Focusing on applications and use cases of analytics in the U.S. health care industry provides a clear window into the opportunities and challenges for big data analytics in general.
The datasets involved are large. They are diverse, ranging from handwritten notes on paper to film records to electronic formats that include databases and unstructured text notations. The business processes must follow important regulations about data privacy. And the people who manage those processes have years of specialized training to do their jobs.
Analytics use cases in health care can range from efforts to improve operations at a hospital, to helping doctors use more data in their clinical work, to advanced research projects that seek new insights about the onset of disease and paths to treatment. Below, find highlights from Data Informed’s coverage of analytics applications, technologies and use cases that focus on health care.
The key challenge in adopting analytics in the health care industry is not all that different from the challenges line of business managers in other industries face: you need to win over and engage the front-line people who can make a real difference in producing new kinds of results. Here, that means doctors and their clinical colleagues. Read more.
Shahram Ebadollahi, the program director of health informatics research at IBM, explains details about research project to develop predictive analytics for primary care doctors to identify patients at risk of heart failure as much as two years ahead of time. Read more and hear a podcast discussion of the project.
In this podcast, Graham Hughes, the chief medical officer of analytics provider SAS, talks about the difference analytics can make in examining the cost and quality of health care in the United States. Read more and listen to the podcast.
Findings from health informatics researchers at Weill Cornell Medical College offer reassurance that even though electronic health records (EHRs) tend towards analyzing data on a technical, rather than instinctive level, they almost always offer health professionals the same health insights for patients and the public as when those professionals glean information solely through manually-kept health records. Read more.
When it comes to using data to manage patient care, Atrius is already considered an innovator. This article describes how Atrius brings data analysis closer to its decision-makers. Read more.
Stephen Gold, IBM Watson Solutions vice president, discusses using Watson, what IBM calls a cognitive computing system, as an assistant in health care and business contact centers. Read more and listen to the podcast.
An estimated 22 military veterans take their own lives each day—one almost every hour, according to recent research by the U.S. Department of Veterans Affairs. Yet predicting who is likely to commit suicide remains a challenge for mental health professionals. That’s where computer scientist Chris Poulin and a semantics-based prediction tool enter the picture. Read more.
There’s an important effort underway among health care data experts to enable clinicians and medical researchers to share the same data for analytics to improve patient outcomes. Read more.
The founder of Privacy Analytics, a privacy software company based in Ottawa, Ontario, discusses his efforts to build a company that de-identifies large troves of personal data for the purposes of analysis. The company is a player in an emerging field in the health care industry. Read more.
The challenges facing Louisville as it sought to address high rates of asthma illustrate some themes common to big data analytics projects: Get all data sources working together. Design a governance model for the data and processes for people to follow. Establish communications channels to use insights from the data. Set up a way to learn from experience so that project managers can apply lessons to improve the system. Read more.
Researchers at the State University of New York at Buffalo are using data analytics to support their efforts to discover new drugs to treat multiple sclerosis. Read more.
Data-driven projects related to cancer research, drug discovery and clinical trials are part of the government’s efforts launched with a number of partners in industry, academia and the nonprofit sectors. Read more.
Johns Hopkins Hospital in Baltimore is using visualizations to measure performance and the cost of care. Its experience is worth studying. Read more.
Scott Nicholson left his job as a data scientist at LinkedIn to join Accretive Health, a company that works with hospitals on payment systems. At a conference last year, Nicholson, whose title is chief data scientist, explained the work involved in asking the right questions and building analytical models. Read more.
BI is an enablement mechanism for analytics, writes Laura Madsen, leader for the health care practice at Lancet Software. Read more.