Review and Comparison of Electronic Patient-Facing Family Health History Tools

Genetic counselling legislation and practice in cancer in EU Member States

BACKGROUND

Somatic and germline genetic alterations are significant drivers of cancer. Increasing integration of new technologies which profile these alterations requires timely, equitable and high-quality genetic counselling to facilitate accurate diagnoses and informed decision-making by patients and their families in preventive and clinical settings. This article aims to provide an overview of genetic counselling legislation and practice across European Union (EU) Member States to serve as a foundation for future European recommendations and action.

METHODS

National legislative databases of all 27 Member States were searched using terms relevant to genetic counselling, translated as appropriate. Interviews with relevant experts from each Member State were conducted to validate legislative search results and provide detailed insights into genetic counselling practice in each country.

RESULTS

Genetic counselling is included in national legislative documents of 22 of 27 Member States, with substantial variation in legal mechanisms and prescribed details (i.e. the 'who, what, when and where' of counselling). Practice is similarly varied. Workforce capacity (25 of 27 Member States) and genetic literacy (all Member States) were common reported barriers. Recognition and/or better integration of genetic counsellors and updated legislation and were most commonly noted as the 'most important change' which would improve practice.

CONCLUSIONS

This review highlights substantial variability in genetic counselling across EU Member States, as well as common barriers notwithstanding this variation. Future recommendations and action should focus on addressing literacy and capacity challenges through legislative, regulatory and/or strategic approaches at EU, national, regional and/or local levels.

Leveraging Electronic Health Record Data to Understand Gaps Underlying the Underdiagnosis of Lynch Syndrome

Using the electronic health record to address the underdiagnosis of Lynch syndrome.

User experience of a family health history chatbot: A quantitative analysis

OBJECTIVE

Family health history (FHx) is an important tool in assessing one's risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns.

METHODS

We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement.

RESULTS

Of 11,065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 s. Users spent the highest median time on Proband Cancer History (124.00 s) and Family Cancer History (119.00 s) subflows. Search list questions took the longest to complete (median 19.50 s), followed by free text email input (15.00 s).

CONCLUSION

Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection.

Web-based tool for cancer family history collection: A prospective randomized controlled trial

OBJECTIVES

Approximately 1% of individuals have a hereditary cancer predisposition syndrome, however, the majority are not aware. Collecting a cancer family history (CFH) can triage patients to receive genetic testing. To rigorously assess different methods of CFH collection, we compared a web-based tool (WBT) to usual care (clinician collects CFH) in a randomized controlled trial.

METHODS

New gynecologic oncology patients (seen 9/2019-9/2021) were randomized to one of three arms in a 2:2:1 allocation ratio: 1) usual care clinician CFH collection, 2) WBT completed at home, or 3) WBT completed in office. The WBT generated a cancer-focused pedigree and scores on eight validated cancer risk models. The primary outcome was collection of an adequate CFH (based on established guidelines) with usual care versus the WBT.

RESULTS

We enrolled 250 participants (usual care - 110; WBT home - 105; WBT office - 35 [closed early due to COVID-19]). Within WBT arms, 109 (78%) participants completed the tool, with higher completion for office versus home (33 [94%] vs. 76 [72%], P = 0.008). Among participants completing the WBT, 63 (58%) had an adequate CFH versus 5 (5%) for usual care (P < 0.001). Participants completing the WBT were significantly more likely to complete genetic counseling (34 [31%] vs. 15 [14%], P = 0.002) and genetic testing (20 [18%] vs. 9 [8%], P = 0.029). Participant and provider WBT experience was favorable.

CONCLUSIONS

WBTs for CFH collection are a promising application of health information technology, resulting in more comprehensive CFH and a significantly greater percentage of participants completing genetic counseling and testing.

User experience of a family health history chatbot: A quantitative analysis

Objective

Family health history (FHx) is an important tool in assessing one's risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns.

Methods

We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement.

Results

Of 11065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 seconds. Users spent the highest median time on Proband Cancer History (124.00 seconds) and Family Cancer History (119.00 seconds) subflows. Search list questions took the longest to complete (median 19.50 seconds), followed by free text email input (15.00 seconds).

Conclusion

Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection.

Expanding Family Health History to Include Family Medication History

The collection of family health history (FHH) is an essential component of clinical practice and an important piece of data for patient risk assessment. However, family history data have generally been limited to diseases and have not included medication history. Family history was a key component of early pharmacogenetic research, confirming the role of genes in drug response. With the substantial number of known pharmacogenes, many affecting response to commonly prescribed medications, and the availability of clinical pharmacogenetic (PGx) tests and guidelines for interpretation, the collection of family medication history can inform testing decisions. This paper explores the roots of family-based pharmacogenetic studies to confirm the role of genes in these complex phenotypes and the benefits and challenges of collecting family medication history as part of family health history intake.

FHH Quick App Review: How Can a Quality Review Process Assist Primary Care Providers in Choosing a Family Health History App for Patient Care?

Family health history (FHH) is a data type serving risk assessment, diagnosis, research, and preventive health. Despite technological leaps in genomic variant detection, FHH remains the most accessible, least expensive, and most practical assessment tool for assessing risks attributable to genetic inheritance. The purpose of this manuscript is to outline a process to assist primary care professionals in choosing FHH digital tools for patient care based on the new ISO/TS 82304-2 Technical Specification (TS), which is a recently developed method to determine eHealth app quality. With a focus on eHealth in primary care, we applied the quality label concept to FHH, and how a primary care physician can quickly review the quality and reliability of an FHH app. Based on our review of the ISO TS’s 81 questions, we compiled a list of 25 questions that are recommended to be more succinct as an initial review. We call this process the FHH Quick App Review. Our ‘informative-only’ 25 questions do not produce a quality score, but a guide to complete an initial review of FHH apps. Most of the questions are straight from the ISO TS, some are modified or de novo. We believe the 25 questions are not only relevant to FHH app reviews but could also serve to aid app development and clinical implementation.

Impact of Genetic Counseling on Patient-Reported Electronic Cancer Family History Collection

BACKGROUND

Cancer family history is a vital part of cancer genetic counseling (GC) and genetic testing (GT), but increasing indications for germline cancer GT necessitate less labor-intensive models of collection. We evaluated the impact of GC on patient pedigrees generated by an electronic cancer family history questionnaire (eCFHQ).

METHODS

An Institutional Review Board-approved review of pedigrees collected through an eCFHQ was conducted. Paired pre-GC and post-GC pedigrees (n=1,113 each group) were analyzed independently by cancer genetic counselors for changes in patient-reported clinical history and to determine whether the pedigrees met NCCN GT criteria. Discrepancy in meeting NCCN GT criteria between pre-GC and post-GC pedigrees was the outcome variable of logistic regressions, with patient and family history characteristics as covariates.

