Electronic Medical Record-Based Nudge Intervention to Increase Comprehensive Molecular Genotyping in Patients With Metastatic Non-Small Cell Lung Cancer: Results From a Prospective Clinical Trial.

PURPOSE: Less than half of the patients with newly diagnosed metastatic non-small cell lung cancer (NSCLC) undergo comprehensive molecular testing. We designed an electronic medical record (EMR)-based "nudge intervention" to prompt plasma-based molecular testing at the time of initial medical oncology consultation. METHODS: A nonrandomized prospective trial was conducted at the University of Pennsylvania's academic practice and two affiliated community practices. Molecular genotyping was performed by tissue- and/or plasma-based next generation sequencing methods. Comprehensive testing was defined as testing for EGFR, ALK, BRAF, ROS1, MET, RET, KRAS, and NTRK. Guideline-concordant treatment was defined as the use of the appropriate first-line (1L) therapy as per the National Comprehensive Cancer Network (NCCN) guidelines. Proportion of patients with comprehensive molecular genotyping results available at any time, molecular results available before 1L therapy, and guideline-concordant 1L treatment were compared between the preintervention and postintervention cohorts using Fisher's exact test or Pearson's chi-squared test. RESULTS: Five hundred and thirty-three patients were included, 376 in the preintervention cohort and 157 in the postintervention cohort. After implementation of the EMR-based nudge, a higher proportion of patients underwent comprehensive molecular testing in the postintervention versus the preintervention cohort (100% v 88%, P = <.001), had results of comprehensive molecular testing available before initiating 1L treatment (97.3% v 91.6%, P = .026), and received NCCN guideline-concordant care (89.8% v 78.2%, P = .035). CONCLUSION: Across three practice sites in a large health system, implementation of a provider team-focused EMR-based nudge intervention was feasible, and led to a higher number of patients with NSCLC undergoing comprehensive molecular genotyping. These findings demonstrate that behavioral nudges can promote molecular testing and should be studied further as a tool to improve guideline-concordant care in both community and academic sites.

Clinician- and Patient-Directed Communication Strategies for Patients With Cancer at High Mortality Risk: A Cluster Randomized Trial.

Importance: Serious illness conversations (SICs) that elicit patients' values, goals, and care preferences reduce anxiety and depression and improve quality of life, but occur infrequently for patients with cancer. Behavioral economic implementation strategies (nudges) directed at clinicians and/or patients may increase SIC completion. Objective: To test the independent and combined effects of clinician and patient nudges on SIC completion. Design, Setting, and Participants: A 2 × 2 factorial, cluster randomized trial was conducted from September 7, 2021, to March 11, 2022, at oncology clinics across 4 hospitals and 6 community sites within a large academic health system in Pennsylvania and New Jersey among 163 medical and gynecologic oncology clinicians and 4450 patients with cancer at high risk of mortality (≥10% risk of 180-day mortality). Interventions: Clinician clusters and patients were independently randomized to receive usual care vs nudges, resulting in 4 arms: (1) active control, operating for 2 years prior to trial start, consisting of clinician text message reminders to complete SICs for patients at high mortality risk; (2) clinician nudge only, consisting of active control plus weekly peer comparisons of clinician-level SIC completion rates; (3) patient nudge only, consisting of active control plus a preclinic electronic communication designed to prime patients for SICs; and (4) combined clinician and patient nudges. Main Outcomes and Measures: The primary outcome was a documented SIC in the electronic health record within 6 months of a participant's first clinic visit after randomization. Analysis was performed on an intent-to-treat basis at the patient level. Results: The study accrued 4450 patients (median age, 67 years [IQR, 59-75 years]; 2352 women [52.9%]) seen by 163 clinicians, randomized to active control (n = 1004), clinician nudge (n = 1179), patient nudge (n = 997), or combined nudges (n = 1270). Overall patient-level rates of 6-month SIC completion were 11.2% for the active control arm (112 of 1004), 11.5% for the clinician nudge arm (136 of 1179), 11.5% for the patient nudge arm (115 of 997), and 14.1% for the combined nudge arm (179 of 1270). Compared with active control, the combined nudges were associated with an increase in SIC rates (ratio of hazard ratios [rHR], 1.55 [95% CI, 1.00-2.40]; P = .049), whereas the clinician nudge (HR, 0.95 [95% CI, 0.64-1.41; P = .79) and patient nudge (HR, 0.99 [95% CI, 0.73-1.33]; P = .93) were not. Conclusions and Relevance: In this cluster randomized trial, nudges combining clinician peer comparisons with patient priming questionnaires were associated with a marginal increase in documented SICs compared with an active control. Combining clinician- and patient-directed nudges may help to promote SICs in routine cancer care. Trial Registration: ClinicalTrials.gov Identifier: NCT04867850.

