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T e results of such analysis can be applied in real time to patient care. Readmission predictors are a good example of this analytic evolution. Over the years, many readmis- sion models have been described with varying degrees of validity and usefulness. Unfortunately, many have relied on post-discharge billing information and therefore were not applicable at a patient’s hospital arrival or during the hospital stay. But today, new statistically valid measures of readmission risk that are based on electronic data are emerging that can be used at the time of admission. T ese measures provide the clinician with subsequent readmission probabilities to guide current interventions. Point-of-care intelligence on other risks will be available soon as well as data-driven best practice guidelines to improve care for high-risk individuals and populations. Today’s exciting advances will pave the way for mind-boggling possibilities tomorrow.

Martha Thorne, General Manager, Performance and Care Logistics, Allscripts T ink of all the information collected ev- ery day by providers, payers, pharmas and researchers. Bring all that data together in intelligent, actionable ways, and you have incredibly powerful insight for managing

population health, improving outcomes and reducing costs. To fully appreciate the potential of analytics – both for health- care organizations and for the patients in their care – consider the possibilities of adding genomic data into the mix. Orga- nizations are already looking at how genomic profi les impact metabolism of medications. Imagine what this could mean to the healthcare industry and our delivery of care. Being able to predict at the genetic level how a specifi c dose will aff ect a patient’s metabolism of medication could be crucial in preventing an emergent situation. Similarly, think of all the conditions that present similar risks, such as any infectious diseases, and how genomic profi ling could help clinicians fi ne-tune therapies and medications to deliver safer, faster results and better care. T at’s the impact of Big Data. T rough analytics, providers

have powerful tools for spotting potential health risks across their patient populations. Combined with payers’ ability to bring in fi nancial data, you’ll see the true impact of how providers and payers can work together to create value that neither could achieve individually.

Jason Harber, Vice President, Product Management, TeleTracking Technologies We expect Big Data to get even bigger in healthcare analytics because so many areas of healthcare have yet to be scrutinized regarding more effi cient performance, and effi ciency will be a major factor in reigning in the spiraling cost of healthcare.

More data is being created every day in an eff ort to im-

prove operational effi ciency in hospitals. As a simple example, most hospitals can’t tell you the average time it takes for their nurses to receive an IV pump after making the request. T at’s a small item with huge implications not only for running a hospital effi ciently, but even more importantly, for delivering timely care to their patients. Without knowing the lag time, how can you improve it to make sure a patient’s condition doesn’t deteriorate? Operational effi ciency demands not only the constant analysis of currently measured tasks, but the discovery of new measurements which can help to improve daily operations. Simply reporting the implications of existing data isn’t enough when you’re searching for the best ways to improve performance. You need to be constantly watching for new opportunities to improve, and this means creating additional data streams based upon the processes you are reviewing. Complicating matters is the fact that the marketplace now demands this information be collected and made consumable in real time. T at requires a business analytics engine which is integrated with a system capable of moment-by-moment data collection. In fact, it is this very integration which permits the creation of data that never existed before. In the near future, data creation will be the key to predicting a typical day at the hospital before it happens.

Charlie Lougheed, President and Chief Strategy Offi cer, Explorys According to recent statistics from the Of- fi ce of the National Coordinator (ONC), in just over a year [electronic health record] adoption has doubled, leading to a signifi - cant increase in the volume of healthcare data. With increased use of smart medical

equipment, implantable devices, patient portals, mobile health, etc., the amount of data entering the healthcare landscape will only continue to grow. Managing this infl ux of data is one challenge; however,

healthcare leadership also needs to be able to analyze and predict risk, assess opportunities to improve outcomes, reduce unnecessary cost and present actionable information to those engaged at the myriad channels and modalities of care. Like in other market sectors, those that use data to im-

prove their quality and price competitiveness will not only grow their market share, they will also likely be on the good side of mergers; especially as systems consolidate to improve effi ciency. T is will become even more critical as healthcare systems develop clinically integrated networks (CINs), ex- pand their direct-to-employer eff orts and off er risk-bearing plans to the market. In order to leverage data in a meaningful way, healthcare organizations must also implement a culture of data. T is will require support and buy-in from frontline physicians, as well as those involved in the coordination of care.


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