Dataset Information

Characteristics of Opioid Prescribing in Non-surgical Medicine Patients with Acute Pain at Hospital Discharge.

ABSTRACT:

Background

The opioid epidemic and new Joint Commission standards around opioid stewardship have made the appropriate prescribing of opioids a priority. A knowledge gap exists pertaining to the short-term prescription of opioids at hospital discharge for acute pain in non-surgical patients.

Objective

To characterize the quantity, type, and indication of opioids prescribed for non-surgical patients on hospital discharge and subsequent patient utilization.

Design

This multicenter, single-health system retrospective cohort study was conducted for quality improvement purposes from December 2019 to May 2020 with patient follow-up 15 to 29 days after hospital discharge.

Participants

Patients discharged from a medicine service with new opioid prescriptions, defined as no opioid prescription documented within the past 90 days, were identified as eligible through the electronic health record. Surveys were attempted until a total of 200 were completed, with 374 surveys attempted and a 53% response rate.

Intervention

Patients were contacted via phone and surveyed post-discharge. Surveys consisted of 28 questions and assessed opioid consumption, duration of use, refills, patient satisfaction, and opioid disposal.

Main measures

Prescribing indications and morphine milligram equivalents (MME) quantities were collected for patients at discharge. Subsequently, the quantity of prescribed opioids utilized, remaining, and disposed of post-discharge were collected via patient self-reported survey responses.

Key results

Indications for opioid prescribing for 200 surveyed patients were grouped into eight broad prescribing categories. A median of 112.5 total MME was prescribed to patients at hospital discharge. Median MME consumed for surveyed patients was 45. The median total MME remaining at time of survey was 35 MME. Only 5.9% of patients who had leftover opioids reported disposal of the medication.

Conclusions

Given the observed variation in opioid prescribing and utilization data, standardized indication-based opioid prescribing guidance in the non-surgical medical population would help curb the amount of opioids that remain unused post-discharge.

SUBMITTER: Engstrom K

PROVIDER: S-EPMC8858354 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characteristics of Opioid Prescribing in Non-surgical Medicine Patients with Acute Pain at Hospital Discharge.

Engstrom Kellyn K Brown Caitlin S CS Ubl Dan D Hanson Kristine K Bates Ruth R Cunningham Julie J

Journal of general internal medicine 20210811 3

<h4>Background</h4>The opioid epidemic and new Joint Commission standards around opioid stewardship have made the appropriate prescribing of opioids a priority. A knowledge gap exists pertaining to the short-term prescription of opioids at hospital discharge for acute pain in non-surgical patients.<h4>Objective</h4>To characterize the quantity, type, and indication of opioids prescribed for non-surgical patients on hospital discharge and subsequent patient utilization.<h4>Design</h4>This multice ...[more]

PMID: 34382139

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Project description:BackgroundThe epidemic of nonmedical use of prescription opioids has been fueled by the availability of legitimately prescribed unconsumed opioids. The aim of this study was to better understand the contribution of prescriptions written for pediatric patients to this problem by quantifying how much opioid is dispensed and consumed to manage pain after hospital discharge, and whether leftover opioid is appropriately disposed of. Our secondary aim was to explore the association of patient factors with opioid dispensing, consumption, and medication remaining on completion of therapy.MethodsUsing a scripted 10-minute interview, parents of 343 pediatric inpatients (98% postoperative) treated at a university children's hospital were questioned within 48 hours and 10 to 14 days after discharge to determine amount of opioid prescribed and consumed, duration of treatment, and disposition of unconsumed opioid. Multivariable linear regression was used to examine predictors of opioid prescribing, consumption, and doses remaining.ResultsMedian number of opioid doses dispensed was 43 (interquartile range, 30-85 doses), and median duration of therapy was 4 days (interquartile range, 1-8 days). Children who underwent orthopedic or Nuss surgery consumed 25.42 (95% confidence interval, 19.16-31.68) more doses than those who underwent other types of surgery (P < .001), and number of doses consumed was positively associated with higher discharge pain scores (P = .032). Overall, 58% (95% confidence interval, 54%-63%) of doses dispensed were not consumed, and the strongest predictor of number of doses remaining was doses dispensed (P < .001). Nineteen percent of families were informed how to dispose of leftover opioid, but only 4% (8 of 211) did so.ConclusionsPediatric providers frequently prescribed more opioid than needed to treat pain. This unconsumed opioid may contribute to the epidemic of nonmedical use of prescription opioids. Our findings underscore the need for further research to develop evidence-based opioid prescribing guidelines for physicians treating acute pain in children.

