Innovations in research and clinical care using patient-generated health data.

Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and treatment histories, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, smartphones, and the Internet of Things have facilitated new ways to collect PGHD during clinic visits and in daily life. The goal of the current review was to provide an overview of the current clinical, regulatory, technological, and analytic landscape as it relates to PGHD in oncology research and care. The review begins with a rationale for PGHD as described by the US Food and Drug Administration, the Institute of Medicine, and other regulatory and scientific organizations. The evidence base for clinic-based and remote symptom monitoring using PGHD is described, with an emphasis on PROs. An overview is presented of current approaches to digital phenotyping or device-based, real-time assessment of biometric, behavioral, self-report, and performance data. Analytic opportunities regarding PGHD are envisioned in the context of big data and artificial intelligence in medicine. Finally, challenges and solutions for the integration of PGHD into clinical care are presented. The challenges include electronic medical record integration of PROs and biometric data, analysis of large and complex biometric data sets, and potential clinic workflow redesign. In addition, there is currently more limited evidence for the use of biometric data relative to PROs. Despite these challenges, the potential benefits of PGHD make them increasingly likely to be integrated into oncology research and clinical care.

Electronic Health Record Nudges and Health Care Quality and Outcomes in Primary Care: A Systematic Review.

Importance: Nudges have been increasingly studied as a tool for facilitating behavior change and may represent a novel way to modify the electronic health record (EHR) to encourage evidence-based care. Objective: To evaluate the association between EHR nudges and health care outcomes in primary care settings and describe implementation facilitators and barriers. Evidence Review: On June 9, 2023, an electronic search was performed in PubMed, Embase, PsycINFO, CINAHL, and Web of Science for all articles about clinician-facing EHR nudges. After reviewing titles, abstracts, and full texts, the present review was restricted to articles that used a randomized clinical trial (RCT) design, focused on primary care settings, and evaluated the association between EHR nudges and health care quality and patient outcome measures. Two reviewers abstracted the following elements: country, targeted clinician types, medical conditions studied, length of evaluation period, study design, sample size, intervention conditions, nudge mechanisms, implementation facilitators and barriers encountered, and major findings. The findings were qualitatively reported by type of health care quality and patient outcome and type of primary care condition targeted. The Risk of Bias 2.0 tool was adapted to evaluate the studies based on RCT design (cluster, parallel, crossover). Studies were scored from 0 to 5 points, with higher scores indicating lower risk of bias. Findings: Fifty-four studies met the inclusion criteria. Overall, most studies (79.6%) were assessed to have a moderate risk of bias. Most or all descriptive (eg, documentation patterns) (30 of 38) or patient-centeredness measures (4 of 4) had positive associations with EHR nudges. As for other measures of health care quality and patient outcomes, few had positive associations between EHR nudges and patient safety (4 of 12), effectiveness (19 of 48), efficiency (0 of 4), patient-reported outcomes (0 of 3), patient adherence (1 of 2), or clinical outcome measures (1 of 7). Conclusions and Relevance: This systematic review found low- and moderate-quality evidence that suggested that EHR nudges were associated with improved descriptive measures (eg, documentation patterns). Meanwhile, it was unclear whether EHR nudges were associated with improvements in other areas of health care quality, such as effectiveness and patient safety outcomes. Future research is needed using longer evaluation periods, a broader range of primary care conditions, and in deimplementation contexts.

Suicide Risk Screening for Head and Neck Cancer Patients: An Implementation Study.

OBJECTIVES: There is limited research on suicide risk screening (SRS) among head and neck cancer (HNC) patients, a population at increased risk for suicide. To address this gap, this single-site mixed methods study assessed oncology professionals' perspectives about the feasibility, acceptability, and appropriateness of an electronic SRS program that was implemented as a part of routine care for HNC patients. METHODS: Staff who assisted with SRS implementation completed (e.g., nurses, medical assistants, advanced practice providers, physicians, social workers) a one-time survey (N = 29) and interview (N = 25). Quantitative outcomes were assessed using previously validated feasibility, acceptability, and appropriateness measures. Additional qualitative data were collected to provide context for interpreting the scores. RESULTS: Nurses and medical assistants, who were directly responsible for implementing SRS, reported low feasibility, acceptability, and appropriateness, compared with other team members (e.g., physicians, social workers, advanced practice providers). Team members identified potential improvements needed to optimize SRS, such as hiring additional staff, improving staff training, providing different modalities for screening completion among individuals with disabilities, and revising the patient-reported outcomes to improve suicide risk prediction. CONCLUSION: Staff perspectives about implementing SRS as a part of routine cancer care for HNC patients varied widely. Before screening can be implemented on a larger scale for HNC and other cancer patients, additional implementation strategies may be needed that optimize workflow and reduce staff burden, such as staff training, multiple modalities for completion, and refined tools for identifying which patients are at greatest risk for suicide.

