A well-organised data infrastructure

FysioHolland

  • Customer case
  • Data Engineering
  • Data Analytics
fysioholland data
FysioHolland
Reimer-business-manager
Reimer van de Pol
Business Manager
3 min
28 Feb 2022

FysioHolland is an umbrella organisation for physiotherapists in the Netherlands. A central service team relieves therapists of additional work, so that they can mainly focus on providing the best care. In addition to organic growth, FysioHolland is connecting new practices to the organisation. Each of these has its own systems, work processes and treatment codes. This has made FysioHolland's data management large and complex.

There were already some dashboards built in Google Data Studio, but they thought it was time to hit the reset button. That's why they asked us to help centrally store all data, standardise reports, tighten definitions and streamline insights from data. The aim here was to give each employee insight into the performance that is relevant for their job.

Our approach

We started by building a data infrastructure. The data is retrieved from various data sources. While it was not possible for all data sources to automate data entry, we have streamlined this process. For example, there were several Google Sheets used by finance professionals to track treatment prices. We have standardised and centralised these so that FysioHolland can automatically read and process data with a much higher quality. We documented definitions for such data sources, which we refined during the process.

In addition to Google Sheets, data uploaded to Google Cloud Storage via scripts all comes together in Google Big Query. This data is combined with static tables and processed automatically.

FysioHolland wanted insight at four levels: at board level, regional level, practice level and at individual level per physiotherapist. We sketched a dashboard for each level based on the old data. We visualised the data in consultation with the customer. Then we built them in Google Data Studio. This was already being worked with, so it was easy to integrate within the organisation. We first rolled out the dashboards for a test group with a number of stakeholders. After processing their feedback, we made them available to the entire organisation.

With regard to the four levels, it was also important to properly handle access to the data. For this we implemented row-level access in Google Big Query so that, for example, a physiotherapist does not see data from another region in his dashboard. We have also made improvements in the processing of data into a format that can be displayed in the dashboards. By rewriting the processing and removing redundant queries, we have not only optimised but also reduced the overview.

The result

The required data is retrieved and stored in a data lake. From the data lake, the data is exported daily to the data warehouse, where the data is cleaned, supplemented and processed to ultimately serve as a reliable source for the dashboard.

Every FysioHolland employee now has insight into the data that is relevant to the work they do. For example, a physiotherapist can see how many hours have been booked in advance and which administrative actions still require action. These insights are available on a daily basis and can be easily viewed in Datastudio.

Future

In the future we will help FysioHolland to gain even more insights. We do this by adding extra sources to the data warehouse and further expanding the dashboard. In addition, we use our Data Science expertise to predict future planning of flexible schedules and potential wait times for clients at the therapist level.

Want to know more?

Reimer will be happy to talk to you about what we can do for you and your organisation as a data partner.

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