Author: Karolyn Kerr
The University of Auckland
This research began a journey towards improved maturity around data quality management in New Zealand health care, where total data quality management is ‘business as usual’, institutionalised into the daily practices of all those who work in health care. The increasingly information intensive nature of health care demands a proactive and strategic approach to data quality to ensure the right information is available to the right person at the right time in the right format, all in consideration of the rights of the patient to have his/her health data protected and used in an ethical way. The work extends and tests principles to establish good practice and overcome practical barriers. This thesis explores the issues that define and control data quality in the national health data collections and the mechanisms and frameworks that can be developed to achieve and sustain good data quality. The research is interpretive, studying meaning within a social setting. The research provides the structure for learning and potential change through the utilisation of action research. Grounded theory provides the structure for the analysis of qualitative data through inductive coding and constant comparison in the analysis phase of the action research iterative cycle. Participatory observation provided considerable rich data as the researcher was a member of staff within the organisation. Data were also collected at workshops, focus groups, structured meetings and interviews. The development of a Data Quality Evaluation Framework and a national Data Quality Improvement Strategy provides clear direction for a holistic and ‘whole of health sector’ way of viewing data quality, with the ability for organisations to develop and implement local innovations through locally developed strategies and data quality improvement programmes. The researcher utilised the theory of appreciative enquiry (Fry, 2002) to positively encourage change, and to encourage the utilisation of existing organisational knowledge. Simple rules, such as the TDQM process and the data quality dimensions guided the change, leaving room for innovation. The theory of ‘complex systems of adjustment’ (Champagne, 2002; Stacey, 1993) can be instilled in the organisation to encourage change through the constant interaction of people throughout the organisation.
Keywords: Institutionalisation, Data Quality, New Zealand Health Sector