Healthcare industry has in recent years been digitizing data partly driven by compliance to regulatory requirements and also for record keeping and patient care. But this data can also be utilised effectively to provide a wide range of insights into medical and healthcare functions, including clinical decision support, disease surveillance, and population health management. Big data in healthcare is overwhelming not only because of its volume but also because of the diversity of data types and the speed at which it must be managed. At Applied Analytics we provide a suite of offerings in the Healthcare domain. We customise offerings from our Accredited Partners to provide you the most optimum solution for your domain. This ensures that your organisation is able to leverage on time tested technologies from marquee technology providers and for your specific needs. Applied Analytics takes has a flexible engagement structure involving:

  • Customises Solutions Architecture
  • Solutions Engineering
  • DevOps
  • Data preparation and Monitoring

A few representative use cases in Healthcare services:

Patient profile analytics

Advanced analytics can be applied to patient profiles (eg. segmentation and predictive modelling) to identify those who could benefit from proactive healthcare or lifestyle changes eg., those patients at risk of developing a specific disease (such as diabetes) who would benefit from preventive care.

Evidence based medicine

Combine and analyze a variety of structured and unstructured data-EMRs, financial and operational data, clinical data, and genomic data to match treatments with outcomes, predict patients at risk for disease or readmission and provide more efficient care

Clinical Research

Predictive modelling can be utilised to lower attrition and produce a leaner, faster, more targeted research pipeline in drugs and medicines. Customized statistical tools can be implemented to improve clinical trial design and patient recruitment to better match treatments to individual patients which can reduce trial failures and expediting go to market for new products. Critical data analysis of clinical trials and patient records can identify follow-on indications and discover adverse effects before products reach the market.

Public health

Data analytics of disease patterns can track disease outbreaks and transmission to improve public health surveillance and faster transmission time. It can also enable faster development of more accurately targeted vaccines. By turning large amounts of data into actionable information Data analytics can be used to identify needs, provide services, and predict and prevent crises, especially for the benefit of the population.

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