Quality of family history collection with use of a patient facing family history assessment tool

Opportunities for Improving Detection of Cancer Predisposition Syndromes in Pediatric Solid Tumor Patients

BACKGROUND

Detection of cancer predisposition syndromes (CPS) depends on identifying risk factors, including tumor type, family history, and physical findings, to prompt referral for genetic counseling/testing. Whether pediatric oncology providers (POPs) collect adequate family history information is unknown.

METHODS

A single-institution retrospective chart review of solid tumor patients <18 years of age referred for a CPS evaluation between January 1, 2017 and January 31, 2019 was performed. POP adherence to American Society of Clinical Oncology (ASCO) family history collection recommendations was measured and compared with genetic counselor performance. Whether sufficient family history was documented to satisfy the criteria of three genetic counseling referral guidelines [American College of Medical Genetics (ACMG), updated Jongmans (UJ), and McGill Interactive Pediatric OncoGenetic Guidelines (MIPOGG)] was evaluated.

RESULTS

POPs and genetic counselors achieved all 6 ASCO family history metrics in 3% and 99% of 129 eligible cases, respectively. POPs failed to document sufficient family history to satisfy genetic counseling referral criteria in most cases (74% ACMG, 73% UJ, 79% MIPOGG).

CONCLUSIONS

POPs perform poorly in family history collection, raising concern that some patients at risk for a CPS based on their family history may not be referred for genetic counseling/testing. Interventions to improve family history collection are needed to enhance CPS detection.

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.

A Cluster Randomized Trial of a Family Health History Platform to Identify and Manage Patients at Increased Risk for Colorectal Cancer

BACKGROUND

Obtaining comprehensive family health history (FHH) to inform colorectal cancer (CRC) risk management in primary care settings is challenging.

OBJECTIVE

To examine the effectiveness of a patient-facing FHH platform to identify and manage patients at increased CRC risk.

DESIGN

Two-site, two-arm, cluster-randomized, implementation-effectiveness trial with primary care providers (PCPs) randomized to immediate intervention versus wait-list control.

PARTICIPANTS

PCPs treating patients at least one half-day per week; patients aged 40-64 with no medical conditions that increased CRC risk.

INTERVENTIONS

Immediate-arm patients entered their FHH into a web-based platform that provided risk assessment and guideline-driven decision support; wait-list control patients did so 12 months later.

MAIN MEASURES

McNemar's test examined differences between the platform and electronic medical record (EMR) in rates of increased risk documentation. General estimating equations using logistic regression models compared arms in risk-concordant provider actions and patient screening test completion. Referral for genetic consultation was analyzed descriptively.

KEY RESULTS

Seventeen PCPs were randomized to each arm. Patients (n = 252 immediate, n = 253 control) averaged 51.4 (SD = 7.2) years, with 83% assigned male at birth, 58% White persons, and 33% Black persons. The percentage of patients identified as increased risk for CRC was greater with the platform (9.9%) versus EMR (5.2%), difference = 4.8% (95% CI: 2.6%, 6.9%), p < .0001. There was no difference in PCP risk-concordant action [odds ratio (OR) = 0.7, 95% CI (0.4, 1.2; p = 0.16)]. Among 177 patients with a risk-concordant screening test ordered, there was no difference in test completion, OR = 0.8 [0.5,1.3]; p = 0.36. Of 50 patients identified by the platform as increased risk, 78.6% immediate and 68.2% control patients received a recommendation for genetic consultation, of which only one in each arm had a referral placed.

CONCLUSIONS

FHH tools could accurately assess and document the clinical needs of patients at increased risk for CRC. Barriers to acting on those recommendations warrant further exploration.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov NCT02247336 https://clinicaltrials.gov/ct2/show/NCT02247336.

Patients Managing Their Medical Data in Personal Electronic Health Records: Scoping Review

BACKGROUND

Personal electronic health records (PEHRs) allow patients to view, generate, and manage their personal and medical data that are relevant across illness episodes, such as their medications, allergies, immunizations, and their medical, social, and family health history. Thus, patients can actively participate in the management of their health care by ensuring that their health care providers have an updated and accurate overview of the patients' medical records. However, the uptake of PEHRs remains low, especially in terms of patients entering and managing their personal and medical data in their PEHR.

OBJECTIVE

This scoping review aimed to explore the barriers and facilitators that patients face when deciding to review, enter, update, or modify their personal and medical data in their PEHR. This review also explores the extent to which patient-generated and -managed data affect the quality and safety of care, patient engagement, patient satisfaction, and patients' health and health care services.

