Digital technology is instrumental in reforming businesses all over the world. Going digital is a bonanza for the industry. Though digitization makes the process quick, there are some security concerns coming along with it, Health Data Management is a challenge considering the frequency of data breach in the recent past.
Present healthcare system stores patient records in a digital form as EMR (Electronic Medical Record) which gathers all information at one place. A patient health record includes both financial and clinical data.
Clinical data includes physician feedback, prescriptions, medical imaging, laboratory, pharmacy, insurance, and other administrative data. Patients who have leverage wearable devices can sync those data to their respective patient’s record.
Data analytics means finding different patterns with respect to patient health conditions and available medical data. It allows physicians to have a deep-rooted understanding of the problem, and be able to take medically informed decisions while lowering costs.
Analytics helps providers to
Reduces time, and
Ideally developing this pattern will help gain insight in choosing better treatment options resulting in high-quality care.
All healthcare systems generate the large volume of data and this data has to be processed in an effective manner to make a huge difference in the outcome.
Engaging practice with new technology hasn’t been effective so far. Though it may look expensive, implementing a new technology and leveraging big data can be advantageous and prove to be cost-effective over a period of time.
Big data is nothing but a large volume of complex and variable data that require advanced techniques to capture, store and distribute to analyze the information.
Advantages of leveraging big data in healthcare,
Data has always been the basis of healthcare, every healthcare procedure, processes, studies, and diagnosis is recorded for better understanding. But the problem arises when understanding this data collected and generating information out of it. Big data can help in this area by turning data into information. Following are some of the advantages big data present
1. Clinical research and operations
A large volume of data can help clinical researchers to discover cost-effective ways, and diagnose and treat patients. Big data can help physicians to perform better, be more insightful during the process of decision making. Study of diseases and conditions and as a result the search for a cure lies in recognizing the underlying patterns which lead to health or diseases. Some of these patterns are more obvious than others and in some cases, the database is not sufficient to arrive at a conclusion. Big data will help in identifying such patterns faster and more accurately and can reduce the need for trial and error treatment.
2. Prevents diseases and treatments
To reduce the spending and readmission rate insurance companies have started to gather patient data to foretell, and to avoid repeated hospitalization by discovering illness pattern using analytics, also helps to restrict patients from being vulnerable to diseases.
3. Precision treatment
By identifying the disease pattern with available genetic predisposition and family history or disorder it is easy to start appropriate treatment. This treatment steps will be stored for future medication and references.
Many healthcare communities follow present technology for data collection and data mining. Record tracking facility and pattern analyzing technique allows to uncover the disease outbreak and helps to deliver timely care.
With large population data, we can identify patient needs, offer required services, predict diseases and prevent the future crisis to benefit the population.
Data analytics can also contribute to
1. Evidence-based medicine
Various organized and unorganized patterns are discovered from patient’s clinical, operational and genomic data which helps physicians to tackle treatment-related problems and helps to figure out how effectively the treatment can be done to bring the desired results.
And this is done by finding patients who are at risk and providing instant treatment to better the outcome.
2. Genomic analytics
Helps to identify gene pattern more efficiently and cost-effectively. Genomic analysis is a part of the regular medical care decision process.
3. Fraud Analysis
Data analytics helps to cut down fraud requests by analyzing more number of claim requests.
4. Real-Time Monitoring
Real-time capturing of data and analyzing fast-moving data from hospitals and wearable devices for safety monitoring. It prevents adverse effects from medical errors when data monitoring is continuous and real-time.
Hence adopting data analytics technique will improve the care outcome and will also bring in most needed massive changes in healthcare delivery. Schedule a demo with us for free!