Posted by: Jenny Laurello
Anthelio, Business of health care, Data analytics, EBM, Evidence-based medicine, MD, Pulse oximeters, Wendy Whittington
Guest post by: Wendy Whittington, MD, MMM, Chief Medical Officer, Anthelio Healthcare Solutions Inc.
An example outlining why we tend to be conservative in health care in our decisions about business
When most people read news headlines pertaining to medical matters, the answer about what we should do often seems obvious. What the average reader doesn’t generally know is that there is usually a lot more to the story.
Those of us who grew up in health care tend to worry about consequences, regardless of whether that story involves direct or indirect patient care. The adoption of electronic health records (EHRs), the automation of processes, the streamlining of workflows all tend to sound like good ideas and for the most part they are, but the health care environment is so incredibly complex that you darn well better be sure you know what you are doing before you upset the apple cart. To people that run hospitals, every business decision that is made is made with the patient in mind and rightfully so. It is pretty easy to look from the outside in and wonder why hospitals don’t adopt new policies today to make what they do more efficient and cost effective. People that make decisions for health care on the business side of the shop have a tremendous responsibility to keep the environment that clinicians work in as safe and consistent as possible.
Take this clinical scenario as one example. The big new story of the week is that a $5-10 pulse oximetry test may help diagnose heart defects in newborns. What’s interesting about this is that the American Heart Association and others endorsed this type of screening back in 2009. The article in Pediatrics this week wasn’t alone as there was also a recent study in the British journal Lancet.
Why did it take two years to recommend widespread testing? Two states, Maryland and New Jersey, already make the test mandatory and, after all, it’s inexpensive and we’re talking babies here! This is the kind of story that grabs headlines and shows up on the evening news. In 2009, it was determined that the test wasn’t ready for widespread use. There was too much they didn’t know. They knew that babies’ lungs continued to develop after birth, so they delayed the test for 24 hours. They recommended the use of motion tolerant pulse ox equipment, but those were not FDA approved yet. They didn’t know if high altitude, sleep or other environmental factors would affect the test. Also, they needed to add new codes so that the tests could be recorded and billed.
There is a lesson here on Evidence-based Medicine (EBM). This one is on Sensitivity and Specificity. In EBM, those concepts look like this:
Calculation of Sensitivity/Specificity/ Likelihood Ratio
|Disease positive||Disease negative|
|Test positive||a (test positive, had disease)||b (Test positive, no disease)|
|Test negative||c (test negative, had disease)||d (Test negative, no disease)|
|Sensitivity = a/(a+c)|
|Specificity = d/(b+d)|
|Positive Predictive Value – a/(a+b) Negative predictive Value = d/(b+d)|
|LR+ = [sensitivity /(1-specificity)] = [a/(a+c) / [b/(b+d)]|
|LR- = (1-sensitivity)/specificity = / [d/(b+d)]|
The math might be a little heavy, but the concept is there. If the test is positive, did the baby have a heart defect? If the test was negative, was the baby safe from the defects?
In 2009, the result of the cumulative studies was a sensitivity of 69.6% and a PPV of 47%. After 24 hours, the number of false positives was .035%. In a recent Swedish study, the sensitivity number was close at 62.1%, but the PPV had climbed to 99.8 %. The number of false positives was 0.17%.
Numbers won’t tell us how to handle the false positive tests, however. Should a baby in a rural area be transferred to an urban medical center based on the results of this test? The answer, of course, is no. We trust our physicians to add their clinical judgment to the numbers. Experience and clinical judgment, added to the numbers, can help us build an appropriate protocol for all states to implement. This, with the EBM concept of the preferences of the family and patient, will help us figure out what to do next.
If we had put into place the universal screening of newborns with pulse oximetry before knowing all the facts, we may have had many false positive results. Those false positive results could have triggered an arterial blood gas to confirm the result — a very painful, miserable experience — but how do you measure a newborn’s pain? And who would have bothered to calculate what the costs of those ABGs were, the subsequent x-rays and who knows what else. We are beginning now, with analytics, to take a look at things like the cost of inappropriate testing. There is a tremendous brain trust in the field of medicine but in health care as a whole, whether we mean in the trenches where the care is being delivered or in the office of the CEO of a health system, we have often been our own worst enemy. As we evolve and really begin to collect all of the data and apply analytics to that data, we will be better equipped to make decisions in a more timely fashion medically and also in the business environment that we work in.
The problem is that we have had a vicious negative cycle going on that has contributed to health care being so far behind other industries in technology. Because we are cautious and don’t want to adopt new technologies until they are proven, we don’t have the systems in place to capture and analyze the data we need to make decisions. The remedy for fixing our health care system in general may need to parallel the case of screening infants with pulse oximeters. Understand the facts as much as possible, make cautious decisions, collect more data, analyze that data and then make bigger picture decisions and investments. The principles of evidence-based medicine may indeed apply to the business decisions we make in health care as well.