TY - JOUR
T1 - Optimising the secondary use of primary care prescribing data to improve quality of care
T2 - a qualitative analysis
AU - Barbazza, Erica
AU - Verheij, Robert A.
AU - Ramerman, Lotte
AU - Klazinga, Niek
AU - Kringos, Dionne
N1 - Funding Information: This work was carried out by the Marie Skłodowska-Curie Innovative Training Network for Healthcare Performance Intelligence Professionals (HealthPros) that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nr. 765141. Publisher Copyright: © 2022 BMJ Publishing Group. All rights reserved.
PY - 2022/7/21
Y1 - 2022/7/21
N2 - OBJECTIVES: To explore available data sources, secondary uses and key considerations for optimising the actionability of primary care prescribing data to improve quality of care in the Dutch context. DESIGN: An exploratory qualitative study was undertaken based on semi-structured interviews. We anchored our investigation around three tracer prescription types: antibiotics; benzodiazepines and opioids. Descriptive and explanatory themes were derived from interview data using thematic analysis. SETTING: Stakeholders were sampled from across the micro (clinical), meso (organisational) and macro (policy) contexts of the Dutch primary care system. PARTICIPANTS: The study involved 28 informants representing general practitioners (GPs), community pharmacists, regional chronic care networks (care groups), academia and research institutes, insurers, professional associations, electronic health record (EHR) vendors and national authorities. RESULTS: In the Netherlands, three main sources of data for improving prescribing in primary care are in use: clinical data in the EHRs of GP practices; pharmacy data in community pharmacy databases and claims data of insurers. While the secondary use of pharmacy and claims data is well-established across levels, the use of these data together with EHR data is limited. Important differences in the types of prescribing information needed by micro-meso-macro context are found, though the extent to which current indicators address these varies by prescription type. Five main themes were identified as areas for optimising data use: (1) measuring what matters, (2) increasing data linkages, (3) improving data quality, (4) facilitating data sharing and (5) optimising fit for use analysis. CONCLUSIONS: To make primary care prescribing data useful for improving quality, consolidated patient-specific data on the indication for a prescription and dispensed medicine, over time, is needed. In the Netherlands, the selection of indicators requires further prioritisation to better signal the appropriateness and long-term use of prescription drugs. Prioritising data linkages is critical towards more actionable use.
AB - OBJECTIVES: To explore available data sources, secondary uses and key considerations for optimising the actionability of primary care prescribing data to improve quality of care in the Dutch context. DESIGN: An exploratory qualitative study was undertaken based on semi-structured interviews. We anchored our investigation around three tracer prescription types: antibiotics; benzodiazepines and opioids. Descriptive and explanatory themes were derived from interview data using thematic analysis. SETTING: Stakeholders were sampled from across the micro (clinical), meso (organisational) and macro (policy) contexts of the Dutch primary care system. PARTICIPANTS: The study involved 28 informants representing general practitioners (GPs), community pharmacists, regional chronic care networks (care groups), academia and research institutes, insurers, professional associations, electronic health record (EHR) vendors and national authorities. RESULTS: In the Netherlands, three main sources of data for improving prescribing in primary care are in use: clinical data in the EHRs of GP practices; pharmacy data in community pharmacy databases and claims data of insurers. While the secondary use of pharmacy and claims data is well-established across levels, the use of these data together with EHR data is limited. Important differences in the types of prescribing information needed by micro-meso-macro context are found, though the extent to which current indicators address these varies by prescription type. Five main themes were identified as areas for optimising data use: (1) measuring what matters, (2) increasing data linkages, (3) improving data quality, (4) facilitating data sharing and (5) optimising fit for use analysis. CONCLUSIONS: To make primary care prescribing data useful for improving quality, consolidated patient-specific data on the indication for a prescription and dispensed medicine, over time, is needed. In the Netherlands, the selection of indicators requires further prioritisation to better signal the appropriateness and long-term use of prescription drugs. Prioritising data linkages is critical towards more actionable use.
KW - Health & safety
KW - Information management
KW - PRIMARY CARE
KW - QUALITATIVE RESEARCH
KW - Quality in health care
UR - http://www.scopus.com/inward/record.url?scp=85134789237&partnerID=8YFLogxK
U2 - https://doi.org/10.1136/bmjopen-2022-062349
DO - https://doi.org/10.1136/bmjopen-2022-062349
M3 - Article
C2 - 35863830
SN - 2044-6055
VL - 12
SP - e062349
JO - BMJ Open
JF - BMJ Open
IS - 7
M1 - e062349
ER -