RESULTS

Overall, 780 (70%) patients had cancer (affected), 869 (78%) were female, and the median age was 57 years (interquartile range, 45-66 years; range, 21-91 years). Of the 1,113 pairs of pre-GC and post-GC pedigrees analyzed, 85 (8%) were blank, 933 (84%) were not discrepant, and 95 (9%) were discrepant in meeting any NCCN GT criteria. Of the discrepant pedigrees, n=79 (83%) became eligible for testing by at least one of the NCCN GT criteria after GC. Patients with discrepant pedigrees were more likely to report no or unknown history of GT (odds ratio [OR], 4.54; 95% CI, 1.66-18.70; P=.01, and OR, 18.47; 95% CI, 5.04-88.73; P<.0001, respectively) and belonged to racially and/or ethnically underrepresented groups (OR, 1.91; 95% CI, 1.08-3.25; P=.02).

CONCLUSIONS

For most patients (84%), a standalone eCFHQ was sufficient to determine whether NCCN GT criteria were met. More research is needed on the performance of the eCFHQ in diverse patient populations.

Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

BACKGROUND

Risk assessment for hereditary cancer syndromes is recommended in primary care, but family history is rarely collected in enough detail to facilitate risk assessment and referral - a roadblock that disproportionately impacts individuals with healthcare access barriers. We sought to qualitatively assess a literacy-adapted, electronic patient-facing family history tool developed for use in diverse, underserved patient populations recruited in the Cancer Health Assessments Reaching Many (CHARM) Study.

METHODS

Interview participants were recruited from a subpopulation of CHARM participants who experienced barriers to tool use in terms of spending a longer time to complete the tool, having incomplete attempts, and/or providing inaccurate family history in comparison to a genetic counselor-collected standard. We conducted semi-structured interviews with participants about barriers and facilitators to tool use and overall tool acceptability; interviews were recorded and professionally transcribed. Transcripts were coded based on a codebook developed using inductive techniques, and coded excerpts were reviewed to identify overarching themes related to barriers and facilitators to family history self-assessment and acceptability of the study tool.

RESULTS

Interviewees endorsed the tool as easy to navigate and understand. However, they described barriers related to family history information, literacy and language, and certain tool functions. Participants offered concrete, easy-to-implement solutions to each barrier. Despite experience barriers to use of the tool, most participants indicated that electronic family history self-assessment was acceptable or preferable in comparison to clinician-collected family history.

CONCLUSIONS

Even for participants who experienced barriers to tool use, family history self-assessment was considered an acceptable alternative to clinician-collected family history. Barriers experienced could be overcome with minor adaptations to the current family history tool.

TRIAL REGISTRATION

This study is a sub-study of the Cancer Health Assessments Reaching Many (CHARM) trial, ClinicalTrials.gov, NCT03426878. Registered 8 February 2018.

Prevalence of Americans reporting a family history of cancer indicative of increased cancer risk: Estimates from the 2015 National Health Interview Survey

The collection and evaluation of family health history in a clinical setting presents an opportunity to discuss cancer risk, tailor cancer screening recommendations, and identify people with an increased risk of carrying a pathogenic variant who may benefit from referral to genetic counseling and testing. National recommendations for breast and colorectal cancer screening indicate that men and women who have a first-degree relative affected with these types of cancers may benefit from talking to a healthcare provider about starting screening at an earlier age and other options for cancer prevention. The prevalence of reporting a first-degree relative who had cancer was assessed among adult respondents of the 2015 National Health Interview Survey who had never had cancer themselves (n = 27,999). We found 35.6% of adults reported having at least one first-degree relative with cancer at any site. Significant differences in reporting a family history of cancer were observed by sex, age, race/ethnicity, educational attainment, and census region. Nearly 5% of women under age 50 and 2.5% of adults under age 50 had at least one first-degree relative with breast cancer or colorectal cancer, respectively. We estimated that 5.8% of women had a family history of breast or ovarian cancer that may indicate increased genetic risk. A third of U.S. adults who have never had cancer report a family history of cancer in a first-degree relative. This finding underscores the importance of using family history to inform discussions about cancer risk and screening options between healthcare providers and their patients.

Family history tools for primary care: A systematic review

Background

Many medical family history (FH) tools are available for various settings. Although FH tools can be a powerful health screening tool in primary care (PC), they are currently underused.

Objectives

This review explores the FH tools currently available for PC and evaluates their clinical performance.

Methods

Five databases were systematically searched until May 2021. Identified tools were evaluated on the following criteria: time-to-complete, integration with electronic health record (EMR) systems, patient administration, risk-assessment ability, evidence-based management recommendations, analytical and clinical validity and clinical utility.

Results

We identified 26 PC FH tools. Analytical and clinical validity was poorly reported and agreement between FH and gold standard was commonly inadequately reported and assessed. Sensitivity was acceptable; specificity was found in half of the reviewed tools to be poor. Most reviewed tools showed a capacity to successfully identify individuals with increased risk of disease (6.2–84.6% of high and/or moderate or increased risk individuals).

Conclusion

Despite the potential of FH tools to improve risk stratification of patients in PC, clinical performance of current tools remains limited as well as their integration in EMR systems. Twenty-one FH tools are designed to be self-administered by patients.

PREDICTION OF HEREDITARY CANCERS USING NEURAL NETWORKS

Family history is a major risk factor for many types of cancer. Mendelian risk prediction models translate family histories into cancer risk predictions, based on knowledge of cancer susceptibility genes. These models are widely used in clinical practice to help identify high-risk individuals. Mendelian models leverage the entire family history, but they rely on many assumptions about cancer susceptibility genes that are either unrealistic or challenging to validate, due to low mutation prevalence. Training more flexible models, such as neural networks, on large databases of pedigrees can potentially lead to accuracy gains. In this paper we develop a framework to apply neural networks to family history data and investigate their ability to learn inherited susceptibility to cancer. While there is an extensive literature on neural networks and their state-of-the-art performance in many tasks, there is little work applying them to family history data. We propose adaptations of fully-connected neural networks and convolutional neural networks to pedigrees. In data simulated under Mendelian inheritance, we demonstrate that our proposed neural network models are able to achieve nearly optimal prediction performance. Moreover, when the observed family history includes misreported cancer diagnoses, neural networks are able to outperform the Mendelian BRCAPRO model embedding the correct inheritance laws. Using a large dataset of over 200,000 family histories, the Risk Service cohort, we train prediction models for future risk of breast cancer. We validate the models using data from the Cancer Genetics Network.

