How improving health IT improves the delivery of quality health care
Current Challenges in Health Care
Let’s start by identifying some of the key problems in health care delivery.
Problem number one is the considerable variability in the quality of care.
Problem number two is that if people do come in to care, a lot of them end up being harmed. The estimates are that about 10% of people admitted to hospital will be harmed as a result; this is also known as iatrogenic harm. Many are also harmed in primary and ambulatory care settings.
Problem number three is the very considerable costs of health care with anything up to about 17% (in the U.S.) of GDP being spent on health care. Governments across the world are struggling to curtail costs and to try to ensure that other essential budgets, for example, education and welfare, are not unduly compromised as a result.
Health systems cannot continue in the same vein. We need therefore – urgently – to envision and develop new ways of organizing our health systems.
Health Information Technology and Data
So much of the rest of our lives are going digital and it’s high time that health care followed suit. While health information technology (HIT) is an essential part of the solution to the above problems, it must not be seen as a ‘silver bullet’ or a panacea.
HIT is extremely important because of the data that it generates. These data can, for example, make the above-mentioned variability in care transparent and illustrate where there is room for improvement. Conversely, they can also allow us to see where there is brilliance and shine a spotlight on it so others can learn by example. This identification of areas of care that are worrying or exemplary can only really be identified with data. But without data, without baselining, comparing and then monitoring, you can’t do any of this.
Unless you can reliably baseline, in a meaningful way,
how on earth do you know if you’ve made an improvement or not?
These data also allow monitoring of care processes and outcomes over time to see if initiatives undertaken – whether policy, research or quality improvement-based – are working or not.
The sequence of steps for improvement are in a nutshell: getting reliable data; baselining; understanding these data by, for example, comparing outcomes between settings; developing a plan to address any issues uncovered; and constantly monitoring until things improve. It’s an iterative cycle, and that’s essentially what the learning health system is about.
In situations where it’s not clear what to do, this should be a trigger to undertake research in an attempt to identify effective solutions. The U.S. currently spends more money on research than anywhere else in the world. Consideration needs to be given to spending more of this on applied health services research to improve the outcomes that patients most care about.
In summary, every health system is or will do digital – there’s no two ways about it. Those countries that successfully manage to develop mechanisms to support the trusted, secure reuse and repurposing of these data to drive forward learning across the health landscape will see the greatest and most rapid benefits resulting from the move from paper to digitized health infrastructures. Those who don’t manage to crack this nut will struggle to demonstrate benefits or returns on their very substantial investments.
Iterate and Carry On
Constantly iterating until outcomes are demonstrably better is the key to improving the quality of health care delivery. Some of the places that do this best in the world are in the U.S. – for example, Kaiser Permanente, Geisinger Health System and, perhaps the best known example, Intermountain Healthcare. They have long histories of exploiting their digitized infrastructures to support the transformation of health care.
That’s what the learning health system is all about: liquefying data, baselining, understanding the signals, prioritizing efforts and developing consensus around a plan of action, intervening to improve, constant monitoring and if necessary iterating until it’s clear that the desired goals have been achieved.