Evaluation criteria for the district health management information systems: lessons from the Ministry of Health, Kenya.
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BACKGROUND: The District Health Management Information Systems (DHMISs) were established by the Ministry of Health (MoH) in Kenya more than two decades ago. Since then, no comprehensive evaluation has been undertaken. This can partly be attributed to lack of defined criteria for evaluating them. OBJECTIVE: To propose evaluation criteria for assessing the design, implementation and impact of DHMIS in the management of the District Health System (DHS) in Kenya. METHODS: A descriptive cross-sectional study conducted in three DHSs in Kenya: Bungoma, Murang'a and Uasin Gishu districts. Data was collected through focus group discussions, key informant interviews, and documents' review. The respondents, purposely selected from the Ministry of Health headquarters and the three DHS districts, included designers, managers and end-users of the systems. RESULTS: A set of evaluation criteria for DHMISs was identified for each of the three phases of implementation: pre-implementation evaluation criteria (categorised as policy and objectives, technical feasibility, financial viability, political viability and administrative operability) to be applied at the design stage; concurrent implementation evaluation criteria to be applied during implementation of the new system; and post-implementation evaluation criteria (classified as internal - quality of information; external - resources and managerial support; ultimate - systems impact) to be applied after implementation of the system for at least three years. CONCLUSIONS: In designing a DHMIS model there is need to have built-in these three sets of evaluation criteria which should be used in a phased manner. Pre-implementation evaluation criteria should be used to evaluate the system's viability before more resources are committed to it; concurrent (operational) - implementation evaluation criteria should be used to monitor the process; and post-implementation evaluation criteria should be applied to assess the system's effectiveness. (+info)
Telephone-linked care for physical activity: a qualitative evaluation of the use patterns of an information technology program for patients.
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Automated health behavior interventions that involve discretionary use by patients or consumers over extended periods of time are becoming more common and it is generally assumed that adherence to the recommended schedule is related to the impact of the system on users. Yet reasons for use or non-use of such systems have not been carefully explored. An understanding of factors that influence people to use, not use, or underutilize these automated behavioral change and self-care management systems can help in designing systems that are more effective and acceptable to users. Using qualitative research methods, this study explored the experiences of 45 users of a multiple-contact health promotion application with the goal of understanding the major factors that affect patterns of use (frequency of and duration of contact). The in-depth exploration of users' perceptions and views made possible by the qualitative research methods revealed a number of important themes. Reported reasons for underutilization or non-use were found to be both user-related and system-related. User-related reasons encompassed personal and individual events that prevented or impeded system utilization. System-related reasons included those that related to the medium itself as well as the content of the application. The qualitative methods employed in this study created a forum through which users' feedback could be fully explored and then synthesized to assist in the improvement of this and other automated health behavior interventions. (+info)
Potential use of routine databases in health technology assessment.
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OBJECTIVES: To develop criteria for classifying databases in relation to their potential use in health technology (HT) assessment and to apply them to a list of databases of relevance in the UK. To explore the extent to which prioritized databases could pick up those HTs being assessed by the National Coordinating Centre for Health Technology Assessment (NCCHTA) and the extent to which these databases have been used in HT assessment. To explore the validation of the databases and their cost. DATA SOURCES: Electronic databases. Key literature sources. Experienced users of routine databases. REVIEW METHODS: A 'first principles' examination of the data necessary for each type of HT assessment was carried out, supplemented by literature searches and a historical review. The principal investigators applied the criteria to the databases. Comments of the 'keepers' of the prioritized databases were incorporated. Details of 161 topics funded by the NHS R&D Health Technology Assessment (HTA) programme were reviewed iteratively by the principal investigators. Uses of databases in HTAs were identified by literature searches, which included the title of each prioritized database as a keyword. Annual reports of databases were examined and 'keepers' queried. The validity of each database was assessed using criteria based on a literature search and involvement by the authors in a national academic network. The costs of databases were established from annual reports, enquiries to 'keepers' of databases and 'guesstimates' based on cost per record. For assessing effectiveness, equity and diffusion, routine databases were classified into three broad groups: (1) group I databases, identifying both HTs and health states, (2) group II databases, identifying the HTs, but not a health state, and (3) group III databases, identifying health states, but not an HT. Group I datasets were disaggregated into clinical registries, clinical administrative databases and population-oriented databases. Group III were disaggregated into adverse event reporting, confidential enquiries, disease-only registers and health surveys. RESULTS: Databases in group I can be used not only to assess effectiveness but also to assess diffusion and equity. Databases in group II can only assess diffusion. Group III has restricted scope for assessing HTs, except for analysis of adverse events. For use in costing, databases need to include unit costs or prices. Some databases included unit cost as well as a specific HT. A list of around 270 databases was identified at the level of UK, England and Wales or England (over 1000 including Scotland, Wales and Northern Ireland). Allocation of these to the above groups identified around 60 databases with some potential for HT assessment, roughly half to group I. Eighteen clinical registers were identified as having the greatest potential although the clinical administrative datasets had potential mainly owing to their inclusion of a wide range of technologies. Only two databases were identified that could directly be used in costing. The review of the potential capture of HTs prioritized by the UK's NHS R&D HTA programme showed that only 10% would be captured in these databases, mainly drugs prescribed in primary care. The review of the use of routine databases in any form of HT assessment indicated that clinical registers were mainly used for national comparative audit. Some databases have only been used in annual reports, usually time trend analysis. A few peer-reviewed papers used a clinical register to assess the effectiveness of a technology. Accessibility is suggested as a barrier to using most databases. Clinical administrative databases (group Ib) have mainly been used to build population needs indices and performance indicators. A review of the validity of used databases showed that although internal consistency checks were common, relatively few had any form of external audit. Some comparative audit databases have data scrutinised by participating units. Issues around coverage and coding have, in general, received little attention. NHS funding of databases has been mainly for 'Central Returns' for management purposes, which excludes those databases with the greatest potential for HT assessment. Funding for databases was various, but some are unfunded, relying on goodwill. The estimated total cost of databases in group I plus selected databases from groups II and III has been estimated at pound 50 million or around 0.1% of annual NHS spend. A few databases with limited potential for HT assessment account for the bulk of spending. CONCLUSIONS: Suggestions for policy include clarification of responsibility for the strategic development of databases, improved resourcing, and issues around coding, confidentiality, ownership and access, maintenance of clinical support, optimal use of information technology, filling gaps and remedying deficiencies. Recommendations for researchers include closer policy links between routine data and R&D, and selective investment in the more promising databases. Recommended research topics include optimal capture and coding of the range of HTs, international comparisons of the role, funding and use of routine data in healthcare systems and use of routine database in trials and in modelling. Independent evaluations are recommended for information strategies (such as those around the National Service Frameworks and various collaborations) and for electronic patient and health records. (+info)
Top 10 health care ethics challenges facing the public: views of Toronto bioethicists.
