Effects of librarian-provided services in healthcare settings: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of librarian-provided services in healthcare settings on patient, healthcare provider, and researcher outcomes. MATERIALS AND METHODS: Medline, CINAHL, ERIC, LISA (Library and Information Science Abstracts), and the Cochrane Central Register of Controlled Trials were searched from inception to June 2013. Studies involving librarian-provided services for patients encountering the healthcare system, healthcare providers, or researchers were eligible for inclusion. All librarian-provided services in healthcare settings were considered as an intervention, including hospitals, primary care settings, or public health clinics. RESULTS: Twenty-five articles fulfilled our eligibility criteria, including 22 primary publications and three companion reports. The majority of studies (15/22 primary publications) examined librarians providing instruction in literature searching to healthcare trainees, and measured literature searching proficiency. Other studies analyzed librarian-provided literature searching services and instruction in question formulation as well as the impact of librarian-provided services on patient length of stay in hospital. No studies were found that investigated librarians providing direct services to researchers or patients in healthcare settings. CONCLUSIONS: Librarian-provided services directed to participants in training programs (eg, students, residents) improve skills in searching the literature to facilitate the integration of research evidence into clinical decision-making. Services provided to clinicians were shown to be effective in saving time for health professionals and providing relevant information for decision-making. Two studies indicated patient length of stay was reduced when clinicians requested literature searches related to a patient's case.
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 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 | 0.013 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".