Abstract
Background
Addiction and overdose death associated with high-risk prescription medications such as benzodiazepines and opioids, are significant global issues. Prescription Drug Monitoring Programs (PDMP), which allow healthcare providers to track and monitor patients’ high-risk medication history have been implemented widely throughout North America and recently in Victoria, Australia. Australia’s PDMP uses a red alert notification to notify healthcare providers to patients at ‘high risk’ of medication related harm. Very little is known about healthcare providers beliefs about the meaning of these notifications and what impact these meanings have on the clinical encounter and patient outcome.
Methods
Twenty-nine interviews with Victorian healthcare providers (15 prescribers and 14 pharmacists) were thematically analyzed.
Results
Red alerts were understood as being both synonymous with addiction, as well as a single data point with further investigation required to draw conclusion from. The red alert both disrupted and exposed underlying addiction stigma. Healthcare providers assumptions about patient’s readiness to change influenced their decision to discuss the red alert with patients.
Conclusions
How healthcare providers make sense of and response to PMDP generated red alerts can impact upon the clinical encounter, including clinical decision-making and the care that patients receive. By identifying and understanding the social factors and forces driving beliefs, attitudes and behaviors toward people who use addictive prescription medications, healthcare providers may be able to pause, assess and reflect on how these factors shape their decision making in unhelpful or unethical ways.
Introduction
The rising rates of death and addiction associated with controlled substance medications, such as opioids and benzodiazepines, is an issue of global concern (Murray et al. Citation2020; Vos et al. Citation2020; Jayawardana et al. Citation2021). One widespread policy response to reduce these harms has been the implementation of clinically focused, electronic prescription drug monitoring programs (PDMP; Holmgren et al. Citation2020). PDMP are electronic databases that monitor and track a patients’ prescribed medication history (Wilson et al. Citation2019). Although the specifics of PDMP vary widely according to the jurisdiction, many PDMP use an algorithm to classify patient risk status, typically identified by a ‘high dose’ threshold (e.g. daily dose exceeds 100 mg morphine equivalent, risky medication combinations (e.g. opioid and benzodiazepine) or patients attending multiple providers (a practice pejoratively known as ‘doctor shopping’; Paulozzi et al. Citation2011; Deloitte Citation2018). Despite being mandatory in many jurisdictions, research findings on the effectiveness of PDMPs in reducing opioid addiction at a population level is unclear (Fink et al. Citation2018; Alogaili et al. Citation2020; Picco et al. Citation2021; Haines et al. Citation2022a).
PDMP are designed to encourage healthcare provider to reassess their decision to supply medication or to coordinate care to reduce the risk of overdose or dependence (Alogaili et al. Citation2020). PDMP have been touted as a tool to facilitate important conversations between healthcare providers and patients in the context of prescription medication related harms (Deloitte Citation2018). However, research has found that healthcare providers do not always seize this opportunity or may discriminate unfairly against those identified as high risk by a PDMP (Picco et al. Citation2021). This may include treatment refusal, abrupt medication discontinuation and unpleasant clinical interactions (Islam and McRae Citation2014; Fink et al. Citation2018; Haines et al. Citation2022a). Addiction stigma plays an important role in the way PDMP are implemented by healthcare providers in harmful or inappropriate ways (Cicero and Ellis Citation2017; Antoniou et al. Citation2019; Holmgren et al. Citation2020). For example, PDMP have been described by some healthcare providers as a means to ‘purge’ their practices of ‘deceptive’ or ‘bad’ patients who they believe are addicted to or ‘misusing’ their medication (Allen et al. Citation2020).
In March 2020, the state of Victoria, Australia implemented its first, mandatory use PDMP. Victoria’s PDMP uses a traffic light algorithm (green, amber, or red alert) to indicate potential risk. The pop-up red alert is accompanied by a message that informs the healthcare provider that a substantial risk of harm exists, to counsel the patient on the risks, and to reassess the need for the dose or prescription (Department of Health Citation2019). It is unclear how this ‘red alert’ is interpreted by healthcare providers, namely as a warning, problem, or threat. Technology design is not passive, but closely related to the values of those who designed it and for whom it is designed for (Lockton et al. Citation2008). The assumption that PDMP technologies will have a singular and predictable effect in any given context, fails to consider the complex real-world factors (e.g. clinicians, health systems, existing practices, norms) that may result in unanticipated applications and outcomes (Rhodes et al. Citation2016). It is therefore important to examine how PDMP technology is understood, used and implemented, in clinical practice.
