University of Pennsylvania Telehealth Research Center of Excellence.

Drawing from insights from communication science and behavioral economics, the University of Pennsylvania Telehealth Research Center of Excellence (Penn TRACE) is designing and testing telehealth strategies with the potential to transform access to care, care quality, outcomes, health equity, and health-care efficiency across the cancer care continuum, with an emphasis on understanding mechanisms of action. Penn TRACE uses lung cancer care as an exemplar model for telehealth across the care continuum, from screening to treatment to survivorship. We bring together a diverse and interdisciplinary team of international experts and incorporate rapid-cycle approaches and mixed methods evaluation in all center projects. Our initiatives include a pragmatic sequential multiple assignment randomized trial to compare the effectiveness of telehealth strategies to increase shared decision-making for lung cancer screening and 2 pilot projects to test the effectiveness of telehealth to improve cancer care, identify multilevel mechanisms of action, and lay the foundation for future pragmatic trials. Penn TRACE aims to produce new fundamental knowledge and advance telehealth science in cancer care at Penn and nationally.

Pilot Study of a Mobile Phone Chatbot for Medication Adherence and Toxicity Management Among Patients With GI Cancers on Capecitabine.

PURPOSE: Capecitabine is an oral chemotherapy used to treat many gastrointestinal cancers. Its complex dosing and narrow therapeutic index make medication adherence and toxicity management crucial for quality care. METHODS: We conducted a pilot study of PENNY-GI, a mobile phone text messaging-based chatbot that leverages algorithmic surveys and natural language processing to promote medication adherence and toxicity management among patients with gastrointestinal cancers on capecitabine. Eligibility initially included all capecitabine-containing regimens but was subsequently restricted to capecitabine monotherapy because of challenges in integrating PENNY-GI with radiation and intravenous chemotherapy schedules. We used design thinking principles and real-time data on safety, accuracy, and usefulness to make iterative refinements to PENNY-GI with the goal of minimizing the proportion of text messaging exchanges with incorrect medication or symptom management recommendations. All patients were invited to participate in structured exit interviews to provide feedback on PENNY-GI. RESULTS: We enrolled 40 patients (median age 64.5 years, 52.5% male, 62.5% White, 55.0% with colorectal cancer, 50.0% on capecitabine monotherapy). We identified 284 of 3,895 (7.3%) medication-related and 13 of 527 (2.5%) symptom-related text messaging exchanges with incorrect recommendations. In exit interviews with 24 patients, participants reported finding the medication reminders reliable and user-friendly, but the symptom management tool was too simplistic to be helpful. CONCLUSION: Although PENNY-GI provided accurate recommendations in >90% of text messaging exchanges, we identified multiple limitations with respect to the intervention's generalizability, usefulness, and scalability. Lessons from this pilot study should inform future efforts to develop and implement digital health interventions in oncology.

Remote Patient-Reported Outcomes and Activity Monitoring to Improve Patient-Clinician Communication Regarding Symptoms and Functional Status: A Randomized Controlled Trial.

PURPOSE: Routine collection of patient-generated health data (PGHD) may promote earlier recognition of symptomatic and functional decline. This trial assessed the impact of an intervention integrating remote PGHD collection with patient nudges on symptom and functional status understanding between patients with advanced cancer and their oncology team. METHODS: This three-arm randomized controlled trial was conducted from November 19, 2020, to December 17, 2021, at a large tertiary oncology practice. We enrolled patients with stage IV GI and lung cancers undergoing chemotherapy. Over 6 months, patients in two intervention arms received PROStep-weekly text message-based symptom surveys and passive activity monitoring using a wearable accelerometer. PGHD were summarized in dashboards given to patients' oncology team before appointments. One intervention arm received an additional text-based active choice prompt to discuss worsening symptoms or functional status with their clinician. Control patients did not receive PROStep. The coprimary outcomes patient perceptions of oncology team symptom and functional understanding at 6 months were measured on a 1-5 Likert scale (5 = high understanding). RESULTS: One hundred eight patients enrolled: 55% male, 81% White, and 77% had GI cancers. Patient-reported clinician understanding did not differ between control and intervention arms for symptoms (4.5 v 4.5; P = .87) or functional status (4.5 v 4.3; P = .31). In the intervention arms, combined patient adherence to weekly symptom reports and daily activity monitoring was 64% and 53%, respectively. Intervention patients in the PROStep versus PROStep + active choice arms reported low burden from wearing the accelerometer (mean burden [standard deviation], 2.7 [1.3] v 2.1 [1.3]; P = .15) and completing surveys (2.1 [1.2] v 1.9 [1.3]; P = .44). CONCLUSION: Patients receiving PROStep reported high understanding of symptoms and functional status from their oncology team, although this did not differ from controls.

Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.

Re-envisioning the Paradigm for Oncology Electronic Health Record Documentation by Paying for What Matters for Patients, Quality, and Research.

This Viewpoint discusses re-envisioning and incentivizing a unique approach to oncology electronic health record documentation.

Development of Machine Learning Algorithms Incorporating Electronic Health Record Data, Patient-Reported Outcomes, or Both to Predict Mortality for Outpatients With Cancer.

PURPOSE: Machine learning (ML) algorithms that incorporate routinely collected patient-reported outcomes (PROs) alongside electronic health record (EHR) variables may improve prediction of short-term mortality and facilitate earlier supportive and palliative care for patients with cancer. METHODS: We trained and validated two-phase ML algorithms that incorporated standard PRO assessments alongside approximately 200 routinely collected EHR variables, among patients with medical oncology encounters at a tertiary academic oncology and a community oncology practice. RESULTS: Among 12,350 patients, 5,870 (47.5%) completed PRO assessments. Compared with EHR- and PRO-only algorithms, the EHR + PRO model improved predictive performance in both tertiary oncology (EHR + PRO v EHR v PRO: area under the curve [AUC] 0.86 [0.85-0.87] v 0.82 [0.81-0.83] v 0.74 [0.74-0.74]) and community oncology (area under the curve 0.89 [0.88-0.90] v 0.86 [0.85-0.88] v 0.77 [0.76-0.79]) practices. CONCLUSION: Routinely collected PROs contain added prognostic information not captured by an EHR-based ML mortality risk algorithm. Augmenting an EHR-based algorithm with PROs resulted in a more accurate and clinically relevant model, which can facilitate earlier and targeted supportive care for patients with cancer.

Training digital natives to transform healthcare: a 5-tiered approach for integrating clinical informatics into undergraduate medical education.

Expansive growth in the use of health information technology (HIT) has dramatically altered medicine without translating to fully realized improvements in healthcare delivery. Bridging this divide will require healthcare professionals with all levels of expertise in clinical informatics. However, due to scarce opportunities for exposure and training in informatics, medical students remain an underdeveloped source of potential informaticists. To address this gap, our institution developed and implemented a 5-tiered clinical informatics curriculum at the undergraduate medical education level: (1) a practical orientation to HIT for rising clerkship students; (2) an elective for junior students; (3) an elective for senior students; (4) a longitudinal area of concentration; and (5) a yearlong predoctoral fellowship in operational informatics at the health system level. Most students found these offerings valuable for their training and professional development. We share lessons and recommendations for medical schools and health systems looking to implement similar opportunities.

Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients.

One core measure of healthcare quality set forth by the Institute of Medicine is whether care decisions match patient goals. High-quality "serious illness communication" about patient goals and prognosis is required to support patient-centered decision-making, however current methods are not sensitive enough to measure the quality of this communication or determine whether care delivered matches patient priorities. Natural language processing (NLP) offers an efficient method for identification and evaluation of documented serious illness communication, which could serve as the basis for future quality metrics in oncology and other forms of serious illness. In this study, we trained NLP algorithms to identify and characterize serious illness communication with oncology patients.

Real-World Adherence to Patient-Reported Outcome Monitoring as a Cancer Care Quality Metric.

