To this end, it makes sense that IT solutions (and technology in general) are playing a vital role in many population health initiatives. Several recent advancements in tech perfectly lend themselves to the needs and challenges this concept presents.
And one such advancement stands out above the rest.
How Advanced Analytics Apply to Population Health
Regardless of your healthcare job description or personal interest in emerging technologies, you’ve probably heard of big data: The collection, comparison, and analysis of information pulled from numerous sources and sifted through at large scale. Though we haven’t come close to realizing this concept’s potential in healthcare markets or the world at large, its current capabilities (and projected near-future ones) are so useful to the ideals of population health that the technology could have been created for that express purpose.
One exciting benefit is sheer versatility. From a general healthcare perspective, this video from IBM shows what one tool, the “celebrity computer” Watson, can do with the right numbers. In the video, a professional is able to see how patients with a certain illness in a specific age range respond, on average, to a given medication. It also shows many other stats, including care experience and cost per member per month.
The implications for population health in this example alone are eye-opening. Big data can crunch unstructured (that is, hard to classify and sort) data from a large number of sources, then sniff out findings. For example, a properly equipped hospital’s big data platform could analyze social media posts, internal EHR figures, area news stories, and other sources to determine whether a given preventable illness is on the rise in its area of influence.
As analysts draw conclusions
from data fed into an organization’s platform, they are able to examine more trends in a predictive capacity. This can help decision-makers complete such crucial tasks as how best to spend budgets and which medical specialties to hire for, among others.
On a broad scale, big data tools can help providers and healthcare systems better understand the communities in which they work. The hospital that serves a large population of older Americans will likely need an approach different from the clinic with a younger distribution of potential patients, for example.
Sharing Is Caring
Analytics represent the contribution to population health with the largest potential: When a field of medicine is all about understanding a large group of people, many of whom you haven’t served, analytics are second only to individual interviews. And even then, a data platform would still crunch the numbers in the end!
This makes data from any number of populations and geographical locations valuable — and that, in turn, makes initiatives like one covered in Health Data Management all the more exciting. Instead of relying solely on their own data, the users of a certain commercial data analysis tool can analyze data from 55 million patients (with the PHI removed, of course), which it imports from the roughly 360 hospitals that served them.
Any time a discovery is made, the partnering hospitals can share it with each other, making overall population health data more effective. The same correlation could, and realistically will, be shared with other, similar data-sharing networks. The more hospitals that join a given alliance, the more data there is to pluck insights from.
If it sounds like a near-future development, think again. These data-sharing alliances are happening now. While there’s always room for statistical analysis to improve, it feels like medicine has hit the future — even though, in all reality, this is only the beginning.
Data Is the Key to Population Health’s Future
Numerous existing and emergent technologies can and will transform population health practices over the years, and data is the glue that binds them all. Healthcare in general is moving toward evidence-based activity, making advanced analysis more of a gatekeeper than an end result: Whatever technologies a system implements or initiatives it puts forth, you can expect to see more data-informed decisions in coming years.
To be sure, there are still challenges to overcome. As with any technology, current-day capability still lags behind ideal use-cases. There are also “questions about the ownership of health data” to consider, according to Greenway Health: Besides perhaps finance, no field is more preoccupied with protecting privacy than healthcare, making the mass collection and analysis of any patient-related data (PHI removed or not) a possible minefield for hospitals and their legal teams to tiptoe through.
Even then, though, progress is coming, and present-day applications are already impressive. As data continues to guide, inform, and produce, expect to use it more often in whatever capacity you fill — no matter how much you use it now.