There has been little research exploring healthcare providers’ perspectives, experiences and responses to Victoria’s newly implemented PDMP. This paper aims to address this gap through a qualitative analysis of healthcare provider accounts of red alerts generated by the PDMP. Specifically, we address the following research questions: (1) How do healthcare providers interpret red alerts? And (2) What impacts do red alerts have on healthcare providers’ clinical practice and engagement with patients?
Method
We conducted a qualitative study of healthcare providers in Victoria, Australia. A qualitative study design was utilized to enable rich and detailed insights about PDMP that is sensitive to the complexities and heterogeneity of clinical policy implementation (Crouch and McKenzie Citation2006).
Participants
Twenty-nine participants (15 prescribers and 14 pharmacists) who used the PDMP in their clinical practice were recruited through publicly available online databases of doctors and pharmacists in Victoria (n = 20), personal and academic networks (n = 5), and snowball sampling (n = 4). Participant information and demographics are presented in .
Table 1. Participant information and demographics.
Data collection and analysis
Semi-structured interviews were conducted from March to August 2020 (SH). Questions were open ended, informed by the authors critical review of the literature (Haines et al. Citation2022a). Questions focused on how healthcare providers understood the PDMP red alert and what impact this understanding had on the clinical encounter (e.g. ‘What is the first thing that comes to mind when you see a red alert?’ ‘Can you tell me about a time a patient had a red alert? How did it make you feel?’ ‘What does it mean for you when a patient receives a red alert?’). These questions sought to reveal subtle phenomena within the clinical encounter – not just what was said or done, but why, and what underlying thoughts or emotions prompted healthcare providers response to the red alert. Interviews were conducted online via Zoom (20) or via telephone (9) based on participant preference, audio-recorded and transcribed verbatim. Interviews ranged from 0.5-1.5 h in duration, with a medium length of 1 hr. The length of interview appeared to differ based on individual difference alone, e.g. how much time or interest the participant had, or how naturally talkative they were. Transcripts were coded using NVivo 12 Plus coding software, and adopted an inductive thematic analyze approach (Braun and Clarke Citation2006; QSR International Citation2020).
To enhance rigor, generate nuanced interpretation of data, and avoid any overly subjected or distorted views or interpretations of the data by any one researcher (Carter et al. Citation2014), all three authors were collectively engaged in the coding of transcripts, generating of themes and discussion of data interpretations until consensus was reached. Pseudonyms were used to maintain participant privacy. The study was approved by the Monash University Human Research Ethics Committee (Project number:21128).
Results
Three key themes were identified. (1) Meaning of the red alert: Just one data point or synonymous with addiction? (2) Red alert both disrupts and exposes underlying prejudice, (3) Factors influencing discussion of red alert.
Meaning of the red alert: Just one data point or synonymous with addiction?
Participants appeared to understand the red alert in two distinct and at times contradictory ways. The red alert was either understood as simply one data point amongst many that provided information about a patient’s medication history. Or, the red alert appeared to be understood as being synonymous with addiction. Participants reactions to the red alert tended to differ based on these meanings.
‘Just one data point’
Participants who understood the red alert as a single data point believed this was due to their inability to reach a conclusion about the patient without more information. They felt that any assumption of addiction was premature as the PDMP algorithm was unable to consider higher level factors, like diagnosis, medication type, treatment type or patient context. For example: ‘The traffic-light system is completely automated. There’s no doctor on the other end making the clinical judgment. That’s still on us’ (Susan, GP); ‘[The PDMP alert] is only as useful as the clinician interpreting it’ (Ira, Psychiatrist); This stance was expressed strongly in relation to questions around the influence that a red alert may have had on clinical decision making.
These participants tended to have experience working with patients engaged in drug treatment programs. These patients were more likely to trigger a red alert due to being on a high methadone dose or by engaging with and receiving scripts from multiple services, such as addiction specialist and psychiatrists. When recalling these patients, participants described the red alert as a helpful reminder to make sure healthcare was being co-ordinated between medical teams, and to offer harm reduction medications, such a naloxone (an opioid antagonist that is used to arrest opioid overdose). For example: ‘Just about every single methadone consumer raises a red alert because of their dose of morphine equivalent is above 100 milligrams. It’s a good reminder to check they have Naloxone too’ (Will, Pharmacist).