Comparison of a Focused Family Cancer History Questionnaire to Family History Documentation in the Electronic Medical Record

INTRODUCTION

Family health history can be a valuable indicator of risk to develop certain cancers. Unfortunately, patient self-reported family history often contains inaccuracies, which might change recommendations for cancer screening. We endeavored to understand the difference between a patient's self-reported family history and their electronic medical record (EMR) family history. One aim of this study was to determine if family history information contained in the EMR differs from patient-reported family history collected using a focused questionnaire.

METHODS

We created the Hereditary Cancer Questionnaire (HCQ) based on current guidelines and distributed to 314 patients in the Department of Family Medicine waiting room June 20 to August 1, 2018. The survey queried patients about specific cancers within their biological family to assess their risk of an inherited cancer syndrome. We used the questionnaire responses as a baseline when comparing family histories in the medical record.

RESULTS

Agreement between the EMR and the questionnaire data decreased as the patients' risk for familial cancer increased. Meaning that the more significant a patient's family cancer history, the less likely it was to be recorded accurately and consistently in the EMR. Patients with low-risk levels, or fewer instances of cancer in the family, had more consistencies between the EMR and the questionnaire.

CONCLUSIONS

Given that physicians often make recommendations on incomplete information that is in the EMR, patients might not receive individualized preventive care based on a more complete family cancer history. This is especially true for individuals with more complicated and significant family history of cancer. An improved method of collecting family history, including increasing patient engagement, may help to decrease this disparity.

Comparison of a Cancer Family History Collection and Risk Assessment Tool - ItRunsInMyFamily - with Risk Assessment by Health-Care Professionals

INTRODUCTION

Primary care providers (PCPs) and oncologists lack time and training to appropriately identify patients at increased risk for hereditary cancer using family health history (FHx) and clinical practice guideline (CPG) criteria. We built a tool, "ItRunsInMyFamily" (ItRuns) that automates FHx collection and risk assessment using CPGs. The purpose of this study was to evaluate ItRuns by measuring the level of concordance in referral patterns for genetic counseling/testing (GC/GT) between the CPGs as applied by the tool and genetic counselors (GCs), in comparison to oncologists and PCPs. The extent to which non-GCs are discordant with CPGs is a gap that health information technology, such as ItRuns, can help close to facilitate the identification of individuals at risk for hereditary cancer.

METHODS

We curated 18 FHx cases and surveyed GCs and non-GCs (oncologists and PCPs) to assess concordance with ItRuns CPG criteria for referring patients for GC/GT. Percent agreement was used to describe concordance, and logistic regression to compare providers and the tool's concordance with CPG criteria.

RESULTS

GCs had the best overall concordance with the CPGs used in ItRuns at 82.2%, followed by oncologists with 66.0% and PCPs with 60.6%. GCs were significantly more likely to concur with CPGs (OR = 4.04, 95% CI = 3.35-4.89) than non-GCs. All providers had higher concordance with CPGs for FHx cases that met the criteria for genetic counseling/testing than for cases that did not.

DISCUSSION/CONCLUSION

The risk assessment provided by ItRuns was highly concordant with that of GC's, particularly for at-risk individuals. The use of such technology-based tools improves efficiency and can lead to greater numbers of at-risk individuals accessing genetic counseling, testing, and mutation-based interventions to improve health.

Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review

Background

Chatbot is a timely topic applied in various fields, including medicine and health care, for human-like knowledge transfer and communication. Machine learning, a subset of artificial intelligence, has been proven particularly applicable in health care, with the ability for complex dialog management and conversational flexibility.

Objective

This review article aims to report on the recent advances and current trends in chatbot technology in medicine. A brief historical overview, along with the developmental progress and design characteristics, is first introduced. The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation.

Methods

A search of the literature published in the past 20 years was conducted using the IEEE Xplore, PubMed, Web of Science, Scopus, and OVID databases. The screening of chatbots was guided by the open-access Botlist directory for health care components and further divided according to the following criteria: diagnosis, treatment, monitoring, support, workflow, and health promotion.

Results

Even after addressing these issues and establishing the safety or efficacy of chatbots, human elements in health care will not be replaceable. Therefore, chatbots have the potential to be integrated into clinical practice by working alongside health practitioners to reduce costs, refine workflow efficiencies, and improve patient outcomes. Other applications in pandemic support, global health, and education are yet to be fully explored.

Conclusions

Further research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, rebalance the workload for clinicians, and revolutionize the practice of medicine.

Experience and Perceptions of a Family Health History Risk Assessment Tool among Multi-Ethnic Asian Breast Cancer Patients

A family health history-based risk assessment is particularly valuable for guiding cancer screening and treatment strategies, yet an optimal implementation depends upon end-users' values and needs. This is not only true prior to disease development, but also for those already affected. The aim of this study is to explore perceptions of the value of knowing one's family health history (FHH)-based risk, experience using a patient-facing FHH tool and the potential of the tool for wider implementation. Twenty multi-ethnic Asian patients undergoing breast cancer treatment in Singapore completed an FHH-based risk assessment. Semi-structured one-on-one interviews were conducted and data were thematically analyzed. All participants were female and slightly more than half were Chinese. The acceptance and usage of an FHH risk assessment tool for cancers and its broader implementation was affected by a perceived importance of personal control over early detection, patient concerns of anxiety for themselves and their families due to risk results, concerns for genetic discrimination, adequacy of follow-up care plans and Asian cultural beliefs toward disease and dying. This study uniquely sheds light on the factors affecting Asian breast cancer patients' perceptions about undergoing an FHH-based risk assessment, which should inform steps for a broader implementation in Asian healthcare systems.

Physicians' strategies for using family history data: having the data is not the same as using the data

Objective

To identify needs in a clinical decision support tool development by exploring how primary care providers currently collect and use family health history (FHH).

Design

Survey questionnaires and semi-structured interviews were administered to a mix of primary and specialty care clinicians within the University of Utah Health system (40 surveys, 12 interviews).

Results

Three key themes emerged regarding providers' collection and use of FHH: (1) Strategies for collecting FHH vary by level of effort; (2) Documentation practices extend beyond the electronic health record's dedicated FHH module; and (3) Providers desire feedback from genetic services consultation and are uncertain how to refer patients to genetic services.

Conclusion

Study findings highlight the varying degrees of engagement that providers have with collecting FHH. Improving the integration of FHH into workflow, and providing decision support, as well as links and tools to help providers better utilize genetic counseling may improve patient care.

