Connected vision care for eradication of preventable blindness

Results of a field trial based on wireless mobile decision support system with real-time analytics

Nataraj Kuntagod, Sanjoy Paul, Senthil Kumaresan Accenture Technology Labs

Bangalore, India {Nataraj.S.Kuntagod, Sanjoy.Paul, Senthil. Kumaresan}@accenture.com

Bharat Balasubramaniam, Imtiaz Ahmed Sankara Eye Care Hospital

Coimbatore, India {Bharat Balasubramaniam, Imtiaz Ahmed}@sankaraeye.com

Abstract—90% of the visually impaired worldwide live in a low income setting, and 80% of all visual impairment can be prevented or cured provided, a timely care is given. A large portion of at risk population does not avail timely vision care due to low awareness and inability to afford nor access quality vision care. Generating high patient volumes by reaching out into the community is a general approach taken by many hospitals to provide quality and affordable vision care. However, all of them rely on semi-skilled field workers to reach out to the community. A significant challenge to the effectiveness of field workers is the paper-based systems they use to register patients, gather information about them, and analyze the collected data. The lack of online monitoring and access to real-time analytics makes the process inefficient when scaled across large geographies. This paper proposes a connected vision care wireless solution comprising of a mobile decision support system and an analysis and reporting server connected via an existing cellular infrastructure. This solution upgrades every field worker to a knowledge worker, enables automatic compliance and status tracking of patients, and provides real-time analysis for efficient program management. This paper highlights the improved efficiency of the vision care program achieved using the solution in a field trial conducted by Sankara Eye Care hospital in Tamil Nadu, India.

Index Terms—ICT, Healthcare, Mobile, mHealth, Vision Care, Community Outreach Programs

INTRODUCTION Blindness is fast becoming a problem of global proportions.

As per a WHO report [1], 285 million people have visual impairments and 90% of them live in low-income settings. Timely vision care can prevent 80% of all visual impairments.

For example, in India, providing vision care faces

numerous challenges, especially in the rural areas, where nearly 70% of India’s population live. These rural areas have little access to vision care of any kind. Usually there is no resident eye doctor, and a patient might have to travel up to 150 miles to undergo a surgery. Lack of awareness among

people about vision care aggravates the problem, resulting in the incidence of preventable and treatable blindness or low vision being highest among those with the fewest options.

A study conducted in Southern India indicated that a large proportion of people who require vision care did not do so [2], with cost and accessibility being the major factors. In order to make high quality vision care affordable and efficient, generating a high patient volume by reaching out into the community is one of the approaches taken [3].

However, a significant majority of ophthalmologist (82.3%) identified low training as a barrier to providing low vision care services in a community eye care setting, as most low vision care services are concentrated in cities, and there is a severe shortage of qualified healthcare staff in rural areas [4]. A recent study of training the primary health care workers in rural areas to recognize specific symptoms and signs and identifying people who need eye care referral by “task shifting” did not yield conclusive results [5]. For the outreach vision care to be effective, the comprehensiveness of the low vision care services offered, either by direct delivery of services or through an appropriate screening and referral network is necessary [6].

Programs such as Sankara Eye Care’s outreach program [7] aim to proactively reach out to potential patients among the high-risk groups (rural poor, elderly, and women) and ensure early detection through extensive field level screening and treatment programs. In 2012-13, Sankara Eye Care hospital conducted 2025 camps, 373,257 screenings, and 150,558 surgeries and this number has been steadily growing over the years with a 10% CAGR. The challenges faced are similar. There is a need for efficient skill enhancement of field workers, making sure only people with real vision problems attend the camp, to dispense routine vision care advices right at the patient’s door step, real-time monitoring of the field workers and camp effectiveness, efficient camp planning and tracking and reminding patients about vision care services

automatically. Not having these needs met is resulting in revenue leakage and missed opportunities to provide vision care services to the people who need them most. There are numerous instances of using wireless technologies to address some of these needs of community vision care. For example, using satellite links, outreach sites transmit digital images to a base hospital for analysis [8]. Aravind Eye hospital uses long distance Wi-fi networking to enable high quality video conferencing between camps and base hospital [9]. However, these solutions require the availability of electricity expensive equipment and people who are skilled in maintaining them – an impediment in rural areas. Another area that has seen tremendous growth is the availability of “smart phone based mobile apps” for vision care. As per [10], iPhone platform itself has 182 apps, but most of them had a low level of qualified professional involvement in the development, and designed for ophthalmologists and optometrists. For large scale delivery of vision care services via community based intervention, a comprehensive wireless digital solution that addresses efficient “task shifting” to field workers, camp site planning, household surveys, camp site examination and surgeries at empanelled hospital is required – piecemeal approach is not suitable. In this paper, we present results of a 700 patient field trial conducted in two districts of Tamil Nadu, India implemented using a smart tablet based wireless solution with reporting and analytics services on a Cloud platform. The pilot maximized the reach of each field worker, resulted in adherence to goals/targets due to online monitoring, enabled field workers to arrive at decision faster and provide timely intervention, and resulted in overall cost savings and wider coverage of patients due to improved efficiency of the entire planning process.

