Patient experiences of prescription drug monitoring programs: a qualitative analysis from an Australian pharmaceutical helpline

Haines, Sarah; Lam, Ashley; Savic, Michael; Carter, Adrian

doi:10.1016/j.drugpo.2022.103847

Cited by 4 publications

(4 citation statements)

References 65 publications

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“…Stevenson et al [46] argued that meaningful shared decision making requires: (i) the establishment of an atmosphere in which a patient's views and opinions about their treatment are valued; (ii) treatment opinions discussed are compatible with patient values and lifestyle; (iii) information about options, risks and benefits is shared in a clear and unbiased manner; (iv) assisting patients to weigh up the benefits and risks of treatment; and (v) healthcare providers share treatment recommendations based on expertise while affirming patient preferences. In line with previous research, instances where the PDMP algorithm identified the patients' medication use as 'high risk', little room appeared to be left for shared decision making in the form of discussion with the patient around their context or understanding of their own perceived risk status [47]. In cases where consumers are already not being listened to or invited to share their perspective or knowledge, there is a risk that this may be exacerbated by the presence of a PDMP-generated alert.…”

Section: Patients To Play An Active Role In Their Own Healthcaresupporting

confidence: 66%

Opioid‐related policy changes: Experiences and perspectives from people who use opioids to manage non‐cancer chronic pain

Haines

Savic

Nielsen

et al. 2023

Drug and Alcohol Review

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IntroductionPeople who use prescription opioids to manage non‐cancer chronic pain are particularly vulnerable to opioid‐related policy change. This study aims to better understand what prescription opioids provide this population, what concerns they have in the context of new and changing opioid policies, such as the recently implemented prescription drug monitoring program in Victoria, Australia, their experiences of prescription opioid use, chronic pain and what they would like their healthcare to look like.MethodsSemi‐structured interviews were conducted with 30 people who use opioids to manage chronic non‐cancer pain.ResultsPrescription opioids played an important role in supporting quality of life and mental health. However, experiences of stigma and lack of empathy from healthcare providers were common. Participants sought accurate information about their medications and expressed a desire for shared decision‐making in healthcare.Discussion and ConclusionPrescription opioids can play an important role in pain management as well as social and psychological functioning for people living with non‐cancer chronic pain. Opioid‐related policy changes to medication availability need to consider the potential impacts that reducing, limiting or discontinuing opioids may have on this population. Including the voices of people who use prescription opioids to manage non‐cancer chronic pain in respectful, compassionate and meaningful ways.

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Section: Patients To Play An Active Role In Their Own Healthcaresupporting

confidence: 66%

Opioid‐related policy changes: Experiences and perspectives from people who use opioids to manage non‐cancer chronic pain

Haines

Savic

Nielsen

et al. 2023

Drug and Alcohol Review

Self Cite

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“…Even if these systems might not be the overall predominant method of practice (yet), empirical studies have shown that concern that these systems are leading to a worrisome shift in medical practice is legitimate. 29 As Oliva points out, 'due to state PDMP use mandates and law enforcement surveillance, clinicians (…) increasingly rely on PDMP risk scores to diagnose and treat patients. And there is little doubt that such clinical reliance will become even more pervasive' 8 (p. 109).…”

Section: Testimonial Injustice In Medicinementioning

confidence: 99%

Testimonial injustice in medical machine learning

Pozzi

2023

J Med Ethics

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Machine learning (ML) systems play an increasingly relevant role in medicine and healthcare. As their applications move ever closer to patient care and cure in clinical settings, ethical concerns about the responsibility of their use come to the fore. I analyse an aspect of responsible ML use that bears not only an ethical but also a significant epistemic dimension. I focus on ML systems’ role in mediating patient–physician relations. I thereby consider how ML systems may silence patients’ voices and relativise the credibility of their opinions, which undermines their overall credibility status without valid moral and epistemic justification. More specifically, I argue that withholding credibilitydue tohow ML systems operate can be particularly harmful to patients and, apart from adverse outcomes, qualifies as a form of testimonial injustice. I make my case for testimonial injustice in medical ML by considering ML systems currently used in the USA to predict patients’ risk of misusing opioids (automated Prediction Drug Monitoring Programmes, PDMPs for short). I argue that the locus of testimonial injustice in ML-mediated medical encounters is found in the fact that these systems are treated asmarkers of trustworthinesson which patients’ credibility is assessed. I further show how ML-based PDMPs exacerbate and further propagate social inequalities at the expense of vulnerable social groups.

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Section: Introductionmentioning

confidence: 99%

“…A perhaps unforeseen influence of PDMP use has been to facilitate practitioner communication with both other practitioners [21,22] and patients [13,23,24]. Haines et al [24] proposed that effective communication is essential when discussing prescription medicine dependence with patients. Effective communication in the health-care setting can improve patient outcomes, however, there are opportunities to improve collaboration and communication between prescribers and pharmacists [25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Health‐care practitioner use of prescription drug monitoring programs in clinical practice in Australia: A qualitative study

Hoppe

Liu

Khalil

2023

Drug and Alcohol Review

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IntroductionPrescription drug monitoring programs (PDMP) are electronic databases used by prescribers and pharmacists to monitor the use of high‐risk prescription medications subject to extramedical use. This study aimed to explore how Australian pharmacists and prescribers are using PDMPs in practice and to gain an understanding of barriers to tool use, as well as practitioner recommendations to increase tool usability and uptake.MethodsSemi‐structured interviews were conducted with pharmacists and prescribers who use a PDMP (n = 21). The interviews were audio‐recorded, transcribed and thematically analysed.ResultsThe four themes that emerged were: (i) PDMP notifications combined with practitioner clinical judgement guide PDMP usability; (ii) practitioners use PDMPs to facilitate patient and practitioner communication; (iii) workflow systems integration impacts tool usability; and (iv) optimising PDMP information and data access including practitioner‐tool engagement to improve tool uptake and usability.Discussion and ConclusionsPractitioners appreciate the value of PDMP information support for clinical decisions and patient communication. However, they also acknowledge the challenges to tool use and recommend improvements including enhanced workflow, systems integration, optimisation of tool information and national data sharing. Practitioners provide an important perspective on PDMP use in clinical practice. The findings can be drawn on by PDMP administrators to improve tool usefulness. Consequently, this may lead to an increase in practitioner PDMP use and optimise the delivery of quality patient care.

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Patient experiences of prescription drug monitoring programs: a qualitative analysis from an Australian pharmaceutical helpline

Cited by 4 publications

References 65 publications

Opioid‐related policy changes: Experiences and perspectives from people who use opioids to manage non‐cancer chronic pain

Opioid‐related policy changes: Experiences and perspectives from people who use opioids to manage non‐cancer chronic pain

Testimonial injustice in medical machine learning

Health‐care practitioner use of prescription drug monitoring programs in clinical practice in Australia: A qualitative study

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