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.

Distinct genomic and immunologic tumor evolution in germline TP53-driven breast cancers.

Pathogenic germline TP53 alterations cause Li-Fraumeni Syndrome (LFS), and breast cancer is the most common cancer in LFS females. We performed first of its kind multimodal analysis of LFS breast cancer (LFS-BC) compared to sporadic premenopausal BC. Nearly all LFS-BC underwent biallelic loss of TP53 with no recurrent oncogenic variants except ERBB2 (HER2) amplification. Compared to sporadic BC, in situ and invasive LFS-BC exhibited a high burden of short amplified aneuploid segments (SAAS). Pro-apoptotic p53 target genes BAX and TP53I3 failed to be up-regulated in LFS-BC as was seen in sporadic BC compared to normal breast tissue. LFS-BC had lower CD8+ T-cell infiltration compared to sporadic BC yet higher levels of proliferating cytotoxic T-cells. Within LFS-BC, progression from in situ to invasive BC was marked by an increase in chromosomal instability with a decrease in proliferating cytotoxic T-cells. Our study uncovers critical events in mutant p53-driven tumorigenesis in breast tissue.

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.

The association between telemedicine, advance care planning, and unplanned hospitalizations among high-risk patients with cancer.

BACKGROUND: Despite the widespread implementation of telemedicine, there are limited data regarding its impact on key components of care for patients with incurable or high-risk cancer. For these patients, high-quality care requires detailed conversations regarding treatment priorities (advance care planning) and clinical care to minimize unnecessary acute care (unplanned hospitalizations). Whether telemedicine affects these outcomes relative to in-person clinic visits was examined among patients with cancer at high risk for 6-month mortality. METHODS: This retrospective cohort study included adult patients with cancer with any tumor type treated at the University of Pennsylvania who were newly identified between April 1 and December 31, 2020, to be at high risk for 6-month mortality via a validated machine learning algorithm. Separate modified Poisson regressions were used to assess the occurrence of advance care planning and unplanned hospitalizations for telemedicine as compared to in-person visits. Additional analyses were done comparing telemedicine type (video or phone) as compared to in-person clinic visits. RESULTS: The occurrence of advance care planning was similar between telemedicine and in-person visits (6.8% vs. 6.0%; adjusted risk ratio [aRR], 1.25; 95% CI, 0.92-1.69). In regard to telemedicine subtype, patients exposed to video encounters were modestly more likely to have documented advance care planning in comparison to those seen in person (7.5% vs. 6.0%; aRR, 1.48; 95% CI, 1.03-2.11). The 3-month risk for unplanned hospitalization was comparable for telemedicine compared to in-person clinic encounters (21% vs. 18%; aRR, 1.06; 95% CI, 0.81-1.38). CONCLUSIONS: In this study, care delivered by telemedicine, compared to in-person clinic visits, produced comparable rates of advance care planning conversations without increasing hospitalizations, which suggests that vulnerable patients can be managed safely by telemedicine.