SANKARA COMMUNITY OUTREACH VISION CARE PROGRAM The Community Outreach program works in 4 phases – (I)

Camp Site Planning (II) Household Surveys (III) Camp Site Examination (IV) Surgeries at empanelled hospitals. Most care providers follow a similar process.

1. Field workers visit households near the planned camp

location, conduct preliminary vision tests to identify patients requiring surgery, and refers them to a nearby camp. Challenges: Referral quality depends upon the skill of field worker in identifying the appropriate patients.

2. Field workers maintain paper based records for each

patient surveyed and based on their judgment, refer them to camps for further tests. The data is collated and sent to the base hospital for any data analysis and planning support Challenges: It is a time consuming process, with higher chance of data error. Data consolidation takes time and happens with a lag

3. Field workers follow-up for the patients who did not visit

the camp when it was organized Challenges: It is difficult to monitor which patient did not visit and efficacy of follow-up after the camp is limited

4. Referred as well as walk-in patients arrive at the camps to

be tested Challenges: The quality of conversion from referred to surgery is low. It is difficult to track patients who are suggested delayed surgeries

5. Patients requiring surgery and who are fit to undertake surgery are referred to hospitals Challenges: Difficult to track post-surgery follow-ups

6. Camp planning at the start of the year Challenges: It is difficult to summarize camp performance, which can help in understanding if a follow-up camp is required at the same location. Unable to understand the extent of coverage through a camp, which can help in deciding future camp locations due to unavailability of real-time data and data visualization.

7. General administration of the program Challenges: With no real time monitoring, it is difficult to monitor field workers, leading to an estimated 10 days of absenteeism in a year by each field worker. Performance of field workers Vis a Vis plan or peer comparison is not possible

Technology intervention cannot solve all challenges and the field trial concentrated on improving the five levers shown in Fig. 1.

Fig. 1. Five areas where technology intervention can make an impact

More households covered by Field

Workers

Better conversion of referrals into surgery

Less absenteeism of Field Workers

Lower publicity costs

Less Review & Monitoring by HQ

Each survey takes lesser time; More days available for surveys as no weekly/ monthly data transfer from paper to computer

Accenture Vision Care Management System provides pre-defined rule based decision support, improving referral quality

HQ gets timely consolidated data and pre-defined reports, supporting decision making

Better tracking through Accenture Vision Care Management Systemleads to lower absenteeism

Targeted communication by sending SMS only to referred patients reduces publicity costs

CONNECTED VISION CARE USING MOBILE DECISION SUPPORT

SYSTEM AND CLOUD BASED REPORTING SERVICES

Fig. 2. Community vision care process flow

Fig. 2 depicts the workflow using the smart tablet based application supported by the reporting services in the cloud to optimize the vision care delivery in a community setting.

The following section explains the major components

in the connected vision care system [Fig 3].

Fig. 3. Client Server implementation of connected vision care

The wireless link manager resident on the mobile device shields the application from the status of link connection. As is very common in rural areas, the cellular connection is intermittent, and the application synchronizes the data when the connection is available, but can continue to work even without connecting to the server- with full functionality.

The decision support system provides rule based decision support to the outreach field worker [Fig. 4] and to the nurse and paramedical staff at the camp who provide patient counselling before they exit the camp [Fig. 5]. The rules embedded in the application makes the care giving uniform and consistent, irrespective of the skill of the fieldworker and paramedical staff at the camp, and speeds up the care giving process.

Fig. 4. Rule based decision support for field worker during household survey

Fig. 5. Rule based decision support for nurse/paramedical staff before patient exit the camp

GPS based location services are a drain on the battery life of the handheld tablet device, and becomes an impediment for field workers, as recharging of battery is difficult in rural areas due to intermittent electricity. The battery safe location services on the handheld optimizes the location services – switching from acquiring the location using a fine-grained GPS provider to a coarse-grained cell tower based location provider, based on the field worker’s context, thus extending battery life until the end of the day. All data entry is Geo tagged for GIS mapping. Automatically suggesting the nearest camp, generating alerts about patients who need care nearby or patients who did not turn up at the camp earlier are all features enabled by location services on the handheld device - improving the service delivery effectiveness.

Workflow manager ensures standardized data

collection procedure. Most data collection is via a drop down selection list, minimizing errors in data capture. Prefilling of patient address based on Geo-coordinates reduces monotonous

Field worker with Android

tablet application

Community vision care server

Household survey data

Real-time operational reports

Vision care advisory

Refer to Vision Camp

@Camp site

Prescription Medicine

Vision correction

Surgery referral

Schedule a follow-up

Rx

Household survey

Update patient examination data1

2b

2aor 3

4

5

6

Wireless link management

Android

Decision support system

{household survey & CAMP site }

Battery safe location tracking

Adaptive UX

Workflow manager

JAVA platform

GIS reports Performance report

Community care field worker

Nurse and paramedics at

CAMP site

Community care program manager

WAN wireless link

Cloud server

Android tablet

Patient Data

Systemic illness

Decision support system on Android

tablet

Location of the patient

Refer patient to nearest camp site

Provide vision care advisory

eye surgery history

Torch Light Examination

Vision Test –Snellen Chart

Vision complaints

or

Patient Data

Assets owned and access to facilities

Select patient for free or paid surgery

Provide advisory for follow up after

1 to 3 Months

Fitness level orDecision support

system on Android tablet

Financial status derived indirectly

data entry. The mobile application displays preventive vision care videos and multi-media content at the right time during the household survey.