Using a Chatbot to Assess Hereditary Cancer Risk

PURPOSE

We developed a Web-based chatbot (ItRunsInMyFamily.com) to help individuals collect their family health history (FHx) and determine their risk for hereditary cancer. The purpose of the current study was to assess the characteristics of users and identify opportunities to improve the FHx collection tool.

METHODS

During Family Health History Month (November 2019) we launched an FHx campaign using social media advertisements to raise awareness about hereditary cancers and encourage individuals in the general population to use ItRunsInMyFamily to collect their FHx. Through this campaign, we were able to gather information about users and identify opportunities to improve the tool.

RESULTS

We reached 14,140 users in November 2019 through online marketing campaigns-Facebook, Google, previous ItRuns users, and Web site marketing. Of those, 3,204 completed the full FHx assessment and received risk recommendations. The campaign targeted women between age 40 and 60 years. Users came from 3,783 counties around the United States, 48 unique cancers were reported among probands, and 79 unique cancers were reported among family members, an average of two and a half cancers per family.

CONCLUSION

Our results demonstrate that it is possible to gather FHx information at the population level, with high levels of engagement and interest in the topic. There is room for future enhancements and improvements to ItRunsInMyFamily to broaden its reach and encourage individuals to learn about and record their health information.

Mapping Users' Experience of a Family History and Genetic Risk Algorithm Tool in Primary Care

INTRODUCTION

The development of a family history (FH) questionnaire (FHQ) provides an insight into a patient's familiarity of a trait and helps to identify individuals at increased risk of disease. A critical aspect of developing a new tool is exploring users' experience.

OBJECTIVE

The objective of this study was to examine users' experience, obstacles and challenges, and their views and concerns in the applicability of a new tool for determining genetic risk in Slovenia's primary care.

METHODS

We used a qualitative approach. The participants completed a risk assessment software questionnaire that calculates users' likelihood of developing familial diseases. Audio-taped semi-structured telephone interviews were conducted to evaluate their experience. There were 21 participants, and analyses using the constant comparative method were employed.

RESULTS

We identified 3 main themes: obstacles/key issues, suggestions for improvements, and coping. The participants were poorly satisfied with the clarity of instructions, technical usability problems, and issues with the entry of relatives' data. They expressed satisfaction with some of the characteristics of the FHQ (e.g., straightforward and friendly format, easy entry, and comprehension). They suggested simpler language, that the disease risk should be targeted toward the disease, that the FHQ should include patient-specific recommendations, and that it should be part of the electronic medical records. When discussing what would they do with the results of the FHQ, the participants used different coping strategies: active (e.g., seeking information) or passive (e.g., avoidance).

DISCUSSION/CONCLUSION

User experience was shown to be a synthesis of obstacles, overcoming them with suggestions for improvements, and exploration of various coping mechanisms that may emerge from dealing with the stressor of "being at risk."

Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO

Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many syndromes are overlapping, motivating the development of models that incorporate family history on several cancers and predict mutations for a comprehensive panel of genes.

We present PanelPRO, a new, open-source R package providing a fast, flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. It includes a customizable database with default parameter values estimated from published studies and allows users to select any combinations of genes and cancers for their models, including well-established single syndrome BayesMendel models (BRCAPRO and MMRPRO). This leads to more accurate risk predictions and ultimately has a high impact on prevention strategies for cancer and clinical decision making. The package is available for download for research purposes at https://projects.iq.harvard.edu/bayesmendel/panelpro.

Leveraging Health Information Technology to Collect Family Cancer History: A Systematic Review and Meta-Analysis

PURPOSE

Collection of family cancer histories (FCHs) can identify individuals at risk for familial cancer syndromes. The aim of this study is to evaluate the literature on existing strategies whereby providers use information technology to assemble FCH.

METHODS

A systematic search of online databases (Ovid MEDLINE, Cochrane, and Embase) between 1980 and 2020 was performed. Statistical heterogeneity was assessed through the chi-square test (ie, Cochrane Q test) and the inconsistency statistic (I²). A random-effects analysis was used to calculate the pooled proportions and means.

RESULTS

The comprehensive search produced 4,005 publications. Twenty-eight studies met inclusion criteria. Twenty-seven information technology tools were evaluated. Eighteen out of 28 studies were electronic surveys administered before visits (18, 64.3%). Five studies administered tablet surveys in offices (5, 17.8%). Four studies collected electronic survey via kiosk before visits (4, 14.3%), and one study used animated virtual counselor during visits (1, 3.6%). Among the studies that use an FCH tool, the pooled estimate of the overall completion rate was 86% (CI, 72% to 96%), 84% (CI, 65% to 97%) for electronic surveys before visits, 89% (CI, 0.74 to 0.98) for tablet surveys, and 85% (CI, 0.66 to 0.98) for surveys via kiosk. Mean time required for completion was 31.0 minutes (CI, 26.1 to 35.9), and the pooled estimate of proportions of participants referred to genetic testing was 12% (CI, 4% to 23%).

CONCLUSION

Our review found that electronic FCH collection can be completed successfully by patients in a time-efficient manner with high rates of satisfaction.

Synthetic data for annotation and extraction of family history information from clinical text

BACKGROUND

The limited availability of clinical texts for Natural Language Processing purposes is hindering the progress of the field. This article investigates the use of synthetic data for the annotation and automated extraction of family history information from Norwegian clinical text. We make use of incrementally developed synthetic clinical text describing patients' family history relating to cases of cardiac disease and present a general methodology which integrates the synthetically produced clinical statements and annotation guideline development. The resulting synthetic corpus contains 477 sentences and 6030 tokens. In this work we experimentally assess the validity and applicability of the annotated synthetic corpus using machine learning techniques and furthermore evaluate the system trained on synthetic text on a corpus of real clinical text, consisting of de-identified records for patients with genetic heart disease.

RESULTS

For entity recognition, an SVM trained on synthetic data had class weighted precision, recall and F₁-scores of 0.83, 0.81 and 0.82, respectively. For relation extraction precision, recall and F₁-scores were 0.74, 0.75 and 0.74.

CONCLUSIONS

A system for extraction of family history information developed on synthetic data generalizes well to real, clinical notes with a small loss of accuracy. The methodology outlined in this paper may be useful in other situations where limited availability of clinical text hinders NLP tasks. Both the annotation guidelines and the annotated synthetic corpus are made freely available and as such constitutes the first publicly available resource of Norwegian clinical text.

