Building an oncology focused digital health solution

In the wake of increasing cancer cases and the poor specialist: patient ratio in India, we worked with our client to develop a digital health solution that could be deployed across their entire network of 25 hospitals

We were able to achieve a 95% paperless operation with a TAT reduction of 30%, improving patient and provider experience across facilities.

The client, one of India’s largest philanthropic groups, wanted to design and develop an oncology focused digital health solution for a network of 25 cancer hospitals.

India has high cancer incidence of over 1.45 million people per year and there is only 1 oncologist per million population, making access to cancer care difficult. The client wanted an IT solution to enable an integrated model of care where diagnosis, care planning and monitoring could be delivered seamlessly across the network.

The cancer care continuum begins with screening for the disease and ends with palliative care. Most systems focus on treatment and system’s capabilities must be expanded to provide cross continuum care with real time sharing of clinical data and collaboration.

This solution was designed through a multi-pronged approach. Data of existing practices was scarce and unstructured, so we studied large volume cancer centers in India and abroad.

To develop a unique system, the patient has to be central to the solution

• The cancer care continuum was split into 27 unique modules encompassing radiation oncology, medical oncology, surgical oncology, community oncology, cancer registry, telemedicine and others
• Unique phygital workflows were developed to enable maximum virtualization of care with a mobile-first approach
• Specific features required by each of the stakeholders across various modules were developed e.g., doctors’ lists were zeroed down to either touch based or auto fill options
• EMR, machine communication, data security, data transfer and other regulations were incorporated into workflows
• Drug databases & clinical databases were enabled to create comprehensive care plans and provide evidence-based care
• A command center for centralized monitoring and data integration across the network hospitals was developed.
• Dashboards which could display real time metrics from all hospitals or by location were deployed
• Prescriptive and predictive analytics, machine learning and natural language processing were used to aid decision making

The project

• Achieved a 95% paperless operation
• Enabled seamless care delivery and patient transfers across the network
• Reduced turnaround time for critical processes by ~ 30%
• Curbed the time spent by medical personnel on administrative tasks by 25%
• Improved clinical resource utilization by 10%
• Increased patient engagement and education, thereby reducing counselling and navigation effort of clinical personnel
• Enabled evidence-based care with decision support systems that decrease the probability of medical errors
• Created a centralized command center