scholarly journals Evaluation of a novel metric for personalized opioid prescribing after hospitalization

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244735
Author(s):  
Nicholas R. Iverson ◽  
Catherine Y. Lau ◽  
Yumiko Abe-Jones ◽  
Margaret C. Fang ◽  
Kirsten N. Kangelaris ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Absolute Difference ◽  
Opioid Use ◽  
Patient Centered ◽  
Electronic Health Record Data ◽  
Opioid Prescription ◽  
Academic Medical ◽  
Maximum Absolute Difference ◽  
Marked Variability

Background The duration of an opioid prescribed at hospital discharge does not intrinsically account for opioid needs during a hospitalization. This discrepancy may lead to patients receiving much larger supplies of opioids on discharge than they truly require. Objective Assess a novel discharge opioid supply metric that adjusts for opioid use during hospitalization, compared to the conventional discharge prescription signature. Design, setting, & participants Retrospective study using electronic health record data from June 2012 to November 2018 of adults who received opioids while hospitalized and after discharge from a single academic medical center. Measures & analysis We ascertained inpatient opioids received and milligrams of opioids supplied after discharge, then determined days of opioids supplied after discharge by the conventional prescription signature opioid-days (“conventional days”) and novel hospital-adjusted opioid-days (“adjusted days”) metrics. We calculated descriptive statistics, within-subject difference between measurements, and fold difference between measures. We used multiple linear regression to determine patient-level predictors associated with high difference in days prescribed between measures. Results The adjusted days metric demonstrates a 2.4 day median increase in prescription duration as compared to the conventional days metric (9.4 vs. 7.0 days; P<0.001). 95% of all adjusted days measurements fall within a 0.19 to 6.90-fold difference as compared to conventional days measurements, with a maximum absolute difference of 640 days. Receiving a liquid opioid prescription accounted for an increased prescription duration of 135.6% by the adjusted days metric (95% CI 39.1–299.0%; P = 0.001). Of patients who were not on opioids prior to admission and required opioids during hospitalization but not in the last 24 hours, 325 (8.6%) were discharged with an opioid prescription. Conclusions The adjusted days metric, based on inpatient opioid use, demonstrates that patients are often prescribed a supply lasting longer than the prescription signature suggests, though with marked variability for some patients that suggests potential under-prescribing as well. Adjusted days is more patient-centered, reflecting the reality of how patients will take their prescription rather than providers’ intended prescription duration.

scholarly journals Postoperative opioid prescribing patterns and use after vascular surgery

2018 ◽  
Vol 24 (1) ◽  
pp. 63-69 ◽  
Author(s):  
Ilsley B Colton ◽  
Mayo H Fujii ◽  
Thomas P Ahern ◽  
Charles D MacLean ◽  
Julie E Lahiri ◽  
...  
Keyword(s):  
Vascular Surgery ◽  
Best Practice ◽  
Medical Center ◽  
Academic Medical Center ◽  
Prescribing Patterns ◽  
Opioid Use ◽  
Patient Centered ◽  
Opioid Prescription ◽  
Opioid Prescribing ◽  
Prescribing Practice

The aim of this study was to assess postoperative opioid prescribing patterns, usage, and pain control after common vascular surgery procedures in order to develop patient centered best-practice guidelines. We performed a prospective review of opioid prescribing after seven common vascular surgeries at a rural, academic medical center from December 2016 to July 2017. A standardized telephone questionnaire was prospectively administered to patients ( n = 110) about opioid use and pain management perceptions. For comparison we retrospectively assessed opioid prescribing patterns ( n = 939) from July 2014 to June 2016 normalized into morphine milligram equivalents (MME). Prescribers were surveyed regarding opioid prescription attitudes, perceptions, and practices. Opioids were prescribed for 78% of procedures, and 70% of patients reported using opioid analgesia. In the prospective group, the median MMEs prescribed were: VEIN (31, n = 16), CEA (40, n = 14), DIAL (60, n = 17), EVAR (108, n = 8), INFRA (160, n = 16), FEM TEA (200, n = 11), and OA (273, n = 4). The median proportion of opioids used by patients across all procedures was only 30% of the amount prescribed across all procedures (range 14–64%). Patients rated the opioid prescribed as appropriate (59%), insufficient (16%), and overprescribed (25%), and pain as very well controlled (47%), well controlled (47%), poorly controlled (4%), and very poorly controlled (2%). In conclusion, we observed significant variability in opioid prescribing after vascular procedures. The overall opioid use was substantially lower than the amount prescribed. These data enabled us to develop guidelines for opioid prescribing practice for our patients.

scholarly journals Patient Centered Medical Home transformation at an academic medical center

