Jennifer F. Waljee

BACKGROUND: Trauma patients frequently have comorbid substance use disorders (SUD), which may complicate pain management and increase the risk of opioid-related adverse outcomes after discharge. We hypothesized that trauma patients with SUD would be prescribed more opioids at discharge than those without SUD. METHODS: We retrospectively analyzed a cohort of adult trauma patients across the state from 2022 to 2025 using a statewide collaborative database. Primary outcomes were opioid prescription at discharge (yes/no) and amount prescribed standardized to oxycodone 5 mg pills. A multivariable approach assessed risk-adjusted differences in outcomes among patients with SUD versus without SUD. RESULTS: Among 29,805 total patients, 8,672 (29.1%) had a diagnosis of SUD. 71.2% of patients with SUD received a discharge opioid prescription, compared with 59.6% of patients without SUD ( p p <0.001) compared with those without. Prescribing patterns also differed by race and ethnicity: Hispanic or Latino patients were 5.4-percentage points more likely to receive an opioid prescription than non-Hispanic or Latino patients, while, among prescription recipients, Black patients received 3.56 fewer pills than White patients. CONCLUSIONS: Our findings demonstrate that patients with SUD received opioids more frequently and in greater amounts at discharge, yet absolute differences were small in magnitude and may not represent clinically meaningful differences. Differences in prescribing by race and ethnicity were larger in magnitude and warrant further investigation. LEVEL OF EVIDENCE: Prognostic and epidemiological; Level III.

Background: Relaxation-based mobile health (mHealth) interventions hold strong potential to address perioperative anxiety and pain management in a scalable manner. However, there is limited research on how surgical patients engage with these interventions and what aspects may be most helpful. Objective: This study had 3 goals: (1) explore how users interact with a relaxation-based mHealth intervention during the perioperative period; (2) understand how user performance and perceptions relate to perceived benefits; and (3) identify design considerations to enhance user engagement and behavior change outcomes in mHealth interventions. Methods: We conducted a prospective longitudinal cohort, mixed methods study to evaluate user engagement with MiCarePath, a relaxation-based mHealth intervention. A total of 19 perioperative patients (mean age 41.3 years; 14/19, 74%, female) undergoing elective surgery and reporting sometimes-to-always anxiety were enrolled using 3 recruitment methods. Participants used the app from 10 days before surgery to 4 weeks after surgery. We collected quantitative data on video engagement metrics (eg, duration of watching, response rate to video prompts) and ecological momentary assessments of anxiety and pain. Concurrently, we conducted semistructured, data-prompted interviews at 3 time points to assess user perceptions. These data were integrated using descriptive statistics, repeated-measures ANOVA, and qualitative thematic analysis to examine the relationship between user performance and perceived benefits. Results: Eleven participants reported developing or improving relaxation-based self-management strategies (high benefit), whereas 8 reported little benefit from the intervention. The high-benefit group showed significantly greater total watching time (difference 223.8 minutes, 95% CI 95.54-366.46 minutes, P<.001), higher adherence to video prompts (73.45% vs 34.60%, P<.001), and greater perceived helpfulness of the content (79.80% vs 25.50%, P<.001) compared with the low-benefit group. A significant group-by-time interaction effect was observed for engagement (F1,17=17.02, P<.001). No difference was observed in delay in response to video prompts. However, within each group, participant perceptions were not fully reflected in performance. Some participants in the high-benefit group showed decreased video watching after surgery but still reported feeling engaged with the intervention. Interview data revealed that “intentional use” behavior—where users actively seek content to manage symptoms independent of prompts—distinguished these participants. Those who developed intentional use were able to practice relaxation techniques without the app and resume app engagement following contextual disruptions. Conclusions: This study explored user engagement with a relaxation-based mHealth intervention for perioperative care, advancing the literature by integrating user perceptions and performance for digital anxiety and pain management. Results indicate that perceived benefit may not always be reflected in user performance. Intentional use emerges as a promising indicator of effective mHealth engagement in perioperative care. Future designs should aim to foster intentional use through features such as reflection prompts and adaptive notifications. Future work should also develop computational models to detect intentional use and evaluate adaptive interventions in larger cohorts.

