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Record W2903700699 · doi:10.1093/pm/pnx326

“Do No Harm. Do Some Good.” A Call for Members to Attend the Upcoming Annual AAPM Meeting in Vancouver, BC

2017· article· en· W2903700699 on OpenAlexaboutno aff
Steven P. Stanos

Bibliographic record

VenuePain Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Services Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHarmMedicineDo no harmFamily medicineMedical emergencyPsychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Primum non nocere vs deinde benefacere A recent description in the National Academy of Sciences (NAS) reminded me of our role as physicians to “do no harm,” but also “do some good.” Given the current landscape we practice in as pain specialists, this deceptively simple mantra may be more challenging to follow than it sounds. The opioid overdose epidemic, which has been fueled in part by the overprescribing of opioid medications as well as by the profoundly troubling influx of illicit fentanyl and cheap heroin into US neighborhoods, has caused the death rate to continue rising. Pain patients and those carefully monitored and selected who benefit from this therapy are being stigmatized and their treatment being questioned. Misinterpretations of the Centers for Disease Control and Prevention (CDC) guideline for prescribing opioids for chronic pain, the increase in prior authorizations required for medication management, reactive state initiatives, and insurance plan and pharmacy limitations on prescribing continue to add to the confusion, making physicians feel unsure about what to do and how to proceed. 2017 was a tough and challenging year. Can we look forward to an environment that supports better multidisciplinary care while bending the curve of overdose deaths in the right direction? A lot is happening, and we as providers need to be educated so we can make informed decisions for our patients and further support our field of multidisciplinary pain management. Important state, federal, and organized medicine efforts have been underway. Clinicians need to be the most informed so they can better care for patients, advocate for their care, and lead these changes in the right direction. I want to briefly describe a short list from a busy 2017 highlighting important announcements and initiatives and how these events make it ever so important to attend the American Academy of Pain Medicine (AAPM) Annual Meeting this coming April in Vancouver, British Columbia. Featured Programs at AAPM: CDC Guideline for Chronic Opioid Therapy. Although released in March of 2016, the guideline continues to have significant impact on state guidelines, pharmacy benefit decisions, and payer collaboration with pain management. Steven Hanling, MD, Kurt Kroenke, MD, and AMA Immediate Past Chair, Patrice Harris, MD (CDC Guidelines: Where Do We Stand? Advocating for Physicians and Their Patients in Pain[304]– Saturday 11:30–12:30 am) will review efforts by the AAPM and organized medicine to put the CDC Guideline in perspective, helping clinicians apply the guideline while balancing safety concerns for patients with individually based medical management of pain. Pain Management Best Practices Task Force. A product of Comprehensive Addiction and Recovery Act and the Affordable Care Act, Health and Human Services (HHS) has called for experts to serve on the Pain Management Best Practices Inter-Agency Task Force. The group will devise recommendations to HHS and help to coordinate efforts around the National Pain Strategy. Vanila Singh, MD, Chief Medical Officer for the Office of the Assistant Secretary for Health, who serves as the point person for HHS, will enlighten attendees during Saturday’s Plenary Session (The National Strategy and USTask Force on Pain and Opioids[104]–Saturday at 8:00am). Joining Dr. Singh will be AAPM Past President, Sean Mackey, MD, PhD, who helped to co-author the recent National Academy of Medicine paper “First, Do No Harm: Marshaling Clinician Leadership to Counter the Opioid Epidemic.” Together they will provide an important update on HHS efforts to address pain management. JAMA’s publication of the paper“Effect of Radiofrequency Denervation on Pain Intensity Among Patientswith Chronic Low Back Pain: The Mint Randomized Clinical Trials.” Following the publication of this study, the AAPM and several other pain organizations have worked together to respond to difficulties at both the national and state levels to increased challenges to the validity of RFN. Several of our sessions at the Annual Meeting 2018 will provide important information on interventional pain management. (Fake News: The Risk of Promoted Flawed Data and Crucial Role of Evidence-Based Interventional Pain Management[306], featuring D. J. Kennedy, MD,presenting on Lumbar Medial Branch Radiofrequency Neurotomy: An EBM Overview of Selection and Technique; Timothy P. Maus, MD, discussing Epidural Steroid Injections: Evidence-Based Techniques Yield Positive Outcomes; and Yakov M. Vorobeychik, MD PhD, moderating and presenting on Practical Application of Evidence-Based Medicine Principles to the Mint Randomized Clinical Trials. This coming year’s annual meeting, “Managing Acute & High-Impact Chronic Pain through Multidisciplinary Care,” April 25–29, 2018, is closely approaching. Our scientific committee has put together a wonderful course, including must-see symposia to help update attendees on these initiatives and offer discussion on how we can move forward. Learn more about at http://annualmeeting.painmed.org/.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.141
Threshold uncertainty score0.471

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0110.012
Insufficient payload (model declined to judge)0.1410.085

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.461
Teacher spread0.391 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
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