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

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.

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Preparing Clinical Text for Use in Biomedical Research

Medical Informatics ◽

10.4018/978-1-60566-050-9.ch159 ◽

2011 ◽

pp. 2085-2095

Author(s):

John P. Pestian ◽

Lukasz Itert ◽

Charlotte Andersen

Keyword(s):

Language Processing ◽

Medical Center ◽

Clinical Care ◽

Academic Medical Center ◽

Clinical Text ◽

Delivery Of Care ◽

Radiology Reports ◽

Academic Medical ◽

Textual Data ◽

Regulatory Actions

Approximately 57 different types of clinical annotations construct a patient’s medical record. These annotations include radiology reports, discharge summaries, and surgical and nursing notes. Hospitals typically produce millions of text-based medical records over the course of a year. These records are essential for the delivery of care, but many are underutilized or not utilized at all for clinical research. The textual data found in these annotations is a rich source of insights into aspects of clinical care and the clinical delivery system. Recent regulatory actions, however, require that, in many cases, data not obtained through informed consent or data not related to the delivery of care must be made anonymous (as referred to by regulators as harmless), before they can be used. This article describes a practical approach with which Cincinnati Children’s Hospital Medical Center (CCHMC), a large pediatric academic medical center with more than 761,000 annual patient encounters, developed open source software for making pediatric clinical text harmless without losing its rich meaning. Development of the software dealt with many of the issues that often arise in natural language processing, such as data collection, disambiguation, and data scrubbing.

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

Journal of Opioid Management ◽

10.5055/jom.2018.0450 ◽

2018 ◽

Vol 14 (3) ◽

pp. 203-210 ◽

Cited By ~ 1

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.

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

Harm Reduction Journal ◽

10.1186/s12954-020-00438-4 ◽

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.

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Data-Driven Identification of Risk Factors of Patient Satisfaction at a Large Urban Academic Medical Center

PLoS ONE ◽

10.1371/journal.pone.0156076 ◽

2016 ◽

Vol 11 (5) ◽

pp. e0156076 ◽

Cited By ~ 9

Author(s):

Li Li ◽

Nathan J. Lee ◽

Benjamin S. Glicksberg ◽

Brian D. Radbill ◽

Joel T. Dudley

Keyword(s):

Risk Factors ◽

Patient Satisfaction ◽

Medical Center ◽

Academic Medical Center ◽

Data Driven ◽

Academic Medical

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

Anesthesia & Analgesia ◽

10.1213/ane.0000000000005182 ◽

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

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A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement

International Journal of Healthcare Information Systems and Informatics ◽

10.4018/ijhisi.2016070102 ◽

2016 ◽

Vol 11 (3) ◽

pp. 19-41 ◽

Cited By ~ 3

Author(s):

Jim Ryan ◽

Barbara Doster ◽

Sandra Daily ◽

Carmen Lewis

Keyword(s):

Process Improvement ◽

Operations Management ◽

Management Practices ◽

Medical Center ◽

Academic Medical Center ◽

Data Driven ◽

Process Reengineering ◽

Academic Medical ◽

Complex Relationships

Based on a 143-month longitudinal study of an academic medical center, this paper examines operations management practices of continuous improvement, workflow balancing, benchmarking, and process reengineering within a hospital's perioperative operations. Specifically, this paper highlights data-driven efforts within perioperative sub-processes to balance overall patient workflow by eliminating bottlenecks, delays, and inefficiencies. This paper illustrates how dynamic technological activities of analysis, evaluation, and synthesis applied to internal and external organizational data can highlight complex relationships within integrated processes to identify process limitations and potential process capabilities, ultimately yielding balanced patient workflow through data-driven perioperative process improvement. Study implications and/or limitations are also included.

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A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement

Hospital Management and Emergency Medicine ◽

10.4018/978-1-7998-2451-0.ch003 ◽

2020 ◽

pp. 45-70

Author(s):

Jim Ryan ◽

Barbara Doster ◽

Sandra Daily ◽

Carmen Lewis

Keyword(s):

Process Improvement ◽

Operations Management ◽

Management Practices ◽

Medical Center ◽

Academic Medical Center ◽

Data Driven ◽

Process Reengineering ◽

Academic Medical ◽

Complex Relationships

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Grading reflective essays: the reliability of a newly developed tool- GRE-9

BMC Medical Education ◽

10.1186/s12909-020-02213-2 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Nisrine N. Makarem ◽

Basem R. Saab ◽

Grace Maalouf ◽

Umayya Musharafieh ◽

Fadila Naji ◽

...

Keyword(s):

Assessment Tool ◽

Medical Center ◽

Academic Medical Center ◽

Correlation Coefficients ◽

Rater Reliability ◽

American University ◽

American University Of Beirut ◽

Academic Medical ◽

Comprehensive Search

Abstract Background The main objective of this study is the development of a short reliable easy-to-use assessment tool in the aim of providing feedback to the reflective writings of medical students and residents. Methods This study took place in a major tertiary academic medical center in Beirut, Lebanon. Seventy-seven reflective essays written by 18 residents in the department of Family Medicine at the American University of Beirut Medical Center (AUBMC) were graded by 3 raters using the newly developed scale to assess the scale reliability. Following a comprehensive search and analysis of the literature, and based on their experience in reflective grading, the authors developed a concise 9-item scale to grade reflective essays through repeated cycles of development and analysis as well as the determination of the inter-rater reliability (IRR) using intra-class correlation coefficients (ICC) and Krippendorff’s Alpha. Results The inter-rater reliability of the new scale ranges from moderate to substantial with ICC of 0.78, 95% CI 0.64–0.86, p < 0.01 and Krippendorff’s Alpha was 0.49. Conclusions The newly developed scale, GRE-9, is a short, concise, easy-to-use reliable grading tool for reflective essays that has demonstrated moderate to substantial inter-rater reliability. This will enable raters to objectively grade reflective essays and provide informed feedback to residents and students.

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Evaluation of a novel metric for personalized opioid prescribing after hospitalization

PLoS ONE ◽

10.1371/journal.pone.0244735 ◽

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.

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