Information Technology (IT) plays a vital role in improving health care systems by enhancing the quality, efficiency, safety, security, collaboration and informing decision making. Dementia, a decline in mental ability which affects memory, concentration and perception, is a key issue in health and social care, given the current context of an aging population. The quality of dementia care is noted as an international area of concern. Dementia Care Mapping (DCM) is a systematic observational framework for assessing and improving dementia care quality. DCM has been used as both a research and practice development tool internationally. However, despite the success of DCM and the annual generation of a huge amount of data on dementia care quality, it lacks a governance framework, based on modern IT solutions for data management, such a framework would provide the organisations using DCM a systematic way of storing, retrieving and comparing data over time, to monitor progress or trends in care quality. Data Governance (DG) refers to the implications of policies and accountabilities to data management in an organisation. The data management procedure includes availability, usability, quality, integrity, and security of the organisation data according to their users and requirements. This novel multidisciplinary study proposes a comprehensive solution for governing the DCM data by introducing a data management framework based on a data warehousing approach. Original contributions have been made through the design and development of a data management framework, describing the DCM international database design and DCM data warehouse architecture. These data repositories will provide the acquisition and storage solutions for DCM data. The designed DCM data warehouse facilitates various analytical applications to be applied for multidimensional analysis. Different queries are applied to demonstrate the DCM data warehouse functionality. A case study is also presented to explain the clustering technique applied to the DCM data. The performance of the DCM data governance framework is demonstrated in this case study related to data clustering results. Results are encouraging and open up discussion for further analysis.

No / Over the years there have been advances in the quality of care provision for people with dementia. How to measure the impact of care on the person with dementia has challenged researchers as, until recently, no evaluation tool offered a comprehensive overview of the behaviour patterns and well-being of persons with dementia. Dementia Care Mapping (DCM) is a tool used by care practitioners and researchers to capture both the process (behaviours) and outcome (well-being) of care and is therefore of use as a tool to evaluate quality of care. This study aims to assess, through DCM, the experience of dementia care provision in residential and nursing homes in two voluntary organizations in England. The data illustrates similarities in the well-being and behaviour patterns of 76 persons with dementia living in six care settings throughout England. Examples of instances when people with dementia were "put down" and when well-being was enhanced, are outlined. The homes in the study were meeting the physical care but not the broader psychosocial care needs of the observed residents. The action taken by the organizations as a result of the DCM evaluations is summarized.

No / Objectives This paper describes DCM 8 and reports on the initial validation study of DCM 8. Methods Between 2001-2003, a series of international expert working groups were established to examine various aspects of DCM with the intention of revising and refining it. During 2004-2005 the revised tool (DCM 8) was piloted in seven service settings in the UK and validated against DCM 7th edition. Results At a group score level, WIB scores and spread of Behavioural Category Codes were very similar, suggesting that group scores are comparable between DCM 7 and 8. Interviews with mappers and focus groups with staff teams suggested that DCM 8 was preferable to DCM 7th edition because of the clarification and simplification of codes; the addition of new codes relevant to person-centred care; and the replacement of Positive Events with a more structured recording of Personal Enhancers. Conclusions DCM 8 appears comparable with DCM 7th edition in terms of data produced and is well received by mappers and dementia care staff.

The secondary use of Dementia Care Mapping (DCM) data, if that data were held in a data warehouse, could contribute to global efforts in monitoring and improving dementia care quality. This qualitative study identifies requirements for the secondary use of DCM data within a data warehouse using a user-driven approach. The thesis critically analyses various technical methodologies and then argues the use and further demonstrates the applicability of a modified grounded theory as a user-driven methodology for a data warehouse. Interviews were conducted with 29 DCM researchers, trainers and practitioners in three phases. 19 interviews were face to face with the others on Skype and telephone with an average length of individual interview 45-60 minutes. The interview data was systematically analysed using open, axial and selective coding techniques and constant comparison methods. The study data highlighted benchmarking, mappers’ support and research as three perceived potential secondary uses of DCM data within a data warehouse. DCM researchers identified concerns regarding the quality and security of DCM data for secondary uses, which led to identifying the requirements for additional provenance, ethical and contextual data to be included in a warehouse alongside DCM data to meet requirements for secondary uses of this data for research. The study data was also used to extrapolate three main factors such as an individual mapper, the organization and an electronic data management that can influence the quality and availability of DCM data for secondary uses. The study makes further recommendations for designing a future DCM data warehouse.

The secondary use of Dementia Care Mapping (DCM) data, if that data were held in a data warehouse, could contribute to global efforts in monitoring and improving dementia care quality. This qualitative study identifies requirements for the secondary use of DCM data within a data warehouse using a user-driven approach. The thesis critically analyses various technical methodologies and then argues the use and further demonstrates the applicability of a modified grounded theory as a user-driven methodology for a data warehouse. Interviews were conducted with 29 DCM researchers, trainers and practitioners in three phases. 19 interviews were face to face with the others on Skype and telephone with an average length of individual interview 45-60 minutes. The interview data was systematically analysed using open, axial and selective coding techniques and constant comparison methods. The study data highlighted benchmarking, mappers’ support and research as three perceived potential secondary uses of DCM data within a data warehouse. DCM researchers identified concerns regarding the quality and security of DCM data for secondary uses, which led to identifying the requirements for additional provenance, ethical and contextual data to be included in a warehouse alongside DCM data to meet requirements for secondary uses of this data for research. The study data was also used to extrapolate three main factors such as an individual mapper, the organization and an electronic data management that can influence the quality and availability of DCM data for secondary uses. The study makes further recommendations for designing a future DCM data warehouse.