METHODS

We searched the MEDLINE, Embase, CINAHL, PsycINFO, Cochrane Library, Web of Science, and Google Scholar web-based databases, as well as reference lists of all primary and review articles using a predefined search query.

RESULTS

Of the 182 eligible papers, 37 (20%) provided sufficient information about patients' data management activities. The results showed that patients tend to use their PEHRs passively rather than actively. Patients refrain from generating and managing their medical data in a PEHR, especially when these data are complex and sensitive. The reasons for patients' passive data management behavior were related to their concerns about the validity, applicability, and confidentiality of patient-generated data. Our synthesis also showed that patient-generated and -managed health data ensures that the medical record is complete and up to date and is positively associated with patient engagement and patient satisfaction.

CONCLUSIONS

The findings of this study suggest recommendations for implementing design features within the PEHR and the construal of a dedicated policy to inform both clinical staff and patients about the added value of patient-generated data. Moreover, clinicians should be involved as important ambassadors in informing, reminding, and encouraging patients to manage the data in their PEHR.

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.

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.

Landscape of germline cancer predisposition mutations testing and management in pediatrics: Implications for research and clinical care

As germline genetic testing capacities have improved over the last two decades, increasingly more people are newly diagnosed with germline cancer susceptibility mutations. In the wake of this growth, there remain limitations in both testing strategies and translation of these results into morbidity- and mortality-reducing practices, with pediatric populations remaining especially vulnerable. To face the challenges evoked by an expanding diversity of germline cancer mutations, we can draw upon a model cancer-associated genetic condition for which we have developed a breadth of expertise in managing, Trisomy 21. We can additionally apply advances in other disciplines, such as oncofertility and pharmacogenomics, to enhance care delivery. Herein, we describe the history of germline mutation testing, epidemiology of known germline cancer mutations and their associations with childhood cancer, testing limitations, and future directions for research and clinical care.

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.

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.

Concordance Between Electronic Health Record and Tumor Registry Documentation of Smoking Status Among Patients With Cancer

PURPOSE

Patients with cancer who use tobacco experience reduced treatment effectiveness, increased risk of recurrence and mortality, and diminished quality of life. Accurate tobacco use documentation for patients with cancer is necessary for appropriate clinical decision making and cancer outcomes research. Our aim was to assess agreement between electronic health record (EHR) smoking status data and cancer registry data.

MATERIALS AND METHODS

We identified all patients with cancer seen at University of Florida Health from 2015 to 2018. Structured EHR smoking status was compared with the tumor registry smoking status for each patient. Sensitivity, specificity, positive predictive values, negative predictive values, and Kappa statistics were calculated. We used logistic regression to determine if patient characteristics were associated with odds of agreement in smoking status between EHR and registry data.

RESULTS

We analyzed 11,110 patient records. EHR smoking status was documented for nearly all (98%) patients. Overall kappa (0.78; 95% CI, 0.77 to 0.79) indicated moderate agreement between the registry and EHR. The sensitivity was 0.82 (95% CI, 0.81 to 0.84), and the specificity was 0.97 (95% CI, 0.96 to 0.97). The logistic regression results indicated that agreement was more likely among patients who were older and female and if the EHR documentation occurred closer to the date of cancer diagnosis.

CONCLUSION

Although documentation of smoking status for patients with cancer is standard practice, we only found moderate agreement between EHR and tumor registry data. Interventions and research using EHR data should prioritize ensuring the validity of smoking status data. Multilevel strategies are needed to achieve consistent and accurate documentation of smoking status in cancer care.

Clinical implementation of an oncology-specific family health history risk assessment tool

BACKGROUND

The presence of hereditary cancer syndromes in cancer patients can have an impact on current clinical care and post-treatment prevention and surveillance measures. Several barriers inhibit identification of hereditary cancer syndromes in routine practice. This paper describes the impact of using a patient-facing family health history risk assessment platform on the identification and referral of breast cancer patients to genetic counselling services.

METHODS

This was a hybrid implementation-effectiveness study completed in breast cancer clinics. English-literate patients not previously referred for genetic counselling and/or gone through genetic testing were offered enrollment. Consented participants were provided educational materials on family health history collection, entered their family health history into the platform and completed a satisfaction survey. Upon completion, participants and their clinicians were given personalized risk reports. Chart abstraction was done to identify actions taken by patients, providers and genetic counsellors.

