Remaining competitive in healthcare is a constant challenge. If you’re a CTO or IT Manager at a healthcare organization then you already understand the speed of progress for technology in the industry. Providing quality patient care and balancing resources for lower treatment cost and facility overhead is changing. Every patient touch—from appointment scheduling to follow-up to check-in at your waiting room—is another opening for creating a more positive patient experience.
Whether you’re at a medical practice, hospital or health system, your data can be a positive force for your patient experience now that artificial intelligence (AI) is powering a new kind of patient experience.
AI is everywhere healthcare is.
AI is popping up in different areas of healthcare treatment and preventative care. From selecting candidates primed for clinical trials to performing AI-based mammograms to that can instantly detect breast cancer to catching other chronic illnesses sooner or even preventing suicide.
And AI doesn’t look robotic—that’s automation—instead it’s powered by machine learning (ML) using powerful algorithms that help to make more exacting and faster diagnoses.
AI still requires human intervention to capture and apply the right data, and that’s what’s really powering AI and ML, data.
AI solutions mandate uniform data to accurately process information using algorithms for heightened accuracy. So, what does storing AI data look like?
Here are a few approaches that are used now:
- Data housing: Data is stored in a single location for easy access.
- Data format: Data follows a unified format for AI systems to analyze.
- Data quality: Thoroughness and attention to detail enhance patient care.
How can we get started?
Your facility or practice completes an objective patient evaluation. The impartial data collected must follow a standardized response—removing any possible bias.
For example, data can be collected by selecting exam sections from a drop-down menu.
These 5 steps are necessary to any successful implementation:
Having the right managed services provided (MSP) can make these processes seamless. An MSP can partner with your organization to implement and train staff members responsible for accuracy in implementation.
1. Start by educating your stakeholders.
A main reason AI isn’t being used to its total potential in healthcare is the challenge in facilities keeping up with patient care while investing time in system updates. Meeting increasing care demands while complying with mounting governmental requirements in documentation isn’t just difficult, it presents a real learning gap. Putting a focus on education during the early phases of implementation is a must.
Training is a key factor in the success and implementation time of a large infrastructure organizational change. The bottom line for healthcare involves accurate patient care and improving facility overhead costs. Key stakeholders are involved in this process—you’ll want to tailor the system to fit your organization.
2. Make your admin teams aware.
Your organizational management and support staff need a basic working knowledge of what AI is. They should also understand how it affects the quality of care and how it can improve your facility’s business and finance practices.
Make sure you are communicating the real-life patient benefits that can prevent more serious health issues from occurring. Let your teams know that AI has been shown to predict health conditions before they ever arise by measuring all the associated factors and checking them through an algorithm.
There are many great examples to share like the ones above. Want a quick use case to share with your team that underscores the importance of new technology? AI can predict if even a slight drop in blood pressure during an operation indicates an oncoming cardiac event for your patient.
One of the critical benefits of AI in healthcare is its ability to support preventative care.
3. Enlist engineering to train your clinical team.
Engineers from the managed service provider can assist in training clinical teams on new processes for data collection. Engineers from an MSP can quickly show clinicians the benefits (why they should be training). Then those technical subject matter experts can walk your medical staff through the basic steps in repeating approaches to algorithms for exacting results.
4. Document, document, document!
Engineers from the managed service provider can assist in training clinical teams on new processes for data collection. Engineers from an MSP can quickly show clinicians the benefits (why they should be training). Then those technical subject matter experts can walk your medical staff through the basic steps in repeating approaches to algorithms for precision and accuracy.
5. Bring in the Subject Matter Experts.
Large-scale data management implementation for AI supports better patient care by identifying health issues before they strike. Patient data runs through advanced algorithms—comparing and analyzing the stats and prior outcomes for quick clinical results.
Whether your healthcare facility is using AI for early disease detection, preventative care or diagnosis of treatment options, results are quickly returned to improve your staff’s ability to make accurate and educated decisions. Sounds smart, right?
Exactly. This is where MicroAge can help.
Move Your Healthcare Technology Forward with MicroAge
MicroAge has been in the industry for over 40 years, and we are ranked in the top 170 of 500 on the CRN Solution list for North America. Our team of experts has experience supporting healthcare providers on their digital transformation journey—and we’re HIPAA certified.
Contact us today to get started.