Synonymous with addiction
For some participants, the presence of a red flag was understood as being synonymous with addiction. For these participants, the red flag elicited strong embodied and emotionally charged responses. For example: ‘my instinct when I see a patient has a red alert is for my stomach to drop’ (Ravi, GP), ‘your chest kinda tightens’ (Paula, GP); ‘your eyes widen, and you take a big breath’ (Helen, GP); ‘you feel sick and think ‘oh no’’ (Suki, GP); ‘your heart can start to race’ (Amanda, GP). These responses typically came from GPs who were either unfamiliar with the patient, felt uncomfortable discussing their concerns about drug dependence, or were concerned about how the patient might respond. For example: ‘I would get that awful gut feeling because then I worried that I’m going to have a conversation that’s going to lead to me feeling unsafe or an aggressive patient’ (Suki, GP).
When explicitly asked if these self-reported emotional responses influenced decision making, the response was ubiquitously that it did not: ‘oh, of course not, you’re still a professional’ (Ira, psychiatrist); ‘whether you should prescribe an opiate or not should definitely not be based on your mood, or your personal feeling toward the patient’ (Ravi, GP).
Previous negative experiences working with patients experiencing addiction was a reason for caution and distrust from participants. For example: ‘these people have lied to me before’ (Helen, GP), ‘people get really angry… when they don’t get what they came for’ (Ravi, GP) ‘my colleague had a patient who overdosed 10 years ago and she still feels guilty, so I’m very cautious’ (Amanda, GP).
When the red flag was unexpected or surprising to participants, they were more likely to have a strong emotional response that affected them personally. These participants described feelings of ‘betrayal’, being ‘used’, ‘hurt’, ‘disappointed’ and even experiencing a sense of injustice: ‘You just feel used because they don’t really want your medical care, they just want your script… That’s so unfair’ (Susan, GP); ‘they’ve lied to me about it, it can feel like a bit of a betrayal -as a clinician it can hurt a little bit (Ira, psychiatrist). Such responses also had negative implications for the therapeutic alliance, particularly regarding an erosion of trust. For example, ‘If you were comfortably prescribing opioids to them before, this situation really dissolves that comfort (Helen, GP); ‘there’s no more trust, they’ve gone and lied so how can you just try them again? You can’t’ (Ravi, GP)
Red alert both disrupts and exposes underlying prejudice
The red alert allowed participants to challenge their underlying prejudiced assumptions about patients, and in doing so highlighted the very presence of entrenched addiction stigma.
In situations where a patient presented in ways that made the participant suspicious of extramedical drug seeking, the ability to check the PDMP helped to overcome this prejudiced assumption. For example: ‘sometimes you go ‘oh man, this person looks dodgy’ so you check the PDMP and go, oh it’s actually okay’ (Alison, Pharmacist).’; ‘I think PDMP takes away that tendency toward bias that practitioners have around who is abusing drugs and who’s not’ (Liam, GP).
Interestingly, there was a common acknowledgement that prejudice toward people who are dependent on drugs is ‘only natural’ and that participants (or any doctor) could easily make assumptions based on negative stereotypes without the ‘objective’ PDMP data to challenge this underlying bias. For example: ‘I think what’s really hard is to actually build that trust with someone that you already have this inherent mistrust for when they come in. Obviously - I think every doctor’s walls go up when the patient says ‘oh I'm here for Endone’ (Chris, GP); ‘I’m not making my call based on… not just ‘I don’t trust you’ or ‘I don’t believe you’. The facts are in front of me. [The PDMP] takes it away from being a personal judgment’ (Bridget, GP).
By citing PDMP as an effective tool for reducing underlying prejudice, it was made clear that underlying prejudice was present for many participants. This was evident in not only language used (e.g. ‘aberrant drug user’, ‘real drug addict’) but also by positioning the PDMP as an arbiter of truth. In instances where when the patient’s explanation and account of their medication use did not correspond with the healthcare providers interpretation of the PDMP (i.e. that the red flag should be interpreted as a high-risk of dependence), then the patient was seen to be lying. For example: ‘[The PDMP] is powerful in the sense that it – it shines a light and reveals the truth. [Patients] kinda can’t lie anymore’ (Nina, Pharmacist).
