Using electronic health record data to link families: an illustrative example using intergenerational patterns of obesity.

OBJECTIVE: Electronic health record (EHR) data are a valuable resource for population health research but lack critical information such as relationships between individuals. Emergency contacts in EHRs can be used to link family members, creating a population that is more representative of a community than traditional family cohorts. MATERIALS AND METHODS: We revised a published algorithm: relationship inference from the electronic health record (RIFTEHR). Our version, Pythonic RIFTEHR (P-RIFTEHR), identifies a patient's emergency contacts, matches them to existing patients (when available) using network graphs, checks for conflicts, and infers new relationships. P-RIFTEHR was run on December 15, 2021 in the Northwestern Medicine Electronic Data Warehouse (NMEDW) on approximately 2.95 million individuals and was validated using the existing link between children born at NM hospitals and their mothers. As proof-of-concept, we modeled the association between parent and child obesity using logistic regression. RESULTS: The P-RIFTEHR algorithm matched 1 157 454 individuals in 448 278 families. The median family size was 2, the largest was 32 persons, and 247 families spanned 4 generations or more. Validation of the mother-child pairs resulted in 95.1% sensitivity. Children were 2 times more likely to be obese if a parent is obese (OR: 2.30; 95% CI, 2.23-2.37). CONCLUSION: P-RIFTEHR can identify familiar relationships in a large, diverse population in an integrated health system. Estimates of parent-child inheritability of obesity using family structures identified by the algorithm were consistent with previously published estimates from traditional cohort studies.

Oncologist Perspectives on Telemedicine for Patients With Cancer: A National Comprehensive Cancer Network Survey.

PURPOSE: The use of telemedicine expanded dramatically in March 2020 following the COVID-19 pandemic. We sought to assess oncologist perspectives on telemedicine's present and future roles (both phone and video) for patients with cancer. METHODS: The National Comprehensive Cancer Network (NCCN) Electronic Health Record (EHR) Oncology Advisory Group formed a Workgroup to assess the state of oncology telemedicine and created a 20-question survey. NCCN EHR Oncology Advisory Group members e-mailed the survey to providers (surgical, hematology, gynecologic, medical, and radiation oncology physicians and clinicians) at their home institution. RESULTS: Providers (N = 1,038) from 26 institutions responded in Summer 2020. Telemedicine (phone and video) was compared with in-person visits across clinical scenarios (n = 766). For reviewing benign follow-up data, 88% reported video and 80% reported telephone were the same as or better than office visits. For establishing a personal connection with patients, 24% and 7% indicated video and telephone, respectively, were the same as or better than office visits. Ninety-three percent reported adverse outcomes attributable to telemedicine visits never or rarely occurred, whereas 6% indicated they occasionally occurred (n = 801). Respondents (n = 796) estimated 46% of postpandemic visits could be virtual, but challenges included (1) lack of patient access to technology, (2) inadequate clinical workflows to support telemedicine, and (3) insurance coverage uncertainty postpandemic. CONCLUSION: Telemedicine appears effective across a variety of clinical scenarios. Based on provider assessment, a substantial fraction of visits for patients with cancer could be effectively and safely conducted using telemedicine. These findings should influence regulatory and infrastructural decisions regarding telemedicine postpandemic for patients with cancer.

Rapid deployment of virtual mind-body interventions during the COVID-19 outbreak: feasibility, acceptability, and implications for future care.

INTRODUCTION: COVID-19 increased stress levels while reducing access to mind-body services in patients with cancer. We describe the rapid deployment of remotely delivered mind-body services to people with cancer during COVID-19, rates of participation, and acceptability from patients' perspectives. METHODS: Eligible participants were patients with cancer age ≥ 18 years enrolled in a single academic cancer center's online patient portal. Interventions included mind-body group therapy sessions in fitness, meditation, yoga, dance, tai chi, and music delivered using Zoom video conferencing. Sessions were 30-45 min and led by an integrative medicine clinician. Following each session, participants were asked to complete a three-item questionnaire assessing (1) satisfaction with the class session, (2) reduction in stress/anxiety, and (3) likelihood of recommending the class to others. Patients could also provide comments in real-time using the Zoom chat function. RESULTS: Among 5948 unique visits, the most frequently attended classes were fitness (n = 2513, 42.2%) followed by meditation (n = 1176, 19.8%) and yoga (n = 909, 15.3%). Of these visits, 3902 (65.6%) had an associated completed questionnaire. Across class types, a large majority of participants reported being extremely satisfied (n = 3733, 95.7%), experiencing extreme reductions in anxiety/stress (n = 3268, 83.8%), and being extremely likely to recommend the class to others (n = 3605, 92.4%). Fitness had the highest endorsement among class types (all p values < 0.001). Themes from the chat responses included gratitude, expressions of helpfulness, and feelings of connection. CONCLUSION: High utilization of and satisfaction with these virtual mind-body services demonstrate the significant potential of remote delivery to facilitate patient access to services.

