Big Data and Analytics: Simplifying Care
Big data has become an important part of a wide range of industries. Healthcare is ripe for big data initiatives—as one of the largest and most complex industries in the U.S., there is an incredible number of potential applications for predictive analytics. However, on the one hand, some healthcare organizations have already started seeing the value in using big data, the flip side shows that the industry as a whole has been very sluggish to accept big data initiatives for numerous reasons. But, now that the healthcare sector can scrutinize the potential of data they have started utilizing the same in many areas.
Reducing Medication Errors:
This is a serious problem in healthcare organizations because humans will always make the errors even something as simple as choosing the appropriate medication from a pull-down menu, patients often end up with the wrong medication—which could cause harm or even death. Big data can help decrease these error rates dramatically by analyzing the patient’s records with all medications prescribed, and flagging anything that seems out of place.
Reducing Costs:
Numerous healthcare systems have to compete with high rates of patients frequently using the emergency department. This scenario drives up healthcare costs and does not lead to better care or outcomes for these patients. Using predictive analytics, some hospitals have been able to lessen the number of ER visits by identifying high-risk patients and providing customized, patient-centric care.
Lesser Wait-time:
Data analytics helped us in reducing Attendances and Emergency Admissions waiting times, giving healthcare facilities a greater perspective of where patients are in their care – improving discharge levels, minimizing readmissions and reducing delays. The visual management and alerts help healthcare institutes to make sure patients are prioritized in the correct order, achieving a decreased median time of stay by 30 minutes.
Enhancing Patient Engagement:
The rising interest among consumers in devices that monitor their daily chores like steps taken, hours slept, heart rate and other data shows, how introducing these devices as a physician aid could help progress patient engagement and outcomes. New wearables can track specific health trends and relay them back to the cloud where physicians can observe them. The same can be applied for measuring asthma to blood pressure, and assist patients so that they can stay independent and decrease unnecessary doctors’ visits.
Electronic Health Records (EHR):
In coexistence with Electronic Medical Records (EMR), EHR has been undeviatingly increasing in use over the last decade. According to reports from 2001 to late 2014 EMR usage in any practitioners, office rose from 20 percent to over 82 percent. With the debut of the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, Meaningful Use reasons for higher billing and reimbursement rates from the federal government proceed to drive adoption rates. With the adoption of EMRs, the boost in EHRs has grown incredibly. EHRs are a wider view of a patient’s cumulative individual EMR practice and hold a historical 360-degree view of a patient’s medical history. While the sharing and interchanging of the available EHR data has been the chief focus in recent years through Continuity of Care Documents (CCD) and Consolidated Clinical Document Architecture (C-CDA), the enormous collection of clinical data by large health systems and treatment centers (public, private, and academic) has enthused into the area of big data.
Now the advancements enable patients to share their data with the doctor who can use it as part of their diagnostic toolbox when the patient visits them with an ailment. Even if there’s nothing wrong with the patient, access to this pool of ever-growing databases of information about the state of the health of the general public is allowing problems to be marked before they happen, and remedies – either medicinal or educational – to be equipped in advance.