RESULTS

Of 195 patients approached, 102 consented and completed the study (mean age 55.7, 100 % women). Sixty-six (65 %) met guideline criteria for genetic counseling of which 24 (36 %) were referred for genetic counseling. Of those referred, 13 (54 %) participants attended and eight (33 %) completed genetic testing. On multivariate logistic regression, referral was not associated with age, cancer stage, or race but was associated with clinical provider (p = 0.041). Most providers (71 %) had higher referral rates during the study compared to prior. The majority of participants found the experience useful (84 %), were more aware of their health risks (83 %), and were likely to recommend using a patient-facing platform to others (69 %).

CONCLUSIONS

65 % of patients attending breast cancer clinics in this study are at-risk for hereditary conditions based on current guidelines. Using a patient-facing risk assessment platform enhances the ability to identify these patients systematically and with widespread acceptability and recognized value by patients. As only a third of at-risk participants received referrals for genetic counseling, further understanding barriers to referral is needed to optimize hereditary risk assessment in oncology practices.

TRIAL REGISTRATION

NIH Clinical Trials registry, NCT04639934 . Registered Nov 23, 2020 -- Retrospectively registered.

Family history assessment significantly enhances delivery of precision medicine in the genomics era

BACKGROUND

Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection.

METHODS

To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes.

RESULTS

Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant.

CONCLUSIONS

These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02791152 . Retrospectively registered on May 31, 2016.

At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care

Background

Risk assessment is a precision medicine technique that can be used to enhance population health when applied to prevention. Several barriers limit the uptake of risk assessment in health care systems; and little is known about the potential impact that adoption of systematic risk assessment for screening and prevention in the primary care population might have. Here we present results of a first of its kind multi-institutional study of a precision medicine tool for systematic risk assessment.

Methods

We undertook an implementation-effectiveness trial of systematic risk assessment of primary care patients in 19 primary care clinics at four geographically and culturally diverse healthcare systems. All adult English or Spanish speaking patients were invited to enter personal and family health history data into MeTree, a patient-facing family health history driven risk assessment program, for 27 medical conditions. Risk assessment recommendations followed evidence-based guidelines for identifying and managing those at increased disease risk.

Results

One thousand eight hundred eighty-nine participants completed MeTree, entering information on N = 25,967 individuals. Mean relatives entered = 13.7 (SD 7.9), range 7–74. N = 1443 (76.4%) participants received increased risk recommendations: 597 (31.6%) for monogenic hereditary conditions, 508 (26.9%) for familial-level risk, and 1056 (56.1%) for risk of a common chronic disease. There were 6617 recommendations given across the 1443 participants. In multivariate analysis, only the total number of relatives entered was significantly associated with receiving a recommendation.

Conclusions

A significant percentage of the general primary care population meet criteria for more intensive risk management. In particular 46% for monogenic hereditary and familial level disease risk. Adopting strategies to facilitate systematic risk assessment in primary care could have a significant impact on populations within the U.S. and even beyond.

Trial registration

Clinicaltrials.gov number NCT01956773, registered 10/8/2013.

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.

Population prevalence of individuals meeting criteria for hereditary breast and ovarian cancer testing

Background

Personal cancer diagnosis and family cancer history factor into which individuals should undergo genetic testing for hereditary breast and ovarian cancer (HBOC) syndrome. Family history is often determined in the research setting through kindreds with disease clusters, or clinically from self‐report. The population prevalence of individuals with diagnostic characteristics and/or family cancer history meeting criteria for HBOC testing is unknown.

Methods

Utilizing Surveillance, Epidemiology, and End Results (SEER) cancer registry data and a research resource linking registry records to genealogies, the Utah Population Database, the population‐based prevalence of diagnostic and family history characteristics meeting National Comprehensive Cancer Network (NCCN) criteria for HBOC testing was objectively assessed.

Results

Among Utah residents with an incident breast cancer diagnosis 2010‐2015 and evaluable for family history, 21.6% met criteria for testing based on diagnostic characteristics, but the proportion increased to 62.9% when family history was evaluated. The proportion of cases meeting testing criteria at diagnosis was 94% for ovarian cancer, 23% for prostate cancer, and 51.1% for pancreatic cancer. Among an unaffected Utah population of approximately 1.7 million evaluable for family history, 197,601 or 11.6% met testing criteria based on family history.

Conclusions

This study quantifies the population‐based prevalence of HBOC criteria using objectively determined genealogy and cancer incidence data. Sporadic breast cancer likely represents a portion of the high prevalence of family cancer history seen in this study. These results underline the importance of establishing presence of a deleterious mutation in an affected family member, per NCCN guidelines, before testing unaffected relatives.