Factors influencing discussion of red alert
The presence of a red alert was only discussed if the participant was either familiar with and trusted the patient. For example: ‘I knew the patient, and I trusted the patient. So I said ‘look, you’re actually getting a red alert which means that there’s some patterns of unsafe opioid use here’ (Reshma, GP); ‘if it’s just someone who walks off the street…I wouldn’t discuss drug dependence with them’ (Margret, Pharmacist). However, if there was a lack of trust and the participant believed the patient was ‘intentionally’ being an ‘aberrant’ or ‘real drug addict’ (i.e. that dependence had not occurred through mismanagement of pain, but through intentional drug seeking for extramedical use), then participant concerns raised by the presence of the red flag were not discussed with the patient. For example, ‘there is a major difference between someone that accidently becomes addicted and a real drug addict that doctor shops as a full-time job’ (Bridget, GP); ‘I don’t feel as much sympathy for patients that kinda did this [developed dependence] to themselves, I know that sounds bad’ (Tracey, Pharmacist). The stigmatizing nature of the language used by participants contained unhelpful notions of individual responsibility and moral judgment about the patient and how much the clinician believed that they deserve treatment.
Additionally, sharing concerns about the presence of dependence appeared to hinge heavily on the perception of the patient’s willingness to change (i.e. receive addiction treatment), making the patient responsible for initiating discussion about their extramedical use of medications, that often included some mea culpa and a desire to change. In some instances, this sense of the patients responsibility was explicit: ‘I'm happy to help, but if they don’t reach out then they’re probably not ready to’ (Xiao, GP); ‘the reality is that it really comes down to patient motivation and commitment…there’s no point [raising concerns about dependence] if they don’t want to hear it’ (John, Psychiatrist). In other instances, participants felt that the presence of the red alert alone meant that the patient implicitly understood the concern about dependence and that they did not need to explicitly discuss it. For example, ‘they know why they have a red alert, no need to really talk it over’ (Cheng, Pharmacist).
Discussion
This study provides an exploration of how healthcare providers understand and respond to PDMP generated red alerts, including factors that influence the interpretations and communication of worrisome data to patients, and the impact that the red alert has on their attitudes toward and engagement with patients, and their clinical decisions. The findings can be used by policy makers to broaden insight into how PDMP are implemented into practice and by clinicians to reflect on their own experiences and practice in the use of PDMP.
Emotional responses to PDMP alerts and unconscious bias
The findings from this study indicate that PDMP generated alerts can elicit strong emotional moral responses, characterized by visceral reactions, in healthcare providers. Visceral reactions (e.g. racing heart, chest tightening) as described by the participants, are instinctive automatic responses that are often accompanied by uncomfortable physical sensations (e.g. changes in heart rate, breathing, gastrointestinal mobility) and emotions (e.g. worry, fear) and are well understood as the body’s natural response to a perceived threat (James Citation1994). Participants who had less experience or negative prior experiences with people who used opioids extramedically appeared to be more strongly influenced by this physiological or emotional response to the red alert. The use of prior experience as a source of knowledge production and attitude formation in the context of engaging with patients experiencing dependence is well established in the literature (Crowley-Matoka and True Citation2012; Van Boekel Citation2013). Healthcare providers who believe they have been ‘burnt’ by patients seeking opioids in the past are more likely to distrust patients seeking (or assumed to be seeking) opioids in the future (Baldacchino et al. Citation2010). The findings from this study suggest that at least some participants understood the red alert as being associated or synonymous with risky or inappropriate drug use. Interestingly, participants were clear in their belief that their emotional response did not influence their behavior or clinical decision making - a claim that was discordant with follow up responses that suggested their emotional response did influence their feelings toward the patient or associated prescribing (e.g. ‘you can’t trust them anymore’).
This stance is consistent with the training and guidelines provided to healthcare providers that emphasizes the importance of not allowing the red alert to dictate clinical decision making or to make snap judgements about a patient’s drug dependence status (Deloitte Citation2018). It is also inline with research that has found healthcare providers may percieve PDMP use as an erosion of their decision making autnomy, and therefore resist overvaluing any automated output, such as a red flag, that it offers (Blum et al. Citation2016). Additonally, there is a strong cultural and professional expectation for healthcare providers to present as unbiased and nondiscriminatory, which may have influenced these responses.
