Implementation of the pain and symptom assessment record (PSAR)
Notice bibliographique
Résumé
BACKGROUND: Symptom control is a major component of care for the terminally ill patients. Although uncontrolled pain is distressing for patients and families, there are other symptoms that can be distressing such as dyspnea and fatigue. Determining methods to consistently assess and manage pain and other symptoms is a challenge for nurses, physicians and other health care professionals. In the Ottawa Region of Canada, health care providers raised concerns related to inconsistencies in pain assessment due to a variety of formats used, as the patient moved through the health care system. Recognizing the need for a common assessment tool, a working group was formed composed of 14 nurses associated with institutions and agencies delivering palliative care services in the Ottawa region, as well as a faculty member of the School of Nursing of the University of Ottawa. The mandate of the working group was to develop a consistent method to assess patients' pain and symptoms in order to facilitate communication among health care professionals within various health care settings. The Pain and Symptom Assessment Record (PSAR) was developed over 24 months. AIM: To determine the feasibility of implementing the PSAR in a variety of settings. METHODS: This exploratory study used focus groups and chart audits to gather data related to the utility of the PSAR. Education sessions were used to introduce the tool to nurses in the various settings. RESULTS: The tool was implemented in 12 settings. Thirty-seven education sessions were given to nurses prior to use of the tool and the feedback revealed that this is an important process in tool introduction. The results of the chart audits indicated that pain was assessed 93% of the time. Symptoms were less documented but fatigue was most prominent. Overall, patients were satisfied with their pain and symptom control. Data from the focus groups were analysed using content analysis and the two themes that emerged related to the tool were 'structure' and 'process'. CONCLUSION: There were many challenges in this project and lessons learned will be discussed. Based on the results, the tool has been modified and is currently utilized in diverse settings.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| 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.
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