[MA 2022 03] Quality registries

Furore

Proposed by: Bas Wencker [b.wencker@furore.com ]

The Dutch healthcare system belongs to one of the best in the world. To maintain this ranking, there is a continuous striving to preserve and improve the quality of care. Insights into health care structures, processes and patient outcomes are indispensable when wanting to preserve or improve the quality of health care. One way to gain insights into the quality of health care is by means of national quality registries (QR). A QR is a registration of a well-defined patient population which collects data on patients and care with the aim to measure, improve and account for the quality of care by short-cycle audit and feedback. Examples of QRs in the Netherlands are the NICE registry, DICA and the NHR.

Despite countless examples proving the importance and value of QRs in improving care and patient outcomes, there are still many snags in the current way of delivering data to QRs. In some cases (partial) manual data extraction by health care providers is still necessary which is often experienced as an administrative burden. Other problems related to manual extraction of data is poor data quality. There are currently multiple developments to automate this process to tackle the administrative burden and improve the quality of the data. Furore is one of those organisations that are working on a tool, based on FHIR, to automate the delivery of data from hospitals to QRs.

Challenge

The implementation of an automated data delivery to QRs seems to be practically feasible, if certain criteria are met. Nevertheless, there remain several challenges that are interesting for Furore and open to discuss. Together with the data team at Furore, you can formulate your own research question which can be related to one of the following topics.

• Healthcare providers responsible for the delivery of data to QRs indicated that they are concerned with the quality of the data if the process of extraction were to be automated. How could a data quality check be involved in the tool?

• There is a list of criteria that increases the chances of a successful implementation of an automated exchange of data. In what order should these criteria be followed to complete the implementation of the tool as efficiently as possible.

• What other techniques could be used to automate the process. In what way would this differ from a tool based on FHIR?

• How could the tool be applied to/by QRs to send the feedback to the hospitals?

As mentioned, we (Furore) are open for ideas and preferences from students.

Expected project outcome

In this project, you are expected to select one of these challenges and investigate various solution. You are expected to either design a methodology or a technique to help improve the process of data exchange between hospitals and QRs. You can carry out a literature study on existing techniques to automate data exchange. You could also build upon or extend the existing methods/techniques as long as it can be applied in the QR context.

You will be working closely together with the Furore Data department.

Candidate profile

We are looking for a student with the following profile:

• Good at object-oriented programming, or functional programming, e.g., Python, Java

• Interested in applied data science and research

• Team players

• Able and willing to work closely with Furore

• Dutch speaking and writing

Are you interested?

Feel free to contact Bas Wencker. HR adviseur b.wencker@furore.com