Abstract
Background
Databases are frequently used for pharmacoepidemiological research. However, most of these databases consist either of prescribing, dispensing or administrative data and therefore lack insight in the interaction between the several health professionals around the patient.
Methods
To determine the success rate of linking records from the dispensing database of the Foundation for Pharmaceutical Statistics to the prescribing database of the second Dutch national survey of general practice, conducted by NIVEL (Netherlands Institute for Health Services Research), a deterministic record linkage approach was used with patient and prescription characteristics as matching variables between the two databases.
Results
The catchment area included 123 community pharmacies, 90 GP practices and approximately 170,000 unique patients. Overall 110,102 (64.8%) unique patients were linked using the matching variables patient's gender, year of birth, the 4-digit part of the postal code, date of dispensing/prescribing and ATC-code. The final database contains of the 110,102 both prescribing data from 83 GP practices and dispensing data of 112 community pharmacies.
Conclusion
This study shows that linkage of dispensing to prescribing data is feasible with a combination of patient characteristics, such as gender, year of birth and postal code, and prescription characteristics like prescription date and ATC-code. We obtained a linkage proportion of 64.8% resulting in complete prescribing and dispensing history of 110,102 patients. This offers an opportunity to gain insight in the mechanisms and factors influencing drug utilisation in general practice.
Databases are frequently used for pharmacoepidemiological research. However, most of these databases consist either of prescribing, dispensing or administrative data and therefore lack insight in the interaction between the several health professionals around the patient.
Methods
To determine the success rate of linking records from the dispensing database of the Foundation for Pharmaceutical Statistics to the prescribing database of the second Dutch national survey of general practice, conducted by NIVEL (Netherlands Institute for Health Services Research), a deterministic record linkage approach was used with patient and prescription characteristics as matching variables between the two databases.
Results
The catchment area included 123 community pharmacies, 90 GP practices and approximately 170,000 unique patients. Overall 110,102 (64.8%) unique patients were linked using the matching variables patient's gender, year of birth, the 4-digit part of the postal code, date of dispensing/prescribing and ATC-code. The final database contains of the 110,102 both prescribing data from 83 GP practices and dispensing data of 112 community pharmacies.
Conclusion
This study shows that linkage of dispensing to prescribing data is feasible with a combination of patient characteristics, such as gender, year of birth and postal code, and prescription characteristics like prescription date and ATC-code. We obtained a linkage proportion of 64.8% resulting in complete prescribing and dispensing history of 110,102 patients. This offers an opportunity to gain insight in the mechanisms and factors influencing drug utilisation in general practice.
| Original language | English |
|---|---|
| Article number | 18 |
| Number of pages | 7 |
| Journal | BMC medical informatics and decision making [E] |
| Volume | 6 |
| DOIs | |
| Publication status | Published - 2006 |