Leveraging technology in the correct manner can bring about a revolutionary change in the healthcare industry. One of the technologies that have enabled the healthcare industry to become more affordable and efficient as well as allowed them to save more lives has been the increasing adoption and implementation of big data.
What is Big Data?
Big data deals with the digitization, consolidation, standardization, analysis and model of large volumes of information. Within healthcare, big data uses specific statistics from a population or an individual to research new advancements, decrease costs, and also cure and prevent the onset of diseases. In the past few years, healthcare data collection has crossed over to the digital realm, facilitating faster and more accurate analysis.
The growing popularity of big data means improvements not just for individual patients, but to the entire healthcare industry. Healthcare providers are making decisions based on more big data research instead of relying on just their background and experience. Using this new approach, the demand for big data in healthcare and medicine is at the highest it has ever been and healthcare institutions are actively trying to acquire and implement the technology to meet the rising need.
How Big Data Is Helping Healthcare Right Now
1. Managed Care
In value-based reimbursement, the purpose of big data is to serve as the foundation for how a healthcare provider is assessed and rewarded for ensuring the good health of a patient. Providers are judged based on the quality of care they provide, often received from biometric data (BMI, A1c, Blood Pressure etc.) as well as the completion of yearly preventive and routine care for their patients
Many government-sponsored health plans integrate big data to report Healthcare Effectiveness Data and Information Set (HEDIS) and STAR measures to the state authorities which assess their data and scores and rank them accordingly. Depending on the level of risk associated with their arrangement, health plans reward or abstain payments to their healthcare providers based on this data.
Nowadays, several health plans include some type of risk stratification program. Risk stratification is based on utilizing big data to assign a risk score (low to high) to a patient depending on the criteria set including diagnosis, comorbidity, gender and age. The higher the score, the more expensive it is to treat the patient. Using deep insight, health plans can be implemented to feature target management strategies formulated for specific aspects of their population.
For instance, many health plans know that when a high-risk patient is discharged from a medical institution they are less likely to follow up with their provider or fill their script. As a result, they might have a transition of the care process to motivate them to follow up with their primary care provider and adhere to filling their script. The plan will also be capable of assessing their social determinants of health and coordinate the provision of specific considerations like transportation, home care or meals. With the proper transition of care, healthcare plans can be vital in avoiding costly readmissions.
2. More Accurate Treatment
Information collected from big data provides more insights for healthcare professionals than they would have otherwise. Collecting data in this manner facilitates better decision making, fewer cases of guessing and leads to better overall patient care. Big data analytics have also been leveraged to help patients with multiple conditions. Such patients usually stand to benefit from home care, which drastically improves their quality of life. Big data can also detect and identify people that have a higher chance of contracting an illness, allowing them more control of their health with minimal medical intervention.
3. Preventing Cases Before They Occur
The advent of IoT has led to the invention of smart wearable devices that are capable of tracking physical movements and monitoring health conditions. They can also transmit that data directly to physicians to monitor progress. To promote health and fitness, these smart wearable device brands are awarding consumers for meeting their exercise goals, thus promoting health and fitness. These devices are also being implemented with software to help people with diabetes.
Traditional healthcare databases are often too complex and costly to maintain. Big data can help address this issue through simpler design and a more user-friendly interface and maintenance. Software developers help to store big data by rebuilding failed nodes. This allows them to make technological mishaps a lot easier to recover from. Big data also provides medical professionals with the ability to synthesize disparate data enables users to detect conditions, underlying or otherwise, that may be missed by doctors.
4. Reducing Errors
It is estimated that prescription errors in the United States affect more than 7 million people annually, leading to about 7,000 deaths and costing the healthcare organizations around $21 billion annually. Big data can be employed to combat this disturbing statistic by catching errors early, sometimes even before they occur. Big data applications when implemented in healthcare have the potential to save money, reputation and credibility and most importantly, lives.