- Infosys Cobalt
Health and human services (HHS) programs are becoming more complex for jurisdictions to administer. They are looking for a more proactive approach of anticipating and responding, not reacting, to the needs of their citizens. This is driving adoption of new technologies that allow jurisdictions to draw insights from a wide range of data rapidly and efficiently to intervene before crises emerge. However, the recent pandemic has highlighted that despite investments, jurisdictions’ data infrastructure remains inadequate and ineffective. It has also shed light on longstanding challenges with legacy systems and processes that keep jurisdictions from bringing together the wide range of data needed to make critical decisions.
As data science and analytics evolves with more niche cognitive capabilities and a far more advanced way of doing things, jurisdictions need to rely on automation for the entire life cycle of their data. From automated data aggregation and harmonization to predictive model development and insights generation, an automated data-science based approach will address all the analytics related challenges that jurisdictions face and transform HHS program delivery - from enterprise strategy discussions to frontline decision-making. Automated data-science platforms will allow jurisdictions to turn their data into actions and share those actions with healthcare professionals, enabling them deliver proactive interventions that result in the best outcomes.
Download this paper to learn more about the automated data-science approach and how jurisdictions can adopt automated data-science platforms to transform program outcomes.