A Dutch care organisation provides emergency social care for vulnerable patients in and around one of the major cities in the Netherlands. To speedily and accurately identify areas of need, it looked to overhaul the way it handled patient data.
The Faces Behind the Data
Many people need help at some point in their lives and the ability of a country to protect and assist vulnerable citizens is a prime metric of the value of that society. With social care being a high priority in the Netherlands, this care organisation is tasked to provide first-point-of-contact assistance to residents, creating social infrastructures around vulnerable people.
The company aims to intervene quickly in order to prevent social problems from getting any worse, providing a lot of help through day care centres in the city’s poorer neighbourhoods. Yet it must do so within tight financial boundaries. When welfare services became the responsibility of individual municipalities, rather than central government, it was this organisation that realised that it would not only have to provide ongoing care to it's customers, but also supply detailed reports to the municipalities that funded it. To do so, it needed to dramatically overhaul it's data management processes.
Proving Targeted Results
It was the responsibility of the project leader for the company to implement the digitalisation of the organisation in order to provide much-needed data-driven decision making.
“A lot of the new legislation was made on the promise of improving services,” says the project leader responsible for digitalisation.
“We had to start reporting on which interventions had been successful when previously, we’d just had to report on how many people we had seen, or how many had attended day centres. Now we had to talk about the effects of these social investments.”
He explained that part of the organisation’s new challenge was to find a way of demonstrating a return on investment on services that previously hadn’t been assessed in that way. It quickly became clear that the only way to define what types of work were being conducted in each area was for the company to understand the data it was handling.
We have a national bureau for statistics in the Netherlands,” says he. “Through its data, you can pinpoint – almost to a street level – what the social problems of a neighborhood are. You can see which areas have a lot of youths, or a lot of elderly.”
The problem, however, is that these statistics are only one data source out of many. Since the company is an umbrella organisation, covering a number of support and welfare services, it has access to numerous different systems holding vital – yet often incomplete – data. That is, while one customer might be in every system, their full details might be scattered across all of them. “We couldn’t combine all of this data so we weren’t able to get any insight into the effects of our work in each neighbourhood,” says the project leader.
A Data-Driven and GDPR Compliant Solution
The company turned to Pink Elephant (www.pinkelephant.nl/) a local partner of TimeXtender, for technical assistance. They had already seen Qlik in action and knew it could be a powerful tool for presenting complex information. What they needed was a way of linking that to all the data sources.
Pink Elephant was able to educate the company on how they could make their records anonymous within the TimeXtender database. With GDPR on the horizon, the company knew this would be an asset in staying compliant with regulations and maintaining secure storage of sensitive customer information.
“By shifting to TimeXtender to export data for further analytics, we can now combine and share data but we can also anonymise it. In this way, we can give a data set to the government in a report, or to other parties to have it analysed, while still protecting the rights of customers. TimeXtender also has automatic documentation – and data lineage that, amongst other things, can facilitate GDPR compliance.”
Fit For Purpose and Future-Proof IT
“Timextender, used in combination with Qlik, has become essential for our organisation,” notes the project leader, six months after implementation. “Working with Pink Elephant was so valuable because they looked at our company and, within a day, I think they truly understood what our biggest challenges were.”
The company reported that their TimeXtender solution was implemented quickly, within seven to ten days, and integrated seamlessly with their Qlik application. With the new speed and agility of their system, the care organisation is able to add new data sources as needed and are even looking into adding additional front-end tools like ‘R’ and also possibly using machine learning to analyse questionnaire responses to further unlock the potential of their data. Additionally, the company was able to future-proof their data estate and now have a solid foundation for future cloud migration ambitions, simply by implementing TimeXtender.