The growing amount of healthcare data and the use of analytics can improve patient care and reduce costs. But can radiologists take advantage?
Meet the data entry clerk of my medical school era: A large and ponderous person slowly entering the written orders into the computer terminal. The clerks sat guarding their terminals, protecting unauthorized access, scaring away all but the most intrepid.
These women, in their implacable solidity, were unlikely representatives of the future, but were indeed the bridge from the handwritten to the world of the EMR and CPOE. Without their support, your orders never got entered, and as such each one was my best friend on every nursing station.
This was the beginning of meaningful use, the first baby steps to today.
By its very nature, medicine is an art, complex and fully nuanced. A science, yes, but more than that. The interface of medicine and the computer is a test of the information age. To reduce our art to a binary system of "yes" or "no" remains a challenge despite the great advances of the information age.
Consider something as simple as a belly X-ray: KUB, flat and upright abdomen, abdominal series, flat plat of the abdomen, abdominal film, r/O free air. The same? Different? How to enter? This is still a challenge for CPOE.
When a person read the doctor's order and entered it into the system, they knew a lot about what the doctor actually wanted and what they really meant by their order - and usually they were right. They translated the written order and served as a human interface to technology. Since then we have made progress, but even how to integrate all the data we have today is uncertain. And more data is coming soon.
Discrete data elements, data mining, big data, clouds, meaningful use - what can that mean to us as radiologists? In 2014, as meaningful use stage 2 rolls out, we will have a tsunami of data. How will we use all that data to improve care? Can we take baby steps, or jump in feet first to the storm?
Americans are big spenders on healthcare with poor results, as compared to our peers around the world, but how to do it better?
Can we as radiologists make sure to be involved, and create a world where more information is better and helps us do our job better? Something as seemingly simple as making sure the right test done right the first time? In the ACO model costs will be cut. We must meet this challenge, and with fewer resources deliver better care. Can we?
What does this mean for us? As radiologists we have to ensure that the right test is done the first time, make the correct interpretation, and deliver the reports to the right docs and ultimately to the patient. Knowing more about our patients will be imperative. More and more data, shared and available from millions of patients, will allow us to deliver better care. Unlocking this data and using it to improve care delivery is a pressing challenge today facing radiology.
Data analytics will allow delivery of personalized radiology.
With a personalized approach, we will be able to recommend the right tests, and have the data to back us up. This might mean suggesting that one patient not have a breast biopsy, but rather an MRI. Then at once we could communicate this suggestion, not only to the referring physician, but also to the patient herself - directly and quickly, via patient portals.
For another patient, perhaps superficially similar, we might suggest routine follow-up, and a third, with the same imaging findings, might get an immediate tissue sampling. Looking at large scale data using sophisticated data analytics allows a more complete and confident conclusion than does looking at one individual in isolation. We will be able to not only integrate this patient's data, but that from similar patients, looking from things as simple as their zip code to complex genetic information, and make a recommendation specifically tailor-made for that individual - indeed personalized radiology.
Using the power of data analytics, the cloud and big data, we will be able to better direct and monitor patient care.
By tailoring imaging to meet the needs of each patient and strategically selecting imaging care plans tailored to each individual, I believe we will reduce costs, reduce unnecessary radiation, protect ourselves from ligation, and allow patients to be increasingly involved in their own care, with more patient-centered radiology.
What do you think?
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.