Although the red alert was conceptualized by some participants as a tool to reduce underlying negative assumptions about patients, it also appeared to trigger and reveal unconscious bias as well - especially for those who associated the red alert with extramedical drug use. In healthcare, unconscious bias is the involuntary association between two things that unknowing alters perception, and influences behavior and decision making (FitzGerald and Hurst Citation2017). Unconscious bias in clinical contexts is most likely to be activated under conditions where cognitive resources are challenged, such as time pressure, complex patient presentations or fatigue – common occurrences for healthcare providers (Burgess et al. Citation2006; Teal et al. Citation2012). Most people, including healthcare professionals significantly underestimate the influence unconscious bias has on their perceptions, interactions and decision making (Teal et al. Citation2012). The very fact that all participants denied any influence of the red alert on decision making, and yet reported strong physiological responses and emotive reactions supports the lack of conscious insight healthcare providers have about the impact of the red alert on their thinking and decision-making.
PMDP data should not overshadow patient accounts
This study found that PDMP were perceived by participants to reduce bias and improve ‘objectivity’ by offering reliable, accurate and unbiased information about a patient’s medication history. This is consistent with previous research on the topic (Leichtling et al. Citation2017; Radomski et al. Citation2018). However, by positioning PDMP data as honest and reliable, patient accounts and experiences became unreliable, untrustworthy or unnecessary. Devaluing patient narratives has been shown to be damaging to the therapeutic alliance, particularly when patients feel that the PDMP has been given more weight than their own reporting (Antoniou et al. Citation2019). Discounting the patient narrative not only impacts the therapeutic alliance but can also lead to inaccurate risk assessment. A similar, algorithm based opioid risk assessment tool in the United States was found to have a false-positive rate of 17.2% and a false-negative rate of 13.4% (Cochran et al. Citation2021). Consequently, approximately one in five patients were inaccurately categorized as high risk by the algorithm.
Participants acknowledged that prejudice and discrimination based on stereotypes were common when working with this population and felt that the PDMP was a useful way to ensure that they did not misjudge patients. However, in cases where the red alert was completely unexpected (e.g. unbeknownst to them the patient had been obtaining prescriptions from multiple providers), participants felt that they had been ‘used’, ‘cheated on’ or ‘betrayed’ by the patient. This over personalization of patients’ behavior suggests an underlying belief that the behavior is somehow malicious, duplicitous, or in the case of addiction, a moral choice. However, there are many reasons that patients may not provide full disclosure to their provider or be using medications extramedically, including coping with psychosocial stressors (Wilson et al. Citation2020), previous negative experiences with healthcare providers, including not being believed (Haines et al. Citation2022b), tolerance to dose or the development of dependence and withdrawal (Pergolizzi et al. Citation2020), or the inability to obtain adequate pain relief (Baker et al. Citation2021). These possibilities highlight the importance of the patient’s context, perspectives and experiences to clinical judgment that are not adequately captured in simplistic alerts.
It is imperative that healthcare providers do not personalize the presence of a PDMP generated red alert, even if it reveals that a patient had not been completely honest or forthcoming. It is worth noting that fear of supplying medications due to previous negative experiences where supply resulted in patient harm, such as overdose, as reported by one participant in this study, or safety concerns due to previous experience with aggressive patients, are very reasonable responses. Healthcare providers have a right to feel safe in their workplace, and it is the responsibility of the workplace to ensure measures are in place to avoid incidences of violence to staff, (e.g. a minimum of two staff on site). However, it should be noted that patients also report fear of not gaining access to needed medications, and fear of judgment or punitive action from healthcare providers when seeking treatment for drug dependence, or harm reduction measures such as a prescription for opioid antagonist, naloxone (Green et al. Citation2017; Haines et al. Citation2022b). Given the uneven distribution of power between healthcare providers and patients, it is important to ensure that healthcare provider concerns are not privileged over patient concerns. Previous research has found that for some patients were hopeful that red alert would communicate to their provider on their behalf that they had been struggling with dependence, something they were not comfortable disclosing directly (Haines et al. Citation2022b). In this way, it is important that PDMP generated red alerts are not seen as a way to ‘catch criminals’ (Fendrich et al. Citation2018) or avoid engaging with potentially high-risk patients, but are more helpfully conceptualized as an informative piece of information that can facilitate harm reduction conversations, without emotional reactivity or judgment.
