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4CPS-170 Clinical pharmacy prioritisation algorithm for patients in psychiatric long-term care: a pilot study
  1. R Knauseder1,
  2. A Sonnleitner-Heglmeier2,
  3. M Jeske3,
  4. M Munz3,
  5. M Costa3,
  6. AE Weidmann4
  1. 1Leopold Franzens University, Clinical Pharmacy, Innsbruck, Austria
  2. 2Innsbruck University Hospital, Pharmacy Department, Innsbruck, Austria
  3. 3Innsbruck University Hospital, Pharmacy, Innsbruck, Austria
  4. 4Leopold Franzens University, Department Of Clinical Pharmacy, Innsbruck, Austria


Background and Importance A prioritisation algorithm for long-term psychiatric patients contributes to patient safety by identifying the individual’s risk of experiencing drug-related problems (DRPs). To date no such algorithm is applicable to long-term psychiatric care.

Aim and Objectives This pilot study aimed to develop a clinical pharmacist prioritisation algorithm for psychiatric patients in a long-term care facility.

Material and Methods This retrospective, mixed methods study was conducted in three phases. Phase I: A narrative literature review to identify a validated methodological approach that guides algorithm development. Phase II: Medication reviews for 66 long-term psychiatric inpatients were conducted by a clinical pharmacist (ASH) in a specialist care facility. Phase III: An expert panel of three clinical pharmacists (MM/MC/AEW) independently rated a statistically relevant sample size of all identified drug related problems (DRPs) and their intervention on their contribution to patient safety using the classification system by Overhage and Lukes. Based on these findings and non-parametric statistical analysis (Mann-Whitney U test, Kruskal-Wallis test), a pilot algorithm for clinical pharmacists interventions in this patient population was developed. The study received ethical approval from the Medical University Innsbruck [no. 1064/2023].

Results A total of 382 DRPs were identified across 66 patients. The most common types of DRPs were ‘drug-interaction’ (51,4%/n=196) and ‘adverse drug reaction’ (39,0%/n=149) with the most frequent interventions being ‘controlling for symptoms’ (34,6%/n=132) and ‘drug switch’ (22,6%/n=86). The five drug classes most often associated with DRPs were N05A ANTIPSYCHOTICS (36%/n=272), N06A ANTIDEPRESSANTS (14,7%/n=110), N05B ANXIOLYTICS (13,1%/n=98), N03A ANTIEPILEPTICS (5,9%/n=44) and N02A OPIOIDS (3,5%/n=26). Intervention rating was categorised as avoiding ‘significant’ or ‘major’ complications in 33,9% (n=126) and 12,4% (n=46) of cases, respectively. DRPs identified to carry the highest patient risk and included in the prioritisation algorithm were: combination of sedative agents; concomitant use of QT interval prolonging drugs; cumulative anticholinergic burden; combination of acetylsalicylic acid and valproic acid.

Conclusion and Relevance The pilot algorithm proposed in this study provides a means for clinical pharmacists to prioritise patients at greatest risk of DRPs in this unique patient population. While it is the first algorithm for this patient population, further research is needed to ensure internal and external validation.

Conflict of Interest No conflict of interest.

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