2015 ◽  
Vol 5 (1) ◽  
pp. 34
Author(s):  
Randy Wexler ◽  
Jennifer Lehman ◽  
Mary Jo Welker
Keyword(s):  
Family Medicine ◽  
Patient Outcomes ◽  
Medical Home ◽  
Medical Center ◽  
Academic Medical Center ◽  
Lessons Learned ◽  
Patient Centered Medical Home ◽  
Model Of Care ◽  
Patient Centered ◽  
Academic Medical

Background: Primary care is playing an ever increasing role in the design and implementation of new models of healthcare focused on achieving policy ends as put forth by government at both the state and federal level. The Patient Centered Medical Home (PCMH) model is a leading design in this endeavor.Objective: We sought to transform family medicine offices at an academic medical center into the PCMH model of care with improvements in patient outcomes as the end result.Results: Transformation to the PCMH model of care resulted in improved rates of control of diabetes and hypertension and improved prevention measures such as smoking cessation, mammograms, Pneumovax administration, and Tdap vaccination. Readmission rates also improved using a care coordination model.Conclusions: It is possible to transform family medicine offices at academic medical centers in methods consistent with newer models of care such as the PCMH model and to improve patient outcomes. Lessons learned along the way are useful to any practice or system seeking to undertake such transformation.

Opioid use in the acute setting: A survey of providers at an academic medical center

2018 ◽  
Vol 14 (3) ◽  
pp. 203-210 ◽  
Author(s):  
Douglas R. Oyler, PharmD ◽  
Kristy S. Deep, MD ◽  
Phillip K. Chang, MD
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Healthcare Providers ◽  
High Risk Patient ◽  
Opioid Analgesics ◽  
Opioid Use ◽  
Cross Sectional ◽  
Academic Medical ◽  
Clinical Scenarios ◽  
Nonopioid Analgesics

Objective: To examine attitudes, beliefs, and influencing factors of inpatient healthcare providers regarding prescription of opioid analgesics.Design: Electronic cross-sectional survey.Setting: Academic medical center.Participants: Physicians, advanced practice providers, and pharmacists from a single academic medical center in the southeast United States.Main Outcome Measures: Respondents completed survey items addressing: (1) their practice demographics, (2) their opinions regarding overall use, safety, and efficacy of opioids compared to other analgesics, (3) specific clinical scenarios, (4) main pressures to prescribe opioids, and (5) confidence/comfort prescribing opioids or nonopioids in select situations.Results: The majority of the sample (n = 363) were physicians (60.4 percent), with 69.4 percent of physicians being attendings. Most respondents believed that opioids were overused at our institution (61.7 percent); nearly half thought opioids had similar efficacy to other analgesics (44.1 percent), and almost all believed opioids were more dangerous than other analgesics (88.1 percent). Many respondents indicated that they would modify a chronic regimen for a high-risk patient, and use of nonopioids in specific scenarios was high. However, this use was often in combination with opioids. Respondents identified patients (64 percent) and staff (43.1 percent) as the most significant sources of pressure to prescribe opioids during an admission; the most common sources of pressure to prescribe opioidson discharge were to facilitate discharge (44.8 percent) and to reduce follow-up requests, calls, or visits (36.3 percent). Resident physicians appear to experience more pressure to prescribe opioids than other providers. Managing pain in patients with substance use disorders and effectively using nonopioid analgesics were the most common educational needs identified by respondents.Conclusion: Most individuals believe opioid analgesics are overused in our specific setting, commonly to satisfy patient requests. In general, providers feel uncomfortable prescribing nonopioid analgesics to patients.

scholarly journals Two Data-Driven Approaches to Identifying the Spectrum of Problematic Opioid Use: A Pilot Study within a Chronic Pain Cohort

2021 ◽  
Author(s):  
Lori Schirle ◽  
Alvin D Jeffery ◽  
Ali Yaqoob ◽  
Sandra Sanchez-Roige ◽  
David C. Samuels
Keyword(s):  
Language Processing ◽  
Medical Center ◽  
Academic Medical Center ◽  
Correlation Coefficients ◽  
Pilot Project ◽  
Data Driven ◽  
Risk Scores ◽  
Opioid Use ◽  
Academic Medical ◽  
Manual Review