Protocol for a pragmatic stepped wedge cluster randomized clinical trial testing behavioral economic implementation strategies to increase supplemental breast MRI screening among patients with extremely dense breasts.

BACKGROUND: Increased breast density augments breast cancer risk and reduces mammography sensitivity. Supplemental breast MRI screening can significantly increase cancer detection among women with dense breasts. However, few women undergo this exam, and screening is consistently lower among racially minoritized populations. Implementation strategies informed by behavioral economics ("nudges") can promote evidence-based practices by improving clinician decision-making under conditions of uncertainty. Nudges directed toward clinicians and patients may facilitate the implementation of supplemental breast MRI. METHODS: Approximately 1600 patients identified as having extremely dense breasts after non-actionable mammograms, along with about 1100 clinicians involved with their care at 32 primary care or OB/GYN clinics across a racially diverse academically based health system, will be enrolled. A 2 × 2 randomized pragmatic trial will test nudges to patients, clinicians, both, or neither to promote supplemental breast MRI screening. Before implementation, rapid cycle approaches informed by clinician and patient experiences and behavioral economics and health equity frameworks guided nudge design. Clinicians will be clustered into clinic groups based on existing administrative departments and care patterns, and these clinic groups will be randomized to have the nudge activated at different times per a stepped wedge design. Clinicians will receive nudges integrated into the routine mammographic report or sent through electronic health record (EHR) in-basket messaging once their clinic group (i.e., wedge) is randomized to receive the intervention. Independently, patients will be randomized to receive text message nudges or not. The primary outcome will be defined as ordering or scheduling supplemental breast MRI. Secondary outcomes include MRI completion, cancer detection rates, and false-positive rates. Patient sociodemographic information and clinic-level variables will be examined as moderators of nudge effectiveness. Qualitative interviews conducted at the trial's conclusion will examine barriers and facilitators to implementation. DISCUSSION: This study will add to the growing literature on the effectiveness of behavioral economics-informed implementation strategies to promote evidence-based interventions. The design will facilitate testing the relative effects of nudges to patients and clinicians and the effects of moderators of nudge effectiveness, including key indicators of health disparities. The results may inform the introduction of low-cost, scalable implementation strategies to promote early breast cancer detection. TRIAL REGISTRATION: ClinicalTrials.gov NCT05787249. Registered on March 28, 2023.

Protocol to evaluate sequential electronic health record-based strategies to increase genetic testing for breast and ovarian cancer risk across diverse patient populations in gynecology practices.

BACKGROUND: Germline genetic testing is recommended by the National Comprehensive Cancer Network (NCCN) for individuals including, but not limited to, those with a personal history of ovarian cancer, young-onset (< 50 years) breast cancer, and a family history of ovarian cancer or male breast cancer. Genetic testing is underused overall, and rates are consistently lower among Black and Hispanic populations. Behavioral economics-informed implementation strategies, or nudges, directed towards patients and clinicians may increase the use of this evidence-based clinical practice. METHODS: Patients meeting eligibility for germline genetic testing for breast and ovarian cancer will be identified using electronic phenotyping algorithms. A pragmatic cohort study will test three sequential strategies to promote genetic testing, two directed at patients and one directed at clinicians, deployed in the electronic health record (EHR) for patients in OB-GYN clinics across a diverse academic medical center. We will use rapid cycle approaches informed by relevant clinician and patient experiences, health equity, and behavioral economics to optimize and de-risk our strategies and methods before trial initiation. Step 1 will send patients messages through the health system patient portal. For non-responders, step 2 will reach out to patients via text message. For non-responders, Step 3 will contact patients' clinicians using a novel "pend and send" tool in the EHR. The primary implementation outcome is engagement with germline genetic testing for breast and ovarian cancer predisposition, defined as a scheduled genetic counseling appointment. Patient data collected through the EHR (e.g., race/ethnicity, geocoded address) will be examined as moderators of the impact of the strategies. DISCUSSION: This study will be one of the first to sequentially examine the effects of patient- and clinician-directed strategies informed by behavioral economics on engagement with breast and ovarian cancer genetic testing. The pragmatic and sequential design will facilitate a large and diverse patient sample, allow for the assessment of incremental gains from different implementation strategies, and permit the assessment of moderators of strategy effectiveness. The findings may help determine the impact of low-cost, highly transportable implementation strategies that can be integrated into healthcare systems to improve the use of genomic medicine. TRIAL REGISTRATION: ClinicalTrials.gov. NCT05721326. Registered February 10, 2023. https://www. CLINICALTRIALS: gov/study/NCT05721326.