Project description:BackgroundChronic opioid therapy for chronic pain treatment has increased. Hospital physicians, including hospitalists and medical/surgical resident physicians, care for many hospitalized patients, yet little is known about opioid prescribing at hospital discharge and future chronic opioid use.ObjectiveWe aimed to characterize opioid prescribing at hospital discharge among 'opioid naïve' patients. Opioid naïve patients had not filled an opioid prescription at an affiliated pharmacy 1 year preceding their hospital discharge. We also set out to quantify the risk of chronic opioid use and opioid refills 1 year post discharge among opioid naïve patients with and without opioid receipt at discharge.DesignThis was a retrospective cohort study.ParticipantsFrom 1 January 2011 to 31 December 2011, 6,689 opioid naïve patients were discharged from a safety-net hospital.Main measureChronic opioid use 1 year post discharge.Key resultsTwenty-five percent of opioid naïve patients (n = 1,688) had opioid receipt within 72 hours of discharge. Patients with opioid receipt were more likely to have diagnoses including neoplasm (6.3% versus 3.5%, p < 0.001), acute pain (2.7% versus 1.0 %, p < 0.001), chronic pain at admission (12.1% versus 3.3%, p < 0.001) or surgery during their hospitalization (65.1% versus 18.4%, p < 0.001) compared to patients without opioid receipt. Patients with opioid receipt were less likely to have alcohol use disorders (15.7% versus 20.7%, p < 0.001) and mental health disorders (23.9% versus 31.4%, p < 0.001) compared to patients without opioid receipt. Chronic opioid use 1 year post discharge was more common among patients with opioid receipt (4.1% versus 1.3%, p < 0.0001) compared to patients without opioid receipt. Opioid receipt was associated with increased odds of chronic opioid use (AOR = 4.90, 95% CI 3.22-7.45) and greater subsequent opioid refills (AOR = 2.67, 95% CI 2.29-3.13) 1 year post discharge compared to no opioid receipt.ConclusionOpioid receipt at hospital discharge among opioid naïve patients increased future chronic opioid use. Physicians should inform patients of this risk prior to prescribing opioids at discharge.

Project description:ImportanceOpioid medications are commonly prescribed for the management of acute postoperative pain. In light of increasing awareness of the potential risks of opioid prescribing, data are needed to define the procedures and populations for which most opioid prescribing occurs.ObjectiveTo identify the surgical procedures accounting for the highest proportion of opioids dispensed to adults after surgery in the United States.Design, setting, and participantsThis cross-sectional analysis of the 2020-2021 Merative MarketScan Commercial and Multi-State Databases, which capture medical and pharmacy claims for 23 million and 14 million annual privately insured patients and Medicaid beneficiaries, respectively, included surgical procedures for individuals aged 18 to 64 years with a discharge date between December 1, 2020, and November 30, 2021. Procedures were identified using a novel crosswalk between 3664 Current Procedural Terminology codes and 1082 procedure types. Data analysis was conducted from November to December 2023.Main outcomes and measuresThe total amount of opioids dispensed within 3 days of discharge from surgery across all procedures in the sample, as measured in morphine milligram equivalents (MMEs), was calculated. The primary outcome was the proportion of total MMEs attributable to each procedure type, calculated separately among procedures for individuals aged 18 to 44 years and those aged 45 to 64 years.ResultsAmong 1 040 934 surgical procedures performed (mean [SD] age of patients, 45.5 [13.3] years; 663 609 [63.7%] female patients), 457 016 (43.9%) occurred among individuals aged 18 to 44 years and 583 918 (56.1%) among individuals aged 45 to 64 years. Opioid prescriptions were dispensed for 503 058 procedures (48.3%). Among individuals aged 18 to 44 years, cesarean delivery accounted for the highest proportion of total MMEs dispensed after surgery (19.4% [11 418 658 of 58 825 364 MMEs]). Among individuals aged 45 to 64 years, 4 of the top 5 procedures were common orthopedic procedures (eg, arthroplasty of knee, 9.7% of total MMEs [5 885 305 of 60 591 564 MMEs]; arthroscopy of knee, 6.5% [3 912 616 MMEs]).Conclusions and relevanceIn this cross-sectional study of the distribution of postoperative opioid prescribing in the United States, a small number of common procedures accounted for a large proportion of MMEs dispensed after surgery. These findings suggest that the optimal design and targeting of surgical opioid stewardship initiatives in adults undergoing surgery should focus on the procedures that account for the most opioid dispensed following surgery over the life span, such as childbirth and orthopedic procedures. Going forward, systems that provide periodic surveillance of opioid prescribing and associated harms can direct quality improvement initiatives to reduce opioid-related morbidity and mortality.

