Your browser doesn't support javascript.
loading
Clinical risk assessment of modelled situations in a pharmaceutical decision support system: a modified e-Delphi exploratory study.
Bouet, Juline; Potier, Arnaud; Michel, Bruno; Mongaret, Céline; Ade, Mathias; Dony, Alexandre; Larock, Anne-Sophie; Dufay, Édith.
Afiliación
  • Bouet J; Pharmacy Department, CHU Nîmes, 4 Rue du Professeur Robert Debré, 30000, Nîmes, France. juline.bouet@gmail.com.
  • Potier A; Pharmacy Department, CHRU Nancy, 29 Avenue du Maréchal de Lattre de Tassigny, 54000, Nancy, France. juline.bouet@gmail.com.
  • Michel B; Pharmacy Department, CH Lunéville, 54300, 6 Rue Jean Girardet, Lunéville, France.
  • Mongaret C; Pharmacy Department, HU Strasbourg, 1 Place de l'Hopital, 67000, Strasbourg, France.
  • Ade M; Pharmacy Department, CHU Clermont-Ferrand, 58 Rue Montalembert, 63000, Clermont-Ferrand, France.
  • Dony A; Pharmacy Department, CP Nancy, 1 Rue Dr Archambault, 54000, Laxou, France.
  • Larock AS; Pharmacy Department, CH Lunéville, 54300, 6 Rue Jean Girardet, Lunéville, France.
  • Dufay É; Pharmacy Department, CHU UCL Namur, Place Louise Godin 15, 5330, Yvoir, Belgium.
Int J Clin Pharm ; 46(3): 727-735, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38551750
ABSTRACT

BACKGROUND:

Pharmaceutical decision support systems (PDSSs) use reasoning software to match patient data to modelled situations likely to cause drug-related problems (DRPs) or adverse drug events. To aid decision-making, modelled situations must be linked to well-defined systemic clinical risks.

AIM:

To obtain expert consensus on the level of clinical risk for patients associated with each modelled situation that could be addressed using a PDSS.

METHOD:

A two-round e-Delphi survey was conducted from February to April 2022, involving 20 experts from four French-speaking countries. Participants had to rate modelled situations on two five-point Likert scales, assessing the likelihood of clinical consequences and their severity. The degree of consensus was determined as the proportion of participants providing risk scores in line with the median. The combined median scores for likelihood and severity provided the level of risk according to the Clinical Risk Situation for Patients (CRiSP) scale, formalized via validated tools.

RESULTS:

The expert panel achieved consensus (≥ 75% agreement) on 48 out of 52 modelled clinical situations. Among these, 45 were categorized as high or extreme risk. The most common DRP identified was overdosing, accounting for 22% of cases. Furthermore, DRPs involving cardiovascular, psychiatric, and endocrinological drug classes were prevalent, constituting 45, 13, and 9% of cases, respectively.

CONCLUSION:

Through consensus, our study identified 45 modelled clinical situations associated with high or extreme risks. This study highlights the interest of using PDSSs to prevent harm in patients and, on a large scale, document the impact of the pharmacist in preventing, intercepting and managing iatrogenic drug risk.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Técnica Delphi / Sistemas de Apoyo a Decisiones Clínicas / Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Int J Clin Pharm Año: 2024 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Técnica Delphi / Sistemas de Apoyo a Decisiones Clínicas / Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Int J Clin Pharm Año: 2024 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Países Bajos