Background: Although electronic health records (EHR) have significant potential for the study of opioid use disorders (OUD), detecting OUD in clinical data is challenging. Models using EHR data to predict OUD often rely on case/control classifications focused on extreme opioid use. There is a need to expand this work to characterize the spectrum of problematic opioid use. Methods: Using a large academic medical center database, we developed 2 data-driven methods of OUD detection: (1) a Comorbidity Score developed from a Phenome-Wide Association Study of phenotypes associated with OUD and (2) a Text-based Score using natural language processing to identify OUD-related concepts in clinical notes. We evaluated the performance of both scores against a manual review with correlation coefficients, Wilcoxon rank sum tests, and area-under the receiver operating characteristic curves. Records with the highest Comorbidity and Text-based scores were re-evaluated by manual review to explore discrepancies. Results: Both the Comorbidity and Text-based OUD risk scores were significantly elevated in the patients judged as High Evidence for OUD in the manual review compared to those with No Evidence (p = 1.3E-5 and 1.3E-6, respectively). The risk scores were positively correlated with each other (rho = 0.52, p < 0.001). AUCs for the Comorbidity and Text-based scores were high (0.79 and 0.76, respectively). Follow-up manual review of discrepant findings revealed strengths of data-driven methods over manual review, and opportunities for improvement in risk assessment. Conclusion: Risk scores comprising comorbidities and text offer differing but synergistic insights into characterizing problematic opioid use. This pilot project establishes a foundation for more robust work in the future.

scholarly journals Disparities in Pediatric Patient Portal Activation and Feature Use

JAMIA Open ◽  
2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Jennifer H LeLaurin ◽  
Oliver T Nguyen ◽  
Lindsay A Thompson ◽  
Jaclyn Hall ◽  
Jiang Bian ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
White Female ◽  
Patient Portal ◽  
Patient Portals ◽  
Electronic Health Record Data ◽  
Factors Associated ◽  
Academic Medical ◽  
Vulnerable Individual ◽  
Records Access

Abstract Objective Disparities in adult patient portal adoption are well-documented; however, less is known about disparities in portal adoption in pediatrics. This study examines the prevalence and factors associated with patient portal activation and the use of specific portal features in general pediatrics. Materials and methods We analyzed electronic health record data from 2012 to 2020 in a large academic medical center that offers both parent and adolescent portals. We summarized portal activation and use of select portal features (messaging, records access and management, appointment management, visit/admissions summaries, and interactive feature use). We used logistic regression to model factors associated with patient portal activation among all patients along with feature use and frequent feature use among ever users (ie, ≥1 portal use). Results Among 52 713 unique patients, 39% had activated the patient portal, including 36% of patients aged 0–11, 41% of patients aged 12–17, and 62% of patients aged 18–21 years. Among activated accounts, ever use of specific features ranged from 28% for visit/admission summaries to 92% for records access and management. Adjusted analyses showed patients with activated accounts were more likely to be adolescents or young adults, white, female, privately insured, and less socioeconomically vulnerable. Individual feature use among ever users generally followed the same pattern. Conclusions Our findings demonstrate that important disparities persist in portal adoption in pediatric populations, highlighting the need for strategies to promote equitable access to patient portals.

scholarly journals Implementation of a medical student-run telemedicine program for medications for opioid use disorder during the COVID-19 pandemic

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Marcus Castillo ◽  
Brianna Conte ◽  
Sam Hinkes ◽  
Megan Mathew ◽  
C. J. Na ◽  
...  
Keyword(s):  
Medical Student ◽  
People Who Inject Drugs ◽  
Medical Center ◽  
Academic Medical Center ◽  
Opioid Use Disorder ◽  
Health Issues ◽  
Opioid Use ◽  
Academic Medical ◽  
Life Saving ◽  
Attending Physicians

Abstract Objectives The COVID-19 pandemic led to the closure of the IDEA syringe services program medical student-run free clinic in Miami, Florida. In an effort to continue to serve the community of people who inject drugs and practice compassionate and non-judgmental care, the students transitioned the clinic to a model of TeleMOUD (medications for opioid use disorder). We describe development and implementation of a medical student-run telemedicine clinic through an academic medical center-operated syringe services program. Methods Students advertised TeleMOUD services at the syringe service program on social media and created an online sign-up form. They coordinated appointments and interviewed patients by phone or videoconference where they assessed patients for opioid use disorder. Supervising attending physicians also interviewed patients and prescribed buprenorphine when appropriate. Students assisted patients in obtaining medication from the pharmacy and provided support and guidance during home buprenorphine induction. Results Over the first 9 weeks in operation, 31 appointments were requested, and 22 initial telehealth appointments were completed by a team of students and attending physicians. Fifteen appointments were for MOUD and 7 for other health issues. All patients seeking MOUD were prescribed buprenorphine and 12/15 successfully picked up medications from the pharmacy. The mean time between appointment request and prescription pick-up was 9.5 days. Conclusions TeleMOUD is feasible and successful in providing people who inject drugs with low barrier access to life-saving MOUD during the COVID-19 pandemic. This model also provided medical students with experience treating addiction during a time when they were restricted from most clinical activities.

