Advances in Health Informatics Conference (AHIC 2010) The Realities of eHealth. April 2010
Bibliographic record
Abstract
Co-hosted by the National Institutes of Health Informatics, University of Waterloo Institute for Health Informatics Research, University of Waterloo School of Pharmacy, University of Waterloo School of Optometry, and Conestoga College The Advances in Health Informatics Conference in 2010 brought together clinicians, researchers, and industry partners to present work describing the realities of Health Informatics in practice in Canada and around the world. AHIC is an bi-annual, top-tier, peer-reviewed, Health Informatics conference addressing innovation, research, and education, attracting national and international visionaries, researchers, industry experts and government leaders from around the globe. AHIC will alternate annually with the Information Technology and Communications in Health (ITCH) conference, held in Victoria, B.C. The work presented at AHIC aims at answering the question, “How can we make a difference?” We invited papers from industry and academia, which were peer-reviewed and presented at the conference. The authors of the papers that were most highly ranked during peer review were invited to participate in this special issue of the electronic Journal of Health Informatics. Each of the nine papers provides a valuable contribution to the Health Informatics literature. Papers that exhibited the qualities of novelty and generalizability in their were judged to be suitable for inclusion in a peer-reviewed journal. The articles encompass much of the field of Health Informatics. A case study by van Gemert-Pijnen and colleagues describes how a web based communication tool was developed with user-participation to assist Methicillin Resistant Staphylococcus Aureus-colonized individuals in finding reliable and updated information related to their condition. Heimly and Hygen describe how information and communication technologies may support coordination of health care in Norway, and in particular, where effort needs to be applied to empower patients. One crucial area for the successful adoption of eHealth centers on the area of project management. Archer describes how project management can be integrated into eHealth curricula with the objective of improving student’s potential for achieving project success. Tolar and colleagues describe a difficult implementation where the researcher assisted staff during the adoption of an electronic medical record, confirming the need for highly trained IT staff with an understanding of the work of the individuals who use the system. Cowan and colleagues provide a fascinating account of the potential for collaborative geomatics to provide a space to develop new ideas and foster innovation and resilience within communities. Leonard and Dalziel provide valuable commentary in favor of including patient perspectives in order to identify significant opportunities to reform healthcare systems effectively. Paterson and colleagues present a methodology where the barriers and benefits to EMR implementation clarified areas which need further care and attention. Hurley and colleagues provide a valuable description of the what Canadian medical students are currently learning about medical informatics. Finally, Schleyer and colleagues put forth their vision for dental informatics now and in the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.062 | 0.028 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".