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Moncur, Megan

Mayo Clinic

United States Food and Drug Administration

Citations 3

Exploring Opioid Prescriber Decision‐Making: A Qualitative Study
Smith, Jamie L., Jeffery, Molly M., Egginton, Jason S. , Adams, Kim, Oloyede, Sey V. , McCoy, Jessica, Yost, Kathleen J. , Coleman, Blair, Eggers, Sara, Shaw, Katherine Hyatt Hawkins, Moncur, Megan, Hooten, W. Michael, McCoy, Jessica J, Ridgeway, Jennifer L , Jeffery, Molly Moore , Coleman, Blair , Eggers, Sara L. , Hawkins, Katherine Hyatt, Moncur, Megan, Hooten, W. Michael , Ridgeway, Jennifer L.

Pharmacoepidemiology and Drug Safety | May 29, 2026 | Volume: 35 | Issue: 6 | Pages: No page available

10.1002/pds.70402 Get It

ABSTRACT Purpose To explore the opioid decision‐making process of prescribers in primary care, surgery, and subspecialty pain management. Methods This was a multistage qualitative‐qualitative study with clinicians involved in opioid prescribing and management from a single healthcare organization with locations in Minnesota, Florida, Arizona, and Wisconsin. Clinicians in this study included physicians, nurse practitioners (NPs), and physician assistants (PAs) practicing in primary care, surgery, or pain medicine. The interview guide was organized in three domains of a conceptual model for opioid use: (1) prescriber characteristics, (2) patient characteristics, and (3) practice environment characteristics. Individual interviews ( N = 20) were performed first, and data were summarized using a rapid template‐based approach. Subsequently, focus groups (FGs) ( N = 4) were conducted with an additional 21 clinicians to confirm and explore interview results. Data from interviews and FGs were analyzed using a common codebook. Results Findings were organized as decision factors into the three domains. Factors in the prescriber domain included characteristics such as formal pain management training, as well as factors that influenced knowledge and beliefs (e.g., advice from or observation of supervising clinicians and expert colleagues). Decision factors in the patient domain included patient pain etiology, comorbid medical or mental health conditions, and demographic characteristics. Clinicians' perceptions of these factors, such as viewing older age as having lesser risk for opioid misuse, influenced prescribing decisions. Clinicians also described challenges associated with “legacy patients” whose therapy was previously managed by a different clinician. Primary care clinicians, in particular, expressed difficulties managing post‐surgical or trauma‐related pain after care transition. Relevant decision factors reported by prescribers in the practice environment domain included guidelines and practice oversight. Most participants reported practicing in an environment that promoted conservative opioid use and having access to standardized institutional guidelines that reduced perceived decision‐making burden. Clinicians described how they used prescribing guidelines to help them communicate with patients about opioid use and prescribing decisions. Conclusions Intersecting prescriber, patient, and practice environment factors shape opioid analgesic prescribing decisions. Available resources in the practice environment, including peer input and institutional guidelines, may support clinician decision‐making and conversations with patients at the point of care, including in cases where patients have complex histories or personal characteristics that influence decision making.
Acute pain pathways: protocol for a prospective cohort study
Jeffery, Molly M. , Ahadpour, Mitra , Allen, Summer V. , Araojo, Richardae , Bellolio, Fernanda , Chang, Nancy, Ciaccio, Laura , Emanuel, Lindsay, Fillmore, Jonathan J., Gilbert, Gregg H. , Koussis, Patricia, Lee, Christine , Lipkind, Heather S. , Mallama, Celeste A. , Meyer, Tamra E. , Moncur, Megan, Nuckols, Teryl K. , Pacanowski, Michael , Page, David B. , Papadopoulos, Elektra J., Ritchie, Jessica , Shah, Nilay D. , Soukup, Mat, Clair, Christopher St. , Tamang, Stephen, Torbati, Sam , Wallace, Douglas W. , Zhao, Yueqin, Heckmann, Rebekah, Jeffery, Molly Moore , Allen, Summer , Fillmore, Jonathan, Bellolio, M Fernanda , Fillmore, Jonathan, Lee, Christine H. , Ross, Joseph S.

