Good outputs always rely on good inputs. And nowhere is this more important than where human health is concerned.
For almost the whole of human history, patients have had to rely on the subjective judgement calls and experience of individual doctors. Yet even the most talented physicians make mistakes.
The digital revolution is now changing all of that. It is ushering in a new era of predictive analytics, which offers better outcomes for everyone. This is because applying machine learning to troves of historical data enables medical professionals to make evidence-based decisions. It creates a virtous circle: more data inputs facilitate more nuanced outputs. And everyone involved in the healthcare systems benefits: from the governments funding it through to the patients accessing it.
Improving patient outcomes
The recent Covid-19 pandemic provides a good example of this process in action. In a recent study, published by the JAMA Network, US researchers conducted a retrospective analysis of almost two million adults who had been hospitalised with the virus between January and December 2020.
The inputs were data points commonly collected within 24 hours of admission. The outputs, thanks to machine learning algorithms and predictive analytics, were the risk variables related to severe cases of Covid-19. This offers a cutting-edge approach to enhancing health outcomes. Machine learning algorithms can be programmed to provide insights into treatment strategies for current patients based on data and outcomes from previous ones. They can be taught to spot warning symptoms before they become acute. Improved diagnostic accuracy enables more effective treatments.
Predictive analytics also provides us with a valuable tool for analysing how different patients react to the same treatment. For example, researchers at the University of Michigan’s Rogel Cancer Center are developing a blood test that can predict whether a particular treatment for HPV-positive throat cancer is effective months before standard imaging scans can. This will allow clinicians to switch treatment courses sooner if the current one is not working, potentially saving patients months of unnecessary and painful treatment. The overall quality of patient treatment will improve.
Enhancing operational efficiency
The rise of the Internet and Smartphones means that people, all across the world, now have access to a vast store of knowledge and information at their fingertips. This is benefitting the healthcare industry in numerous ways.
The digitalisation of health records, access to big data and cloud storage, improved software, and mobile application technologies are all improving the way the medical industry operates. More efficient workflows and faster access to information means less resource duplication, leading to financial savings that can be used to boost healthcare expenditures elsewhere.
Technology can provide hospitals with real-time evaluation and analysis of staff performance based on historical and real-time patient admittance rates. Rising hospital bed shortages can also be addressed through predictive analysis, helping to prevent the issue from occurring in the first place.
Extra personnel can be directed towards in need. As a result, total service delivery to patients improves, ensuring the latter receive the highest possible quality of care. Yet, while big data analytics is improving patient care and efficiency, we should not forget how easy it is for healthcare personnel to become overwhelmed by a growing deluge of electronic data. We need good IT systems, which are not only able to talk to each other, but are also easily accessible through user-friendly interfaces.
There is growing evidence that doctors are rapidly transitioning. A recent study, published in the JAMA Network, noted how physicians now spend 62% of their time with each patient evaluating electronic health records (EHRs), with clinical data reviews taking up the majority of that time.
Researchers from Stanford University surveyed doctors working in the gastroenterology department. A total of 11 of the 12 said that they preferred using artificial intelligence (AI) compared to conventional methods. It saved them almost one fifth of their time.
Using AI provides timely and accurate patient information, as well as treatment recommendations. It relieves the burden on healthcare workers and has a bright and promising future in healthcare delivery. What we are witnessing is a wholesale transformation from a labour-intensive to a technology-driven model across the healthcare value chain. Big data is starting to supplement human expertise, allowing physicians to make faster decisions that create favourable patient outcomes.
Technology will continue to augment clinical diagnosis and patient care, but it will never completely replace human intervention and the personal touch. The end result will be a healthcare system that prioritises both.
Sigal Atzmon, Founder and CEO Medix Global
(DISCLAIMER: The views expressed are solely of the author and ETHealthworld does not necessarily subscribe to it. ETHealthworld.com shall not be responsible for any damage caused to any person / organisation directly or indirectly.)