Development and evaluation of an online, patient-driven, family outreach intervention to facilitate sharing of genetic risk information in families with Lynch syndrome

BACKGROUND

Identifying at-risk relatives of individuals with genetic conditions facilitates 'cascade' genetic testing and cancer prevention. Although current standards of care give mutation-positive (index) patients the responsibility of sharing genetic risk information with relatives, the communication is suboptimal, limited largely to close relatives. We developed FamilyCONNECT, a provider-mediated, patient-navigated online tool to facilitate family outreach, and assessed its feasibility, usability and acceptability.

METHODS

(1) Development of the FamilyCONNECT prototype; (2) testing using online surveys of: (a) members of Lynch Syndrome (LS) International (LSI); (b) genetics service providers; and (3) hands-on testing with patients with LS.

RESULTS

(1) FamilyCONNECT's features include introductory email to elicit participation, informational website/video, identity authentication/account creation, informed consent, sharing of genetic test results, pedigree expansion and process to invite at-risk relatives. (2a) 33% of the 170 LSI participants completed the survey. FamilyCONNECT's features received favourable responses from at least 79% of respondents. Unfavourable responses were for length of the consent document and mistrust of opening emailed links. (2b) Thirty-five genetics professionals responded to the providers' survey. Key perceived barriers to FamilyCONNECT's usage were privacy/confidentiality (83%), a lack of institutional resources (76%), a defined process (66%) and time (69%). (3) Ten patients navigated data collection fields and provided feedback for improvements.

CONCLUSION

FamilyCONNECT tool's content and features were well received among patients with LS as well as providers. The tool could be a viable alternative to increase family outreach among patients with LS. Future efforts will focus on refining FamilyCONNECT and assessing its uptake and utilisation by patients with LS.

Patient Decision Aid Selection for Shared Decision Making: A Multicase Qualitative Study

The patient decision aid (PDA) is a promising patient engagement tool for use in shared decision making (SDM). Selecting a PDA is an essential precursor to successful SDM implementation. Little is known regarding the organizational stakeholder process for assessing and selecting a PDA. We conducted a qualitative, multicase study within the context of a maternal health decision to identify the criteria used by stakeholders to select a PDA. We further explored the perceived value of PDA certification on PDA selection. We reported the PDA selection criteria within the domains of (1) Design and Functionality, (2) User Fit, (3) Context and Climate, (4) Support, and (5) Strategic Vision and found that certification was perceived to be a valuable screening mechanism for smaller health organizations. Health organizations and researchers may use our PDA selection criteria and conceptual model to plan future deployments of PDAs and patient engagement tools.

Utility of a virtual counselor (VICKY) to collect family health histories among vulnerable patient populations: A randomized controlled trial

OBJECTIVES

This study is a randomized controlled trial comparing the efficacy of a virtual counselor (VICKY) to the My Family Health Portrait (MFHP) tool for collecting family health history (FHx).

METHODS

A total of 279 participants were recruited from a large safety-net hospital and block randomized by health literacy to use one of the digital FHx tools, followed by a genetic counselor interview. A final sample of 273 participants were included for analyses of primary study aims pertaining to tool concordance, which assessed agreement between tool and genetic counselor.

RESULTS

Tool completion differed significantly between tools (VICKY = 97%, MFHP = 51%; p < .0001). Concordance between tool and genetic counselor was significantly greater for participants randomized to VICKY compared to MFHP for ascertaining first- and second-degree relatives (ps<.0001), and most health conditions examined. There was significant interaction by health literacy, with greater differences in concordance observed between tools among those with limited literacy.

CONCLUSIONS

A virtual counselor overcomes many of the literacy-related barriers to using traditional digital tools and highlights an approach that may be important to consider when collecting health histories from vulnerable populations.

PRACTICE IMPLICATIONS

The usability of digital health history tools will have important implications for the quality of the data collected and its downstream clinical utility.

Adaptation and early implementation of the PREdiction model for gene mutations (PREMM5™) for lynch syndrome risk assessment in a diverse population

Lynch syndrome (LS) is the most common inherited cause of colorectal and endometrial cancers. Identifying individuals at risk for LS without personal cancer history requires detailed collection and assessment of family health history. However, barriers exist to family health history collection, especially in historically underserved populations. To improve LS risk assessment in historically underserved populations, we adapted the provider-facing PREdiction Model for gene Mutations (PREMM₅™ model), a validated LS risk assessment model, into a patient-facing electronic application through an iterative development process involving expert and patient stakeholders. We report on preliminary findings based on the first 500 individuals exposed to the adapted application in a primary care population enriched for low-literacy and low-resource patients. Major adaptations to the PREMM₅™ provider module included reduction in reading level, addition of interactive literacy aids, incorporation of family history assessment for both maternal and paternal sides of the family, and inclusion of questions about individual relatives or small groups of relatives to reduce cognitive burden. In the first 500 individuals, 90% completed the PREMM₅™ independently; of those, 94% did so in 5 min or less (ranged from 0.2 to 48.8 min). The patient-facing application was able to accurately classify 84% of patients as having clinically significant or not clinically significant LS risk. Our preliminary results suggest that in this diverse study population, most participants were able to rapidly, accurately, and independently complete an interactive application collecting family health history assessment that accurately assessed for Lynch syndrome risk.

Risk assessment and genetic counseling for hereditary breast and ovarian cancer syndromes-Practice resource of the National Society of Genetic Counselors

Cancer risk assessment and genetic counseling for hereditary breast and ovarian cancer (HBOC) are a communication process to inform and prepare patients for genetic test results and the related medical management. An increasing number of healthcare providers are active in the delivery of cancer risk assessment and testing, which can have enormous benefits for enhanced patient care. However, genetics professionals remain key in the multidisciplinary care of at-risk patients and their families, given their training in facilitating patients' understanding of the role of genetics in cancer development, the potential psychological, social, and medical implications associated with cancer risk assessment and genetic testing. A collaborative partnership of non-genetics and genetics experts is the ideal approach to address the growing number of patients at risk for hereditary breast and ovarian cancer. The goal of this practice resource is to provide allied health professionals an understanding of the key components of risk assessment for HBOC as well as the use of risk models and published guidelines for medical management. We also highlight what patient types are appropriate for genetic testing, what are the most appropriate test(s) to consider, and when to refer individuals to a genetics professional. This practice resource is intended to serve as a resource for allied health professionals in determining their approach to delivering comprehensive care for families and individuals facing HBOC. The cancer risk and prevalence figures in this document are based on cisgender women and men; the risks for transgender or non-binary individuals have not been studied and therefore remain poorly understood.