PURPOSE: Routine collection of patient-reported outcomes (PROs) for patients with advanced solid malignancies is an evidence-based practice and critical component of high-quality cancer care, but real-world adherence is poorly characterized. We sought to describe real-world adherence to PRO monitoring and its potential predictors. METHODS: We conducted a retrospective cross-sectional study using deidentified electronic health record data from a National Cancer Institute Cancer Center, encompassing one academic and two community sites. Participants included individuals with lung cancer receiving systemic therapy from January 1 to December 31, 2019. The primary outcome was patient-level adherence, defined as the proportion of treatment visits during which a PRO questionnaire (spanning symptoms, functional status, and global quality-of-life domains) was completed within 30 days. Practice-level performance was calculated as unadjusted mean patient-level adherence. We modeled patient-level adherence using multivariable ordinary least squares regression and identified covariates associated with adherence using a significance threshold of P < .05. RESULTS: In 2019, there were 18,604 encounters for 1,105 patients with lung cancer (mean [standard deviation] age 65.8 [10.2] years; 621 [56.2%] female; 216 [19.6%] Black) receiving systemic therapy. The mean patient-level PRO adherence ranged from 27.2% to 70.0% across sites and was 49.4% overall. Advanced age (≥ 65 years) and Black or African American race were negatively associated with PRO adherence (P < .01). CONCLUSION: Across this real-world cohort of patients undergoing treatment for lung cancer, adherence to PRO monitoring lagged that achieved in seminal clinical trials, with potential age- and race-based disparities, demonstrating an implementation gap that could be addressed with standardized reporting of an adherence-based quality metric.

Patient and clinician nudges to improve symptom management in advanced cancer using patient-generated health data: study protocol for the PROStep randomised controlled trial.

INTRODUCTION: Patients with advanced cancers often face significant symptoms from their cancer and adverse effects from cancer-associated therapy. Patient-generated health data (PGHD) are routinely collected information about symptoms and activity levels that patients either directly report or passively record using devices such as wearable accelerometers. The objective of this study was to test the impact of an intervention integrating remote collection of PGHD with clinician and patient nudges to inform communication between patients with advanced cancer and their oncology team regarding symptom burden and functional status. METHODS AND ANALYSIS: This single-centre prospective randomised controlled trial randomises patients with metastatic gastrointestinal or lung cancers into one of three arms: (A) usual care, (B) an intervention that integrates PGHD (including weekly text-based symptom surveys and passively recorded step counts) into a dashboard delivered to oncology clinicians at each visit and (C) the same intervention as arm B but with an additional text-based active choice intervention to patients to encourage discussing their symptoms with their oncology team. The study will enrol approximately 125 participants. The coprimary outcomes are patient perceptions of their oncology team's understanding of their symptoms and their functional status. Secondary outcomes are intervention utility and adherence. ETHICS AND DISSEMINATION: This study has been approved by the institutional review board at the University of Pennsylvania. Study results will be disseminated using methods that describe the results in ways that key stakeholders can best understand and implement. TRIAL REGISTRATION NUMBERS: NCT04616768 and 843 616.

Adoption of Patient-Generated Health Data in Oncology: A Report From the NCCN EHR Oncology Advisory Group.