Discussion of red alerts regardless of perception of patient readiness to change
In previous research, PDMP helped healthcare providers to initiate conversations around this concern, and facilitate opportunities for education around dependence, controlled substances and pain management (Smith et al. Citation2007; Leichtling et al. Citation2017). However, the findings from this study suggest that familiarity and trust in the patient, as well as perception of patients’ readiness to change may be precipitating factors for the initiation of these conversations. This is consistent with previous research that found prescribers kept PDMP data ‘secret’ from patients they did not trust or believed may be drug seeking for extramedical use (Hildebran et al. Citation2016). This is problematic. Guidelines aimed at reducing opioid related harm recommend that healthcare providers check PDMP databases as well as educate patients about opioid risks, including the potential for dependence (Dowell et al. Citation2016). Regardless of PDMP alert, consistent screening of any patient prescribed controlled substances can help to prevent opioid related harm through the identification of early warning signs. Trust is widely recognized as a ‘critical ingredient’ for good doctor-patient relationships and improved patient outcomes (Buchman et al. Citation2016). However, if healthcare providers consider it a prerequisite to be able to share their concerns in the context of a PDMP red alert, then this will likely lead to missed opportunities to avoid patient harm (Picco et al. Citation2021).
This study found that healthcare providers perceived etiology of dependence (i.e. whether its development was ‘accidental’ or ‘intentional’) played an important role in healthcare providers attitude toward patients who had received red alerts. This finding is consistent with stigma research showing that causal attribution beliefs (e.g. the perception of a person’s ability to control their illness), is strongly correlated with negative attitudes and low tolerance toward the person experiencing the illness (Weiner et al. Citation1988; Corrigan, Citation2000; Corrigan et al. Citation2006; Creswell Citation2014).
Drawing on concepts from the behavior change literature (Prochaska and DiClemente, Citation1983), participants in this study evoked ideas of patient motivation and ‘readiness to change’ when explaining why they may not raise their concern about dependence with patients. However, it is impossible to accurately assess ‘readiness to change’ without engaging patients in conversation. If a patient is in a pre/contemplative stage of change (e.g. unaware, in denial, ambivalent or conflicted about the problem) then this conversation might help to build insight for the patient through awareness of the risks of medication use as well as possible alternatives (Prochaska and DiClemente Citation1983). The focus on patient motivation and readiness to change fails to understand both the mechanisms of drug dependence and use and the normality of relapse in treatment. Either way, this approach positions the patients as being responsible for initiating conversation about risk, despite the healthcare provider being the one who has access to the PDMP which alerts them to potential risk. Arguably, a patient has a right to know if the PDMP considers their medication use risky, regardless of what they will do with that information.
Further, this study also found that healthcare providers may be conflating the discussion of the red alert with their patients with insinuating that they are addicted to their medication. The presence of a red alert does not necessarily indicate drug dependence (Deloitte Citation2018). Initiating conversations about what a red alert may be indicating is not the same as diagnosing a patient with dependence or engaging a patient in treatment for drug dependence, where motivation and readiness to change would perhaps be more pertinent considerations.
Limitations
Although no clear or consistent differences in belief or attitudes were found between pharmacists and or prescribing doctors in this study, future work might consider a more systematic comparison to garner discipline specific insights. This would include the use of close ended questions or quantitative surveys based that are well suited to capture between group differences.
Conclusion
This study highlights the importance of exploring how an intervention emerges when it is implemented in clinical practice (Rhodes et al. Citation2016). Various factors may influence what an intervention like PDMP does or can do when it is implemented in complex and often messy ‘real world’ implementation contexts. Our findings suggest that how healthcare providers make sense of and response to PMDP generated red alerts can impact upon the clinical encounter, their clinical decision-making, and the care that patients receive. Future research on the effectiveness of PDMP might benefit from attending more closely to the complex array of factors that may influence experiences and impacts of PDMP in different contexts. Similarly, by identifying and understanding the social factors and forces driving beliefs, attitudes and behaviors toward people who use addictive prescription medications, healthcare providers may be able to pause, assess and reflect on how these factors shape their decision making in unhelpful or unethical ways. Our findings suggest that how healthcare providers make sense of and response to PMDP generated red alerts can impact upon the clinical encounter, their clinical decision-making, and the care that patients receive. By identifying and understanding the social factors and forces driving beliefs, attitudes and behaviors toward people who use addictive prescription medications, healthcare providers may be able to pause, assess and reflect on how these factors shape their decision making in unhelpful or unethical ways.
Ethics statement
This study was approved by the Monash University Human Research Ethics Committee (Project number:21128). Informed consent was obtained from all participants.
Disclosure statement
No potential conflict of interest was reported by the authors.
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