Case study of the integration of electronic patient-reported outcomes as standard of care in a head and neck oncology practice: Obstacles and opportunities.

BACKGROUND: Patient-reported outcomes (PROs) allow for the direct measurement of functional and psychosocial effects related to treatment. However, technological barriers, survey fatigue, and clinician adoption have hindered the meaningful integration of PROs into clinical care. The objective of the authors was to develop an electronic PROs (ePROs) program that meets a range of clinical needs across a head and neck multidisciplinary disease management team. METHODS: The authors developed the ePROs module using literature review and stakeholder input in collaboration with health informatics. They designed an ePROs platform that was integrated as the standard of care for personalized survey delivery by diagnosis across the disease management team. Tableau software was used to create dashboards for data visualization and monitoring at the clinical enterprise, disease subsite, and patient levels. All patients who were treated for head and neck cancer were eligible for ePROs assessment as part of the standard of care. A descriptive analysis of ePROs program implementation is presented herein. RESULTS: The Head and Neck Service at Memorial Sloan Kettering Cancer Center has integrated ePROs into clinical care. Surveys are delivered via the patient portal at the time of diagnosis and longitudinally through care. From August 1, 2018, to February 1, 2020, a total of 4154 patients completed ePROs surveys. The average patient participation rate was 69%, with a median time for completion of 5 minutes. CONCLUSIONS: Integration of the head and neck ePROs program as part of clinical care is feasible and could be used to assess value and counsel patients in the future. Continued qualitative assessments of stakeholders and workflow will refine content and enhance the health informatics platform. LAY SUMMARY: Patients with head and neck cancer experience significant changes in their quality of life after treatment. Measuring and integrating patient-reported outcomes as a part of clinical care have been challenging given the multimodal treatment options, vast subsites, and unique domains affected. The authors present a case study of the successful integration of electronic patient-reported outcomes into a high-volume head and neck cancer practice.

Validation of Case Identification for Alopecia Areata Using International Classification of Diseases Coding.

BACKGROUND: Search algorithms used to identify patients with alopecia areata (AA) need to be validated prior to use in large databases. OBJECTIVES: The aim of the study is to assess whether patients with an International Statistical Classification of Diseases and Related Health Problems (ICD) 9 or 10 code for AA have a true diagnosis of AA. MATERIALS AND METHODS: A multicenter retrospective review was performed at Columbia University Irving Medical Center, Brigham and Women's Hospital, and Massachusetts General Hospital to determine whether patients with an ICD 9 codes (704.01 - AA) or ICD 10 codes (L63.0 -Alopecia Totalis, L63.1 - Alopecia Universalis, L63.2 - Ophiasis, L63.8 - other AA, and L63.9 - AA, unspecified) for AA met diagnostic criteria for the disease. RESULTS: Of 880 charts, 97.5% had physical examination findings consistent with AA, and 90% had an unequivocal diagnosis. AA was diagnosed by a dermatologist in 87% of the charts. The positive predictive value (PPV) of the ICD 9 code 704.01 was 97% (248/255). The PPV for the ICD 10 codes were 64% (75/118) for L63.0, 86% (130/151) for L63.1, 50% (1/2) for L63.2, 91% (81/89) for L63.8, and 93% (247/265) for L63.9. Overall, 89% (782/880) of patients with an ICD code for AA were deemed to have a true diagnosis of AA. CONCLUSIONS: Patients whose medical records contain an AA-associated ICD code have a high probability of having the condition.

Challenges with quality of race and ethnicity data in observational databases.

