Disease Management

Disease Management


People with chronic conditions generally need more health care attention and regular monitoring. Increase in the number of incidence of chronic diseases coupled with rising health care expenditures are driving the government agencies,  insurance providers and Pharma companies to look for ways to reduce health care use and costs. Disease management is one approach that can help in providing better way of life while reducing the costs of health care for the chronically ill patients.

Avekxa’s objective is to customized chronic disease management programs taking into consider the specification and parameters of each chronic disease and utilize new technologies, analytics and delivery mechanism to pass on the benefit to end users.

Value Proposition for Pharmaceuticals / Nutraceuticals

In Generally Observed Situations Post Implementation
  • Chances of non-compliance
  • Daily SMS reminders would increase the compliance of treatment
  • Data Collection on paper
  • Data collection will online using mobile friendly application on mobile phones or tablets
  • Data Entry from paper to Application
  • Not Required
  • Manual Text Messages from Counselors to Patients
  • Automated and Cheaper Systematic Messages (SMS and Emails), to multiple stakeholders including sales reps and doctors
  • Lack of integrated collaboration and communication between Patients, Doctors and Counsellors
  • Integrated collaboration and communication between Patients, Doctors and Counsellors using patient portals and text messaging
  • Manual and Counselor based Knowledge Management
  • Manual and Counselor based Knowledge Management augmented with Patient Portal informing the patient about Drug usage, Dietary needs, Exercise Needs, etc.
  • Lack of readily available dashboards and reports
  • User based access to online dashboard
  • Difficulty in viewing and monitoring the patient history
  • Patient history to be available online for patients, doctors and care managers

Value Added Services

Quantitative models developed from the real-world patient data to understand the drug effectiveness and mechanistic disease progression

  • Outcome Modeling:  Statistical regression models will be developed to understand the effectiveness of the disease management program (therapy) by adjusting the effect of several factors such as socio-economic status, provider setting, life style, other medications and financial incentives etc.
  • Disease Progression Modeling: Mechanistic disease progression models using the longitudinal individual level biomarker data to understand the covariates of disease progression and quantify the drug effects by the application of non-linear mixed effects methods.
  • Predictive Analytics
  • Alert
  • Dashboard