Clinical Decision Support Systems: In Search of the Whys and Wherefores
Beyond dashboards and health indicators.
It is essential to have efficient and safe health systems, equipped with tools that permit the analysis and evaluation of the healthcare quality in an objective manner.
I think that sometimes, if not always, it is fitting to look into the whys of things, looking into the past to discover the origins and the problems that will help us have a better understanding the present.
When it comes to exploiting health information and clinical and administrative decision support systems, there is a particular need to know the history and the causes, going beyond basic interpretations through dashboards and indicators for healthcare institutions.
The history begins in the 70’s when they begin to computerize hospital admissions in a unique manner in the USA. At the time, computerized systems were not used for the practice of medicine, their sole purpose being patient billing.
Administrators and managers began raising the need to reduce the cost of production in healthcare, proposing shorter stays, fewer tests, fewer check-ups, etc.
The response from clinicians was immediate: “You can’t put a price on health, you can’t decrease the quality of care, I won’t be responsible for patient deaths, etc.”
Then a confrontation arose with the management that was not taking into account the care and the quality of the care, for which the only objective data available at the time was a very biased in-hospital mortality rate.
Talking about effiency
A solution to this problem, with the availability of more data and information, was clearly needed. It was around this time when they started hearing about new concepts. In contrast to effectiveness on the one hand and quality on the other, the Concept of efficiency began to emerge and gain acceptance within this sector.
But in order to talk about efficiency, you needed to have new formulas and data available in the numerator and denominator; that is to say, the cost of hospital admissions, as well as the costs of each and every illness leading to hospitalization.
This is how tools such as DRGs (Diagnosis Related Groups) paved the way. This is a patient classification system based on risk adjustment through iso-resource groups to help understand the casuistry of a hospital, which can be very useful in the management and financing of hospitals. This clear way forward was agreed between managers, payers and clinicians, one that was understandable by everyone.
But clinicians continued campaigning for the need to safeguard the quality of care at any price, while on the other hand, and rightly so, managers needed to have tools to could measure that quality, so it would stop being used as a political weapon that was impossible to measure and compare.
Thus began the long road in search of consensus and evidence to measure the quality of care, finally reaching what we agreed to call “Quality Indicators” that were measurable, objective and specific, and were harder to determine than we had thought.
When we were finally able to reach consensus and decide on certain indicators for the three components of the care process – Structure (use of means and resources), processes and results – along came the “Healthcare Quality Fever ” and all the hospitals began to establish so-called “Quality Commissions”.
So far so good, except for one minor detail: We did not have enough data or information to create and analyze the Indicators that we had designed.
The objective of Information Systems, then and now, is still the collection of data for management purposes, and not for the purpose of increasing the quality of care, efficiency or patient safety, which is what health information systems should focus on. This makes for rather sterile hospital Quality Commissions, with no impact on the care dynamics.
Hence the importance of health information systems that bridge this information gap and can contribute to the objective agreed upon: Providing safe and efficient Healthcare Systems that are equipped with tools that permit the objective analysis and evaluation of the quality of care.
Think of the number of years, conferences, articles, discussions, efforts and frustrations behind a goal that can be realized today thanks to technology.