As I explored in a previous post on stranger things in data, many healthcare organizations consistently run into the case of the missing information
"Most healthcare analytics tend to give you only what you ask for: procedures performed by surgeons, a list of patients with congestive heart failure, ICD codes, etc.
But what about those procedures that haven't been performed? Or patients that aren't on that registry? Or claims that involve a run-in with a Demogorgon (anyone know the ICD code for demon attack?)
Sometimes, the most important thing to know in healthcare is when something DIDN'T happen. These are things you can find in the Upside-Down World."
Now that we're into Season 2 of Healthcare analytics, and we've visited the Upside-Down a few times, what other things do you need to combat that which lurks in the darkness? I'd argue that you'd need to look not only the data that's missing, but data from other systems.
Healthcare organizations have used analytic capabilities to bring in additional sources of data. For instance, to fight the Opioid Crisis, you could bring in information from HHS, CMS, and DEA.
Have you thought about using geographic data sources? A leading healthcare payer uses location intelligence to identify access to care issues for patient members based on where they live in relation to hospitals, clinics, and pharmacies.
We've seen the challenges in working with external data sources - and Qlik's DataMarket team has made bringing in numerous data sources much easier. Released just in September, healthcare and life sciences organizations can pull in new data sets from CMS, enriched with additional metrics and measures, to get a better picture of how hospital's quality programs stack up against one another, or how demographic factors influence your population health management programs:
So as you prepare to take on the darkness, don't be afraid of what you don't know. Embrace it. Seek out the stranger things in your data and beyond, with Qlik Sense at your side.
It may be dark in the upside down, let data be your light. Learn how with a #healthcare #analytics specialist: