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The ways in which technology benefits healthcare
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Bringing Big Data Analytics To Health Care

Bringing Big Data Analytics To Health Care | healthcare technology |

Big data offers breakthrough possibilities for new research and discoveries, better patient care, and greater efficiency in health and health care, as detailed in the July issue of Health Affairs. As with any new tool or technique, there is a learning curve.

Here are some guidelines to help take full advantage of big data's potential:

Acquire the “right” data for the project, even if it might be difficult to obtain.

Many organizations – both inside and outside of health care – tend to stick with the data that’s easily accessible and that they’re comfortable with, even if it provides only a partial picture and doesn’t successfully unlock the value big data analytics may offer. But we have found that when organizations develop a “weighted data wish list” and allocate their resources towards acquiring high-impact data sources as well as easy-to-acquire sources, they discover greater returns on their big data investment.

Ensure that initial pilots have wide applicability.

Health organizations will get the most from big data when everyone sees the value and participates. Too often, though, initial analytics projects may be so self-contained that it is hard to see how any of the results might apply elsewhere in the organization.

Before using new data, make sure you know its provenance (where it came from) and its lineage (what’s been done to it).

Often in the excitement of big data, decision-makers and project staff forget this basic advice. They are often in a hurry to immediately start data mining efforts to search for unknown patterns and anomalies. We’ve seen many cases where such new data wasn’t properly scrutinized – and where supposed patterns and anomalies later turned out to be irrelevant or grossly misleading.

Don’t start with a solution; introduce a problem and consult with a data scientist.

Unlike conventional analytics platforms, big data platforms can easily allow subject-matter experts direct access to the data, without the need for database administrators or others to serve as intermediaries in making queries. This provides health researchers with an unprecedented ability to explore the data – to pursue promising leads, search for patterns and follow hunches, all in real time. We have found, however, that many organizations don’t take advantage of this capability.

Health organizations often build a big data platform, but fail to take full advantage of it. They continue to use the small-data approaches they’re accustomed to, or they rush headlong into big data, forgetting best practices in analytics.

It’s important to aim for initial pilots with wide applicability, a clear understanding of where one’s data comes from, and an approach that starts with a problem, not a solution. Perhaps the hardest task is finding the right balance.

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APIs Boost Health Information Exchange

APIs Boost Health Information Exchange | healthcare technology |

No matter how innovative the personal health records (PHRs) or electronic health records (EHRs) become, given the highly fragmented and specialized US healthcare system they still need to exchange data in a secure way that preserves privacy and trust. That is the goal of health information exchange (HIE).

The key HIE technical challenges are easily understood. Parts of a patient's clinical data will often be stored in many EHRs. For a patient with four, five, or more chronic diseases (these drive half of all Medicare costs) research shows that this will typically exceed 10 EHR implementations from multiple vendors! A conscientious provider seeing such a patient would want a comprehensive view of all of this care in order to save time collecting information that already exists, avoid duplicating tests and procedures that have already been done, and prevent mistakes from lack of information.

Historically, there have been two attempted solutions: 1) store everything centrally and, in essence, create a community record, or 2) keep the data at the source but build central indexes to patients and their medical documents and provide some kind of translation service to bridge differences in the way clinical data is represented across EHRs. This is the so-called hybrid exchange.

More recently there is Fast Healthcare Interoperability Resources (FHIR), which is essentially based on the idea that healthcare information can be exchanged the same way that other information is shared on the Internet. If you've used Amazon to look for goods to purchase, you might have noticed that, up there in the URL, text appears when you click the search button that specifies what you want. Although it might be a bit cryptic, even a non-technical person can usually figure out most of what it says.

What's really going on here? You're at your computer (which, of course, these days might be a mobile device such as a smartphone), and the information you want is securely stored in, for example, Amazon's cloud. You specify what you want, and your browser creates a query and sends it to the cloud, where it might be routed to any one of thousands of Amazon servers that will interpret it, query a database, and return the information you requested. This ability to route requests to any server in the cloud that is available is another key technical property that lowers costs and is exploited in FHIR.

As with Direct, there is more to the story than I've described (technically inclined readers should read the FHIR Summary, which is also available as a two-page PDF). But this should suffice to give you the basic idea of what is increasingly termed "API-based HIE."

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Craig Allen Keefner's curator insight, January 29, 2014 11:20 AM

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Stephen Greengrass's curator insight, January 31, 2014 4:56 AM

APIs are the way forward for so many aspects of digital content.  Combine these with patient info and it's a powerful opportunity for real innovation in care.

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How can HIE patient queries save millions in repeat tests?

How can HIE patient queries save millions in repeat tests? | healthcare technology |

How can health information exchange lead to savings? A case study by Western New York’s clinical information exchange HEALTHeLINK claims more than a million dollars could have been saved by avoiding unnecessary CT scans. And patients stand to benefit as well.

“These findings demonstrate the value an HIE provides by reducing the number of unnecessary tests which saves time, money and radiation exposure to our patients,” HEALTHeLINK chairman Dr. David Scamurra said in a public statement.

Using a sample of patients having received more than one CT scan during six-month period — sometime between July 1 , 2011 and Dec. 31, 2014) — the study broke duplicate scans into three categories: known (3,361), inconclusive (1,878), and unknown (885). Known studies were removed and the remaining 2,763 CT scans deemed to potentially unnecessary duplicative tests.

Based on the findings, an overwhelming majority of duplicative CT scans (90%) were the result of orders made by physicians who either never (0 queries) or infrequently (1-499 queries) used the HEALTHeLINK patient query function, the virtual health record (VHR).

What’s more, the use of VHR could have prevented 48.2 percent of duplicate CT scans from being performed based on the patients having consented to their information being available for HIE and their data being searchable by HEALTHeLINK users.

The study also shows that hospital-based physicians were the most frequent users of CT scans and the greatest source of duplicate scans, representing more than 95 percent of those deemed potentially unnecessary.

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Can sharing patient records among hospitals eliminate duplicate tests and cut costs?

Can sharing patient records among hospitals eliminate duplicate tests and cut costs? | healthcare technology |

A recent analysis of the impact of health information exchanges, which allow health-care providers to share patient records electronically and securely, shows the systems hold promise for reducing health costs and unnecessary care in emergency departments.

For the study (subscription required), University of Michigan researchers examined information on hospital health information exchange participation and affiliation from the Health Information Management Systems Society’s annual survey as well as data the  California and Florida state emergency department databases from 2007 through 2010. Both states were early adopters of health information exchanges. According to a university release:

The findings show that the use of repeat CT scans, chest X-rays and ultrasound scans was significantly lower when patients had both their emergency visits at two unaffiliated hospitals that took part in a [health information exchange]. The data come from two large states that were among the early adopters of [health information exchanges]: California and Florida.

Patients were 59 percent less likely to have a redundant CT scan, 44 percent less likely to get a duplicate ultrasound, and 67 percent less likely to have a repeated chest X-ray when both their emergency visits were at hospitals that shared information across an [health information exchange].

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