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.

Biallelic BRCA Loss and Homologous Recombination Deficiency in Nonbreast/Ovarian Tumors in Germline BRCA1/2 Carriers.

PURPOSE: Breast and ovarian tumors in germline BRCA1/2 carriers undergo allele-specific loss of heterozygosity, resulting in homologous recombination deficiency (HRD) and sensitivity to poly-ADP-ribose polymerase (PARP) inhibitors. This study investigated whether biallelic loss and HRD also occur in primary nonbreast/ovarian tumors that arise in germline BRCA1/2 carriers. METHODS: A clinically ascertained cohort of BRCA1/2 carriers with a primary nonbreast/ovarian cancer was identified, including canonical (prostate and pancreatic cancers) and noncanonical (all other) tumor types. Whole-exome sequencing or clinical sequencing results (n = 45) were analyzed. A pan-cancer analysis of nonbreast/ovarian primary tumors from germline BRCA1/2 carriers from The Cancer Genome Atlas (TCGA, n = 73) was used as a validation cohort. RESULTS: Ages of nonbreast/ovarian cancer diagnosis in germline BRCA1/2 carriers were similar to controls for the majority of cancer types. Nine of 45 (20%) primary nonbreast/ovarian tumors from germline BRCA1/2 carriers had biallelic loss of BRCA1/2 in the clinical cohort, and 23 of 73 (32%) in the TCGA cohort. In the combined cohort, 35% and 27% of primary canonical and noncanonical BRCA tumor types, respectively, had biallelic loss. High HRD scores (HRDex > 42) were detected in 81% of tumors with biallelic BRCA loss compared with 22% (P < .001) of tumors without biallelic BRCA loss. No differences in genomic profile, including mutational signatures, mutation spectrum, tumor mutational burden, or microsatellite instability, were found in primary nonbreast/ovarian tumors with or without biallelic BRCA1/2 loss. CONCLUSION: A proportion of noncanonical primary tumors have biallelic loss and evidence of HRD. Our data suggest that assessment of biallelic loss and HRD could supplement identification of germline BRCA1/2 mutations in selection of patients for platinum or PARP inhibitor therapy.

Cluster Randomized Pragmatic Clinical Trial Testing Behavioral Economic Implementation Strategies to Improve Tobacco Treatment for Patients With Cancer Who Smoke.

PURPOSE: Few cancer centers systematically engage patients with evidence-based tobacco treatment despite its positive effect on quality of life and survival. Implementation strategies directed at patients, clinicians, or both may increase tobacco use treatment (TUT) within oncology. METHODS: We conducted a four-arm cluster-randomized pragmatic trial across 11 clinical sites comparing the effect of strategies informed by behavioral economics on TUT engagement during oncology encounters with cancer patients. We delivered electronic health record (EHR)-based nudges promoting TUT across four nudge conditions: patient only, clinician only, patient and clinician, or usual care. Nudges were designed to counteract cognitive biases that reduce TUT engagement. The primary outcome was TUT penetration, defined as the proportion of patients with documented TUT referral or a medication prescription in the EHR. Generalized estimating equations were used to estimate the parameters of a linear model. RESULTS: From June 2021 to July 2022, we randomly assigned 246 clinicians in 95 clusters, and collected TUT penetration data from their encounters with 2,146 eligible patients who smoke receiving oncologic care. Intent-to-treat (ITT) analysis showed that the clinician nudge led to a significant increase in TUT penetration versus usual care (35.6% v 13.5%; OR = 3.64; 95% CI, 2.52 to 5.24; P < .0001). Completer-only analysis (N = 1,795) showed similar impact (37.7% clinician nudge v 13.5% usual care; OR = 3.77; 95% CI, 2.73 to 5.19; P < .0001). Clinician type affected TUT penetration, with physicians less likely to provide TUT than advanced practice providers (ITT OR = 0.67; 95% CI, 0.51 to 0.88; P = .004). CONCLUSION: EHR nudges, informed by behavioral economics and aimed at oncology clinicians, appear to substantially increase TUT penetration. Adding patient nudges to the implementation strategy did not affect TUT penetration rates.

