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The study was user survey method based, performed to get the overview of use and perceptions of health caremanagers towards Lithuanian computerized health information system as a tool for decision – making. Aims of the study were to describe LCHIS, its inputs and potential use; to account for a surveyofpotential users, health care administrators; to discuss the need for improvement of the system and itsuse. Methods. User survey method was applied. Literature search was performed and the questionnaire was constructed after interview with four respondents and clarification of questions. Totally 100 ofrespondents from different health care institutions were interviewed. Data was analysed using normal statistical methods, using MS Excel 2000 and statistical package SPSS 10.0 as tools. Main results. Concerning the awareness about the existing of LCHIS, 68% of the respondents saidtheyhave heard about it and 15% said theyhave been using this system daily. As many as 68% of respondents didn’t really take care about the existence of LCHIS, while the size of respondents being satisfied and not was pretty the same. The number of satisfied with the structure was rather small ifcomparing with those partially satisfied. As many as 76% of the respondents said they haven’t been using the system at all. 24% of the respondents were satisfied with the certain groups of healthindicators within the system. Group of morbidity indicators and group of hospital activity indicatorswere among the mostly used (17% together). Almost 20% of the respondents said it was easy for them to use LCHIS; the same number of health care administrators trusted the information comingfrom LCHISand they have experienced the situation, where they have used LCHIS for planning ormanagement in current situation. As many as 82% of health care managers agreed heads or administrative staff of hospitals supposed to be the key members, who must encourage them to use the system. Conclusions. About two thirds of health care administrators interviewed knew about LCHIS and the rest had been or were users. In the comments this group claimed they were supporting their decisions by using the systemand indicators in it. As many as 96% of the respondents stated there was a needfor statistical information and skills for dailydecision - making and managerial activities. The respondents, who used LCHIS, trusted the information in the system and found it useful in their dailywork as health managers. The main comments, why respondents didn’t use the system or didn’tknow about it, was lack of information technologies in work place, lack of computer skills and lackof support from hospital authorities / <p>ISBN 91-7997-097-4</p>

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.

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.

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.

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.

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.

[pt] A indústria da saúde é gerida, no Brasil, por administradores de saúde que, em grande parte, migraram da atividade médica tradicional para a de gestão. São pessoas que em algum momento de suas carreiras, aceitaram responsabilidades administrativas e assumiram cargos de gestão em um dos mais desafiadores e caros segmentos produtivos da economia. O propósito dessa pesquisa foi procurar desvendar a complexidade do desafio de ser administrador de saúde, a partir da vivência de executivos do sistema de saúde privado, exercendo cargos em operadoras de saúde ou hospitais. A estratégia de investigação escolhida para responder ao problema de pesquisa - o que é ser administrador de saúde? – foi o método fenomenológico. Este método foi considerado adequado por permitir que o entrevistado, com base em sua experiência vivida, formulasse por si próprio seus significados, sem o direcionamento de um roteiro pré-estabelecido. A descrição textual conformou, então, uma descrição da essência da experiência vivida pelos sujeitos entrevistados, agrupada em clusters de significação: a mudança de papéis de médico a médico-administrador, o sentimento de onipotência e tolerância ao próprio erro, a tolerância ao erro da equipe e atenção aos detalhes, a visão do trabalho gerencial, a qualificação da ética e o escopo da gestão de saúde. As entrevistas foram feitas com base em apenas duas perguntas: o que é ser administrador de saúde e que contextos ou situações você considera típicos desta experiência? Pouco se tem escrito, no Brasil, sobre quem toma as decisões que têm impacto em todo o segmento. Nesse contexto, o presente trabalho contribui com insights importantes acerca das ocupações e das preocupações que tomam a agenda do administrador de saúde. / [en] The healthcare industry is managed, in Brazil, for health managers, in large part, who migrated from traditional medical assistance. These are people who at some point in their careers, accepted administrative responsibilities and assumed management positions in one of the most challenging and expensive production segments of the economy. The purpose of this research was to attempt to unravel the complexity of the challenge of being a health manager, from the experience of executives of private health care, acting positions in health insurance companies or hospitals. The research strategy chosen to address the problem of research - what consists on being a health manager? - was the phenomenological method. This method was deemed appropriate to allow the interviewee, based on their experience, to formulate their meaning by himself, without the guidance of a preestablished guidance. The textual description conformed, then a description of the essence of lived experience by interviewees, grouped in clusters of meaning: the changing roles of physician to health manager; the sense of omnipotence and tolerance to their own error; the tolerance to staff error and attention to detail; the view of managerial work, the qualification of ethics and scope of healthcare management. The interviews were based on only two questions: what is a health manager and what contexts or situations you consider typical for this experience? Little has been written in Brazil, about who makes decisions that impact the entire segment. In this context, this study contributes important insights about the occupations and preoccupations that take the agenda of health care managers.

