Understanding Healthcare Analytics
Given the rise in competitive pressures, mounting operational costs, dynamic patient needs, and pandemic-induced challenges, healthcare organizations need to up the ante if they aim to succeed in the long run. Notably, the drastic turn of events coupled with the evolving healthcare challenges has made it crucial for healthcare organizations to evolve their decision-making process by applying incisive insights obtained through analytics in healthcare.
Data analytics in healthcare has changed the way the healthcare industry manages, analyzes, and leverages data. Healthcare analytics has proven to reduce treatment costs, predict the outbreak of diseases and improve quality of life. The longevity of human life is also a gift of medical sciences, and this has been possible due to changes driven by analytics in healthcare. Analytics in healthcare helps healthcare providers notice increased exposure to or early warning signs of chronic or severe diseases and draw an accurate and comprehensive picture of a patient’s condition and next steps.
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Why Healthcare Analytics?
Healthcare analytics solutions help healthcare organizations leverage data for insights in every area of operation. It provides a 360-degree view of doctor records, patient histories, and hospital administrations, making the exchange of information between different departments seamless, which leads to optimal patient care.
As fast-paced and complex as the current healthcare market is, it is expected to become more complicated in the coming years. Challenges such as changing market dynamics, increasing administrative regulations, and consumers becoming more intelligent and demanding, healthcare organizations are expected to deliver more value.
In the last decade, only a handful of healthcare organizations have started leveraging advanced analytics to improve patient satisfaction and the care process. There is a vast ocean of organizational data that can be used to optimize operations across the healthcare spectrum.
Enhance all areas of the care continuum to drive bottom-line results, improve patient outcomes with innovative healthcare analytics, and unlock the true potential of healthcare data with Quantzig’s advanced analytics solutions. Request a free proposal to know more.
Use Cases for Analytics in Healthcare
- Improves Staffing – One of the classic problems faced by a healthcare organization is optimal staffing. If required staff is not scheduled for a particular patient, it may add unnecessary pressure to an otherwise well-balanced system, and the patient may face an unwanted care silo. On the contrary, if extra staff is scheduled, it will increase labor costs. The use of healthcare analytics enables healthcare organizations to predict the flow of patients and optimize workforce planning accordingly.
- Disaster Planning – Natural and artificial disasters put tremendous pressure on healthcare organizations and workers. During a disaster, the demand for a particular healthcare service shoots up beyond capacity. For example, the COVID-19 outbreak created a heavy surge in demand for ventilators. Healthcare analytics, in this case, can help organizations with real-time access to outbreak patterns which can be helpful for authorities in managing such disasters.
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- Reduces Healthcare Costs – Healthcare data analytics has been used to compare the cost and effectiveness of treatments and public healthcare policies. Healthcare organizations across the globe are also making use of cost and outcome data to check the efficacy of particular medications.
- Risk Scoring and Population Health – Prediction, prevention, and curing of diseases go hand-in-hand. Healthcare organizations can now leverage healthcare analytics to detect individuals at higher risks of developing chronic diseases, helping patients with long-term health problems avoid costly treatments. Risk scores based on lab tests, biometric data, insurance claims, and social determinants of health can give healthcare organizations the necessary insights into patients who need enhanced healthcare services.
- Predicts Appointment No-Shows – Unexpected gap in a scheduled calendar leads to financial loss. Using healthcare analytics, organizations can now predict patients who are likely to skip appointments without prior notice. Healthcare organizations can further utilize this information to send reminders to patients who are most likely to fail to show up. It also helps organizations optimally offer transportation and other facilities to help individuals show up for scheduled appointments. Organizations can also utilize this insight to assist their patients in choosing alternate timings that work for them.
Through an in-depth analysis of unique challenges facing the healthcare industry, we aim to help our clients harness the true power of healthcare data analytics. This will enable them to drive better outcomes across different segments within the healthcare industry – involving patients, clinicians, providers, payers, medical researchers, and health regulators alike. Please speak with our SMEs to know how we can help you.