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A Promising Enabler for Smoother Healthcare Transitions

A Promising Enabler for Smoother Healthcare Transitions

The healthcare industry is undergoing a constant state of flux, thanks to breakthrough technology advancements and medical innovation in this digitised world. An exorbitant amount of healthcare information is available from heterogeneous sources like clinical data from Electronic Health Records (EHR), insurance and claims, regulatory compliance, research and development, pharmaceutical transactions, patient preferences and feedback.

The vast enormity and complexity of this data pose several challenges in analysis and its subsequent applications to a practical clinical environment. Using Data Analytics (DA) in Healthcare Information Technology  can serve as an enabling tool for deriving meaningful perspectives and actionable insights for clinical decision-making. Thus DA guides healthcare executives and leaders in building a clinical data platform with descriptive and predictive analysis. The global healthcare data analytics market is estimated to be approximately USD 53.65 billion by 2025!

  • Improves Care Delivery
  • Results in reduced waste
  • Encourages personalized attention to medical needs fostering a patient-centric approach
  • Promotes proactive disease detection
  • Guarantees better patient satisfaction
  • Decreases healthcare costs

By availing the professional services and expertise of Healthcare Consulting Firms, healthcare DA may be harnessed to

  • Derive clinically meaningful outcomes with respect to healthcare costs by in-depth mining of EHR
  • Identify inherent medical inaccuracies in the system for offering cost-effective treatments to patients
  • Aid efficient resource management
  • Reduce patient waiting times and rate of hospital re-admissions
  • Enhance the performance of healthcare providers
  • Provide robust healthcare risk mitigation
  • Promote usage of personalized medicine
  • Minimize the need for undergoing additional diagnostic tests unnecessarily

Besides the above, Predictive Analytics, an advanced form of DA, may be utilized in healthcare financial systems primarily to avoid payment frauds.

  • Complete eradication of life-threatening diseases: The insights derived from operational data analytics empowers healthcare professionals to track and predict the impact of dangerous diseases, which is critical for stopping its spread. By extrapolating the visualization of healthcare workers and weather information in geographical maps, DA outcomes can proactively intervene for preventing disease outbreak in potentially risky areas. This is better than the reactive approach where treatment starts post-infection.
  • Minimization of medical errors: Often irreversible organ damages or even deaths occur due to wrong diagnosis, post-surgery complications and clinical errors. DA can help overcome this by producing near real-time information and insights using the latest data for medical decision-making. That results in safe patient engagements and experiences.
  • Better infection control: Despite conscious efforts for maintaining hygiene and sterile conditions in hospitals, outbreak and spread of infections is likely. These infections can be very dangerous or even fatal to vulnerable patients. By using DA infection control dashboards, hospital staff can get one-stop quick access to the origin and root-cause of infections. Hence better tracking equips the staff with the right information to avoid infections in the future and also take better preventive measures.
  • Leveraging Information and Communication Technology (ICT) Healthcare – Coupled with ICT Healthcare initiatives, DA can aid strategic development for transforming healthcare into an integrated and comprehensive system. This efficiently addresses the requirements of all patient care stages starting from diagnosis, treatment to post-discharge follow-ups.
  • Extracting Maximum Value from Patient Outcomes: By enabling authorized access to data insights gained from DA and facilitating appropriate training, relevant medical staff may be empowered to autonomously execute data-led clinical decisions. DA’s near real-time reports and graphs play a vital role in time-critical events like epidemic outbreak prevention.

The right application of DA can indeed encompass healthcare significantly for saving more human lives and ensuring gigantic leaps for better care outcomes!