BMJ Open | July 5, 2022 | Volume: 12 | Issue: 7 | Pages: e058782

10.1136/bmjopen-2021-058782 Get It

Introduction Opioid analgesics are often used to treat moderate-to-severe acute non-cancer pain; however, there is little high-quality evidence to guide clinician prescribing. An essential element to developing evidence-based guidelines is a better understanding of pain management and pain control among individuals experiencing acute pain for various common diagnoses. Methods and analysis This multicentre prospective observational study will recruit 1550 opioid-naïve participants with acute pain seen in diverse clinical settings including primary/urgent care, emergency departments and dental clinics. Participants will be followed for 6 months with the aid of a patient-centred health data aggregating platform that consolidates data from study questionnaires, electronic health record data on healthcare services received, prescription fill data from pharmacies, and activity and sleep data from a Fitbit activity tracker. Participants will be enrolled to represent diverse races and ethnicities and pain conditions, as well as geographical diversity. Data analysis will focus on assessing patients’ patterns of pain and opioid analgesic use, along with other pain treatments; associations between patient and condition characteristics and patient-centred outcomes including resolution of pain, satisfaction with care and long-term use of opioid analgesics; and descriptive analyses of patient management of leftover opioids. Ethics and dissemination This study has received approval from IRBs at each site. Results will be made available to participants, funders, the research community and the public. Trial registration number NCT04509115 .
Assessing Values for Health: Numeracy Matters
Woloshin, Steven , Schwartz, Lisa M., Moncur, Megan, Gabriel, Sherine E., Tosteson, Anna N.A.

Medical Decision Making | April 1, 2009 | Volume: 21 | Issue: 5 | Pages: 382-390

10.1177/0272989x0102100505 Get It

Background. Patients’ values are fundamental to decision models, cost-effectiveness analyses, and pharmacoeconomic analyses. The standard methods used to assess how patients value different health states are inherently quantitative. People without strong quantitative skills (i.e., low numeracy) may not be able to complete these tasks in a meaningful way. Methods. To determine whether the validity of utility assessments depends on the respondent’s level of numeracy, the authors conducted in-person interviews and written surveys and assessed utility for the current health for 96 women volunteers. Numeracy was measured using a previously validated 3-item scale. The authors examined the correlation between self-reported health and utility for current health (assessed using the standard gamble, time trade-off, and visual analog techniques) across levels of numeracy. For half of the women, the authors also assessed standard gamble utility for 3 imagined health states (breast cancer, heart disease, and osteoporosis) and asked how much the women feared each disease. Results. Respondent ages ranged from 50 to 79 years (mean = 63), all were high school graduates, and 52% had a college or postgraduate degree. Twenty-six percent answered 0 or only 1 of the numeracy questions correctly, 37% answered 2 correctly, and 37% answered all 3 correctly. Among women with the lowest level of numeracy, the correlation between utility for current health and self-reported health was in the wrong direction (i.e., worse health valued higher than better health): for standard gamble, Spearman r = -0.16, P =0.44; for time trade-off, Spearman r = -0.13, P = 0.54. Among the most numerate women, the authors observed a fair to moderate positive correlation with both standard gamble (Spearman r = 0.22, P = 0.19) and time trade-off (Spearman r = 0.50, P = 0.002). In contrast, using the visual analog scale, the authors observed a substantial correlation in the expected direction at all levels of numeracy (Spearman r =0.82, 0.50, and 0.60 for women answering 0-1, 2, and 3 numeracy questions, respectively; all P s ≤ 0.003). With regard to the imagined health states, the most feared disease had the lowest utility for 35% of the women with the lowest numeracy compared to 76% of the women with the highest numeracy (P = 0.03). Conclusions. The validity of standard utility assessments is related to the subject’s facility with numbers. Limited numeracy may be an important barrier to meaningfully assessing patients’ values using the standard gamble and time trade-off techniques.