Why is the introduction of digital technologies in the healthcare sector
This is the 2nd blog exploring how digitalization is transforming regulated industries (agriculture, healthcare, energy and mobility in particular). The transformation goes hand in hand with a growing need to establish, scale and manage innovation ecosystems. Nobody has ready-to-use answers how to do that, but by asking critical questions and exploring good practices, we may end up to know what works and what doesn't.
In order to make the healthcare sector more sustainable, to improve its efficiency and to work in a patient-centered way, considerable efforts must be made to introduce digital applications at an accelerated pace. However, the digital transformation will not take place as long as the sector itself doesn’t start to work differently.
After the Covid19 pandemic, there will be a mounting pressure to increase public budgets for healthcare, while government deficits are already historically high. An unavoidable dilemma? This does not have to be the case, provided that we rethink the healthcare sector - new financing models (e.g. abandoning the fee-for-service approach), a rearrangement of the healthcare landscape and extensive digitization are different inroads to renew the sector and keep it sustainable.
I focus in this blog on the digitalization in the healthcare industry. Extensive digitization will not only simplify administrative processes, but also determine how care is best provided, how data can be exchanged between different organizations, how patients can gain access to and control their medical files, how medical services can be reimbursed in novel ways and how the follow-up of data should be handled technically and legally. Digitization can lead to significant savings in health care, but the main advantage is that it can ensure better, faster and personalized care. A "personalized care model" means that the integration of lab results, radiological examinations, a patient's history, DNA data, etc. makes it possible to individualize the therapy for each patient. This, in turn, will drastically improve the success rate of various treatments and unsuccessful treatments can be stopped or adjusted in time. All this will have a major impact on total costs.
An integrated data approach can save doctors and caregivers a lot of time and limit the number of medical errors. In a state-of-the-art EMR (electronic medical record), smart connections ensure that medical staff can pass on the data without errors. No more typing and associated errors, no more incomplete files, or “forgotten” allergies. The use of the EMR is slowly gaining momentum in most European countries: the question now is whether we can integrate the various data to take the step towards personalized care. The data exist but should be linked to personalize diagnoses (e.g. by linking radiological images with DNA or other patient data) and to prescribe appropriate treatment. Data has to “talk” across data systems and that requires a far-reaching standardization in storage and exchange of data. This is already a challenge within one hospital, let alone the exchange of data between hospitals or other players in the healthcare space.
Digitization can improve medical care and make it cheaper thanks to rapid diagnosis and prevention. By integrating digital data ranging from smartwatches, fitness exercises, prevention and medical data to home care, we can take a holistic approach to measuring value. Outcomes are tracked across the continuum of care, taking account of the complete journey of a patient or population through the healthcare system. This broadened approach should lead to a healthier population and a more sustainable healthcare system.
Why digitization is not adopted massively if it can drastically improve and simplify healthcare? Part of the answer can be found in hospitals and other key players in the medical world. They are not very open to adopting digital technologies because existing practices in healthcare are at risk, require extensive collaborations between different organizations, and they fear that revenue generating treatments might be eliminated. Moreover, the current financing system of hospitals offers no incentive to invest in digitization and, more importantly, there is insufficient knowledge about the possibilities that digitization offers. Digitization requires a hospital-wide vision with clear forward-looking choices. In Belgian, non-academic hospitals, doctors have to contribute financially if the hospital wants to make such investments. A hospital cannot convince its specialists of the value of these investments as long as this is not linked to a clear ROI for all parties involved.
A few examples to illustrate why digital technologies don’t get adopted. A variety of digital instruments give patients the opportunity to measure their condition at home. Data is automatically sent to a doctor or specialist, who can then schedule an appointment if necessary. This happens, for example, when measuring blood pressure or glucose levels in the blood - but there are many other uses such as follicle control in IVF, hypertension in pregnant women, or silent epilepsy just to name a few.
Take hypertension in pregnant women, for example: In 2014, the Premom project was set up by the Hasselt University and various hospitals in Flanders (northern part of Belgium). In this project, pregnant women were asked to measure their blood pressure at home and the data is checked daily in a hospital. In case of abnormal values, the attending gynecologist is contacted and an appointment is arranged. The study shows that through the Premom telemonitoring, there were fewer prenatal deliveries, fewer cases of hypertension, babies were born on average 10 days later, and there were fewer induced deliveries. In addition, the average cost of a pregnancy dropped by 1950 euros.
You would expect such a telemonitoring system to be rolled out quickly in all Belgian hospitals, but that’s not the case. Patients and health insurance companies benefit from telemonitoring, but it is a double-edged sword for hospitals: gynecologists are at risk of losing income because the number of consultations is falling. The neonatology department is also not happy because telemonitoring reduces the number of neonatal admissions. In addition, it is not clear who is responsible for misdiagnosis of data - a problem that does not arise when the gynecologist measures blood pressure herself. This example illustrates that digitization will only be implemented if the earnings model of gynecologists and neonatology departments is examined, when remuneration is paid for monitoring activities, and when legal liability for diagnoses is established.
Another example is the use of artificial intelligence (AI) in radiology. All medical images are now digital and AI algorithms succeed in detecting tumors, breast cancer, cerebral hemorrhages, vertebral fractures and blood clots in those images faster and more accurately than radiologists. AI can support radiologists and partly automate the diagnosis. Even if AI has enormous potential in radiology, the switch will not be trivial: hospitals will have to invest in AI applications, the role of the radiologist will change and the collaboration with other doctors in the hospital has to be reviewed. Radiologists must be retrained: they will have to switch from a purely morphological to a data-driven, more quantitative analysis of the information that is hidden in the medical images. Radiologists will therefore play a more important role in determining therapy choices. They will get a different role in the multidisciplinary consultation between doctors determining the treatment of cancer patients. Finally, because new AI algorithms need thousands of images to deliver a good result, a legal or regulatory framework for data exchange between hospitals will also have to be developed.
In short, digital technologies can fundamentally change the healthcare sector, but little will happen as long as policymakers, insurers, providers, hospitals, pharmaceutical companies and other stakeholders do not jointly set goals, change the current working method, review revenue models and redefine the cooperation between the parties. It is a policy and management problem, not a technological problem.