Players in the healthcare industry face a different set of challenges each day, ranging from a new disease outbreak to maintaining optimal operational efficiency. Added to that, the increasing demand for patients to get better care at their convenience, there is only so much that advances in medical science can do. Tackling such challenges requires a different kind of approach. Big data and advanced analytics may be the answer to the toughest of healthcare challenges. With a plethora of data available to players in the healthcare industry, including financial, clinical, R&D, administration, and operational data, big data in healthcare can generate meaningful insights to improve the overall efficiency in this industry. The significant growth in the healthcare data analytics sector also points towards the rapid adoption of big data in healthcare.
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Big Data in Healthcare – Leading Towards a Better Future
Advanced Patient Care
A platform such as electronic health records (EHR) collects all related demographic and medical data, including lab tests, clinical data, diagnoses, medical conditions, and allergy information. Having such data facilitates and supports healthcare practitioners to provide quality care. Healthcare analytics can assist physicians in making better decisions and also provide personalized care.
Improve Operational Efficiency
The importance of big data in healthcare is highlighted by the fact that healthcare companies use it as part of their business intelligence strategy. For instance, by examining historical patient admission rates and analyzing staff efficiency, healthcare facilities can optimally allocate healthcare personnel to a particular shift without having to overstaff or understaff. Predictive analytics is vital to achieving the goal of providing better care and cutting down on healthcare costs simultaneously. Additionally, it can also reduce medication errors, financial and administrative performance, and reduce readmissions.
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Finding a Cure for Diseases
No two persons in the world would have the same genetic sequences, which is the reason why particular medication seems to work for some people but not for others. Since there are millions of things to be observed in a single genome, it is almost impossible to study them in detail. However, big data in healthcare have been revolutionizing the area of genomic medicine. Big data analytics can uncover unknown correlations, hidden patterns, and insights by examining large data-sets. Scientists are banking on big data to find the cure for cancer. By taking a large chunk of data from human genomes to detect patterns across the patients, and applying machine learning, the correct network of mutation for cancer could be identified. Subsequently, correct treatment or drugs could be engineered to treat cancer at an individual level.
Medical abuse and insurance fraud are the two most significant problems facing the healthcare industry. These problems can be solved by the efficient use of big data in healthcare. By analyzing a larger dataset of claims history, fraud patterns can be identified and even predicted before they occur. For instance, multiple hospital visits within a short timeframe and claims from different healthcare facilities are possible to trigger points of insurance fraud. Additionally, analyzing diagnoses, test results, medical histories, follow-ups, and other detail can effectively alert authorities of possible drug abuse cases. Healthcare analytics can effectively process large amounts of data to reduce fraud, wastages, and medical abuse.
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Estimating Optimal Reimbursement
The healthcare industry has been tinkering around with various reimbursement models including fee-for-service, pay-for-coordination, and bundled payment models. However, most of them have looked to favor a value-based reimbursement model recently. It encourages healthcare providers to meet specific metrics for quality and efficiency and focus on the patient outcome. However, quality and outcome are not easily measurable, which is why professionals are resorting to big data in the healthcare industry. Data analytics can effectively ensure payment accuracy, process claims, and measure the quality of healthcare.