Health Tech

Market Outlook:

Data Analytics helps the Health tech industry to create a central structured data repository. This central and structured data repository enables healthcare practitioners to offer better quality services to patients by adapting a holistic treatment approach and offering personalized healthcare services.

The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes, helping them improve upon existing solutions and overcome challenges faster.

Use-Cases

Patient Data Analytics:

Data analytics provides a complete analysis of patient data to discover insights and suggest actions. AI allows the health tech industry to analyze clinical data and generate deep insights into patient health. It provides an opportunity to reduce the cost of care, use resources efficiently, and manage population health easily.

Patient Prescreening:

AI can provide patient pre-screening through a user-friendly pre-screening questionnaire with expanded voice- and text-based communication. Additionally, AI can learn new patterns and more accurately diagnose patients’ symptoms through machine learning. AI could also provide the next steps in seeking care for the patient.

Data-driven Preventive Healthcare:

AI applications are robust in predictive maintenance. In Healthtech, wearable fitness and medical devices act as sensors that support preventative care. The data collected from these wearable devices could revolutionize preventative healthcare by forecasting health issues before they occur. The large amount of data collected from these devices could be used to design analytical models that predict specific diagnoses.

Centralized View:

Predictive analytics could predict everything from the likely number of available ICU beds to supply needs to in-patient bed availability. It could help in creating a centralized view that provides all admin-related information. This system can alert administrators to take proactive decisions for any potential emergency.

Benefits

Improved

patient outcomes

Operational

efficiency

Better

patient insights

Cost-effective

health care

Case Study

Problem:

WeGuide is a patient engagement application which is used by multiple tenants to gauge patient satisfaction. The existing dashboards to analyze patient engagement were quite basic and not structured well.

Solution:

Data Pilot revamped the dashboards by changing the dashboard structure and adding new KPIs so that tenants can monitor patient engagement and take better decisions. Moreover, we also enabled product analytics dashboards to analyze user interactions with the product to identify UI/UX issues and problems in the user funnel.

Results:

Visibility of patient engagement and pain points so that they can be taken care of there and then. Moreover, customer interactions with the mobile app were never recorded before, which were enabled through Mixpanel.

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