Treating chronic health conditions consumes a significant portion of the health care resource. Two–thirds of UK hospital admissions consist of people with chronic conditions (Singh, 2005). To date, health management has tended to focus on service redesign, rather than focusing on the patients, as a way to facilitate improved outcomes and control costs. Typically, these management approaches are premised on the patient as a consumer/end user. An alternative view to the patient being a consumer is that of the patient being a co–producer of the service. Co–production recognises the client (patient) as a resource, in that value cannot easily be created or delivered, unless the patient actively contributes to the service (Alford, 1998). Patients gain health value when they are well and are independent of the health care system and its costs. Health care organisations gain economic value, when chronic patients require less health care. This thesis examines co–production, in the context of contemporary patient involvement and heath services management. ‘Knowing the People Planning’ (KPP), an innovative health management method, is evaluated for its patient management co–production potential. KPP is based on ten key features of service provision. Four of the key features relate to the patient, whilst the remaining six features relate to the organisation. It is the management of these patient and organisation features that better facilitates chronic long-term mental health patients as co–producers. The empirical findings, from this evaluation of KPP provide evidence for the efficacy of co–productive health management theory and practice. Patient health value and health care organisation economic value are created, when both the organisation and the patient co–produce the health service. KPP was initially implemented by eight of New Zealand’s 21 District Health Boards. Socio-ecological action research methodology was used to evaluate KPP — by taking a ‘people-in-environments’ approach. The evaluation covers fourteen action research cycles for 2,021 chronic long-term patients over four years. Measurements include the amount of time these long-term patients spent in hospital and employment rates. The integration of the action research cycles, using the socio-ecological method supported the generation of (what I have called) ‘co–productive health management theory’. Analyses of secondary data, across organisational and patient domains, supplement the action research findings, in order to assess for confounding factors. The organisation outcomes relate to costs and staff turnover. Patient outcomes relate to service utilisation measures, for approximately 60,000 adult patients per year, who access New Zealand’s secondary mental health services. A pivotal finding of this research was that, as the rate of patients with treatment plans increased from 50% to 90%, inpatient bed use decreased by 26%. However, increased funding for mental health services had only a minor impact on decreasing inpatient bed use. Patient employment rates increased, whilst the number of patients who required access to general practitioners and changes to their housing situation, decreased. The patient management co–production view offers a significant opportunity for health care managers and researchers to significantly improve both patient and organisation value. Co–production views the patient as a resource, who contributes to her/his health outcome, rather than a person who simply consumes services. The better patients can co–produce their health outcome the better their health, and the lower their demand for health services.

Workflow in healthcare, particularly for the shared and coordinated management of chronic illnesses, is very difficult to model. It is also difficult to support via current Clinical information Systems and current information technologies. This dissertation contributes significant enhancements to the current methodologies for designing and implementing workflow Management Systems (WfMSs) suitable for healthcare. The contribution comprises three interrelated aspects of workflow system architecture as follows:- Firstly, it shifts the emphasis of workflow modelling and enactment to a focus on goals, and the monitoring and facilitation of their achievement. Secondly, it introduces the concept of self-modifying workflow in the context of health care planning, whereby explicit tasks in the goal-based care plan are devoted to assessing and modifying downstream workflow. Thirdly, this dissertation proposes methodologies for identifying and dealing with tasks which overlap, subsume or interfere with other tasks elsewhere in a given workflow. / PhD Doctorate