Developing a novel pharmaceutical patient prioritization model for inpatient mental health services using a modified-Delphi technique: Early insights

Introduction:
Patient prioritization approaches are effective strategies in mitigating limited healthcare funding and staff shortages. In pharmacy, such approaches were reported to improve patient safety and pharmacy service delivery.1 Our recent multi-method study identified several prioritization approaches used within UK mental health organizations,2 most of which were simplistic in design and developed internally based on expertise. Hence, this study aimed to target a priority research area, recommended by the World Health Organisation,3 by systematically developing a comprehensive evidence-based patient prioritization model for mental health pharmacy team members.

Methods:
Two sequential Delphi studies were conducted: the first sought agreement on what risk indicators to include in the model and how to categorize them, whereas the second aimed to obtain agreement the use of the model and is currently underway. The research team was assisted by five stakeholders to prepare both Delphi questionnaires.

The first Delphi questionnaire included risk indicators for medication-related problems and ranking systems identified from a systematic review of the literature4 and our multi-method study4 and was shared with purposively selected experts. First-round responses were analyzed and shared with participants to complete the second round. The Delphi Likert scale ranged from 1 to 7 (1 = extremely low-risk/importance, 7 = extremely high-risk/importance). Consensus was defined as agreement of ≥85% for both inclusion and risk categorization.

The results from the first Delphi and information from the multi-method study4 were used to prepare a draft patient prioritization model. The second Delphi questionnaire included statements about the use, application, scope, and content of the draft model. Quantitative results were descriptively analyzed using Microsoft Excel and open-ended questions were thematically analyzed. Ethical approval was obtained from the University of Manchester Research Ethics Committee (No. 16447).

Results:
Forty-two experts agreed to participate in the first Delphi questionnaire with 36 (85.7%) completing the first round and 29 (69%) completing the second round. Experts included psychiatrists, academics, and pharmacists (experience 3–20 years). From 109 risk indicators included in the first Delphi, there was an agreement to include 47 risk indicators in round 1. Additionally, 14 risk indicators were added, and 8 were modified based on panel members' suggestion. In round 2, panel members agreed on 82 risk indicators to be included in the final model including high-risk medicines, drug-related factors (e.g., polypharmacy), and patient-related factors (e.g., renal impairment). These 82 risk indicators were used to develop the patient prioritization model using a traffic light system (red, amber, and green).

Conclusion:
This study has developed a novel, evidence-based patient prioritization model for use by mental health pharmacy teams in the United Kingdom. Implementation of this model within mental health hospital pharmacy might improve service efficiency and safety of patient care.

REFERENCES
Abuzour A, Hoad-Reddick G, Shahid M, Steinke D, et al. Patient prioritisation for hospital pharmacy services: current approaches in the UK. Eur J Hosp Pharm. 2021;28(Suppl 2):e102–e108. doi: 10.1136/ejhpharm-2020-002365.
Alshaikhmubarak F, Keers R, Brown P, Lewis P. Exploring current patient prioritisation approaches used by UK mental health inpatient pharmacy teams. Int J Pharm Pract. 2023;31(Suppl 2):ii5. doi: 10.1093/ijpp/riad074.005
Sheikh A, Rudan I, Cresswell K, Dhingra-Kumar N, et al. World Health Organization's Management Team on Research Priorities for Medication Safety. Agreeing on global research priorities for medication safety: an international prioritisation exercise. J Glob Health. 2019;9(1):010422. doi: 10.7189/jogh.09.010422
Alshaikhmubarak FQ, Keers RN, Lewis PJ. Potential risk factors of drug-related problems in hospital-based mental health units: a systematic review. Drug Saf. 2023;46(1):19–37.