Healthcare care is an area that many people agree lives in two worlds: one of scientific cutting-edge studies and another world that consists of old school paper filing and dated documentation systems. Data science and analytics has long been a part of healthcare systems in this country, but many in leadership believe that it has not yet been integrated to its fullest potential. Why might this be? With healthcare workers often being some of the most educated and technically savvy why are they missing out on this golden age of data?
The healthcare industry lags behind others in non-medical innovation.
It is difficult to change how a large and often siloed organization works from the inside. When it comes to data analytics and procedures The Brookings Institute reported that 56% of hospitals have no strategies or plans in place. Some of the reasons why the healthcare industry lags behind other institutions have to do with the healthcare industry’s unique space in following federal policy, institutionalized practices and history, but others are as ingrained as human behavior both from an institutional perspective and a patient perspective. Implementing sound data practices will be a journey and should be done intentionally for the best impact on patients and healthcare providers.
Healthcare is a very human-centric industry.
People are wary of letting machines make life decisions for them beyond which movie to watch on Netflix. Rightfully so. Bias in machine learning and artificial intelligence has shown to amplify some of the racial and sexist decisions of our past. However, when implemented correctly, machine learning in healthcare has been proven to be more effective and accurate than physicians’ diagnosis. And while I don’t condone nixing the doctors, data can be a great way to supplement a health care provider’s arsenal. It may take some time to get patients used to getting routine diagnosis from a machine but paired with healthcare providers’ experience, this data can be invaluable.
Policy can drive many decisions in the healthcare space.
Policy is the metadata in the healthcare space that is never going away and often changing in how it affects how people are able to give and get care. Policies that drive how and when data can be used, what treatments are available for what patients and so much more. It is understandable that many healthcare organizations are intimidated by having to keep this data up-to-date and relevant in how it interacts with their databases. Procedures can be placed around policy changes and how they affect data and logs built into databases can make it easy to find when policy changes went into effect and how the changes have affected the performance and goals of healthcare organizations.
The healthcare industry has ample opportunity to use data analysis to their advantage. Finding when and how to implement these changes will be key for organizations to stay ahead of the curve and provide the best possible care to their patients.