Big data is at the forefront of many industries worldwide, and the healthcare industry is no exception. In healthcare, big data is available in massive amounts, containing the information of human health conditions and activities, and is collected through multiple resources like electronic health records, medical image analysis, wearables and medical devices, and more. As medicine and technology become more and more advanced, so do the abilities of big data. Here we take a look at some of the biggest ways big data has changed the healthcare industry.
One advantage that big data can bring to the healthcare industry is cost reduction in a variety of areas such as staffing, medications, admission rates, operational procedures, and more.
One hospital in Paris is using predictive analytics to assist with staffing by predicting admission rates over a period of two weeks, which will allow the hospital to better allocate staff based on need. This reduces overstaffing issues, increases hospital efficiency, and decreases patient wait times, which is one factor that hospitals worldwide are constantly trying to improve.
Big data can also reduce costs in the medication field, as successfully seen by one of Dimensional Insight’s own customers, Western Maryland Health System in Cumberland, Maryland. Western Maryland Health System was trying to figure out how to manage rising drug costs. More specifically, they were looking at the price of IV acetaminophen, which rose about 250% to $35 per vial, which was nearly $250,000 per year for IV acetaminophen alone. With hospital data analyzed using Dimensional Insight’s business intelligence platform, the hospital was able to reduce its spending on acetaminophen 78% over two years. In addition, the organization found that patients on the drug had a shorter length of stay and less readmission than other patients, resulting in a cost savings of $112,000 over 6 months.
Big data is especially important when it comes to aspects such as follow-up and long-term care as well as preventative healthcare. Big data technology has been used to predict which patients are most likely to follow their doctor’s advice and which ones aren’t in order to help prevent hospital readmissions in the most vulnerable patients.
With the data used in location tracking, GPS-enabled inhalers for asthmatics are now being developed to track when a patient is taking his or her medications. This information actually helps the physician make better and more personalized treatment plans for individual patients, and allows them to more efficiently prevent further illness or injury.
Companies such as Ginger.io are also taking advantage of the benefits data has to offer by implementing healthcare mobile applications for tracking patient improvement or lack thereof. With the patient’s agreement, the app records data found in areas such as calls, geographical location, physical movement, or sleep patterns, and can help alert doctors or family members if the patient is likely feeling unwell or in danger of an anxiety or other psychological attack. Data is required for the success of a mobile application like this, but there’s no doubt that the technology it offers is beginning to open a new gate towards patient follow-up tools.
Advanced real-time care
One of the most important things that hospitals and healthcare organizations can offer their patients is quality real-time care. The constant monitoring of a patient’s vital signs, medications, symptoms, improvement, and more are all things that physicians can do to ensure such high-quality care, and they can be achieved even more efficiently with the use of big data. The benefit of real-time care is that it can provide a clear audit trail of clinical data that was recorded through dates and times of professional observations and assessments. These records are stored automatically and can be used to track things such as nurse check-in schedules, which will also have any incidents and complaints on file, which are useful to the given hospital.
Real-time care also provides the possibility for shorter wait times and a much more accurate way of diagnosing patients using mobile technologies similar to the ones being used with follow-up care.
Let’s take as an example emergency waiting rooms: Most patients who arrive at the emergency room have been directed and transferred there appropriately, but there are many cases in which individuals check themselves in even if it’s something that does not necessarily need emergency treatment. However, doctors must check in with all patients regardless of severity, which means they need to collect data from each individual – usually a time-consuming process, leading to a lack of concrete information on the doctor’s end, an increase in hospital money, and less time for more critical patients. But real-time data used in mobile healthcare apps can offer health professionals an immediate analysis on the patient.
In the case that the patient does not need urgent care, the doctors can review the analysis from the data applications and transfer them to the right department or specialist. Even with regular appointments outside of the emergency room, with the collection of real-time health data, non-critical patients can receive the right point of care or evaluation by phone or other device, all without stepping foot in a hospital. Overall, the benefits of real-time care can create a much timelier process of emergency waiting room procedures and allow for a quicker response time to critical patients while still providing the careful but appropriate care to other patients.
Preventing medication errors
Doctors and health professionals are bound to make some type of mistake during their careers, but many times there are lives on the line. Medication errors made in hospitals are unfortunately much more common than people may think. However, with the help of big data, such serious errors can be prevented or further decreased in frequency. Big data tools can analyze each patient’s individual medical records as well as any other concerns, including allergies, past medications prescribed, dosage amount, and other relevant information. After scanning all records, data analyzing software can ultimately point out any missing information or flag anything that may look skeptical.
In 2012, one of these big data software platforms was developed. Dr. Gidi Stein co-founded an Israel-based company called MedAware, which connects to a hospital’s electronic health-record (EHR) system to detect prescription errors before they happen. Possible errors are avoided when the system flags a chosen drug that doesn’t appropriately correlate to the patient’s records or needs, and then it blocks the drug order until it’s re-evaluated and confirmed. When MedAware was tested at the beginning of its development, it analyzed 747,985 patient records as a clinical study, and 15,693 were flagged for possible medication errors, further proving the data platform’s success as well as proving to be an extremely useful tool to medical providers and hospitals.
While some drug errors can be fixed with little to no damage, there are still many cases in which even the smallest mistake can lead to death, so it’s extremely important for hospitals to address ways in which such malpractice can be avoided.
Big data has undoubtedly brought a new perspective to healthcare technology and how the industry can be improved. Cost reduction, real-time care, follow-up care, and the prevention of medication error are all part of the many advantages that big data has gifted the healthcare industry, and the capabilities of big data technology will only grow stronger with time, saving more lives and improving hospitals worldwide. To learn more about the relationship between healthcare and data, check out our whitepaper—”How to Accelerate EHR Insights with an Enterprise Analytics Platform.”
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