Implementing Digital Scribes to Reduce Electronic Health Record Documentation Burden Among Cancer Care Clinicians: A Mixed-Methods Pilot Study.

PURPOSE: To address shortcomings of human scribes (eg, turnover), clinicians are considering digital scribes (DSs). To our knowledge, to date, no study has assessed DS implementation or clinician user experience in cancer centers. We assessed the DS's feasibility, acceptability, appropriateness, usability and its preliminary association on clinician well-being in a cancer center. We also identified implementation facilitators and barriers to DS use. METHODS: Using a mixed-methods longitudinal pilot study design, we implemented a DS at a cancer center. Data collection included surveys at baseline and 1 month after DS use and a semistructured interview with clinicians. The survey assessed demographics, Mini Z (workplace stress and burnout), sleep quality, and implementation outcomes (feasibility, acceptability, appropriateness, and usability). The interview assessed how the DS was used and its impacts on workflows and recommendations for future implementations of the DS. We used paired t tests to assess differences in Mini Z and sleep quality measures over time. RESULTS: Across nine survey responses and eight interviews, we found that although feasibility scores were slightly lower than our cutoff point (15.2 v 16.0), clinicians rated the DS as marginally acceptable (16.0) and appropriate (16.3). Usability was considered marginally usable (68.6 v 68.0). Although the DS did not significantly improve burnout (3.6 v 3.9, P = .081), it improved perceptions of having sufficient documentation time (2.1 v 3.6, P = .005). Clinicians identified suggestions for future implementations, including training needs and usability improvements. CONCLUSION: Our preliminary findings suggest that DS implementation is marginally acceptable, appropriate, and usable among cancer care clinicians. Individualized training and on-site support may improve implementation.

Examining disparities in large-scale patient-reported data capture using digital tools among cancer patients at clinical intake.

BACKGROUND: Patient-reported data can improve quality of healthcare delivery and patient outcomes. Moffitt Cancer Center ("Moffitt") administers the Electronic Patient Questionnaire (EPQ) to collect data on demographics, including sexual orientation and gender identity (SOGI), medical history, cancer risk factors, and quality of life. Here we investigated differences in EPQ completion by demographic and cancer characteristics. METHODS: An analysis including 146,142 new adult patients at Moffitt in 2009-2020 was conducted using scheduling, EPQ and cancer registry data. EPQ completion was described by calendar year and demographics. Logistic regression was used to estimate associations between demographic/cancer characteristics and EPQ completion. More recently collected information on SOGI were described. RESULTS: Patient portal usage (81%) and EPQ completion rates (79%) were consistently high since 2014. Among patients in the cancer registry, females were more likely to complete the EPQ than males (odds ratio [OR] = 1.17, 95% confidence interval [CI] = 1.14-1.20). Patients ages 18-64 years were more likely to complete the EPQ than patients aged ≥65. Lower EPQ completion rates were observed among Black or African American patients (OR = 0.59, 95% CI = 0.56-0.63) as compared to Whites and among patients whose preferred language was Spanish (OR = 0.40, 95% CI = 0.36-0.44) or another language as compared to English. Furthermore, patients with localized (OR = 1.16, 95% CI = 1.12-1.19) or regional (OR = 1.16, 95% CI = 1.12-1.20) cancer were more likely to complete the EPQ compared to those with metastatic disease. Less than 3% of patients self-identified as being lesbian, gay, or bisexual and <0.1% self-identified as transgender, genderqueer, or other. CONCLUSIONS: EPQ completion rates differed across demographics highlighting opportunities for targeted process improvement. Healthcare organizations should evaluate data acquisition methods to identify potential disparities in data completeness that can impact quality of clinical care and generalizability of self-reported data.