Statistical approaches for meta-analysis of genetic mutation prevalence

Estimating the prevalence of rare germline genetic mutations in the general population is of interest as it can inform genetic counseling and risk management. Most studies that estimate the prevalence of mutations are performed in high-risk populations, and each study is designed with differing inclusion criteria, resulting in ascertained populations. Quantifying the effects of ascertainment is necessary to estimate the prevalence in the general population. This quantification is difficult as the inclusion criteria is often based on disease status and/or family history. Combining estimates from multiple studies through a meta-analysis is challenging due to the variety of study designs and ascertainment mechanisms as well as the complexity of quantifying the effect of these mechanisms. We provide guidelines on how to quantify the ascertainment mechanism for a wide range of settings and propose a general approach for conducting a meta-analysis in these complex settings by incorporating study-specific ascertainment mechanisms into a joint likelihood function. We implement the proposed likelihood-based approach using both frequentist and Bayesian methodologies. We evaluate these approaches in simulations and show that the methods are robust and produce unbiased estimates of the prevalence. An advantage of the Bayesian approach is that it can easily incorporate uncertainty in ascertainment probability values. We apply our methods to estimate the prevalence of PALB2 mutations in the United States by combining data from multiple studies and obtain a prevalence estimate of around 0.02%.

An empirical study investigating the user acceptance of a virtual conversational agent interface for family health history collection among the geriatric population

Critical for the early diagnosis of genetic disorders, a Family Health History (FHx) can be collected in several ways including electronic FHx tools, which aid easy editing and sharing by linking with other information management portals. The user acceptance of such systems is critical, especially among older adults experiencing motor and cognitive issues. This study investigated two types of FHx interfaces, standard and Virtual Conversational Agent (VCA), using 30 young (between 18 and 30) and 24 older participants (over 60). Workload, usability and performance data were collected. Even though participants required less time to complete three of five tasks on the standard interface, the VCA interface performed better in terms of subjective workload and usability. Additionally, 67% of the older adults preferred the VCA interface since it provided context-based guidance during the data collection process. The results from this study have implications for the use of virtual assistants in FHx and other areas of data collection.

A thematic analysis of health information technology use among cancer genetic counselors

As precision medicine becomes a mainstay in health care, the use of health information technology (IT) platforms will play an important role in the delivery of services across the cancer care continuum. Currently, there is both limited understanding about perceptions of health IT tools and barriers to their use among cancer genetic counselors. We assessed open-ended responses from a survey conducted among 128 board-certified cancer genetic counselors in the United States. We evaluated the utility of ten health IT tools and perceived barriers to adoption. Responses about characteristics of health IT tools that influence current use (i.e., technology-specific challenges) were deductively analyzed using the diffusion of innovations (DOI) characteristics. Responses about cancer genetic counselors' perceived challenges to adopting health IT tools (i.e., discipline-specific challenges) were inductively coded using a thematic approach. DOI innovation characteristics included mixed perceptions about the relative advantage, complexity, compatibility, trialability, and observability of tools based on the type of tool and perceived end-user. One-third of participants indicated that they were considering adopting or switching health IT tools. Common barriers to adoption included no perceived need for change, lack of organizational infrastructure, cost, and lack of decision-making power. Our findings indicate that addressing barriers to use and adoption of health IT may allow for expansion of these tools among cancer genetic counselors. Integrating health IT is critical for enhancing cancer genetic counselors' capacity to address patient needs and realizing the potential of precision medicine.

Utilization of health information technology among cancer genetic counselors

Background

Health information technology (IT) is becoming increasingly utilized by cancer genetic counselors (CGCs). We sought to understand the current engagement, satisfaction, and opportunities to adopt new health IT tools among CGCs.

Methods

We conducted a mixed‐mode survey among 128 board‐certified CGCs using both closed‐ and open‐ended questions. We then evaluated the utilization and satisfaction among 10 types of health IT tools, including the following: cancer screening tool, family health history (FHx) collection tools, electronic health records (EHRs), telegenetics software, pedigree drawing software, genetic risk assessment tools, gene test panel ordering tools, electronic patient education tools, patient communication tools, and family communication tools.

Results

Seven of 10 health IT tools were used by a minority of CGCs. The vast majority of respondents reported using EHRs (95.2%) and genetic risk assessment tools (88.6%). Genetic test panel ordering software had the highest satisfaction rate (very satisfied and satisfied) at 80.0%, followed by genetic risk assessment tools (77.1%). EHRs had the highest dissatisfaction rate among CGCs at 18.3%. Dissatisfaction with a health IT tool was associated with desire to change: EHRs (p < .001), cancer screening tools (p = .010), genetic risk assessment tools (p = .024), and family history collection tools (p = .026). We found that nearly half of CGCs were considering adopting or changing their FHx tool (49.2%), cancer screening tool (44.9%), and pedigree drawing tool (41.8%).

Conclusion

Overall, CGCs reported high levels of satisfaction among commonly used health IT tools. Tools that enable the collection of FHx, cancer screening tools, and pedigree drawing software represent the greatest opportunities for research and development.

The enduring importance of family health history in the era of genomic medicine and risk assessment

Improving disease risk prediction and tailoring preventive interventions to patient risk factors is one of the primary goals of precision medicine. Family health history is the traditional approach to quickly gather genetic and environmental data relevant to the patient. While the utility of family health history is well-documented, its utilization is variable, in part due to lack of patient and provider knowledge and incomplete or inaccurate data. With the advances and reduced costs of sequencing technologies, comprehensive sequencing tests can be performed as a risk assessment tool. We provide an overview of each of these risk assessment approaches, the benefits and limitations and implementation challenges.

Evaluation of family health history collection methods impact on data and risk assessment outcomes

Information technology applications for patient-collection of family health history (FHH) increase identification of elevated-risk individuals compared to usual care. It is unknown if the method of collection impacts data collected or if simply going directly to the patient is what makes the difference. The objective of this study was to examine differences in data detail and risk identification rates between FHH collection directly from individuals using paper-based forms and an interactive web-based platform. This is a non-randomized epidemiologic study in Singaporean population from 2016 to 2018. Intervention was paper-based versus web-based interactive platform for FHH collection. Participant demographics, FHH detail, and risk assessment results were analyzed. 882 participants enrolled in the study, 481 in the paper-based group and 401 in the web-based group with mean (SD) age of 45.4 (12.98) years and 47.5% male. Web-based FHH collection participants had an increased number of conditions per relative (p-value <0.001), greater frequency of reporting age of onset (p-value <0.001), and greater odds of receiving ≥1 risk recommendation both overall (OR: 3.99 (2.41, 6.59)) and within subcategories of genetic counselling for hereditary cancer syndromes (p-value = 0.041) and screening and prevention for breast (p-value = 0.002) and colon cancer (p-value = 0.005). This has significant implications for clinical care and research efforts where FHH is being assessed. Using interactive information technology platforms to collect FHH can improve the completeness of the data collected and result in increased rates of risk identification. Methods of data collection to maximize benefit should be taken into account in future studies and clinical care.