Background: Misuse of prescription opioids remains a public health problem. Appropriate short-term use of these medications in opioid-naive patients is indicated in selected settings but can result in unintended prolonged opioid use (UPOU), defined as the continuation of opioid therapy beyond the period by which acute pain would have been expected to resolve. Clinical strategies aimed at preventing UPOU are lacking due to the absence of information about how this poorly understood clinical phenomenon actually develops. Objective: In this research project, 3 Clinical and Translational Science Awards (CTSA) programs (Mayo Clinic, University of Michigan, and Yale University) leveraged the conceptual framework for UPOU to investigate how patient characteristics, practice environment characteristics, and opioid prescriber characteristics facilitate or impede UPOU. All data management and analyses were conducted at a fourth CTSA program (University of Minnesota). This work was accomplished by pursuing 3 specific aims. Methods: In aim 1, opioid-naive adults receiving an initial opioid prescription were recruited for study participation. Opioid prescriptions were identified longitudinally, and patterns of use were categorized as short-term, episodic, or long-term use using established criteria. Using a prospective case-control design, patients progressing to UPOU were matched 1:1 with patients who did not develop UPOU, and differences in patient characteristics were assessed. In aim 2, clinicians who prescribed opioids to patients in aim 1 were identified and recruited for prospective assessments. Institutional and individual practice environments were assessed using a validated self-report survey. In aim 3, structural equation modeling was used to evaluate data collected in aims 1 and 2, and identified interactions were further evaluated in a large national administrative claims database. Results: Patient recruitment began on August 1, 2019. However, due to the COVID-19 pandemic, patient recruitment was slowed and intermittently interrupted over the ensuing 3-year period. As a result of regional variations in the impact of the COVID-19 pandemic on research activities, the majority of patient and clinician recruitment occurred at the Mayo Clinic site. Conclusions: Following complete data analyses, it is anticipated that electronic health record systems will be leveraged to help clinicians identify at risk patients and to develop direct-to-patient educational materials to raise awareness of the risk factors for developing UPOU. Trial Registration: ClinicalTrials.gov NCT04024397; https://clinicaltrials.gov/study/NCT04024397 International Registered Report Identifier (IRRID): DERR1-10.2196/72032

BACKGROUND Misuse of prescription opioids remains a public health problem. Appropriate short-term use of these medications in opioid-naive patients is indicated in selected settings but can result in unintended prolonged opioid use (UPOU), defined as the continuation of opioid therapy beyond the period by which acute pain would have been expected to resolve. Clinical strategies aimed at preventing UPOU are lacking due to the absence of information about how this poorly understood clinical phenomenon actually develops. OBJECTIVE In this research project, 3 Clinical and Translational Science Awards (CTSA) programs (Mayo Clinic, University of Michigan, and Yale University) leveraged the conceptual framework for UPOU to investigate how patient characteristics, practice environment characteristics, and opioid prescriber characteristics facilitate or impede UPOU. All data management and analyses were conducted at a fourth CTSA program (University of Minnesota). This work was accomplished by pursuing 3 specific aims. METHODS In aim 1, opioid-naive adults receiving an initial opioid prescription were recruited for study participation. Opioid prescriptions were identified longitudinally, and patterns of use were categorized as short-term, episodic, or long-term use using established criteria. Using a prospective case-control design, patients progressing to UPOU were matched 1:1 with patients who did not develop UPOU, and differences in patient characteristics were assessed. In aim 2, clinicians who prescribed opioids to patients in aim 1 were identified and recruited for prospective assessments. Institutional and individual practice environments were assessed using a validated self-report survey. In aim 3, structural equation modeling was used to evaluate data collected in aims 1 and 2, and identified interactions were further evaluated in a large national administrative claims database. RESULTS Patient recruitment began on August 1, 2019. However, due to the COVID-19 pandemic, patient recruitment was slowed and intermittently interrupted over the ensuing 3-year period. As a result of regional variations in the impact of the COVID-19 pandemic on research activities, the majority of patient and clinician recruitment occurred at the Mayo Clinic site. CONCLUSIONS Following complete data analyses, it is anticipated that electronic health record systems will be leveraged to help clinicians identify at risk patients and to develop direct-to-patient educational materials to raise awareness of the risk factors for developing UPOU. CLINICALTRIAL ClinicalTrials.gov NCT04024397; https://clinicaltrials.gov/study/NCT04024397 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/72032

Objectives: Limited data exist regarding recovery from surgery from the adolescent’s perspective, or data regarding concordance between adolescent and caregiver symptom reports preventing appreciation of adolescent needs and hindering the provision of appropriate care. Methods: We conducted semi-structured interviews with adolescents ages 12 to 17 and a parent caregiver 2 weeks following a variety of outpatient elective surgeries about recovery symptoms. We used latent manifest content analysis to analyze interview data. Caregiver-adolescent response concordance was assessed using Cohen κ. Results: Interviews were conducted with 31 adolescent-caregiver pairs (median age: 15 y). Fifty-eight percent of adolescents and 84% of caregivers were female; 71% of adolescents were White. Twenty-three percent of children reported severe pain, some of which was not expected given the surgery. Severe pain was associated with nausea (71%, P=0.002), pain-related sleep disturbance (86%, P=0.007), and severe anxiety (43%, P=0.008). Fatigue was also common (58%), but not associated with severe pain (P=0.484) or sleep disturbance (P=0.577). Thirty-nine percent reported anxiety; 32% experienced anger/frustration. Caregiver-adolescent concordance was only substantial for severe pain (κ=0.71) and anger/frustration (κ=0.67). Caregiver reports also often included psychological symptoms not reported by their children, with qualitative evidence supporting caregiver accuracy. Discussion: Adolescents may experience significant physical symptoms, such as pain and fatigue, even after minor surgeries. Fatigue symptoms may be unrelated to pain or sleep. Caregiver report of adolescent psychological symptoms may be necessary to gain a complete understanding of those symptoms in this population.

