A-178 Evaluating a Patient-Centered Education Initiative in Preventing Pre-analytical Errors and Improving Patient Satisfaction in Clinical Diagnostic Laboratories
Notice bibliographique
Résumé
Abstract Background Laboratory medicine plays a crucial role in patient care, informing 70% of medical decisions. While technological advancements have reduced errors in the analytical phase, preanalytical variables remain a significant risk and may cause wrong results. Optimizing patient preparation is therefore vital to mitigate external factors affecting results. This includes ensuring patients are well-informed on preparation requirements. For instance, biotin consumption can interfere with certain assays. Patient education through clear and concise materials may help prevent erroneous patient results. This study aims to (1) examine the knowledge gap in patient education, (2) evaluate current educational materials, and (3) explore potential improvements in partnership with patients and families. Methods A poster and pamphlet to educate patients and mitigate the risk of biotin interference was developed at Sunnybrook Health Sciences Centre in 2016. They are used as examples of education materials in this study. A survey questionnaire was developed, which included patient demographics and a baseline knowledge assessment of biotin followed by knowledge assessment after review of educational materials. Survey respondents were asked to evaluate the quality of educational materials and identify barriers to accessing information. Responses were aggregated and analyzed to assess the effectiveness of the patient education initiative. The survey was conducted from March to October 2024, recruiting adult participants in the outpatient specimen collection centre waiting areas. Individuals with sensory conditions that could impede their ability to read, write, or comprehend the educational materials were excluded. This study was approved by Sunnybrook Research Ethics Board. All participants provided written informed consent. Results Forty individuals participated in the survey. Nineteen participants (47.5%) were aged 18-44 years, 7 (17.5%) were between 45-59 years, and 14 (35%) were 60 years or older. English was the primary language spoken by 53% of participants, while 13% reported Tamil as their first language. Notably, 78% of participants had completed at least post-secondary education. A pre-education knowledge assessment showed that 45% of participants (18/40) were familiar with biotin, with 5 reporting biotin use within the past year and 3 aware of its potential interference with laboratory testing. Following an educational intervention, a post-education knowledge assessment demonstrated a significant improvement, with 87% of participants exhibiting a clear understanding of biotin and its impact on laboratory testing. The educational material was well-received, with 95% of participants rating the format and design as "very easy to follow and understand." Participants expressed a preference for online instructions (70%), while others preferred printed materials or verbal guidance from healthcare personnel. Participants identified communication, technology, language, and time constraints as barriers to accessing information about laboratory testing. Conclusion Our study highlights a successful patient education initiative that improved participant understanding of a specific laboratory issue that could impact test results. It also highlighted barriers that patients experience when trying to access information on laboratory testing. By providing patients with essential information, healthcare providers can enhance patient satisfaction, improve patient-provider communication, and ultimately, deliver better care. Our findings emphasize the need for patient education to become a standard component of laboratory testing.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,376 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».