Examples of Data Analytics in Healthcare
- Electronic Health Records (EHR’s)- This is the most common application of big data analytics in healthcare in the United States, where many hospitals have adopted EHRs. One of the key factors of an EHR is that health information can be created and managed by authorized healthcare providers in a digital format capable of being shared with other providers across more than one healthcare organization.
- Enhancing Patient Engagement- Patients use devices like AppleWatch and FitBit to monitor their health data. The healthcare field is wide open to data leaders who can leverage preventative analytics to help patients change to healthier lifestyles.
- Predictive Analytics- aims to alert healthcare professionals, clinicians, caregivers, etc., of the probability and outcomes before they occur, helping them to prevent or cure health issues. Predictive analytics uses techniques from healthcare data mining, statistics, predictive modeling, machine learning, and artificial intelligence to analyze current data and make predictions about the future.
How Does Data Improve Healthcare?
While every facet of the industry stands to be changed by data analytics in healthcare, data has significantly improved healthcare in three areas: conducting medical studies, understanding the cost of medical tests and health insurance, and making preventative recommendations to patients.
Medical studies help drive healthcare forward. Without drug trials, there would be no way of ensuring that new drugs could be brought to market safely. According to the National Center for Biotechnology Information, medical research is the driving force behind change in the healthcare industry. While medical researchers must have a strong foundation in biology and chemistry to understand what compositions affect human health, there are few deterministic forces inside the body. Because of this, statistics and data are crucial to evaluating the efficacy of a new drug.
Even if a drug has been designed based on biological theory, it must be tested on real people, and a data expert is essential to understand the margin of error on these tests. On the policy side, a leader in the field must also be able to advise organizations, like the FDA, about the effectiveness and safety of a drug before it can be marketed to the public.
The cost of healthcare is a national priority. Estimating future costs is key to crafting an effective healthcare policy that provides Americans with the insurance they need at sustainable rates. Once again, projections of healthcare costs are multidetermined, so they must be estimated, including factors like the changing number of patients and emerging health trends in the population. According to a recent MIT-led study, various healthcare data mining techniques, like regression, are useful in predicting the cost of healthcare.
A leader with a background in data, such as an MBA, with comprehensive knowledge of economics and statistics, is critical in formulating healthcare policy that solves rising costs. As of December 2019, there were 28 million uninsured Americans. With that number expected to rise, more data experts will be needed in the field. For many patients, the workings of their health insurance works or expected costs can seem frustratingly obscure. 57% of healthcare systems don’t make that cost available upfront. Healthcare leaders who leverage data can build trust in healthcare by committing to better financial transparency.
Preventative Care Recommendations
Preventative care is the future of medicine. One way to reduce medical care costs is to help patients avoid diseases and disabilities before they arise. Understanding which patients are vulnerable to specific illnesses is not just a job for doctors or healthcare professionals but also data experts.
With new technology in genomic sequencing and DNA testing, as well as an analysis of lifestyle factors, doctors can now understand a patient’s probability of developing certain conditions in the future. However, a data expert can more deeply analyze a patient’s risk factors. Data analysts can develop software to automatically inform patients about recommended lifestyle changes to prevent certain conditions. This helps improve performance by delivering data-based quality patient care which, in turn, improves patient satisfaction.
Data’s Impact on Healthcare in the Last 10 Years
Data has completely altered the healthcare industry in the last 10 years. New technologies, such as Electronic Medical Records (EMRs), allow doctors to analyze statistics on a larger number of patients without manually inputting the data. One large trend has been collaborating with different healthcare players to pool data. For example, CVS Health and Aetna merged, as well as Rite Aid and Albertsons.
Now, these organizations can pool their data and resources to bring down consumer costs. In fact, according to Health Affairs, more than half of all healthcare consumers said that they would be willing to receive care in a non-traditional setting, such as a pharmacy if it was more efficient and less costly. Data has allowed these collaborators to decrease costs and make it simpler to track patient information.
Access to personal data has also transformed healthcare in the last ten years. Patients and doctors can now better track patient information across multiple specialists, which may reduce the need for patients to get repeat tests.
What Data Will Bring in the Next 10 Years
Artificial Intelligence (AI) will play a significant role in data analytics in healthcare for the next decade. For example, the field of AI-enabled clinical decision support is just emerging. This type of support can compare patients who fit similar profiles within a system, then it can alert doctors to trends in data that may have been overlooked. The use of big data in healthcare will include testing for drug interactions that small studies are unlikely to catch and prevent patients from taking harmful drug combinations.
Decisions made by physicians, like what test or treatments to give a particular patient, makeup 80-90% of all healthcare spending, so using artificial intelligence to make more educated decisions will bring down healthcare costs. It’s crucial to have informed leaders at the vanguard of these innovations in healthcare.
How the SMU Cox Online MBA Helps Develop Leaders in the Healthcare Field
The SMU Cox School of Business Online MBA is the best choice for a student interested in the intersection of data in healthcare. The program emphasizes data analytics in healthcare and leadership theory with practical application. The Cox School of Business at SMU offers an Online MBA that enables professionals interested in healthcare data analytics to switch fields while keeping their existing job.
Additionally, the program emphasizes the importance of hands-on work, and the Cox School holds many corporate relationships with the healthcare industry locally and nationally. For someone interested in working as a leader in healthcare by promoting the use of data analytics in healthcare, the SMU MBA offers the perfect set of coursework, with a level of flexibility that allows a professional to switch careers.