Objective: To define recent trends in opioid prescribing after surgery and new persistent opioid use in the United States. Background: New persistent opioid use after surgery among opioid-naive individuals has emerged as an important postoperative complication. In response, initiatives to promote more appropriate postoperative opioid prescribing have been adopted in recent years. However, current estimates of opioid prescribing and new persistent opioid use following surgery remain unknown. Methods: A retrospective cohort study of opioid-naive privately insured adult patients undergoing 17 common surgical procedures between 2013 and 2021 was conducted utilizing multi-payer claims data from the Health Care Cost Institute (HCCI). Initial opioid prescription size in oral morphine equivalents (OMEs) and new persistent opioid use were the outcomes of interest. Trends in opioid prescribing and rates of new persistent opioid use were evaluated across the study period. Mixed effects logistic regression was performed to evaluate independent predictors of new persistent opioid use while adjusting for patient-level factors and year. Results: Among 989,354 opioid-naive individuals, the adjusted initial opioid prescription size decreased from 282 mg OME to 164 mg OME, a reduction of 118 mg OME (95% CI: 116–120). The adjusted incidence of new persistent opioid use decreased from 2.7% in 2013 (95% CI: 2.6%–2.8%) to 1.1% in 2021 (95% CI: 1.0%–1.2%). For every 30 OME increase in initial opioid prescription size, new persistent opioid use increased by 3.1%. Other predictors of new persistent opioid use included preoperative nonopioid controlled substances fills [31–365 days: adjusted odds ratio (aOR)=1.78, 95% CI: 1.70–1.86; 0–30 days: aOR=2.71, 95% CI: 2.59–2.84] and undergoing orthopedic procedures [total knee arthroplasty (aOR=3.43, 95% CI: 3.15–3.72); shoulder arthroscopy (aOR=2.39, 95% CI: 2.24–2.56)]. Conclusions: Both opioid prescription size after surgery and new persistent opioid use decreased over the last decade, suggesting that opioid stewardship practices had favorable effects on the risk of long-term opioid use.

BACKGROUND Relaxation-based mobile health (mHealth) interventions hold strong potential to address perioperative anxiety and pain management in a scalable manner. However, there is limited research on how surgical patients engage with these interventions and what aspects may be most helpful. OBJECTIVE This study had 3 goals: (1) explore how users interact with a relaxation-based mHealth intervention during the perioperative period; (2) understand how user performance and perceptions relate to perceived benefits; and (3) identify design considerations to enhance user engagement and behavior change outcomes in mHealth interventions. METHODS We conducted a prospective longitudinal cohort, mixed methods study to evaluate user engagement with MiCarePath, a relaxation-based mHealth intervention. A total of 19 perioperative patients (mean age 41.3 years; 14/19, 74%, female) undergoing elective surgery and reporting sometimes-to-always anxiety were enrolled using 3 recruitment methods. Participants used the app from 10 days before surgery to 4 weeks after surgery. We collected quantitative data on video engagement metrics (eg, duration of watching, response rate to video prompts) and ecological momentary assessments of anxiety and pain. Concurrently, we conducted semistructured, data-prompted interviews at 3 time points to assess user perceptions. These data were integrated using descriptive statistics, repeated-measures ANOVA, and qualitative thematic analysis to examine the relationship between user performance and perceived benefits. RESULTS Eleven participants reported developing or improving relaxation-based self-management strategies (high benefit), whereas 8 reported little benefit from the intervention. The high-benefit group showed significantly greater total watching time (difference 223.8 minutes, 95% CI 95.54-366.46 minutes, P<.001), higher adherence to video prompts (73.45% vs 34.60%, P<.001), and greater perceived helpfulness of the content (79.80% vs 25.50%, P<.001) compared with the low-benefit group. A significant group-by-time interaction effect was observed for engagement (F1,17=17.02, P<.001). No difference was observed in delay in response to video prompts. However, within each group, participant perceptions were not fully reflected in performance. Some participants in the high-benefit group showed decreased video watching after surgery but still reported feeling engaged with the intervention. Interview data revealed that “intentional use” behavior—where users actively seek content to manage symptoms independent of prompts—distinguished these participants. Those who developed intentional use were able to practice relaxation techniques without the app and resume app engagement following contextual disruptions. CONCLUSIONS This study explored user engagement with a relaxation-based mHealth intervention for perioperative care, advancing the literature by integrating user perceptions and performance for digital anxiety and pain management. Results indicate that perceived benefit may not always be reflected in user performance. Intentional use emerges as a promising indicator of effective mHealth engagement in perioperative care. Future designs should aim to foster intentional use through features such as reflection prompts and adaptive notifications. Future work should also develop computational models to detect intentional use and evaluate adaptive interventions in larger cohorts.

