Increasingly, patients access their electronic health records online through patient portals. However, medical data, such as diagnoses, are difficult to understand. To improve the understandability of health records, APH researcher Hugo van Mens developed an algorithm to generate diagnosis clarifications in more patient-friendly language. These clarifications were generated by using synonyms, definitions and generalizations from an existing medical terminology system (SNOMED CT).

The functionality created by Hugo van Mens has been implemented in the teaching hospital Franciscus Gasthuis & Vlietland and is currently available to several hospitals in the Netherlands. User statistics showed that more than half of the patients clicked on the information buttons when they could and that most clarifications were rated to be of good quality by patient portal users. For example, one user rated the explanation below in Figure 1 to be very good (7 out of 7) and motivated this score with “Explained short and concisely in plain Dutch”.

Figure 1

Figure 1: Screenshot of example clarification for “osteoarthritis of hip” from the HiX patient portal (ChipSoft, Amsterdam). The clarification is shown in a pop-up after a patient portal user clicks on the diagnosis information button.

Table 1
Diagnosis Osteoarthritis of hip (Dutch: coxartrose)
Clarification Osteoarthritis: This is a chronic joint disease in which a change of the cartilage in the joints leads to pain and stiffness.
Rating 7 very good (from 1 very bad to 7 very good)
Feedback “Explained short and concisely in plain Dutch”

Table 1: Example diagnosis clarification with rating and free-text feedback

Figure 2

Figure 2: Illustration of the generalization method. In the SNOMED CT hierarchy, the medical concept “Paroxysmal atrioventricular tachycardia” is a grandchild of the concept “Heart rhythm disorder”. The algorithm uses this knowledge to generate the clarification “A heart rhythm disorder”. Additionally, it provides a patient-friendly definition when available (not shown here).

An algorithm to explain 80% of all diagnoses

Hugo van Mens is both a postdoctoral researcher at Amsterdam UMC and a software developer at ChipSoft. This company provides the health information system HiX, which is used in the healthcare sector, for example by hospitals, GPs and pharmacies. In a collaboration between Amsterdam UMC and ChipSoft, he carried out his doctoral research about patient portals and medical terminology. Hugo van Mens: “From the patient’s perspective, medical terminology is very complicated. For example, when you go to the doctor for back pain, you might read the diagnosis ‘dorsalgia’ in your health record. Sometimes, these medical terms can be frightening. Patients want clarifications about medical terminology or at least understandable language about what it means to them. Therefore, we investigated possible solutions. However, there were very few patient-friendly explanations available for only a small portion of the diagnoses. For instance, back pain is a simple term for dorsalgia and liver inflammation for hepatitis. These patient-friendly terms covered only 2% of all the diagnoses that are registered in Dutch hospitals. Since there are a lot of types of diseases, we figured out that you can reuse one clarification for different types of those diseases, e.g. clarifying that hepatitis A is a type of liver inflammation, or that “gastro-enteritis due to SARS-CoV-2" is stomach flu due to a coronavirus. To this end, we made an algorithm that generalizes specific medical concepts to more general ones with patient-friendly terms and definitions, which allowed us to clarify 80% of all diagnoses.”

Implementation of the Patient friendly terms

The topic of making medical data more patient friendly is important to enable patients to understand and use their electronic health records. The solution was implemented in clinical practice in April 2022, in the Franciscus Gasthuis & Vlietland HiX patient portal MijnFranciscus. This implementation was a success and the hospital wanted to continue using the functionality. Currently, the results have been taken up by the terminology standards development organization which continues investigating how to further automate medical terminology development. Moreover, the patient-friendly clarifications from SNOMED CT are available in the healthcare information system patient portal of over twenty-five hospitals in the Netherlands. In addition, Amsterdam UMC is investigating how to implement the algorithm in their patient portal Mijn Dossier (MyChart, Epic).

Our motives or incentives are to enable patient portal users to understand and use their own electronic health records. This might help them prepare themselves better for appointments, to adhere to their treatments, find errors in the registered data and learn more about their health.
Hugo van Mens
APH researcher at Amsterdam UMC and a software developer at ChipSoft

Collaboration with stakeholders is key

To create this kind of impact, collaboration with key stakeholders was crucial. Hugo van Mens: “First, the required software and configuration was developed by the health information system software company, ChipSoft. Secondly, we ensured that the clarifications were medically validated by the standards organization, Nictiz. Lastly, the result was implemented and evaluated in a patient portal used in clinical practice, at Franciscus Gasthuis & Vlietland. However, decision-making was challenging. Contracting and formal approval for carrying out the study delayed the implementation. Retrospectively, we could have set stricter deadlines as a requirement to participate in the project and arranged the contracts beforehand. While drafting up the contracts took up a lot of time by legal support, in the end, template contracts were used.”

Do’s:
  • Collaborate with key stakeholders, such as health information system vendors and standards organizations.
  • Design feasible solutions aimed implementation to improve clinical practice
  • Validate your solution before implementation in clinical practice
Don’ts:
  • Don’t work in isolation
  • Don’t design a solution that cannot be integrated in health information systems that are used in clinical practice
  • Don’t forget to evaluate the solution with end-users in clinical practice