Frequently asked questions


  • A rules engine does not get tired 
  • It never gets bored 
  • It never misses anything 
  • It reports back EVERYTHING it does 
  • It offers no opinions 
  • It is consistent 
  • It does not forget, and always follows up 
  • It frees up time to focus on the true task of a professional: evaluation and decision making

(Met dank aan: The In’s and Out’s of a Clinical Rules Engine, Michael R. McDaniel, Director of Pharmacy Services, Huntsville Hospital, Alabama)

For health care professionals, both doctors and pharmacists. The rules can be specified for various roles within the chain of care, from prescribing to dispatching medication. Clinical Rules is currently applied in a hospital pharmacy, where the availability of lab reports and medication files is well organised, to provide support in the care for nursing home patients. A similar application in community pharmacies can be expected once pharmacists are also provided with more accessible lab data (particularly through electronic patient files, Landelijk Schakelpunt, or LSP). The implementation of Clinical Rules at general practices and specialist clinics is still under development. For this, we are seeking collaboration with providers of general practitioners' IT systems and prescription software systems (HIS and EVS providers).

Health care professionals/patient file managers can analyse issues in medication, lab reports and diagnoses that have been entered and saved in a structured way. This analysis is initiated by the health care professional, who allows anonymised data to be exported to the so-called Clinical Rules Engine. The engine with clinical decision rules is maintained centrally and reports detected issues back to the health care professional/patient file manager. These reports are saved in the patient file and can be re-evaluated at a later time, based on relevant changes in the patient file.

This method produces different signals, but these signals are more relevant. Every health care professional is familiar with the current problem of too many medication monitoring signals, which are usually based on too little data. This limits their ability to provide conclusive advice. Clinical Rules takes a broader range of details into account and can therefore detect more specific and more relevant signals. For example, previously, one would receive a notification that decreased kidney functioning could be a possible contraindication for Metformin. Today, one receives a notification of how the dosage could be changed relative to the creatine clearance rate or that the medication should not be prescribed.

In short: Relevant Clues are very time efficient!

The Clinical Rules Engine evaluates completely anonymised data: this evaluation is not saved centrally and outcome reports cannot be traced back to the patient or the health care professional. Reports are saved with the patient file manager before the data becomes identifiable.

Clinical Rules is an information service (web service) that is aimed at health care professionals who are capable of documenting patient data in a structured file and can use part of this data in interdisciplinary exchanges. Health care professionals can initiate the export of anonymised data to the so-called Clinical Rules Engine.
The engine is accessible 24 hours a day and is maintained in a data center ('hosting provider'), where the Clinical Rules protocols are managed.

These protocols are technical implementations of clinical decision rules. Potential issues based on available patient data can be established with these Clinical Rules protocols.

The source receives real-time feedback on these potential issues in the form of a Clinical Rules Report. Clinical Rules Reports are merged with the correct patient file to provide a better context for the health care professional. This structure allows for a functional separation of decision rules and analyses on the one hand, and file keeping and process management on the other.

Additionally, the design of Clinical Rules allows for the analysis of and feedback on batches of thousands of files simultaneously. This is useful for pharmacists, who monitor large populations every day.