BACKGROUND: Collecting, monitoring, and responding to patient-generated health data (PGHD) are associated with improved quality of life and patient satisfaction, and possibly with improved patient survival in oncology. However, the current state of adoption, types of PGHD collected, and degree of integration into electronic health records (EHRs) is unknown. METHODS: The NCCN EHR Oncology Advisory Group formed a Patient-Reported Outcomes (PRO) Workgroup to perform an assessment and provide recommendations for cancer centers, researchers, and EHR vendors to advance the collection and use of PGHD in oncology. The issues were evaluated via a survey of NCCN Member Institutions. Questions were designed to assess the current state of PGHD collection, including how, what, and where PGHD are collected. Additionally, detailed questions about governance and data integration into EHRs were asked. RESULTS: Of 28 Member Institutions surveyed, 23 responded. The collection and use of PGHD is widespread among NCCN Members Institutions (96%). Most centers (90%) embed at least some PGHD into the EHR, although challenges remain, as evidenced by 88% of respondents reporting the use of instruments not integrated. Forty-seven percent of respondents are leveraging PGHD for process automation and adherence to best evidence. Content type and integration touchpoints vary among the members, as well as governance maturity. CONCLUSIONS: The reported variability regarding PGHD suggests that it may not yet have reached its full potential for oncology care delivery. As the adoption of PGHD in oncology continues to expand, opportunities exist to enhance their utility. Among the recommendations for cancer centers is establishment of a governance process that includes patients. Researchers should consider determining which PGHD instruments confer the highest value. It is recommended that EHR vendors collaborate with cancer centers to develop solutions for the collection, interpretation, visualization, and use of PGHD.

Quantifying the impact of the COVID-19 pandemic on gastrointestinal cancer care delivery.

BACKGROUND AND AIM: This study quantifies how changes in healthcare utilization and delivery during the first months of the COVID-19 pandemic have altered the presentation, treatment, and management of patients with gastrointestinal (GI) malignancies within an academic health system. METHODS AND RESULTS: Patients diagnosed with a GI malignancy (ICD10: C15-C26) who received medical care within the health system during the observation period (first 44 weeks of 2019 and 2020) were identified for a retrospective cohort study. Deidentified patient encounter parameters were collected for this observation period and separated into pre-pandemic (weeks 1-10) and early pandemic (weeks 11-20) study periods. Difference-in-difference analyses adjusted for week-specific and year-specific effects quantified the impact of the COVID-19 pandemic on care delivery between pre-pandemic and early pandemic study periods in 2020. Across all GI malignancies, the COVID-19 pandemic has been associated with a significant decline in the number of patients with new patient visits (NPVs) (p = 1.2 × 10-4 ), Radiology encounters (p = 1.9 × 10-7 ), Surgery encounters (p = 1.6 × 10-3 ), Radiation Oncology encounters (p = 4.1 × 10-3 ), and infusion visits (6.1 × 10-5 ). Subgroup analyses revealed cancer-specific variations in changes to delivery. Patients with colorectal cancer (CRC) had the most significant decrease in NPVs (p = 7.1 × 10-5 ), which was significantly associated with a concomitant decrease in colonoscopies performed during the early pandemic period (r2  = 0.722, p = 2.1 × 10-10 ). CONCLUSIONS: The COVID-19 pandemic has been associated with significant disruptions to care delivery. While these effects were appreciated broadly across GI malignancies, CRC, diagnosed and managed by periodic screening, has been affected most acutely.

New Operative Reporting Standards: Where We Stand Now and Opportunities for Innovation.

BACKGROUND: The American College of Surgeons Commission on Cancer's (CoC) new operative standards for breast cancer, melanoma, and colon cancer surgeries will require that surgeons provide synoptic documentation of essential oncologic elements within operative reports. Prior to designing and implementing an electronic tool to support synoptic reporting, we evaluated current documentation practices at our institution to understand baseline concordance with these standards. METHODS: Applicable procedures performed between 1 January 2018 and 31 December 2018 were included. Two independent reviewers evaluated sequential operative notes, up to a total of 100 notes, for documentation of required elements. Complete concordance (CC) was defined as explicit documentation of all required CoC elements. Mean percentage CC and surgeon-specific CC were calculated for each procedure. Interrater reliability was assessed via Cohen's kappa statistic. RESULTS: For sentinel lymph node biopsy, mean CC was 66% (n = 100), with surgeon-specific CC ranging from 6 to 100%, and for axillary dissection, mean CC was 12% (n = 89) and surgeon-specific CC ranged from 0 to 47%. The single surgeon performing melanoma wide local excision had a mean CC of 98% (n = 100). For colon resections, mean CC was 69% (n = 96) and surgeon-specific CC ranged from 39 to 94%. Kappa scores were 0.77, 0.78, -0.15, and 0.78, respectively. CONCLUSIONS: We identified heterogeneity in current documentation practices. In our cohort, rates of baseline concordance varied across surgeons and procedures. Currently, documentation elements are interspersed within the operative report, posing challenges to chart abstraction with resulting imperfect interrater reliability. This presents an exciting opportunity to innovate and improve compliance by introducing an electronic synoptic documentation tool.

Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank.

PURPOSE: Genome-wide association studies have identified hundreds of single nucleotide variations (formerly single nucleotide polymorphisms) associated with several cancers, but the predictive ability of polygenic risk scores (PRSs) is unclear, especially among non-Whites. METHODS: PRSs were derived from genome-wide significant single-nucleotide variations for 15 cancers in 20,079 individuals in an academic biobank. We evaluated the improvement in discriminatory accuracy by including cancer-specific PRS in patients of genetically-determined African and European ancestry. RESULTS: Among the individuals of European genetic ancestry, PRSs for breast, colon, melanoma, and prostate were significantly associated with their respective cancers. Among the individuals of African genetic ancestry, PRSs for breast, colon, prostate, and thyroid were significantly associated with their respective cancers. The area under the curve of the model consisting of age, sex, and principal components was 0.621 to 0.710, and it increased by 1% to 4% with the inclusion of PRS in individuals of European genetic ancestry. In individuals of African genetic ancestry, area under the curve was overall higher in the model without the PRS (0.723-0.810) but increased by <1% with the inclusion of PRS for most cancers. CONCLUSION: PRS moderately increased the ability to discriminate the cancer status in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors in non-White populations to incorporate PRS into cancer risk assessment.

Endocrine Surgical Procedures During COVID-19: Patient Prioritization and Time to Surgery.

BACKGROUND: We tracked endocrine surgery patients with treatment delays due to COVID-19 to investigate the relationship between physician assigned priority scoring (PAPS), the Medically Necessary, Time Sensitive (MeNTS) scoring system and delay to surgery. MATERIAL & METHODS: Patients scheduled for endocrine surgery or clinically evaluated during COVID-19-related elective surgery hold at our institution (2/26/20-5/1/20) were prospectively enrolled. PAPS was assigned based on categories of high, moderate, or low risk, consistent with the American College of Surgeons' priority system. MeNTS scores were calculated. The primary outcome was delay to surgery. Descriptive statistics were performed, and receiver operator characteristic (ROC) curves and area under the curve (AUC) values were calculated for PAPS and MeNTS. RESULTS: Of 146 patients included, 68% (n = 100) were female; the median age was 60 years (IQR:43,67). Mean delay to surgery was significantly shorter (P = 0.01) in patients with high PAPS (35 d), compared with moderate (61 d) and low (79 d) PAPS groups. MeNTS scores were provided for 105 patients and were analyzed by diagnosis. Patients with benign thyroid disease (n = 17) had a significantly higher MeNTS score than patients with thyroid disease which was malignant/suspicious for malignancy (n = 44) patients (51.5 versus 47.6, P = 0.034). Higher PAPS correlated well with a delay to surgery of <30 d (AUC: 0.72). MeNTS score did not correlate well with delay to surgery <30 d (AUC: 0.52). CONCLUSION: PAPS better predicted delay to surgery than MeNTS scores. PAPS may incorporate more complex components of clinical decision-making which are not captured in the MeNTS score.

Why Is the Electronic Health Record So Challenging for Research and Clinical Care?

