Hooks Guide

Innovative News about IT

Big Data & Analytics in Healthcare Delivery

Opportunities & Challenges

Big Data: The volume, variety and velocity of information generation. Technology is enabling the collection of large amounts of patient data at a very fast pace. In-hospital monitoring and wearable technology allow collection, storage and analysis of healthcare data in the hospital and on the go. If the U.S. healthcare sector were to use big data creatively and effectively to drive efficiency and quality, it could create more than $300 billion in revenue every year.1

The Opportunities

Better Patient Outcomes

Big data and analytics can help build better patient profiles and enable predictive models for each patient that allow for better diagnosis and treatment. It can help identify symptomatic patterns for diseases and efficacy of treatment options. Wearable technology can be used to monitor progress of patients remotely and also record their daily habits. Analysis of this data for a large group of patients could reveal triggers of habits that may cause a dip or rise in health conditions.

Hospitals’ emergency response systems are now improving their ability to respond to respond to emergency calls. Jersey City’s Medical EMS employs a system that compares geographic information system technology, wireless communications, and GPS data to help response units arrive at their destinations more quickly, providing the emergency services with real-time analyses about where they are most likely to be needed. This has largely reduced the response rate, increasing the chances of patient survival.

Opportunities & Challenges

Big Data: The volume, variety and velocity of information generation. Technology is enabling the collection of large amounts of patient data at a very fast pace. In-hospital monitoring and wearable technology allow collection, storage and analysis of healthcare data in the hospital and on the go. If the U.S. healthcare sector were to use big data creatively and effectively to drive efficiency and quality, it could create more than $300 billion in revenue every year.1

The Opportunities

Better Patient Outcomes

Big data and analytics can help build better patient profiles and enable predictive models for each patient that allow for better diagnosis and treatment. It can help identify symptomatic patterns for diseases and efficacy of treatment options. Wearable technology can be used to monitor progress of patients remotely and also record their daily habits. Analysis of this data for a large group of patients could reveal triggers of habits that may cause a dip or rise in health conditions.

Hospitals’ emergency response systems are now improving their ability to respond to respond to emergency calls. Jersey City’s Medical EMS employs a system that compares geographic information system technology, wireless communications, and GPS data to help response units arrive at their destinations more quickly, providing the emergency services with real-time analyses about where they are most likely to be needed. This has largely reduced the response rate, increasing the chances of patient survival.

Improved Quality of Care

The quality of care of a patient at a healthcare facility receives goes beyond treatment. It includes scheduling an appointment, wait time, cleanliness of the facility, interactions with the doctors and staff, billing arrangements and more. Big data can help improve quality of care in many ways.

The Cleveland Clinic decided to use analytics to improve patient services. The clinic hired an agency to conduct a quantitative and qualitative study on what the patients expected from the clinic. The data revealed that what the clinic thought the patients expected from the clinic was quite different that was the patients actually expected. The patients expected respect, clear and consistent communication along with a happy hospital staff.

Lower Cost of Healthcare Delivery

Patient re-admission is a major cost associated with healthcare delivery. Hospital admissions in the United States constitute about 30 percent of the total annual healthcare cost and 20 percent of all hospital admissions happening within 30 days of a previous discharge. Medical errors, which can be avoided, also add to this cost. Big data coupled with effective analyses can help identify how, when, and where the problems or gaps lie. These issues can then be addressed with a relevant plan of action, resulting in lower cost of healthcare delivery.

The Challenges

Several issues have to be addressed to tap into the full potential of big data including policies related to patient data privacy and security. Healthcare networks not only need to put the right talent and technology in place but also structure data, workflows, and incentives to optimize the use of big data. Access to data is critical—companies will need to integrate information from multiple data sources, often from third parties, and the incentives have to be in place to enable this.

Patient Privacy & Security

The potential benefits of big data for healthcare are too valuable to overlook; however deciding on the allowable uses of data, while preserving patients right to privacy, is a difficult task.

Availability and access of patient health data along with personal patient information can result in discrimination or harm to the patient. This could mean that insurance companies make decisions about health insurance applicants and then set premiums based on the level of risk each individual represents or potentially deny them altogether. The Health Insurance Portability and Accountability Act (HIPAA) prohibits use of patient data for discriminatory purposes; but other entities holding the same data may be permitted to use it.

Another concern is the rise in the number and sophistication of cyber-attacks. With patient data residing in multiple locations they are susceptible to hacking. Health data is usually coupled with personal data of patients, which can be used to commit fraud, identity theft, and other crimes. It is imperative that data is encrypted and networks are secure.

Complexity & Structure of Healthcare Data

Healthcare data is complex because of several reasons. Health data is found in many locations such as different hospitals, various departments within a hospital, and different supporting office systems. This means that it may be stored in various formats, which may or may not be structured. Consolidating this data and standardizing it will make it more useful, accessible and analyzable.

Shortage of Skill

There is a shortage of talent in healthcare for organizations to take advantage of big data. Gartner states that through 2015, 85% of Fortune 500 organizations will be unable to exploit big data for a competitive advantage. As healthcare big data analytics gets more pivotal to estimate patient outcomes, competitiveness of healthcare organizations and the demand for healthcare IT professionals who can think critically and generate significant insights in a big data environment will increase. Those interested in a career in healthcare analytics should arm themselves with the skills required to take advantage of this opportunity.