MétaCan
Menu
Back to cohort
Record W2945930040 · doi:10.1108/ijhcqa-07-2018-0185

Improving pediatric experience of pain during vaccinations: a quality improvement project

2019· article· en· W2945930040 on OpenAlexaff
Terri MacDougall, Shawna Cunningham, Leeann Whitney, Monakshi Sawhney

Bibliographic record

VenueInternational Journal of Health Care Quality Assurance · 2019
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsQueen's UniversityInnovation Initiatives Ontario North
Fundersnot available
KeywordsMedicineVaccinationBest practicePain assessmentHealth carePhysical therapyTest (biology)Descriptive statisticsPopulationNursingFamily medicinePain management

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this paper is to share lessons learned from a quality improvement (QI) project that studied pediatric pain assessment scores after implementing additional evidence-based pain mitigation strategies into practice. Most nurses will acknowledge they implement some practices to mitigate pain during injections. Addressing pain during vaccination is important to prevent needle fear, vaccine hesitancy and health care avoidance. The aim of this project was to reduce pain as evidenced by pain scores at the time of vaccination at the North Bay Nurse Practitioner-Led Clinic (NBNPLC). DESIGN/METHODOLOGY/APPROACH: The design for this study was quasi-experimental utilizing descriptive statistics and QI tools. The NBNPLC utilized the model for improvement to test change ideas. A validated observation tool to assess pain during vaccination with the pediatric population (revised Face Legs Activity Cry and Consolability) was used to test changes. The team deliberately planned improvements according to best practice guidelines to optimize use of strategies to mitigate pain during injections. QI tools and leadership skills were utilized to improve the pediatric experience of pain during vaccinations. Parents and clinicians provided qualitative and quantitative feedback to the project. FINDINGS: Nurses tested pain assessment tools and agreed to use a validated tool to assess pain during vaccinations. Parents agreed to use of topical anesthetic during vaccinations. Improved pain scores during vaccinations were demonstrated with the use of topical anesthetic. Parents agreed to use of standardized sucrose solution during vaccination. Reduced pain scores were observed with the use of standardized sucrose water. To sustain implementation of the guideline, a nursing documentation form was devised with nurses agreeing to ongoing use of the form. RESEARCH LIMITATIONS/IMPLICATIONS: This is a QI project that examined the intricacies of moving clinical practice guidelines into clinical practice. The project validates guidelines for pain management during vaccinations. Leaders within clinics who want to improve pediatric pain during vaccinations will find this paper helpful as a guide. PRACTICAL IMPLICATIONS: Pain management in the pediatric population will be touched on in the context of parental expectations of pain. QI tools, lessons learned and suggestions for nurses will be outlined. Leadership plays an influential role in translating practice guidelines into practice. ORIGINALITY/VALUE: This paper outlines how organizational supports were instrumental to give clinicians time to deliberately challenge practice to improve quality of care of children during vaccinations.

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 imitation

Not 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.

metaresearch head score (Codex)0.090
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0900.085
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.398
Teacher spread0.372 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Health Care Quality AssuranceSame topicPediatric Pain Management TechniquesFrench-language works237,207