Quick Wins are Nice in Analytics, but Tough to Get
When starting a data analytics program, what are some quick wins an organization can achieve to show early the value of the initiative?
When starting a data analytics program, what are some quick wins an organization can achieve to show early the value of the initiative?
Thats a question a panel of experts tackled during the Healthcare Analytics Symposium in Chicago, sponsored by Health Data Management. Available now are home healthcare technology products that offer a common interface to enable patients, their family members and/or their physicians to better communicate and exchange health data and other messages, said Terri Steinberg, M.D., chief health information officer and vice president of population health informatics at Christiana Care Health System in Wilmington, Del.
Steven Collens, CEO at the MATTER healthcare technology start-up incubator in Chicago, sees wearable sensors as tools that will be helpful. While rapidly evolving, he still believes they are one or two generations of development away from giving real value.
Bruce Smith, senior vice president of information systems and chief information officer at Advocate Health Care in Chicago, had a more cautious tone. Programs of value build over time, he contended, with success breading more success. Resistance to expanding use of data is gone, but an organization still cannot negate the time and effort it will take to get value back.
Also See: Top 10 Priorities for Big Data Management
The panel also tackled how to find people with the right analytics and information skills, with the worry that there arent enough available. Smith said the issue isnt so much that there is not enough talent, but the focus of the talent brought in is not optimal, with people working at cross purposes. The talent is there, he added, and availability is growing.
Niall Brennan, director and chief data officer at the Centers for Medicare and Medicaid Services, said there is a lot of competition to get the right people, but those who seem to be the most right may not be. It isnt necessary just to hire someone with a degree in data science. Hire smart people and give them time to learn, and get great analyses for years, he advised.
On the question of how to close software gaps in data analytics, incubator leader Collens called on healthcare organizations to be more willing to engage with early stage companies in ways that can be constructive for both sides. Early stage companies have a half-baked product and it is tough to get hospitals to join in a relationship and be willing to invest capital and time to shape the product.
The lack of interoperability is hindering analytics, as hospitals have data platforms and clinical platforms, but difficulty integrating them to support workflows, said Steinberg of Christiana Care. Brennan also weighed in on integration woes, saying there is a long way to go until claims and clinical data can interoperate seamlessly.
Thats a question a panel of experts tackled during the Healthcare Analytics Symposium in Chicago, sponsored by Health Data Management. Available now are home healthcare technology products that offer a common interface to enable patients, their family members and/or their physicians to better communicate and exchange health data and other messages, said Terri Steinberg, M.D., chief health information officer and vice president of population health informatics at Christiana Care Health System in Wilmington, Del.
Steven Collens, CEO at the MATTER healthcare technology start-up incubator in Chicago, sees wearable sensors as tools that will be helpful. While rapidly evolving, he still believes they are one or two generations of development away from giving real value.
Bruce Smith, senior vice president of information systems and chief information officer at Advocate Health Care in Chicago, had a more cautious tone. Programs of value build over time, he contended, with success breading more success. Resistance to expanding use of data is gone, but an organization still cannot negate the time and effort it will take to get value back.
Also See: Top 10 Priorities for Big Data Management
The panel also tackled how to find people with the right analytics and information skills, with the worry that there arent enough available. Smith said the issue isnt so much that there is not enough talent, but the focus of the talent brought in is not optimal, with people working at cross purposes. The talent is there, he added, and availability is growing.
Niall Brennan, director and chief data officer at the Centers for Medicare and Medicaid Services, said there is a lot of competition to get the right people, but those who seem to be the most right may not be. It isnt necessary just to hire someone with a degree in data science. Hire smart people and give them time to learn, and get great analyses for years, he advised.
On the question of how to close software gaps in data analytics, incubator leader Collens called on healthcare organizations to be more willing to engage with early stage companies in ways that can be constructive for both sides. Early stage companies have a half-baked product and it is tough to get hospitals to join in a relationship and be willing to invest capital and time to shape the product.
The lack of interoperability is hindering analytics, as hospitals have data platforms and clinical platforms, but difficulty integrating them to support workflows, said Steinberg of Christiana Care. Brennan also weighed in on integration woes, saying there is a long way to go until claims and clinical data can interoperate seamlessly.
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