No / Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. There is growing emphasis on sharing and reusing dementia care-related datasets to improve the quality of dementia care. Consequently, there is a need to develop data management solutions for collecting, integrating and storing these data in formats that enhance opportunities for reuse. Dementia Care Mapping (DCM) is an observational tool that is in widespread use internationally. It produces rich, evidence-based data on dementia care quality. Currently, that data is primarily used locally, within dementia care services, to assess and improve quality of care. Information-rich DCM data provides opportunities for secondary use including research into improving the quality of dementia care. But an effective data management solution is required to facilitate this. A rationale for the warehousing of DCM data as a technical data management solution is suggested. The authors also propose a data model for a DCM data warehouse and present user-identified challenges for reusing DCM data within a warehouse.

Yes / The reuse of existing datasets to identify mechanisms for improving healthcare quality has been widely encouraged. There has been limited application within dementia care. Dementia Care Mapping (DCM) is an observational tool in widespread use, predominantly to assess and improve quality of care in single organisations. DCM data has the potential to be used for secondary purposes to improve quality of care. However, its suitability for such use requires careful evaluation. This study conducted in-depth interviews with 29 DCM users to identify issues, concerns and challenges regarding the secondary use of DCM data. Data was analysed using modified Grounded Theory. Major themes identified included the need to collect complimentary contextual data in addition to DCM data, to reassure users regarding ethical issues associated with storage and reuse of care related data and the need to assess and specify data quality for any data that might be available for secondary analysis. / This study was funded by the Faculty of Health Studies, University of Bradford.

Background: Coronary artery disease is a common cause of morbidity and mortality in the UK. Interventional revascularisation procedures for addressing the disease include percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), which respectively seek to open up or bypass blocked arteries to restore blood flow to heart muscle. Rates at which these procedures are carried out have changed in recent years, as have clinical indications for referral. PCI is delivered by interventional cardiologists, while CABG is carried out by cardiothoracic surgeons, necessitating multi-disciplinary decision making. There is both within- and cross-speciality debate as to the optimal treatment strategy in some case types. Evaluation of the care provided is of clinical and political importance, and requires information about how post-procedure event rates per operator and hospital compare with those expected given the composition of patient populations. Methods: Two UK-wide audit databases of PCI and CABG procedures were used to explore a range of clinical outcome questions. The patient populations contained within each database were compared to see how they differed, and also how each had changed in recent years. In CABG patients, comparative effectiveness of two different surgical techniques (single vs bilateral mammary artery grafting) was assessed with respect to both short-term and long-term mortality outcomes. In PCI patients, a risk model to predict 30-day mortality was developed for use in clinical appraisal. Results: In both patient populations there had been changes to the relative frequencies of many characteristics over time. In the CABG population, multivariable analysis showed that patients undergoing single mammary artery grafting had lower odds of all-cause mortality within 30 days of procedure than those receiving bilateral mammary artery grafting, but had worse overall survival in the long term. In the PCI population, the developed risk model demonstrated good calibration and discrimination at predicting 30-day all-cause mortality. Discussion: The studies described above demonstrate that large-scale routinely collected data can be used to gain insights into clinical care quality and delivery. These resources are under-utilised at present; correcting this requires an understanding of the limitations of the data and how the information contained therein relates to actual clinical care.