Family health history collected by virtual conversational agents: An empirical study to investigate the efficacy of this approach

Family health history (FHx) is one of the simplest and most cost-effective and efficient ways to collect health information that could help diagnose and treat genetic diseases at an early stage. This study evaluated the efficacy of collecting such family health histories through a virtual conversational agent (VCA) interface, a new method for collecting this information. Standard and VCA interfaces for FHx collection were investigated with 50 participants, recruited via email and word of mouth, using a within-subject experimental design with the order of the interfaces randomized and counterbalanced. Interface workload, usability, preference, and satisfaction were assessed using the NASA Task Load Index workload instrument, the IBM Computer System Usability Questionnaire, and a brief questionnaire derived from the Technology Acceptance Model. The researchers also recorded the number of errors and the total task completion time. It was found that the completion times for 2 of the 5 tasks were shorter for the VCA interface than for the standard one, but the overall completion time was longer (17 min 44 s vs. 16 min 51 s, p = .019). We also found the overall workload to be significantly lower (34.32 vs. 42.64, p = .003) for the VCA interface, and usability metrics including overall satisfaction (5.62 vs. 4.72, p < .001), system usefulness (5.76 vs. 4.84, p = .001), information quality (5.43 vs. 4.62, p < .001), and interface quality (5.66 vs. 4.64, p < .001) to be significantly higher for this interface as well. Approximately 3 out of 4 participants preferred the VCA interface to the standard one. Although the overall time taken was slightly longer than with standard interface, the VCA interface was rated significantly better across all other measures and was preferred by the participants. These findings demonstrate the advantages of an innovative VCA interface for collecting FHx, validating the efficacy of using VCAs to collect complex patient-specific data in health care.

Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level - A New Tool for Primary Prevention: A Study Protocol

INTRODUCTION

Family history (FH) is an important part of the patients' medical history during preventive management at model family medicine practices (MFMP). It currently includes a one (or two) generational inquiry, predominately in terms of cardiovascular diseases, arterial hypertension, and diabetes, but not of other diseases with a probable genetic aetiology. Beside family history, no application-based algorithm is available to determine the risk level for specific chronic diseases in Slovenia.

METHODS

A web application-based algorithm aimed at determining the risk level for selected monogenic and polygenic diseases will be developed. The data will be collected in MFMP; approximately 40 overall with a sample including healthy preventive examination attendees (approximately 1,000). Demographic data, a three-generational FH, a medical history of acquired and congenital risk factors for the selected diseases, and other important clinical factors will be documented.

RESULTS

The results will be validated by a clinical genetic approach based on family pedigrees and the next-generation genetic sequencing method. After the risk of genetic diseases in the Slovenian population has been determined, clinical pathways for acting according to the assessed risk level will be prepared.

CONCLUSION

By means of a public health tool providing an assessment of family predisposition, a contribution to the effective identification of people at increased risk of the selected monogenic and polygenic diseases is expected, lessening a significant public health burden.

[Digital public health-an overview]

The rapid development and proliferation of digital health technologies have not only changed the medical professions, but offer great potential for public health, particularly in health promotion and disease prevention.At the same time, this emerging field is also characterized by conceptual and terminological fuzziness, a marked lack of high-quality evidence, and an absence of an honest discussion of unintended consequences and side effects. Further challenges for digital public health lie in the fact that the development of new health technologies is mainly driven by technological progress and less by evidence-based needs and research in public health.In this overview paper, we aim at conceptually denoting the field of digital public health, using principal public health functions as guiding principles. We discuss some current applications of digital health technologies in fulfilling public health functions and propose a needs-based development of digital health technologies.We will further address specific challenges to digital public health, in particular socio-economic differences in the usage of and profiting from digital health technologies, data protection and privacy issues, as well as ethical issues.

Primary care physician experiences utilizing a family health history tool with electronic health record-integrated clinical decision support: an implementation process assessment

Family health history (FHH) screening plays a key role in disease risk identification and tailored disease prevention strategies. Primary care physicians (PCPs) are in a frontline position to provide personalized medicine recommendations identified through FHH screening; however, adoption of FHH screening tools has been slow and inconsistent in practice. Information is also lacking on PCP facilitators and barriers of utilizing family history tools with clinical decision support (CDS) embedded in the electronic health record (EHR). This study reports on PCPs' initial experiences with the Genetic and Wellness Assessment (GWA), a patient-administered FHH screening tool utilizing the EHR and CDS. Semi-structured interviews were conducted with 24 PCPs who use the GWA in a network of community-based practices. Four main themes regarding GWA implementation emerged: benefits to clinical care, challenges in practice, CDS-specific issues, and physician-recommended improvements. Sub-themes included value in improving patient access to genetic services, inadequate time to discuss GWA recommendations, lack of patient follow-through with recommendations, and alert fatigue. While PCPs valued the GWA's clinical utility, a number of challenges were identified in the administration and use of the GWA in practice. Based on participants' recommendations, iterative changes have been made to the GWA and workflow to increase efficiency, upgrade the CDS process, and provide additional education to PCPs and patients. Future studies are needed to assess a diverse sample of physicians' and patients' perspectives on the utility of FHH screening utilizing EHR-based genomics recommendations.

Standards-Based Clinical Decision Support Platform to Manage Patients Who Meet Guideline-Based Criteria for Genetic Evaluation of Familial Cancer

PURPOSE

The ubiquitous adoption of electronic health records (EHRs) with family health history (FHH) data provides opportunities for tailoring cancer screening strategies to individuals. We aimed to enable a standards-based clinical decision support (CDS) platform for identifying and managing patients who meet guidelines for genetic evaluation of hereditary cancer.

METHODS

The CDS platform (www.opencds.org) was used to implement algorithms based on the 2018 National Comprehensive Cancer Network guidelines for genetic evaluation of hereditary breast/ovarian and colorectal cancer. The platform was designed to be interfaced with different EHR systems via the Health Level Seven International Fast Healthcare Interoperability Resources standard. The platform was integrated with the Epic EHR and evaluated in a pilot study at an academic health care system.

RESULTS

The CDS platform was executed against a target population of 143,012 patients; 5,245 (3.7%) met criteria for genetic evaluation based on the FHH recorded in the EHR. In a clinical pilot study, genetic counselors attempted to reach out to 71 of the patients. Of those patients, 25 (35%) scheduled an appointment, 10 (14%) declined, 2 (3%) did not need genetic counseling, 7 (10%) said they would consider it in the future, and 27 (38%) were unreachable. To date, 13 (52%) of the scheduled patients completed visits, and 2 (15%) of those were found to have pathogenic variants in cancer predisposition genes.