scholarly journals Perioperative Factors Associated With Chronic Opioid Use After Spine Surgery

2021 ◽  
pp. 219256822110357
Author(s):  
Eric Y. Montgomery ◽  
Mark N. Pernik ◽  
Zachary D. Johnson ◽  
Luke J. Dosselman ◽  
Zachary K. Christian ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spine Surgery ◽  
Medical Center ◽  
Lumbar Fusion ◽  
Academic Medical Center ◽  
Opioid Use ◽  
Retrospective Case ◽  
Opioid Prescription ◽  
Factors Associated ◽  
Chronic Opioid Use

Study Design: Retrospective case control. Objectives: The purpose of the current study is to determine risk factors associated with chronic opioid use after spine surgery. Methods: In our single institution retrospective study, 1,299 patients undergoing elective spine surgery at a tertiary academic medical center between January 2010 and August 2017 were enrolled into a prospectively collected registry. Patients were dichotomized based on renewal of, or active opioid prescription at 3-mo and 12-mo postoperatively. The primary outcome measures were risk factors for opioid renewal 3-months and 12-months postoperatively. These primarily included demographic characteristics, operative variables, and in-hospital opioid consumption via morphine milligram equivalence (MME). At the 3-month and 12-month periods, we analyzed the aforementioned covariates with multivariate followed by bivariate regression analyses. Results: Multivariate and bivariate analyses revealed that script renewal at 3 months was associated with black race ( P = 0.001), preoperative narcotic ( P < 0.001) or anxiety/depression medication use ( P = 0.002), and intraoperative long lumbar ( P < 0.001) or thoracic spine surgery ( P < 0.001). Lower patient income was also a risk factor for script renewal ( P = 0.01). Script renewal at 12 months was associated with younger age ( P = 0.006), preoperative narcotics use ( P = 0.001), and ≥4 levels of lumbar fusion ( P < 0.001). Renewals at 3-mo and 12-mo had no association with MME given during the hospital stay or with the usage of PCA ( P > 0.05). Conclusion: The current study describes multiple patient-level factors associated with chronic opioid use. Notably, no metric of perioperative opioid utilization was directly associated with chronic opioid use after multivariate analysis.

Development and Impact of an Institutional Enhanced Recovery Program on Opioid Use, Length of Stay, and Hospital Costs Within an Academic Medical Center

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Robert H. Thiele ◽  
Bethany M. Sarosiek ◽  
Susan C. Modesitt ◽  
Timothy L. McMurry ◽  
Mohamed Tiouririne ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Enhanced Recovery ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hospital Costs ◽  
Opioid Use ◽  
Enhanced Recovery Program ◽  
Academic Medical ◽  
Recovery Program

scholarly journals Characterizing non-heroin opioid overdoses using electronic health records

JAMIA Open ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 77-86
Author(s):  
Amelia J Averitt ◽  
Benjamin H Slovis ◽  
Abdul A Tariq ◽  
David K Vawdrey ◽  
Adler J Perotte
Keyword(s):  
Average Rate ◽  
Medical Center ◽  
Academic Medical Center ◽  
Future Research ◽  
Opioid Epidemic ◽  
Opioid Use ◽  
Electronic Health Record Data ◽  
Individual Level ◽  
Electronic Health ◽  
The Individual

Abstract Introduction The opioid epidemic is a modern public health emergency. Common interventions to alleviate the opioid epidemic aim to discourage excessive prescription of opioids. However, these methods often take place over large municipal areas (state-level) and may fail to address the diversity that exists within each opioid case (individual-level). An intervention to combat the opioid epidemic that takes place at the individual-level would be preferable. Methods This research leverages computational tools and methods to characterize the opioid epidemic at the individual-level using the electronic health record data from a large, academic medical center. To better understand the characteristics of patients with opioid use disorder (OUD) we leveraged a self-controlled analysis to compare the healthcare encounters before and after an individual’s first overdose event recorded within the data. We further contrast these patients with matched, non-OUD controls to demonstrate the unique qualities of the OUD cohort. Results Our research confirms that the rate of opioid overdoses in our hospital significantly increased between 2006 and 2015 (P &lt; 0.001), at an average rate of 9% per year. We further found that the period just prior to the first overdose is marked by conditions of pain or malignancy, which may suggest that overdose stems from pharmaceutical opioids prescribed for these conditions. Conclusions Informatics-based methodologies, like those presented here, may play a role in better understanding those individuals who suffer from opioid dependency and overdose, and may lead to future research and interventions that could successfully prevent morbidity and mortality associated with this epidemic.

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