Barriers and enablers towards benzodiazepine-receptor agonists deprescribing in nursing homes: A qualitative study of stakeholder groups

Evrard, Perrine; Damiaens, Amber; Patey, Andrea M.; Grimshaw, Jeremy; Spinewine, Anne

doi:10.1016/j.rcsop.2023.100258

Cited by 2 publications

(1 citation statement)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…5 The decision to consider and suggest stopping or withdrawing medication to the patient, poses a particularly challenging judgement for a clinician. 6,7 Clinicians need to take into consideration a multitude of factors, including the patient, the medication and the process itself. There are a number of tools available or being developed to aid in the deprescribing process.…”

Section: Introductionmentioning

confidence: 99%

Clinical decision‐making in benzodiazepine deprescribing by healthcare providers vs. AI‐assisted approach

Bužančić,

Belec,

Držaić

et al. 2023

Brit J Clinical Pharma

View full text Add to dashboard Cite

AimThe aim of this study was to compare the clinical decision‐making for benzodiazepine deprescribing between a healthcare provider (HCP) and an artificial intelligence (AI) chatbot GPT4‐ (ChatGPT‐4).MethodsWe analysed real‐world data from a Croatian cohort of community‐dwelling benzodiazepine patients (n=154) within the EuroAgeism H2020 ESR 7 project. HCPs evaluated the data using pre‐established deprescribing criteria to assess benzodiazepine discontinuation potential. The research team devised and tested AI prompts to ensure consistency with HCP judgments. An independent researcher employed ChatGPT‐4 with predetermined prompts to simulate clinical decisions for each patient case. Data derived from human‐HCP and ChatGPT‐4 decisions were compared for agreement rates and Cohen’s kappa.ResultsBoth HPC and ChatGPT identified patients for benzodiazepine deprescribing (96.1% and 89.6%, respectively), showing an agreement rate of 95% (κ=0.200, p=0.012). Agreement on four deprescribing criteria ranged from 74.7% to 91.3% (lack of indication κ= 0.352, p<0.001; prolonged use κ=0.088, p=0.280; safety concerns κ=0.123, p=0.006; incorrect dosage κ=0.264, p=0.001). Important limitations of GPT‐4 responses were identified, including 22.1% ambiguous outputs, generic answers, and inaccuracies, posing inappropriate decision‐making risks.ConclusionWhile AI‐HCP agreement is substantial, sole AI reliance poses a risk for unsuitable clinical decision‐making. This study's findings reveal both strengths and areas for enhancement of ChatGPT‐4 in the deprescribing recommendations within a real‐world sample. Our study underscores the need for additional research on chatbot functionality in patient therapy decision‐making, further fostering the advancement of AI for optimal performance.

show abstract

Section: Introductionmentioning

confidence: 99%

Clinical decision‐making in benzodiazepine deprescribing by healthcare providers vs. AI‐assisted approach

Bužančić,

Belec,

Držaić

et al. 2023

Brit J Clinical Pharma

View full text Add to dashboard Cite

show abstract

Relationship between facility number of clinicians and prescribing intensity of psychotropic medications, opioids, and antibiotics in ambulatory practice

Kim,

Strominger,

Zivin

et al. 2024

BMC Health Serv Res

View full text Add to dashboard Cite

Background Promoting appropriate pharmacotherapy requires understanding the factors that influence how clinicians prescribe medications. While prior work has focused on patient and clinician factors, features of the organizational setting have received less attention, though identifying sources of variation in prescribing may help identify opportunities to improve patient safety and outcomes. Objective To evaluate the relationship between the number of clinicians who prescribe medications in a facility and facility prescribing intensity of six individual medication classes by clinician specialty: benzodiazepines, antipsychotics, antiepileptics, and antidepressants by psychiatrists and antibiotics, opioids, antiepileptics, and antidepressants by primary care clinicians (PCPs). Design We used 2017 Veterans Health Administration (VHA) administrative data. Subjects We included patient-clinician dyads of older patients (> 55 years) with an outpatient encounter with a clinician in 2017. Patient-clinician data from 140 VHA facilities were included (n = 13,347,658). Analysis was repeated for years 2014 to 2016. Main measures For each medication, facility prescribing intensity measures were calculated as clinician prescribing intensity averaged over all clinicians at each facility. Clinician prescribing intensity measures included percentage of each clinician’s patients prescribed the medication and mean number of days supply per patient among all patients of each clinician. Key results As the number of prescribing clinicians in a facility increased, the intensity of prescribing decreased. Every increase of 10 facility clinicians was associated with a significant decline in prescribing intensity for both specialties for different medication classes: for psychiatrists, declines ranged from 6 to 11%, and for PCPs, from 2 to 3%. The pattern of more clinicians less prescribing was significant across all years. Conclusion Future work should explore the mechanisms that link the number of facility clinicians with prescribing intensity for benzodiazepines, antipsychotics, antiepileptics, antidepressants, antibiotics, and opioids. Facilities with fewer clinicians may need additional resources to avoid unwanted prescribing of potentially harmful or unnecessary medications.

show abstract

Barriers and enablers towards benzodiazepine-receptor agonists deprescribing in nursing homes: A qualitative study of stakeholder groups

Cited by 2 publications

References 44 publications

Clinical decision‐making in benzodiazepine deprescribing by healthcare providers vs. AI‐assisted approach

Clinical decision‐making in benzodiazepine deprescribing by healthcare providers vs. AI‐assisted approach

Relationship between facility number of clinicians and prescribing intensity of psychotropic medications, opioids, and antibiotics in ambulatory practice

Contact Info

Product

Resources

About