CONCLUSION

A standards-based CDS platform integrated with EHR systems is a promising population-based approach to identify patients who are appropriate candidates for genetic evaluation of hereditary cancers.

Cortés D, Trevino-Talbot M, Bangham C, Winter MR, Cabral H, Norkunas Cunningham T, M. Toledo D, J. Bowen D, K. Paasche-Orlow M, Bickmore T, Wang C. Designing and Evaluating a Digital Family Health History Tool for Spanish Speakers

Digital family health history tools have been developed but few have been tested with non-English speakers and evaluated for acceptability and usability. This study describes the cultural and linguistic adaptation and evaluation of a family health history tool (VICKY: VIrtual Counselor for Knowing Your Family History) for Spanish speakers. In-depth interviews were conducted with 56 Spanish-speaking participants; a subset of 30 also participated in a qualitative component to evaluate the acceptability and usability of Spanish VICKY. Overall, agreement in family history assessment was moderate between VICKY and a genetic counselor (weighted kappa range: 0.4695 for stroke-0.6615 for heart disease), although this varied across disease subtypes. Participants felt comfortable using VICKY and noted that VICKY was very likeable and possessed human-like characteristics. They reported that VICKY was very easy to navigate, felt that the instructions were very clear, and thought that the time it took to use the tool was just right. Spanish VICKY may be useful as a tool to collect family health history and was viewed as acceptable and usable. The study results shed light on some cultural differences that may influence interactions with family history tools and inform future research aimed at designing and testing culturally and linguistically diverse digital systems.

Family Health History: The First Genetic Test in Precision Medicine

The collection of family history has always been a tool for genetic evaluation, but it remains an essential tool even in the age of genomic medicine. Patients may have a risk for a disease based on family history regardless of the results of genetic and genomic tests. How this information is collected is less important than that relevant information is collected in the first place. There are many tools for collecting medical and family history information both by hand and electronically. Genetic and genomic testing should always be interpreted in the context of the personal and family history.

Awareness of family health history in a predominantly young adult population

Family health history (FHH) is a key predictor of health risk and is universally important in preventive care. However, patients may not be aware of the importance of FHH, and thus, may fail to accurately or completely share FHH with health providers, thereby limiting its utility. In this study, we conducted an online survey of 294 young adults and employees based at a US university setting regarding their knowledge, sharing behaviors, and perceived importance of FHH, and use of electronic clinical tools to document and update FHH. We also evaluated two educational interventions (written and video) to promote knowledge about FHH and its importance to health. We found that 93% of respondents were highly aware of their FHH, though only 39% reported collecting it and 4% using an online FHH tool. Seventy-three percent of respondents, particularly women, had shared FHH with their doctor when prompted, and fewer had shared it with family members. Participants in the video group were significantly more likely to understand the benefits of FHH than those in the written group (p = 0.02). In summary, educational resources, either video or written, will be helpful to promote FHH collection, sharing, and use of online FHH tools.

Family health history: underused for actionable risk assessment

Family health history (FHH) is the most useful means of assessing risk for common chronic diseases. The odds ratio for risk of developing disease with a positive FHH is frequently greater than 2, and actions can be taken to mitigate risk by adhering to screening guidelines, genetic counselling, genetic risk testing, and other screening methods. Challenges to the routine acquisition of FHH include constraints on provider time to collect data and the difficulty in accessing risk calculators. Disease-specific and broader risk assessment software platforms have been developed, many with clinical decision support and informatics interoperability, but few access patient information directly. Software that allows integration of FHH with the electronic medical record and clinical decision support capabilities has provided solutions to many of these challenges. Patient facing, electronic medical record, and web-enabled FHH platforms have been developed, and can provide greater identification of risk compared with conventional FHH ascertainment in primary care. FHH, along with cascade screening, can be an important component of population health management approaches to overall reduction of risk.

Opportunities, resources, and techniques for implementing genomics in clinical care

Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.

Opportunities and Challenges for Molecular Understanding of Ciliopathies-The 100,000 Genomes Project

Cilia are highly specialized cellular organelles that serve multiple functions in human development and health. Their central importance in the body is demonstrated by the occurrence of a diverse range of developmental disorders that arise from defects of cilia structure and function, caused by a range of different inherited mutations found in more than 150 different genes. Genetic analysis has rapidly advanced our understanding of the cell biological basis of ciliopathies over the past two decades, with more recent technological advances in genomics rapidly accelerating this progress. The 100,000 Genomes Project was launched in 2012 in the UK to improve diagnosis and future care for individuals affected by rare diseases like ciliopathies, through whole genome sequencing (WGS). In this review we discuss the potential promise and medical impact of WGS for ciliopathies and report on current progress of the 100,000 Genomes Project, reviewing the medical, technical and ethical challenges and opportunities that new, large scale initiatives such as this can offer.

Effect of Sociodemographic Factors on Uptake of a Patient-Facing Information Technology Family Health History Risk Assessment Platform

OBJECTIVE

Investigate sociodemographic differences in the use of a patient-facing family health history (FHH)-based risk assessment platform.

METHODS

In this large multisite trial with a diverse patient population, we evaluated the relationship between sociodemographic factors and FHH health risk assessment uptake using an information technology (IT) platform. The entire study was administered online, including consent, baseline survey, and risk assessment completion. We used multivariate logistic regression to model effect of sociodemographic factors on study progression. Quality of FHH data entered as defined as relatives: (1) with age of onset reported on relevant conditions; (2) if deceased, with cause of death and (3) age of death reported; and (4) percentage of relatives with medical history marked as unknown was analyzed using grouped logistic fixed effect regression.

RESULTS

A total of 2,514 participants consented with a mean age of 57 and 10.4% minority. Multivariate modeling showed that progression through study stages was more likely for younger (p-value = 0.005), more educated (p-value = 0.004), non-Asian (p-value = 0.009), and female (p-value = 0.005) participants. Those with lower health literacy or information-seeking confidence were also less likely to complete the study. Most significant drop-out occurred during the risk assessment completion phase. Overall, quality of FHH data entered was high with condition's age of onset reported 87.85%, relative's cause of death 85.55% and age of death 93.76%, and relative's medical history marked as unknown 19.75% of the time.

CONCLUSION

A demographically diverse population was able to complete an IT-based risk assessment but there were differences in attrition by sociodemographic factors. More attention should be given to ensure end-user functionality of health IT and leverage electronic medical records to lessen patient burden.