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BACKGROUND: There are numerous ethical challenges that can impact patients and families in the health care setting. This paper reports on the results of a study conducted with a panel of clinical bioethicists in Toronto, Ontario, Canada, the purpose of which was to identify the top ethical challenges facing patients and their families in health care. A modified Delphi study was conducted with twelve clinical bioethicist members of the Clinical Ethics Group of the University of Toronto Joint Centre for Bioethics. The panel was asked the question, what do you think are the top ten ethical challenges that Canadians may face in health care? The panel was asked to rank the top ten ethical challenges throughout the Delphi process and consensus was reached after three rounds. DISCUSSION: The top challenge ranked by the group was disagreement between patients/families and health care professionals about treatment decisions. The second highest ranked challenge was waiting lists. The third ranked challenge was access to needed resources for the aged, chronically ill, and mentally ill. SUMMARY: Although many of the challenges listed by the panel have received significant public attention, there has been very little attention paid to the top ranked challenge. We propose several steps that can be taken to help address this key challenge. (+info)
Consequences of health trends and medical innovation for the future elderly.
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Recent innovations in biomedicine seem poised to revolutionize medical practice. At the same time, disease and disability are increasing among younger populations. This paper considers how these confluent trends will affect the elderly's health status and health care spending over the next thirty years. Because healthier people live longer, cumulative Medicare spending varies little with a beneficiary's disease and disability status upon entering Medicare. On the other hand, ten of the most promising medical technologies are forecast to increase spending greatly. It is unlikely that a "silver bullet" will emerge to both improve health and dramatically reduce medical spending. (+info)
Health, technology, and medical care spending.
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The RAND Future Elderly Model illustrates important principles about the relation among medical technologies, health spending, and health. New technologies add to spending because the costs of the new technologies and the health care costs during the added years of life they bring outweigh reductions in annual spending from better health. Many technologies with a low cost per patient per year result in high aggregate costs because of an expanded population being treated. However, the jury is still out on whether a better health-risk profile among future sixty-five-year-olds could moderate health spending for the elderly. (+info)
Desiderata for domain reference ontologies in biomedicine.
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Domain reference ontologies represent knowledge about a particular part of the world in a way that is independent from specific objectives, through a theory of the domain. An example of reference ontology in biomedical informatics is the Foundational Model of Anatomy (FMA), an ontology of anatomy that covers the entire range of macroscopic, microscopic, and subcellular anatomy. The purpose of this paper is to explore how two domain reference ontologies--the FMA and the Chemical Entities of Biological Interest (ChEBI) ontology, can be used (i) to align existing terminologies, (ii) to infer new knowledge in ontologies of more complex entities, and (iii) to manage and help reasoning about individual data. We analyze those kinds of usages of these two domain reference ontologies and suggest desiderata for reference ontologies in biomedicine. While a number of groups and communities have investigated general requirements for ontology design and desiderata for controlled medical vocabularies, we are focusing on application purposes. We suggest five desirable characteristics for reference ontologies: good lexical coverage, good coverage in terms of relations, compatibility with standards, modularity, and ability to represent variation in reality. (+info)
From concepts to clinical reality: an essay on the benchmarking of biomedical terminologies.
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It is only by fixing on agreed meanings of terms in biomedical terminologies that we will be in a position to achieve that accumulation and integration of knowledge that is indispensable to progress at the frontiers of biomedicine. Standardly, the goal of fixing meanings is seen as being realized through the alignment of terms on what are called 'concepts.' Part I addresses three versions of the concept-based approach--by Cimino, by Wuster, and by Campbell and associates--and surveys some of the problems to which they give rise, all of which have to do with a failure to anchor the terms in terminologies to corresponding referents in reality. Part II outlines a new, realist solution to this anchorage problem, which sees terminology construction as being motivated by the goal of alignment not on concepts but on the universals (kinds, types) in reality and thereby also on the corresponding instances (individuals, tokens). We outline the realist approach and show how on its basis we can provide a benchmark of correctness for terminologies which will at the same time allow a new type of integration of terminologies and electronic health records. We conclude by outlining ways in which the framework thus defined might be exploited for purposes of diagnostic decision-support. (+info)