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What does technology really cost? If you have ever bought a costly smartphone you would know that by the end of the day it definitely ends up costing more than the price you paid for the phone. You need to pay for a screen protector, a protective case and even some insurance just in case you tend to be careless. You could also get more out of the music app if you spend a couple of hundred dollars for a good Bose headset. Therefore, the short answer to the question is that technology can end up making you pay more than what you thought it would. This is a simplistic perspective but it is no simpler than the widely held assumption that new digital technologies fitted on to a clunky and inefficient healthcare system would magically make all the systemic waste disappear. This, in my view, is wishful thinking and I will use here the example of a diabetes app to illustrate the unintended consequences and costs of new technologies in healthcare.

It appears to be a no-brainer when a health system decides to give its diabetes patients a mobile app to track medications, ensure discipline in following instructions and most importantly share data like blood glucose results with their providers. Patients who used to visit their provider 3 or 4 times a year can now share their weekly or daily results and other information with their providers, and this makes a face-to-face encounter with the physician unnecessary in most cases. The promise of the app is better long-term control and thereby a much reduced possibility of ending up in the hospital with other complications. However, in the short term this is what happens:

  1. Office visits: This new mobile app allows a practice to proactively monitor hundreds if not thousands of its patients without them having to come to the office. Patient visits in most cases could thus be reduced to just their annual physical. This is obviously a capacity booster for the system freeing up time and resources for new or sicker patients.
  2. Processing the data: Here is where it gets complicated. Blood glucose data that used to be collected by the provider during those 3 or 4 visits is now replaced by data coming in weekly if not daily for some patients. That is a severalfold increase in ‘data encounters’ and more data will in all probability lead to more instances (true and false positives) requiring further scrutiny or more intense intervention by the provider. Providers will have to respond by talking with the patient over the phone to actually asking the patient to come to the office or ER depending on the circumstances. In most practices additional resources would thus be needed to handle this intensified stream of data
  3. Interventions: The increasing number of true and false positive signals will result in more diagnostic and therapeutic activity. While this is good in reducing more costly long-term complications this also opens the door to a lot of unnecessary testing and therapeutic decisions. Practice variability is already common in clinical practice and the increased volume of ‘data encounters’ will only magnify the problem

In summary, the benefit of the new diabetes app would be better long-term disease control but implementation at scale would require more resources. It would also result in an undesirable increase in clinical services. Introducing technology should thus be part of a more comprehensive strategy that looks at all the direct and indirect effects on the system. The app in the above example would have a systemic benefit only if it were a component of a larger digital supply chain. In other words, the diabetes app should be part of a group of technologies that would work in synergy towards the common objectives of the diabetes program. To elaborate on this point, the above-mentioned negative effects on labor intensity could be reduced by simultaneous use of other applications — collaborative workflow systems, intelligent alerts and automation of manual tasks – that help better process the data. Similarly, practice variability leading to over-testing and unnecessary prescriptions could be avoided by making available to providers a variety of clinical decision support tools. Success in digital healthcare is therefore not about an app, it is about the strategy behind its implementation.

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