OBJECTIVE: We sought to assess the quality of race and ethnicity information in observational health databases, including electronic health records (EHRs), and to propose patient self-recording as an improvement strategy. MATERIALS AND METHODS: We assessed completeness of race and ethnicity information in large observational health databases in the United States (Healthcare Cost and Utilization Project and Optum Labs), and at a single healthcare system in New York City serving a racially and ethnically diverse population. We compared race and ethnicity data collected via administrative processes with data recorded directly by respondents via paper surveys (National Health and Nutrition Examination Survey and Hospital Consumer Assessment of Healthcare Providers and Systems). Respondent-recorded data were considered the gold standard for the collection of race and ethnicity information. RESULTS: Among the 160 million patients from the Healthcare Cost and Utilization Project and Optum Labs datasets, race or ethnicity was unknown for 25%. Among the 2.4 million patients in the single New York City healthcare system's EHR, race or ethnicity was unknown for 57%. However, when patients directly recorded their race and ethnicity, 86% provided clinically meaningful information, and 66% of patients reported information that was discrepant with the EHR. DISCUSSION: Race and ethnicity data are critical to support precision medicine initiatives and to determine healthcare disparities; however, the quality of this information in observational databases is concerning. Patient self-recording through the use of patient-facing tools can substantially increase the quality of the information while engaging patients in their health. CONCLUSIONS: Patient self-recording may improve the completeness of race and ethnicity information.

Engaging hospitalized patients with personalized health information: a randomized trial of an inpatient portal.

Objective: To determine the effects of an inpatient portal intervention on patient activation, patient satisfaction, patient engagement with health information, and 30-day hospital readmissions. Methods and Materials: From March 2014 to May 2017, we enrolled 426 English- or Spanish-speaking patients from 2 cardiac medical-surgical units at an urban academic medical center. Patients were randomized to 1 of 3 groups: 1) usual care, 2) tablet with general Internet access (tablet-only), and 3) tablet with an inpatient portal. The primary study outcome was patient activation (Patient Activation Measure-13). Secondary outcomes included all-cause readmission within 30 days, patient satisfaction, and patient engagement with health information. Results: There was no evidence of a difference in patient activation among patients assigned to the inpatient portal intervention compared to usual care or the tablet-only group. Patients in the inpatient portal group had lower 30-day hospital readmissions (5.5% vs. 12.9% tablet-only and 13.5% usual care; P = 0.044). There was evidence of a difference in patient engagement with health information between the inpatient portal and tablet-only group, including looking up health information online (89.6% vs. 51.8%; P < 0.001). Healthcare providers reported that patients found the portal useful and that the portal did not negatively impact healthcare delivery. Conclusions: Access to an inpatient portal did not significantly improve patient activation, but it was associated with looking up health information online and with a lower 30-day hospital readmission rate. These results illustrate benefit of providing hospitalized patients with real-time access to their electronic health record data while in the hospital. Trial Registration: ClinicalTrials.gov Identifier: NCT01970852.

Disease Heritability Inferred from Familial Relationships Reported in Medical Records.

Heritability is essential for understanding the biological causes of disease but requires laborious patient recruitment and phenotype ascertainment. Electronic health records (EHRs) passively capture a wide range of clinically relevant data and provide a resource for studying the heritability of traits that are not typically accessible. EHRs contain next-of-kin information collected via patient emergency contact forms, but until now, these data have gone unused in research. We mined emergency contact data at three academic medical centers and identified 7.4 million familial relationships while maintaining patient privacy. Identified relationships were consistent with genetically derived relatedness. We used EHR data to compute heritability estimates for 500 disease phenotypes. Overall, estimates were consistent with the literature and between sites. Inconsistencies were indicative of limitations and opportunities unique to EHR research. These analyses provide a validation of the use of EHRs for genetics and disease research.

Low Screening Rates for Diabetes Mellitus Among Family Members of Affected Relatives.

Cardiovascular disease is the leading cause of death in the United States, and abnormal blood glucose is an important risk factor. Delayed diagnosis of diabetes mellitus can increase patients' morbidity. In an urban academic medical center with a large clinical data warehouse, we used a novel algorithm to identify 56,794 family members of diabetic patients that were eligible for disease screening. We found that 30.6% of patients did not receive diabetes screening as recommended by current guidelines. Further, our analysis showed that having more than one family member affected and being a female were important contributors to being screened for diabetes mellitus. This study demonstrates that informatics methods applied to electronic health record data can be used to identify patients at risk for disease development, and therefore support clinical care.