Association Between Availability of Molecular Genotyping Results and Overall Survival in Patients With Advanced Nonsquamous Non-Small-Cell Lung Cancer.

PURPOSE: Current guidelines recommend molecular genotyping for patients newly diagnosed with metastatic nonsquamous (mNSq) non-small-cell lung cancer (NSCLC). The association between availability of molecular genotyping before first line (1L) therapy and overall survival (OS) is not known. METHODS: We conducted a real-world cohort study using electronic health records in patients newly diagnosed with mNSq NSCLC. Cox proportional-hazards multivariable regression models were constructed to examine the association between OS and test result availability before 1L therapy, adjusting for covariates. Additional analyses were conducted to assess the consistency and strength of the relationship. Multivariable logistic regression models were used to examine the association between concurrent tissue and plasma testing (v tissue alone) and result availability. RESULTS: Three hundred twenty-six patients were included, 80% (261/326) with results available before 1L (available testing group), and 20% (65/326) without results available (unavailable testing group). With 14.2-month median follow-up, patients in the available testing group had significantly longer OS relative to the unavailable testing group (adjusted hazard ratio, 0.43; 95% CI, 0.30 to 0.62; P < .0001). The adjusted odds of availability of results before 1L therapy was higher with concurrent tissue and plasma testing (v tissue testing alone; adjusted odds ratio, 2.06; 95% CI, 1.09 to 3.90; P = .026). CONCLUSION: Among patients with mNSq NSCLC in a real-world cohort, availability of molecular genotyping results before 1L therapy was associated with significantly better OS. Concurrent tissue and plasma testing was associated with a higher odds of availability of results before 1L therapy. These findings warrant renewed attention to the completion of molecular genotyping before 1L therapy.

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.

Acute toxicity in patients treated with concurrent chemoradiotherapy with proton versus intensity-modulated radiation therapy for nonmetastatic head and neck cancers.

BACKGROUND: We evaluated if proton therapy is associated with decreased acute toxicities compared to intensity-modulated radiation therapy (IMRT) in patients receiving concurrent chemoradiotherapy for head and neck cancers. METHODS: We analyzed 580 patients with nonmetastatic head and neck cancers. Primary endpoint was any 90-day grade ≥3 toxicity, prospectively collected and graded per CTCAEv4. Modified Poisson regression models were used. RESULTS: Ninety-five patients received proton and 485 IMRT. The proton group had more HPV-positive tumors (65.6 vs. 58.0%, p = 0.049), postoperative treatment (76.8 vs. 62.1%, p = 0.008), unilateral neck treatment (18.9 vs. 6.6%, p < 0.001) and significantly lower doses to organs-at-risk compared to IMRT group. Adjusted for patient and treatment characteristics, the proton group had decreased grade 2 dysgeusia (RR0.67, 95%CI 0.53-0.84, p = 0.004) and a trend toward lower grade ≥3 toxicities (RR0.60, 95%CI 0.41-0.88, p = 0.06). CONCLUSIONS: Proton therapy was associated with significantly reduced grade 2 dysgeusia and nonstatistically significant decrease in acute grade ≥3 toxicities compared to IMRT.