Project description:BackgroundPain is one of the most common symptoms encountered in the healthcare system, and opioids are among the top three medications used to treat it. Understanding the reasoning behind physicians' opioid prescribing practices is vital to safe practice. The primary objective of our study was to describe pediatric emergency physicians' decision-making process when prescribing opioids for children's acute pain management.MethodsThis study employed qualitative methodology, using one-on-one semi-structured interviews within a grounded theory analytic framework. We employed purposeful sampling to recruit pediatric emergency physicians from across Canada. Interviews were conducted by telephone (December 2019-January 2021). Transcript analysis occurred concurrently with data collection, supporting data saturation and theory development considerations.ResultsEleven interviews were completed with participants representing each of Canada's geographic regions. Nine major themes emerged: (1) practice setting and outpatient opioid use, (2) condition-specific considerations, (3) physician confidence in medical evidence, (4) pain assessment challenges, (5) patient and family perspectives, (6) opioid safety concerns, (7) personal biases and experiences, (8) personal practice context, and (9) the Opioid Crisis/media influence. Most clinicians felt that they limited opioid use to those who needed it most; all participants described challenges managing acute pain, emphasizing the need for accurate pain measurement and better guidelines, evidence-based data, and knowledge translation. Clinicians were more comfortable treating pain in the emergency department, compared to discharge prescribing. They recognized the importance of co-therapy with non-opioids and the need for opioid risk assessment when prescribing. A family centered approach was recognized as the goal of practice.ConclusionClinicians are less comfortable prescribing opioids to children for at-home use and find pain assessment and lack of clear guidelines to be barriers to pain care. Knowledge translation strategies for safer practice and optimal acute pain management could support responsible and judicious opioid use.

Project description:BackgroundOpioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of OUD and social risks and behaviors. To capture this information at scale, natural language processing (NLP) tools must be developed and evaluated. We developed and applied an annotation schema to deeply characterize OUD and related clinical, behavioral, and environmental factors, and automated the annotation schema using machine learning and deep learning-based approaches.MethodsUsing the MIMIC-III Critical Care Database, we queried hospital discharge summaries of patients with International Classification of Diseases (ICD-9) OUD diagnostic codes. We developed an annotation schema to characterize problematic opioid use, identify individuals with potential OUD, and provide psychosocial context. Two annotators reviewed discharge summaries from 100 patients. We randomly sampled patients with their associated annotated sentences and divided them into training (66 patients; 2,127 annotated sentences) and testing (29 patients; 1,149 annotated sentences) sets. We used the training set to generate features, employing three NLP algorithms/knowledge sources. We trained and tested prediction models for classification with a traditional machine learner (logistic regression) and deep learning approach (Autogluon based on ELECTRA's replaced token detection model). We applied a five-fold cross-validation approach to reduce bias in performance estimates.ResultsThe resulting annotation schema contained 32 classes. We achieved moderate inter-annotator agreement, with F1-scores across all classes increasing from 48 to 66%. Five classes had a sufficient number of annotations for automation; of these, we observed consistently high performance (F1-scores) across training and testing sets for drug screening (training: 91-96; testing: 91-94) and opioid type (training: 86-96; testing: 86-99). Performance dropped from training and to testing sets for other drug use (training: 52-65; testing: 40-48), pain management (training: 72-78; testing: 61-78) and psychiatric (training: 73-80; testing: 72). Autogluon achieved the highest performance.ConclusionThis pilot study demonstrated that rich information regarding problematic opioid use can be manually identified by annotators. However, more training samples and features would improve our ability to reliably identify less common classes from clinical text, including text from outpatient settings.

Dataset Information

Characteristics of Opioid Prescribing in Non-surgical Medicine Patients with Acute Pain at Hospital Discharge.

Background

Objective

Design

Participants

Intervention

Main measures

Key results

Conclusions

Publications

Characteristics of Opioid Prescribing in Non-surgical Medicine Patients with Acute Pain at Hospital Discharge.

Similar Datasets

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