (door-to-door survey) through software; Control arm-field level activity in the activity register manually. VC level data would be extracted from the VCMS, for both control \& intervention VCs. In both arms, programmatic data will be collected, which includes data regarding the villages screened, door-to-door screening, walk-in OPD, those reporting after referrals from the field, spectacles advised \& their uptake, as well as referral for cataract, specialty \& surgical follow-up. Cost data will be collected for direct, indirect \& opportunity costs like rent, human resources, overheads \& community activities. Also, data for revenue from OPD, spectacles \& surgery done.

Quality Assurance: Three sources of data: door-to-door screening data will be collected through the customized android application, data of patients visiting VCs will be captured through VCMS \& additional data pertaining to activities from the control VCs \& staff visits would be collected on the registers. The software has checks \& balances ensuring complete data collection. Manual data collection will be standardized through a checklist. Random monitoring visits will be made periodically to the field. Data collected during the day will be uploaded on the cloud server at least once at the end of the day for review. Data quality will be ensured by clearly defined roles, appropriate resource allocation \& regular meetings with the team members. A regular review process will be followed to ensure quality data collected \& at least 10% of it will be verified by field supervisors. Surgery-related data of SC referrals would be extracted from the SC EMRs. Data would be collated monthly as a part of routine program monitoring.

Data Analysis: Collected data would be tabulated \& analyzed by arm: distance of village; age; gender; eye issues; visual acuity; compliance with treatment- medicine, surgery, glasses \& revenue \& expenditure of VC. The difference from baseline in the number of walk-in patients, referrals, uptake of services \& costs involved in intervention would be analyzed. Z-test will be used to compare the change in walk-in patients between the two arms. A P-value of less than 0.05 would be considered significant.

Cost-Effectiveness Analysis: Cost-effectiveness analysis (CEA) \& Incremental CEA will be performed. The incremental cost for every additional beneficiary attending the VC will be calculated. To calculate the increase in patients, the average number visiting per day during the same months last year would be subtracted from the average in the study period. Change in control VC, if any, would also be deducted before using this as the denominator for calculation.