The effects of pharmacist prescribing on patient outcomes in the hospital setting: a systematic review protocol
Notice bibliographique
Résumé
Review question/objective The objective of this review is to determine the effects of pharmacist prescribing in the hospital setting. More specifically, the objectives are to quantitatively analyze the effectiveness of pharmacist prescribing on patient outcomes, including, but not limited to, the reduction of error rates and adverse events related to medication prescription in patients who present to hospital, either in the inpatient or outpatient setting. Background For conditions that can be medically managed, diagnosis is followed by prescribing of medications to treat a condition or alleviate symptoms associated with it. Traditionally, the act of prescribing has been mainly associated with medical practitioners. Non-medical prescribing is the extension of prescriptive rights provided to certain other professions apart from doctors, including nurses, pharmacists, optometrists and podiatrists. It was originally introduced to allow a more flexible system for the prescribing, supply and administration of medications in order to help improve patients' access to medications and ease the burden on general practitioners.1,2 Nurse prescribing was first introduced in the United States of America in 1969.3 In the last two decades, legislation changes have also occurred in various countries around the world to allow for non-medical prescribing.3-5 Pharmacist prescribing is currently legal in many countries, including Canada, New Zealand, the United Kingdom (UK) and the United States of America.2,6 In the UK, supplementary prescribing was first introduced in 2003, followed by independent prescribing in 2006.7 Different models of pharmacist prescribing have been described in the literature.1,5,6 They include independent, dependent and collaborative prescribing. In independent prescribing, pharmacists are responsible for the assessment, diagnosis and clinical management of patients. Dependent prescribing places more restrictions on the activity using protocols or formularies. The different types of dependent prescribing include: Prescribing by protocol: a written guideline (protocol) describes in explicit detail the activities that may be performed by the non-medical practitioner. This protocol includes the types of diseases and drug classes in which the practitioner may prescribe. Patient group directions: a written direction relating only to supply and administration of a prescription medicine. Prescribing by formulary: a limited list of medicines with limitations on prescribing. Prescribing by patient referral: patients are referred by a physician for specific drug therapy management or to achieve a defined therapeutic outcome. Repeat prescribing: medication-refill services in clinics for patients who require new continuing prescriptions prior to their next available appointment with their physician. Supplementary prescribing: a voluntary partnership between the physician and pharmacist, where the physician undertakes the initial assessment and the supplementary prescriber (pharmacist) prescribes in accordance with the care plan which has been agreed by the physician and patient. In collaborative prescribing, there is a cooperative practice relationship between the pharmacist and physician, where the pharmacist may prescribe medications. The physician diagnoses and makes initial treatment decisions for the patient while the pharmacist selects, monitors, modifies, continues or discontinues the treatment as appropriate. While systematic reviews on nurse prescribing are available,8,9 there are currently no systematic reviews available to quantify the effects of pharmacist prescribing in the hospital setting. One review published in 2011 assessed the contribution of prescribing by nurses and allied health professionals, but this was limited to the primary care setting.3 In 2004, a review focusing on pharmacist prescribing was published, and included prescribing in both the community and hospital setting.10 This review identified only four studies with an experimental design and concluded that additional research was needed to establish the validity of pharmacist prescribing. In a review which evaluated the impact of pharmacists on mental health, some studies involving pharmacist prescribing were included but were not the main focus of the review.11 Other published reviews which have included pharmacist prescribing mainly relate to descriptions of its current practice (including existing policies and procedures) in a specific country or region, barriers to its successful implementation, or the perspectives of pharmacist prescribers, other healthcare professionals or patients on pharmacist prescribing.2,6,12 A systematic review on the effects of pharmacist prescribing on patient outcomes in the hospital setting is therefore warranted.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,040 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,004 |
| Méta-épidémiologie (sens large) | 0,017 | 0,015 |
| Bibliométrie | 0,014 | 0,012 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,035 | 0,003 |
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 source (Gemma direct ou Codex distillé), 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 ».