MétaCan
Menu
Back to cohort
Record W2768605314 · doi:10.20381/ruor-21195

Project Management Practices in Small Projects: 5 cases in a Canadian Hospital Setting

2017· dissertation· en· W2768605314 on OpenAlexaboutno aff
Monika Jasińska

Bibliographic record

VenueuO Research (University of Ottawa) · 2017
Typedissertation
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsEngineering managementProgram managementMedicineOperations managementProject managementEngineeringSystems engineering

Abstract

fetched live from OpenAlex

Healthcare is continuously changing through means of project work. Small projects in healthcare settings are of particular interest since they are usually not adequately supported by the health institution, and present many challenges of their own. However, collective successful completion of small projects has the potential to significantly impact and improve health service delivery. This thesis examined the common and successful project management practices in small projects in Canadian hospital settings to acquire new knowledge on this understudied kind of project and propose basic project management practice guidelines for future small projects conducted within these settings. Data collection was conducted in two hospitals in the form of 23 semi-structured interviews with five interprofessional project teams composed of 4-10 healthcare professionals. Each project was considered as the unit of analysis. Qualitative within-case and cross-case inferential processes were applied and a consolidated list of 43 project management practices deemed important by the majority of participants from all cases was revealed and could serve as basic project management practice guidelines for future small projects conducted in hospitals. Findings also shed light on the beneficial value of adapting principles of project management to small projects in hospital settings. Given the bottom-up nature of small projects, results suggest it is of significant importance to clearly define and understand the small project, as well as perform a thorough stakeholder analysis to be able to gain the right approvals. Insufficient time dedicated to small project management governed these shortcomings, thus team members need to regularly allot time to managing their small project. Lastly, the presence of a team leader was a significant factor influencing continuous project execution. Future studies should take into consideration allied disciplines’ contributions such as organizational behaviour to help explain the interplay between group dynamics and small project outcome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.242
GPT teacher head0.450
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueuO Research (University of Ottawa)Same topicConstruction Project Management and PerformanceFrench-language works237,207