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Blog
Presence and completeness of a medical discharge letter
IQVIA Belux
Mar 11, 2025
Background and challenge

To guarantee a good quality of care, the presence and completeness of a medical discharge letter after a hospital stay is crucial. Such a discharge letter ensures that all relevant information is shared transparently with the GP and any other third parties. They will be close to the patient during follow-up and must be aware of the patient's complete history to be able to make the right decisions in the future - e.g. current medication list after the admission, or information regarding the continuation of treatments, such as wound care or physiotherapy.

It is generally expected that a medical discharge letter is drawn up for every patient staying in the hospital. In addition, the discharge letter must be available at the time of discharge and validated within 14 days after the patient's discharge. A medical discharge letter consists of several fixed paragraphs, such as the reason for admission, anamnesis, diagnostic and therapeutic procedures, and the medication upon discharge. Each of these paragraphs must be available - if relevant.

Within hospitals, it is usually the quality department that is responsible for performing manual checks on the presence and completeness of a medical discharge letter in the Electronic Medical Record (EMR). Doctors for whom the discharge letters are not available on time and/or not completely within the agreed guidelines receive feedback on their results. This feedback loop should encourage doctors to optimize the quality of their discharge letters.

Such manual checks are of course very time-consuming and can be prone to errors. With the help of the clinical data warehouse (Forcea HealthReport Clinical) and CTcue, these checks can be automated. This not only saves a lot of time, but also allows the checks to be performed more frequently and with a lower margin of error.


Approach and results

The above challenge can be divided into two parts, namely the completeness of the discharge letter (1) and the presence and timely validation of the discharge letter (2).

1. Completeness of the discharge letter

To check the completeness of the discharge letter (1), CTcue can be used. CTcue is a Natural Language Processing (NLP) tool that can access both structured and unstructured information from the EMR. For this use case, a query was built that searches for all patients who

  • were discharged in the past month
  • are linked to a specific discipline*
  • have a discharge letter

*By adding a filter at discipline level, targeted feedback can be given to the various medical department heads and they can address the doctors involved.

For this list of patients, it was then checked whether the discharge letter also contains all the required paragraphs. This can be done by retrieving the first few lines that can be found under each paragraph title.

In the example below, you can see that the paragraph 'reason for admission' was available for most reports, and that this paragraph also contains text. However, this paragraph could not be found for the bottom letter. In a similar way, the other paragraphs of the discharge letter were also looked at, and hospitals can give quick and transparent feedback to their doctors. By following this KPI monthly, the quality of the discharge letters can be optimized.

2. Attendance and timely validation of the discharge letter

To follow up on the attendance and timely validation of the discharge letters (2), we used the Forcea HealthReport Clinical – Contacts module. Information from this module allows us to map and closely monitor the various contacts within the hospital.

For this use case, a dashboard was built in which several structured data points were included, such as the closing date of a contact, validation date, doctor linked to the validation, discipline, etc. In the example below, you can find the number of closed contacts for which no validated final report is available. These results can be filtered per doctor or discipline, and in this way targeted feedback can be given to the medical head of the departments.

In addition, lists were also created containing all reports for which validation was not carried out within a period of 14 days after the contact was closed.

Conclusion

Using the clinical data warehouse in combination with CTcue helps hospitals to perform quality checks on discharge letters more efficiently. Where it was previously necessary to check a few discharge letters per doctor or per discipline via a sample, it is now possible to perform a more extensive check. In addition, by bringing together all relevant information in one overview, quality control can be achieved more quickly.

The frequency of the checks can also be increased by using our tools. The data is then shared transparently with the medical department heads, who can then take the right steps to optimize the quality of the reporting. This feedback loop is of crucial importance, and benefits the quality of the data, but also the quality of care.

Do you want to get started with this yourself, or do you have any questions? Then be sure to contact linda.ludikhuyze@iqvia.com for more information.

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