Coordinator research program Learning Health System; endowed professor 'Transparency in healthcare from a patient perspective', Tranzo, Tilburg University, the Netherlands
Publicatie
Publication date
TRANSFoRm Data quality tool.
Verheij, R.A. TRANSFoRm Data quality tool. Journal of Clinical Bioinformatics: 2015, 5(supl. 1), p. S15. Abstract: 1st Clinical Research Informatics (CRI) Solutions Day. Duesseldorf, Germany, 26-27 Mei 2014.
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Tool description
As computerisation of primary care facilities is rapidly increasing, a wealth of information is created in routinely recorded electronic health records (EHR) that can be used and is already used for research purposes. However, we need to be able to assess whether the data these primary care databases contain is ‘fit for purpose’. In the TRANSFoRm project an axiomatic approach was developed that started with defining purpose and population, followed by the definition of a set of metrics for data quality described in terms of completeness, accuracy, correctness and consistency. Based on this approach a web-based prototype of a data quality tool [1] was developed and evaluated in two TRANSFoRm clinical use cases (GORD and Diabetes), allowing researchers to select primary care sites with data that is ´fit for purpose´. For example, a researcher might only be interested in practices with more or less complete recordings of HbA1c, blood glucose and smoking status (Figure 1). Status of development Prototype.
As computerisation of primary care facilities is rapidly increasing, a wealth of information is created in routinely recorded electronic health records (EHR) that can be used and is already used for research purposes. However, we need to be able to assess whether the data these primary care databases contain is ‘fit for purpose’. In the TRANSFoRm project an axiomatic approach was developed that started with defining purpose and population, followed by the definition of a set of metrics for data quality described in terms of completeness, accuracy, correctness and consistency. Based on this approach a web-based prototype of a data quality tool [1] was developed and evaluated in two TRANSFoRm clinical use cases (GORD and Diabetes), allowing researchers to select primary care sites with data that is ´fit for purpose´. For example, a researcher might only be interested in practices with more or less complete recordings of HbA1c, blood glucose and smoking status (Figure 1). Status of development Prototype.
Tool description
As computerisation of primary care facilities is rapidly increasing, a wealth of information is created in routinely recorded electronic health records (EHR) that can be used and is already used for research purposes. However, we need to be able to assess whether the data these primary care databases contain is ‘fit for purpose’. In the TRANSFoRm project an axiomatic approach was developed that started with defining purpose and population, followed by the definition of a set of metrics for data quality described in terms of completeness, accuracy, correctness and consistency. Based on this approach a web-based prototype of a data quality tool [1] was developed and evaluated in two TRANSFoRm clinical use cases (GORD and Diabetes), allowing researchers to select primary care sites with data that is ´fit for purpose´. For example, a researcher might only be interested in practices with more or less complete recordings of HbA1c, blood glucose and smoking status (Figure 1). Status of development Prototype.
As computerisation of primary care facilities is rapidly increasing, a wealth of information is created in routinely recorded electronic health records (EHR) that can be used and is already used for research purposes. However, we need to be able to assess whether the data these primary care databases contain is ‘fit for purpose’. In the TRANSFoRm project an axiomatic approach was developed that started with defining purpose and population, followed by the definition of a set of metrics for data quality described in terms of completeness, accuracy, correctness and consistency. Based on this approach a web-based prototype of a data quality tool [1] was developed and evaluated in two TRANSFoRm clinical use cases (GORD and Diabetes), allowing researchers to select primary care sites with data that is ´fit for purpose´. For example, a researcher might only be interested in practices with more or less complete recordings of HbA1c, blood glucose and smoking status (Figure 1). Status of development Prototype.