Fig. 6. Role based user interface

Fig. 7. GIS visualization

The application provides role-based access and the user interface adapt itself to each role [Fig.6]. Every camp site personnel have the same application, but different workflow and user interface – based on the role, enabling efficient, consistent and error free vision care service delivery.

Data from the mobile application is Geo tagged and

stored in the server over GPRS/3G network when available. The base hospital staff can visualize the spread of the vision care program, the impact in multiple areas, possible next camp location and underserved areas - all in one dashboard in real-time [Fig.7]

The performance reports on the other hand generates detailed a based on the data collected at the camp site and the household survey and tracks the overall program metrics - goals vs. actual data at multiple level of stakeholders [Fig. 8]. We chose two locations for the field trial in the Southern Indian state of Tamil Nadu - Satyamangalam (Erode district), Devanurpudur (Tirupur District), with a referral base at Sankara Eye Hospital in Coimbatore (Tamil Nadu, India).

Within each location, six villages participated in the field trial. 2 weeks before the camp date, two field workers per village carried out the household survey. Both the existing mechanism of delivering vision service and the connected vision care solution ran in parallel – to ensure external environmental conditions remain exactly same for both methods. Sankara eye care hospital conducted the field trial for a month, with 700 patients screened through the connected vision care system.

Fig. 8. Goals vs Actual – Performance of a field worker

RESULTS

Fig. 9. Torch light examination and data capture using connected vision care

solution

Fig. 10. Camp site – data capture and decision support

Table 1 summarizes the entire trial findings around the five key levers we discussed in Fig. 1. Existing

process With Connected vision care solution

Household coverage by field workers Number of Surveys /Day / Field worker

24 42

Number of referral card /Day /Field worker

6 20

Number of patients who turn up to the camp /Month /Field worker

24 135

Conversion of referrals to surgery Number of patients who are selected for surgery /month / field worker

4 67

Absenteeism of field workers Number of days in a month each field worker is absent without informing the Team Lead

1 0

Reduction in monitoring and planning cost

1/12th

1/7th Reduction in publicity cost

Table 1 Summary results of the field trial

A. Increase in household coverage by field workers Data capture via selection-based input, prefilling of address and embedded workflow made the data entry faster. Multimedia content and vision charts in the mobile application reduced the burden of carrying paper charts, books, and visual literacy material and made the field worker more physically mobile, enabling them to reach more households in the given time. The data input time reduced from 17 to 10 min with zero transcription error. Households were more enthusiastic to

participate in the survey as the field worker with a tablet device was perceived to be more credible– a great perception advantage. Decision support system on the handheld device reduced the referral decision time and increased the referral from six to twenty per day, with consistency in referral recommendation maintained across all field workers. The application helped to identify drop out patients and repeatedly reminded patients about the upcoming camps and surgeries. The timely and targeted reminders increased the patients attending the camp from 24 to 135 per field worker/month

B. Increase in conversion of referrals to surgery The quality of referrals to the camp improved and the

decision support system (DSS) turned the field worker to a knowledge worker, referring only patients who needed advanced care by a qualified doctor to the camp. Conversion of referrals to surgery increased from 4 to 69 – a marked improved in the quality of the patient referral.

C. Reduction in absenteeism of field workers While there was no absenteeism during the trial period, the

result was not conclusive. However, qualitatively, we observed the field workers to be more careful in their attendance.

D. Reduction in monitoring cost With GIS dashboards, surveys & camps can be effectively planned using supportive data. These tools and real-time performance report helped to bring down the monitoring cost by 1/12th. This is an area where the cost reduction impact was significant.

E. Reduction in publicity cost Instead of a broadcast message via posters or

advertisements in newspapers, targeted communication by sending SMS automatically to the referred patients only reduced publicity costs by 1/7th. With SMS, it works out to be cheaper than other options, with multiple reminders being sent out, it increased the adherence to referrals.

CONCLUSION Most causes of visual impairment for people living in low-

income settings are treatable and preventable if detected early. While many organizations provide vision care services to “at risk” population under outreach programs, most are paper-based. A significant challenge to the effectiveness of the outreach program, however, is the paper-based systems used to register patients in need of services, gather information about them, and analyze the data collected. Manipulating data manually, takes months, and introduces errors. As a result, quantification of the effectiveness of community outreach services is difficult. The field trial of the connected vision care system has demonstrated that outreach programs can deliver timely, quality vision care efficiently using wireless and mobile

technologies. The trial also demonstrated that for large-scale rollouts, we could minimize the capital expenditure by utilizing off the shelf mobile devices, open source server components, and existing consumer wireless infrastructure like cellular networks.

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