Oncology Providers' and Professionals' Experiences With Suicide Risk Screening Among Patients With Head and Neck Cancer: A Qualitative Study.

PURPOSE: There has been limited study of the implementation of suicide risk screening for patients with head and neck cancer (HNC) as a part of routine care. To address this gap, this study assessed oncology providers' and professionals' perspectives about barriers and facilitators of implementing a suicide risk screening among patients with HNC. MATERIALS AND METHODS: All patients with HNC with an in-person visit completed a suicide risk screening on an electronic tablet. Patients reporting passive death wish were then screened for active suicidal ideation and referred for appropriate intervention. Interviews were conducted with 25 oncology providers and professionals who played a key role in implementation including nurses, medical assistants, patient access representatives, advanced practice providers, physicians, social workers, and informatics staff. The interview guide was based on the Consolidated Framework for Implementation Research. Interviews were transcribed and analyzed for themes. RESULTS: Participants identified multilevel implementation barriers, such as intervention level (eg, patient difficulty with using a tablet), process level (eg, limited nursing engagement), organizational level (eg, limited clinic Wi-Fi connectivity), and individual level (eg, low clinician self-efficacy for interpreting and acting upon patient-reported outcome scores). Participants noted facilitators, such as effective care coordination across nursing and social work staff and the opportunity for patients to be screened multiple times. Participants recommended strengthening patient and clinician education and providing patients with other modalities for data entry (eg, desktop computer in the waiting room). CONCLUSION: Participants identified important intervention modifications that may be needed to optimize suicide risk screening in cancer care settings.

Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center.

Translational bioinformatics for therapeutic discovery requires the infrastructure of clinical informatics. In this chapter, we describe the clinical informatics components needed for successful implementation of translational research at a cancer center. This chapter is meant to be an introduction to those clinical informatics concepts that are needed for translational research. For a detailed account of clinical informatics, the authors will guide the reader to comprehensive resources. We provide examples of workflows from Moffitt Cancer Center led by Drs. Perkins and Markowitz. This perspective represents an interesting collaboration as Dr. Perkins is the Chief Medical Information Officer and Dr. Markowitz is a translational researcher in Melanoma with an active informatics component to his laboratory to study the mechanisms of resistance to checkpoint blockade and an active member of the clinical informatics team.

Correction to: Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center.

The book has been inadvertently published with wrong affiliation for the corresponding author, Randa M. Perkins, of chapter 1. It has now been updated as below in this revised version of the book.

Using Log Data to Measure Provider EHR Activity at a Cancer Center during Rapid Telemedicine Deployment.

OBJECTIVES: Accurate metrics of provider activity within the electronic health record (EHR) are critical to understand workflow efficiency and target optimization initiatives. We utilized newly described, log-based core metrics at a tertiary cancer center during rapid escalation of telemedicine secondary to initial coronavirus disease-2019 (COVID-19) peak onset of social distancing restrictions at our medical center (COVID-19 peak). These metrics evaluate the impact on total EHR time, work outside of work, time on documentation, time on prescriptions, inbox time, teamwork for orders, and undivided attention patients receive during an encounter. Our study aims were to evaluate feasibility of implementing these metrics as an efficient tool to optimize provider workflow and to track impact on workflow to various provider groups, including physicians, advanced practice providers (APPs), and different medical divisions, during times of significant policy change in the treatment landscape. METHODS: Data compilation and analysis was retrospectively performed in Tableau utilizing user and schedule data obtained from Cerner Millennium PowerChart and our internal scheduling software. We analyzed three distinct time periods: the 3 months prior to the initial COVID-19 peak, the 3 months during peak, and 3 months immediately post-peak. RESULTS: Application of early COVID-19 restrictions led to a significant increase of telemedicine encounters from baseline <1% up to 29.2% of all patient encounters. During initial peak period, there was a significant increase in total EHR time, work outside of work, time on documentation, and inbox time for providers. Overall APPs spent significantly more time in the EHR compared with physicians. All of the metrics returned to near baseline after the initial COVID-19 peak in our area. CONCLUSION: Our analysis showed that implementation of these core metrics is both feasible and can provide an accurate representation of provider EHR workflow adjustments during periods of change, while providing a basis for cross-vendor and cross-institutional analysis.

Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice.

Next-generation sequencing (NGS) is rapidly expanding into routine oncology practice. Genetic variations in both the cancer and inherited genomes are informative for hereditary cancer risk, prognosis, and treatment strategies. Herein, we focus on the clinical perspective of integrating NGS results into patient care to assist with therapeutic decision making. Five key considerations are addressed for operationalization of NGS testing and application of results to patient care as follows: (1) NGS test ordering and workflow design; (2) result reporting, curation, and storage; (3) clinical consultation services that provide test interpretations and identify opportunities for molecularly guided therapy; (4) presentation of genetic information within the electronic health record; and (5) education of providers and patients. Several of these key considerations center on informatics tools that support NGS test ordering and referencing back to the results for therapeutic purposes. Clinical decision support tools embedded within the electronic health record can assist with NGS test utilization and identifying opportunities for targeted therapy including clinical trial eligibility. Challenges for project and change management in operationalizing NGS-supported, evidence-based patient care in the context of current information technology systems with appropriate clinical data standards are discussed, and solutions for overcoming barriers are provided.

Reducing Alert Burden in Electronic Health Records: State of the Art Recommendations from Four Health Systems.

BACKGROUND: Electronic health record (EHR) alert fatigue, while widely recognized as a concern nationally, lacks a corresponding comprehensive mitigation plan. OBJECTIVES: The goal of this manuscript is to provide practical guidance to clinical informaticists and other health care leaders who are considering creating a program to manage EHR alerts. METHODS: This manuscript synthesizes several approaches and recommendations for better alert management derived from four U.S. health care institutions that presented their experiences and recommendations at the American Medical Informatics Association 2019 Clinical Informatics Conference in Atlanta, Georgia, United States. The assembled health care institution leaders represent academic, pediatric, community, and specialized care domains. We describe governance and management, structural concepts and components, and human-computer interactions with alerts, and make recommendations regarding these domains based on our experience supplemented with literature review. This paper focuses on alerts that impact bedside clinicians. RESULTS: The manuscript addresses the range of considerations relevant to alert management including a summary of the background literature about alerts, alert governance, alert metrics, starting an alert management program, approaches to evaluating alerts prior to deployment, and optimization of existing alerts. The manuscript includes examples of alert optimization successes at two of the represented institutions. In addition, we review limitations on the ability to evaluate alerts in the current state and identify opportunities for further scholarship. CONCLUSION: Ultimately, alert management programs must strive to meet common goals of improving patient care, while at the same time decreasing the alert burden on clinicians. In so doing, organizations have an opportunity to promote the wellness of patients, clinicians, and EHRs themselves.

Examining the adoption of electronic health records and personal digital assistants by family physicians in Florida.

PURPOSE: The purpose of this paper is to comprehensively characterise the current use of electronic health records (EHRs) and personal digital assistants (PDAs) among family physicians in Florida; and to compare family physicians with other doctors with respect to the functions commonly used on their EHR and PDA systems. METHODS: A postal survey was sent to family physicians (n=2076) and other doctors with a clear and active licence in Florida (total n=14 921). To examine factors among family physicians related to EHR and PDA use, binary logistic regression modelling techniques were utilised. Chi-square analysis was used to compare EHR and PDA functions between family physicians and other doctors. RESULTS: A total of 4203 responses, of which 756 were from family physicians, were available for the current study (28.2% overall response rate). EHR use among family physicians was significantly related to large practice size, urban location and young physician age, after controlling for confounders. Likewise, PDA usage among family physicians was independently associated with male gender and younger physician age. Additionally, even though no differences in overall EHR adoption were found, family physicians, when compared with other physicians, were significantly more likely to be using a more robust set of EHR functions. This included allergy and medication lists, diagnosis, problem lists, patient scheduling and educational materials, preventive services reminders and access to reference material. CONCLUSIONS: Even though family physicians utilise many EHR and PDA functions more commonly than other physician groups, the overall level of EHR adoption among family physicians remains low. Until more barriers to the use of EHR are minimised, the goals of the Future of Family Medicine Report to broadly implement EHR and other health IT functions will not be fully realised.