Importance: Opioid 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.Objective: To identify the surgical procedures accounting for the highest proportion of opioids dispensed to adults after surgery in the United States.Design, Setting, and Participants: This 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 Measures: The 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.Results: Among 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 Relevance: In 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.

Objective: We sought to compare the identification of unhealthy substance use before surgery using Tobacco, Alcohol, Prescription medication, and other Substance use (TAPS), a standardized 4-item instrument, versus routine clinical documentation in the electronic medical record (EHR). Background: Over 20% of individuals exhibit unhealthy substance use before elective surgery. Routine EHR documentation is often based on nonstandard questions that may not fully capture the extent of substance use and are subject to bias. In contrast, brief standardized screening could provide a more efficient and systematic approach. Methods: We conducted a cross-sectional study among adults (≥18 y) at a preoperative clinic from August to September 2021. Positive screens for unhealthy substances by TAPS were compared with data from the EHR. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were reported. Receiver operating characteristic curves were used to assess diagnostic ability. Multivariable logistic regression was used to estimate the predictors of positive screens by TAPS. Results: The cohort included 240 surgical patients. TAPS screening identified significantly more positive screens than EHR documentation (43.3% vs. 14.2%). Patients with unhealthy substance use were younger (50.8 vs. 56.7 y; P =0.003), and TAPS revealed alcohol misuse in 30.8% of cases, contrasting with 0% in clinician documentation ( P <0.001). Of the 104 TAPS-positive patients, 69.2% were missed by EHR documentation. Sensitivity (31%) and accuracy (AUC=0.65) of clinician documentation for any unhealthy substance use were lower compared with TAPS. Conclusions: Standardized TAPS screening detected preoperative unhealthy substance use more frequently than routine clinician documentation, emphasizing the need for integrating standardized measures into surgical practice to ensure safer perioperative care and outcomes.

Importance: Excess opioid prescribing after surgery can result in prolonged use and diversion. Email feedback based on social norms may reduce the number of pills prescribed.Objective: To assess the effectiveness of 2 social norm-based interventions on reducing guideline-discordant opioid prescribing after surgery.Design, Setting, and Participants: This cluster randomized clinical trial conducted at a large health care delivery system in northern California between October 2021 and October 2022 included general, obstetric/gynecologic, and orthopedic surgeons with patients aged 18 years or older discharged to home with an oral opioid prescription.Interventions: In 19 hospitals, 3 surgical specialties (general, orthopedic, and obstetric/gynecologic) were randomly assigned to a control group or 1 of 2 interventions. The guidelines intervention provided email feedback to surgeons on opioid prescribing relative to institutionally endorsed guidelines; the peer comparison intervention provided email feedback on opioid prescribing relative to that of peer surgeons. Emails were sent to surgeons with at least 2 guideline-discordant prescriptions in the previous month. The control group had no intervention.Main Outcome and Measures: The probability that a discharged patient was prescribed a quantity of opioids above the guideline for the respective procedure during the 12 intervention months.Results: There were 38 235 patients discharged from 640 surgeons during the 12-month intervention period. Control-group surgeons prescribed above guidelines 36.8% of the time during the intervention period compared with 27.5% and 25.4% among surgeons in the peer comparison and guidelines arms, respectively. In adjusted models, the peer comparison intervention reduced guideline-discordant prescribing by 5.8 percentage points (95% CI, −10.5 to −1.1; P = .03) and the guidelines intervention reduced it by 4.7 percentage points (95% CI, −9.4 to −0.1; P = .05). Effects were driven by surgeons who performed more surgeries and had more guideline-discordant prescribing at baseline. There was no significant difference between interventions.Conclusions and Relevance: In this cluster randomized clinical trial, email feedback based on either guidelines or peer comparison reduced opioid prescribing after surgery. Guideline-based feedback was as effective as peer comparison-based feedback. These interventions are simple, low-cost, and scalable, and may reduce downstream opioid misuse.Trial Registration: ClinicalTrials.gov NCT05070338