It’s no longer possible to ignore the central role information technology plays into today’s healthcare systems. IT systems are used to process payments, manage patient information, and provide an overall better experience for both healthcare providers and patients alike. However, there are still several hurdles healthcare providers must overcome when implementing and maintain IT systems. Here are some of the most pressing challenges faced by healthcare IT today.
1.) Customer experience
It’s no longer enough for healthcare organizations to simply have an IT system. In order for these organizations to remain competitive, their IT systems also need a corresponding customer service infrastructure and simplified yet comprehensive interfaces to assist users as well.
Having an IT system that is difficult to understand or hard to navigate can very well be a source of frustration to patients and healthcare providers. This means less time resolving issues, more time handling inconsequential minutiae — both of which can result in increased dissatisfaction among patients. This is especially important as patients today are generally expected to shoulder a bigger part of their healthcare bill, which raises their expectations of their providers.
More than ever, healthcare IT implementers will have to focus on streamlining and simplifying processes so patients are better able to handle simple issues themselves. The ability to easily download medical records, book appointments, and check important finance and account information is especially key.
Customer service will also likely need to undergo some changes in the near future. Healthcare providers will also likely have to turn to outsourcing and artificial intelligence to help with the customer service end of their systems, especially in developed countries. This is because older adults are likely to comprise a larger part of the world population, thanks to their longer lifespans, as well as falling birth rates. The increase of the population of older adults compared to younger ones is likely to place additional demands on IT and customer service that cannot be currently met by existing healthcare systems.
2.) Data security
At present, many healthcare providers are running obsolete IT systems, many decades old. This puts patient data at considerable risk, as aging systems tend to be comparatively simple targets for hackers due to the lack of continuing security support. The hardware infrastructure on which the data is actually present is also likely to deteriorate or become more difficult to maintain, increasing the likelihood of unintentional data loss. There are also significant challenges migrating large amounts of data from legacy systems.
The threat of cyber-attacks however, isn’t just restricted to older healthcare IT systems. In the United States alone, around 5 million patient records were exposed in a series of healthcare IT data breaches in 2018. There may even be more attacks that ultimately went unnoticed and the number of exposed records may be even higher. Worldwide, the number of breaches and the amount of stolen data may not even be possible to know with any accuracy.
Both aging systems and malicious hackers still in abundance, it’s clear healthcare IT security professionals have their work cut out for them.
3.) Data rationalization
Healthcare data today tends to be haphazardly distributed among different systems, providers, and parties. As such, it is often difficult, if not impossible to get a true picture of the status of a patient from any single source. There are also often multiple redundancies that serve no real purpose in terms of patient care, and slow down a case worker’s understanding of a situation.
This issue isn’t limited to data held by different entities either. It is also a very real issue within organizations, which can ultimately cause inefficiencies and patient dissatisfaction.
While it is possible to rationalize healthcare data, it may prove easier said than done, as it may require not just technical expertise, but leadership, and a paradigm shift in how we think about data as well. Some solutions put forward to resolve these issues include the use of advanced AI, as used by search engines today, as well as sophisticated modeling. As the amount of data we have stored expands, we may become more and more reliant on these new technologies.
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