Does your health monitor have device bias? – Harvard Health Blog

In recent years, there has been a real explosion in the number and type of health monitoring devices available in smartphones and fitness apps.

Your smartphone likely tracks the number of steps you take, the distance and speed you walk, and the number of flights of stairs you climb each day. Some phones track sleep, heart rate, how much energy you burn, and even “walking health” (how often are both feet on the ground? How regular are your steps? ). And, of course, portable devices and non-phone fitness gadgets are available, such as devices to measure your heart rate, blood pressure, or oxygen levels. The accuracy of these devices varies, and in some cases your skin tone can make a difference.

In general, how accurate are health monitors?

I know from my experience with hospital monitors that they are not always accurate. False alarms from EKG monitors often send medical personnel rushing into patient rooms, only to find the patient feeling good and surprised by the restlessness. A particularly common false alarm is a dangerous and unstable heartbeat on a continuous heart monitor, which may be due to the movement of a patient brushing their teeth.

High-stake devices with monitoring capability, such as defibrillators and pacemakers, are extensively tested by their manufacturers and approved by the FDA, so their accuracy and reliability are generally quite good.

But what about home health monitoring devices intended for consumer use that are not extensively tested by the FDA? Have you ever counted your steps for a few minutes just to see if your phone’s count is okay? Or go up a few flights of stairs to see if you get all the credit for not taking the elevator?

The accuracy of consumer devices depends in part on What is being watched. For example, one study evaluated the accuracy of heart rate monitors and energy expenditure calculators in phones and health apps. The accuracy was quite high for heart rate (often around 95%), but much less accurate for energy expenditure. The accuracy may also vary depending on who is being watched.

Device bias: what is it and why it happens

While no health gadget is perfect, some users get more reliable results than others. For example, if you wear nail polish, a pulse oximeter – a device that snaps onto your fingertip to measure blood oxygen through the skin – may not work properly because the polish interferes with the correct operation of the light sensor. In this situation, there is a simple solution: remove the varnish.

But in other cases, the solution is not easy. Increasingly, we recognize that some medical devices are less accurate based on a person’s skin color, a phenomenon called device bias.

  • Pulse oximeters. Although they are generally considered to be very precise and commonly used in healthcare settings, their accuracy tends to be lower in people of color. This is because the device relies on shining light through the skin to detect the color of the blood, which varies with the level of oxygen. The amount of pigment in the skin can change how light behaves as it travels through blood vessels, causing inaccurate results. The FDA has issued an alert on this and other limitations in the use of the pulse oximeter.
  • Measurement of bilirubin in newborns. Bilirubin is a breakdown product of red blood cells. Newborns are tested for high levels as this can cause permanent brain damage. When detected, light therapy (light treatments) can help the baby get rid of excess bilirubin, thereby preventing brain damage. Screening involves examining a newborn baby’s skin and eyes for jaundice (a yellowing caused by high bilirubin) and a photometer test to detect high levels of bilirubin. But the accuracy of this test is lower in black newborns. This is especially important because jaundice is more difficult to detect in infants with darker skin, and dangerously high bilirubin levels are more common in this population.
  • Heart rate monitors in smartphones. According to at least one study, smartphone apps may also be less accurate in people of color. Again, this is because the more pigment in the skin, the more problems the light sensors have in detecting pulses in the blood stream that reflect the heartbeat.

Why device bias matters

Sometimes a measurement error has no immediate health consequences. An error rate of 5% to 10% when measuring heart rate may have little consequence. (In fact, you might wonder why anyone needs a device to monitor heart rate when you can just count your pulse for 15 seconds and multiply it by 4!)

But pulse oximeter readings are used to help decide whether a person should be hospitalized, who should be admitted to the intensive care unit, and who needs further testing. If the oxygen level is consistently overestimated in people of color, they may be more likely to be under-treated than others with more accurate readings. And this can exacerbate the health disparities that previously existed.

These examples add to the growing list of prejudices inherent in healthcare and other instances where failure to include diverse people has serious consequences. When using a health device, it is reasonable to wonder if it has been tested on people like you. It is also reasonable to expect that people who develop medical and consumer health devices will broaden the demographics of test subjects, to ensure that the results are reliable for all users before putting them on the system. market.

Sometimes a change in technology, like using a different type of light sensor, can make health-related devices work more accurately for a wider range of people.

Or there may not be an easy fix and user characteristics will need to be incorporated into a correct interpretation of the results. For example, a device could offer the user a choice of skin tones to match the color of the skin. Then, based on extensive data from previous tests on people with different skin colors, the device could adjust the results appropriately.

The bottom line

The pressure to monitor our bodies, our health, and our life experiences continues to mount. So we need to test and validate health-related devices to make sure they work for a variety of people before declaring them suitable for the general public. Even then, the device bias will not go away: bodies vary and technology has its limits. The key is to know it exists, to correct what can be fixed, and to interpret the results accordingly.

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Jothi Venkat

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