For example, if a doctor has 45-year-old female patient newly diagnosed with breast cancer, wouldn’t it be great if that doctor could easily do “research on demand” to evaluate treatment options and outcomes based on data from the internal and external sources to help determine the best care pathway.
The doctor may then be able to identify that out of five treatment modalities, one in particular produced the best outcome for 45 year old women whose profiles are similar. EMRs generally don’t provide any way for health professionals to do this type of analysis. They hold a tremendous amount of patient data, but without the right tools surrounding the EMR, there’s no way to unlock the potential value of that data.
At the same time that health organizations are digitizing vast amounts of data, so are health consumers. They’re using social media and other consumer technologies to do things like track blood glucose monitor readings, write journal entries about their diet and exercise, share experiences on health condition forums, provide feedback about healthcare providers, and more. There’s an endless amount of health consumer data out there, but it’s unstructured and spread across a diverse set of sources. Again, without the right tools, it’s difficult to garner any insight from it.
In other words, even though we’re drowning in data, we’re thirsting for insight. The challenge is: How can we generate value from all of this data? How can health professionals make intelligent use of it to improve healthcare?
That’s where health analytics solutions from Microsoft and partners can help.
First, these solutions can help pull together different types of data—whether structured, unstructured, or semi-structured—and marry these diverse data types in ways never before possible.
Second, these solutions provide self-service tools that empower staff across a health organization to not only bring together data, but also look at it in the way they need to for their specific role. Using these tools, health professionals can do their own research on demand, rather than having to wait for an analyst to send it to them. For example, the endocrinologist who knows precisely what he or she is looking for when it comes to patterns for the best, most cost-effective, prediabetes treatment modalities can use familiar tools to consolidate data from many sources. Or, someone in a health organization could use these tools to garner insight from social media/health consumer technologies.
Today’s health analytics solutions provide the tools that health professionals need to generate actionable insights from the rapidly growing data in our industry. And ultimately, these insights can help health organizations and their staff be much more agile and effective in how they manage the quality and cost of health care going forward.
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