The outlay for a new health system can be significant, often comparable to capital investments for a company. No surprise, the system needs to work, be reliable, make sense and produce results quickly, high demand for a field well-known for needing adjustments to tailor to the specific needs of a medical business the tech is applied to. Additionally, the cost of a system isn’t just the system itself. Expenses also include the implementation talent needed to make things work for the first time, the training to bring all relevant staff up to speed with the new system, and the infrastructure changes needed to maintain the system in sync with other network resources as well as migration of data. Unless building a new system, conversions to a new one typically take anywhere from one to three years to complete.
With such high risks and chances for things to go sideways, significant commitment has to be made for both internal teams and external support to make a new health system work, and planning is a key first step. Without knowing what to look for in how to solve a problem, it’s very easy to end up with a healthcare system that doesn’t truly serve the organization.
HIPAA Compatibility
At a fundamental level, any healthcare system brought in has to be HIPAA compliant as well as updateable to the latest HIPAA changes. A medical organization puts itself at significant financial risk without being properly aligned with HIPAA rules, particularly with patient information handling.
Learning Ease
Often left for last on big projects, a good system should be intuitive for the fastest adoption. The longer it takes for a user to understand how to do basic navigation in a new healthcare system applied, the longer it will take to make the new platform work as expected and desired. As long as people are a critical component of data input, manipulation, and output, the user experience matters tremendously for the success of a project. The easiest way to achieve that is to make the learning curve as easy as possible.
Minimal Integration
Ideally, a new healthcare system should integrate seamlessly with an existing network architecture a medical company already has. However, that’s rarely the case. Many times, integration issues don’t appear until one gets to the actual relationship of a particular transaction, and then the issue becomes apparent. Because every company has nuances and quirks, a good system package should include a robust testing and implementation component to work out the integration bugs completely. Avoid any package that promises a quick turn-key install. They simply don’t happen.
Automation Capability
There’s no question that when data is handled in an automated fashion with clear rulesets and related reference tables, error rates go down tremendously. And today’s Automation AI provides some incredible machine learning opportunities for handling the majority of data functions that are redundant and repetitive. Any new system should take advantage of this aspect for a healthcare system install. It’s essential for clear and accurate data transfer management.
Scrutinize the Feature List
Most software sellers and resellers spend an awful lot of on marketing, so take advantage of it when considering healthcare software packages. Push vendors to provide as much detail as possible about every feature included. Then grid them out on a comparative view against your business needs with your internal team’s analysis. It’s free information and available for review, but many times clients forget to ask for as much detail as possible.
If you want the top healthcare software of 2022, you have to hunt for it actively. Too often, companies hire consultants who position themselves as enablers but really are just consolidating the offers of other sellers underneath them as subcontractors. This approach avoids understanding the details of a system and keeps the primary client blind. Getting to the real offer of a potential system means taking time to understand it directly. And when a new system can be a significant outlay for your company, punting that analysis to an outside player can be a mistake. Primary engagement pays off far better in the long run.