BACKGROUND: The electronic health record (EHR) has become increasingly ubiquitous. At the same time, health professionals have been turning to this resource for access to data that is needed for the delivery of health care and for clinical research. There is little doubt that the EHR has made both of these functions easier than earlier days when we relied on paper-based clinical records. Coupled with modern database and data warehouse systems, high-speed networks, and the ability to share clinical data with others are large number of challenges that arguably limit the optimal use of the EHR OBJECTIVES: Our goal was to provide an exhaustive reference for those who use the EHR in clinical and research contexts, but also for health information systems professionals as they design, implement, and maintain EHR systems. METHODS: This study includes a panel of 24 biomedical informatics researchers, information technology professionals, and clinicians, all of whom have extensive experience in design, implementation, and maintenance of EHR systems, or in using the EHR as clinicians or researchers. All members of the panel are affiliated with Penn Medicine at the University of Pennsylvania and have experience with a variety of different EHR platforms and systems and how they have evolved over time. RESULTS: Each of the authors has shared their knowledge and experience in using the EHR in a suite of 20 short essays, each representing a specific challenge and classified according to a functional hierarchy of interlocking facets such as usability and usefulness, data quality, standards, governance, data integration, clinical care, and clinical research. CONCLUSION: We provide here a set of perspectives on the challenges posed by the EHR to clinical and research users.

Venous thromboembolism detected by FDG-PET/CT in cancer patients: a common, yet life-threatening observation.

Cancer patients are at markedly increased risk for venous thromboembolism (VTE). Early detection of VTE may decrease morbidity and mortality in this population. We conducted this study to evaluate the ability of FDG-PET/CT to detect thrombosis in cancer patients. This retrospective study included 131 cancer patients with a history of deep vein thrombosis (DVT) or pulmonary embolism (PE) referred for 2-deoxy-2-[18F]-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT). All subjects underwent PET/CT imaging 60 minutes after FDG injection. Images were visually assessed for increased FDG uptake within the venous lumen. For positive cases, clinical follow-up and Doppler ultrasonography and/or contrast-enhanced CT scans were reviewed. FDG-PET/CT revealed abnormal uptake in the venous system of 26 (19.8%) patients. Eighteen (69.2%) had a history of DVT, and 13 (50%) had a history of PE. The most common site of thrombosis was the inferior vena cava (IVC) (n=14, 53.8%), followed by lower extremities veins (n=9, 34.6%), jugular veins (n=2, 7.7%), and superior vena cava (n=1, 3.8%). The presence of thrombi was confirmed by reviewing clinical follow-up in 6 (23.1%) patients. Among this group, thrombosis was detected in lower extremity veins (n=4, 15.8%), jugular veins (n=1, 3.8%), and IVC (n=1, 3.8%). Our study demonstrates that thrombi prior to their clinical manifestation can be detected by FDG-PET/CT in cancer patients. Moving forward, physicians must carefully consider the venous system when reporting FDG-PET/CT for cancer patients.

Risk of Persistent Opioid Use following Major Surgery in Matched Samples of Patients with and without Cancer.

BACKGROUND: The opioid crisis has reached epidemic proportions, yet risk of persistent opioid use following curative intent surgery for cancer and factors influencing this risk are not well understood. METHODS: We used electronic health record data from 3,901 adult patients who received a prescription for an opioid analgesic related to hysterectomy or large bowel surgery from January 1, 2013, through June 30, 2018. Patients with and without a cancer diagnosis were matched on the basis of demographic, clinical, and procedural variables and compared for persistent opioid use. RESULTS: Cancer diagnosis was associated with greater risk for persistent opioid use after hysterectomy [18.9% vs. 9.6%; adjusted OR (aOR), 2.26; 95% confidence interval (CI), 1.38-3.69; P = 0.001], but not after large bowel surgery (28.3% vs. 24.1%; aOR 1.25; 95% CI, 0.97-1.59; P = 0.09). In the cancer hysterectomy cohort, persistent opioid use was associated with cancer stage (increased rates among those with stage III cancer compared with stage I) and use of neoadjuvant or adjuvant chemotherapy; however, these factors were not associated with persistent opioid use in the large bowel cohort. CONCLUSIONS: Patients with cancer may have an increased risk of persistent opioid use following hysterectomy. IMPACT: Risks and benefits of opioid analgesia for surgical pain among patients with cancer undergoing hysterectomy should be carefully considered.