It is an entirely regular occurrence for Japanese residents to receive a notification on their phones when they’re in close contact with a COVID-19 positive individual. The country’s COCOA app is just one of many examples of user behavior and data tracking leveraged to learn more about the spread of COVID-19.
Yet, the use of data – of the general population and individuals alike – in healthcare goes beyond the efforts to curb the spread of the virus. For example, data in healthcare was used years earlier in areas such as medical imaging, chronic disease management, and precision medicine, to name a few.
The adoption of digital technologies in medicine has become a staple of faster, more accurate, and more secure patient care.
This article discusses data analytics in medicine and its benefits to everyone involved in healthcare procedures.
What is Data Analytics in Healthcare?
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In healthcare, data analytics refers to collecting and interpreting information to improve the quality and efficiency of healthcare services.
There are different applications of data in medicine, such as:
- gathering and analyzing patients’ records for faster and more valid diagnostics, treatment prescription and administration, and health monitoring and reporting
- optimizing and managing medical institutions’ large and complex databases for effective decision-making
- increasing productivity and decreasing costs of medical procedures, research, and testing
- improving the accuracy and speed of identifying high-risk disease patients
So, data analytics can find its place in various uses, from reducing medical expenses, organizing clinical data, tracking patient behavior, and evaluating pharmaceuticals.
Besides, the technology can be leveraged in a laboratory environment, as the latest NIR spectrometer, spectrograph and other lab instruments feature innovative solutions.
Healthcare data analytics can thus be employed at both the macro and micro levels to improve all aspects of healthcare.
Why Data Analytics in Healthcare Matters?
Despite the immense possibilities and enormous benefits, the healthcare industry is slow to adapt to the ongoing digitalization.
According to the World Economic Forum, 97% of hospital data – roughly 50 petabytes, per year, of clinical notes, lab tests, medical images, sensor readings, and operational and financial data – goes unused.
Moreover, medical institutions that generate masses of data and possess the technologies to collect and analyze the compiled information generally lack staff skilled enough to interpret this data.
However, proper integration and use of data analytics within health care systems will prevent poor data quality, time-consuming processes, and unskilled staff from being a common occurrence.
The Benefits of Data Analytics in Healthcare
The role of data analytics in healthcare is substantial, from assisting in disease research and discovering treatments, conducting early condition detection, improving patient documentation, providing telehealth services, removing human bias in the healthcare process, and handling financial error and risk.
Here are some of the primary data analytics benefits in medicine.
Risk Prediction
Collecting mass patient data allows doctors to identify symptoms of various diseases and thus prevent the condition from developing in a patient at risk.
Besides prevention, data analytics helps in early diagnostics and enables treatment to be prescribed and administered as early as possible.
For example, health tracking devices like wearables allow doctors to gain insight into a patient’s health status – insight that would earlier require numerous scans and tests to uncover.
Data analytics allow making data-driven decisions about individual treatment and how likely it is to succeed.
Patient Satisfaction
With the expansion of privately-held healthcare institutions, patients’ satisfaction with the quality, accuracy, and personalization of medical professionals’ service has become a cause of worry.
Luckily for both public and private medical facilities, data analytics can help personalize patient treatment. In addition, this technology can prevent human errors such as inaccurate dosage or medication, exposing patients to the risk of health complications.
Moreover, hospitals can leverage data analytics to reduce long waiting times and prevent shortages of beds.
Industry Advancements
Storing medical data electronically instead of on paper improves efficiency and accuracy, allows multiple healthcare professionals to access the same records, mitigates the chance of a human error, and ensures faster and data-based decision-making.
Besides helping medical professionals serve patients, data analytics provides long-term benefits for industry advancements.
For example, this technology can be adopted for quickly assessing and determining treatment alternatives based on historical medical data, but not only on the level of an individual patient. Instead, data analytics can help predict epidemics, discover cures for diseases, provide solutions for improving the quality of life, risk detection and assessment, etc.
Healthcare Cost Reductions
Data analytics can improve the productivity and accuracy of medical facilities’ operations, cutting treatment costs and other hospital expenses. This helps not only in later healthcare institutions’ budget repurposing but also in allowing the patients access to the care they require.
