New Technologies and Data Analytics in Health Care

By Hayley Lose

My capstone project focuses on the health care industry with respect to the opioid epidemic. After doing my research and analysis, I can see there is room for growth in data analytics in the health care industry.  My mom works in a hospital and it is really interesting to hear how technology shapes the processes she does daily. I wanted to look at more technologies available currently to see where gaps and opportunities are.

The health care industry can benefit from improved technology and innovation in regards to patient care, research, and staffing. The technology available now is working towards better patient care; however, there is room for analytical growth and development. Many tools and techniques are being used and developed, with lots of room for growth.

McKinsey and Company’s 2016 report on/ analytics and competing in a data-driven world identified the healthcare industry as capturing only 10-20% of the analytical value available. The biggest success for the industry is electronic medical records. Electronic medical records are being used — but not to their full potential as a result of patient privacy and regulations. Challenges in fully capturing the value from analytics include lack of incentives, data-sharing difficulties, and regulations.

The report suggests radical personalization as a potential for improvement. Radical personalization can shape the industry in two ways. The first is information asymmetries and incentive issues in the system.  With a complete patient view, incentives can be adjusted to focus on wellness and prevention. The second way radical personalization can shape the industry is by making treatments more precise. More effective outcomes will be a result of more precise treatments. Although with the new technology, there are great uncertainties involved including health care adaptation and research and development producing breakthrough treatments.

The necessity of data analytics and innovation in health care is apparent. Health care costs have been rising over 20 years so the need for data driven decisions is relevant. Physician decisions can become based more on data and evidence rather than professional opinion.

New Technology

New analytical techniques can assist the health care industry. An article in Forbes, by Mike Montgomery, reported that eCare21, a remote patient monitoring system, is changing the way doctors treat senior citizens. The monitoring system can be accessed through a phone app; it uses sensors to collect patient information through smartphones, Fitbits, and Bluetooth. The information collected includes blood pressure, physical activity, weight, medication intake, and glucose levels. eCare21 assists in providing real time information, so authorized caretakers and family to access the data. This information can be placed on a dashboard for doctors, caregivers, and families can see the results.

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Figure 1. Company Logo

eCare21 complete in the area of telehealth. Telehealth is the process of providing health care while eliminating geographical constraints through the use of technology. Telehealth, also referred to as telemedicine, can help relieve some current struggles within the health care industry.  For example, initial consultations and diagnosis can be communicated via videoconference. Wearable technology and monitoring can be done remotely so as data collection is happening there is room for analytics and personalized treatment. Analytics can work to predict medical events in advance. Furthermore, telehealth helps patients stay out of hospitals, thus reducing costs and improving quality of service.

Another device available for wearable monitoring comes from Cardiac Insight. Their device, called Cardea Solo, is a lightweight disposable electrocardiogram (ECG) to monitor a patient’s heartbeat. Through wearing the device, irregularities can be identified that could lead to serious heart problems. The main objective behind the device is identifying and monitoring systems that cannot be replicated in the doctor’s office. The device is small enough that it will not be noticed under clothes and is water resistant.  Cardeo Solo is inexpensive, making it highly accessible.

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Figure 2. Cardea Solo

Forbe’s article regarding hospitals in Paris using machine learning to forecast admission rates showed that four hospitals have combined 10 years of admission data to predict day and hour-level admissions (Marr 2016). External data sets were included containing weather, holidays, and flu patterns. All of the combined data is used on an open-sourced platform (Trusted Analytics Platform) because of the large amount of data. The article notes the importance of using a well-understood algorithm so that it can work over distributed systems. With the ability to predict patient admission, staffing adjustments can be made to reduce waiting times for patients. The prediction of admission rates could not utilize types of admissions as a result of privacy laws. Privacy laws are one of the largest obstacles facing analytics and health care.

Conclusion

These devices and many more are being created and improved constantly. The technologies I researched focus on different aspects that can improve health care.  There is room for more innovation and better devices to improve the health care system and patient health. The shift toward better technology presents the ability for better patient care and data-driven decisions.

A theme in articles I read was the difficulty in accessing patient data. While the effects of electronic records have been important, there is some restriction with the records based on security.

Works Cited

“The Age of Analytics: Competing in a Data Driven World.” McKinsey, http://www.mckinsey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Analytics/Our%20Insights/The%20age%20of%20analytics%20Competing%20in%20a%20data%20driven%20world/MGI-The-Age-of-Analytics-Full-report.ashx.

Marr, Bernard. “Big Data In Healthcare: Paris Hospitals Predict Admission Rates Using Machine Learning.” Forbes, Forbes Magazine, 13 Dec. 2016, http://www.forbes.com/sites/bernardmarr/2016/12/13/big-data-in-healthcare-paris-hospitals-predict-admission-rates-using-machine-learning/#25953ef079a2.

McGrane, Clare. “Cardiac Insight Raises $4.5M, Wins FDA Approval to Launch Wearable ECG Sensor.” GeekWire, GeekWire, LLC, 15 Aug. 2017, http://www.geekwire.com/2017/cardiac-insight-raises-2-m-launches-wearable-ecg-sensor/.

Montgomery, Mike. “The Future Of Health Care Is In Data Analytics.” Forbes, Forbes Magazine, 26 Oct. 2016, http://www.forbes.com/sites/mikemontgomery/2016/10/26/the-future-of-health-care-is-in-data-analytics/#187e837d3ee2.

 

 

 

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