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.

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.

Validation of a digital identification tool for individuals at risk for hereditary cancer syndromes

Background

The number of individuals meeting criteria for genetic counseling and testing for hereditary cancer syndromes (HCS) is far less than the number that actually receive it. To facilitate identification of patients at risk for HCS, Counsyl developed a digital identification tool (digital ID tool) to match personal and family cancer history to National Comprehensive Cancer Network (NCCN) BRCA-related Hereditary Breast and Ovarian Cancer (HBOC), Lynch syndrome, and polyposis testing criteria in one-to-one, automated fashion. The purpose of this study was to validate the ability of the digital ID tool to accurately identify histories that do and do not meet NCCN testing criteria.

Methods

Third-party recorded three-generation pedigrees were retrospectively reviewed by a certified genetic counselor (CGC) to determine if independent events included in pedigree histories met NCCN guidelines, and were then sorted into groups: high risk events (meets criteria) and low risk events (does not meet criteria). Events were entered into the digital ID tool to determine the extent of its concordance with events sorted by CGC review. Statistical tests of accuracy were calculated at a 95% confidence interval (CI).

Results

One hundred ninety-seven pedigrees were reviewed consecutively representing 765 independent events for analysis across groups. 382/382 (100%) high risk events identified by the digital ID tool and 381/383 (99.47%) low risk events identified by the digital ID tool were concordant with CGC sorting. The digital ID tool had a sensitivity of 100% (99.04–100% CI) and specificity of 99.48% (98.13–99.94% CI). The overall accuracy of the digital ID tool was estimated to be 99.74% (99.06–99.97% CI), reflecting the rate at which the digital ID tool reached the same conclusion as that of CGC review of pedigree events for the recommendation of genetic testing for individuals at risk for HCS.

Conclusions

The digital ID tool accurately matches NCCN criteria in one-to-one fashion to identify at-risk individuals for HCS and may be useful in clinical practice, specifically for BRCA-related HBOC and Lynch Syndrome.

Electronic supplementary material

The online version of this article (10.1186/s13053-018-0099-8) contains supplementary material, which is available to authorized users.

What characterizes cancer family history collection tools? A critical literature review

Background

Many tools have been developed for the standardized collection of cancer family history (fh). However, it remains unclear which tools have the potential to help health professionals overcome traditional barriers to collecting such histories. In this review, we describe the characteristics, validation process, and performance of existing tools and appraise the extent to which those tools can support health professionals in identifying and managing at-risk individuals.

Methods

Studies were identified through searches of the medline, embase, and Cochrane central databases from October 2015 to September 2016. Articles were included if they described a cancer fh collection tool, its use, and its validation process.

Results

Based on seventy-nine articles published between February 1978 and September 2016, 62 tools were identified. Most of the tools were paper-based and designed to be self-administered by lay individuals. One quarter of the tools could automatically produce pedigrees, provide cancer-risk assessment, and deliver evidence-based recommendations. One third of the tools were validated against a standard reference for collected fh quality and cancer-risk assessment. Only 3 tools were integrated into an electronic health records system.

Conclusions

In the present review, we found no tool with characteristics that might make it an efficient clinical support for health care providers in cancer-risk identification and management. Adequately validated tools that are connected to electronic health records are needed to encourage the systematic identification of individuals at increased risk of cancer.

Defining Phenotypes from Clinical Data to Drive Genomic Research

The rise in available longitudinal patient information in electronic health records (EHRs) and their coupling to DNA biobanks has resulted in a dramatic increase in genomic research using EHR data for phenotypic information. EHRs have the benefit of providing a deep and broad data source of health-related phenotypes, including drug response traits, expanding the phenome available to researchers for discovery. The earliest efforts at repurposing EHR data for research involved manual chart review of limited numbers of patients but now typically involve applications of rule-based and machine learning algorithms operating on sometimes huge corpora for both genome-wide and phenome-wide approaches. We highlight here the current methods, impact, challenges, and opportunities for repurposing clinical data to define patient phenotypes for genomics discovery. Use of EHR data has proven a powerful method for elucidation of genomic influences on diseases, traits, and drug-response phenotypes and will continue to have increasing applications in large cohort studies.

Challenges with Collecting Smoking Status in Electronic Health Records

Smoking is the leading cause of preventable death in the United States. Obtaining patients' smoking status is the first step in delivering smoking cessation counseling. In this study, we assessed the quality of smoking status captured in an electronic health record from a large academic medical center. We analyzed data from structured notes, finding that smoking status was documented in 98% of 64,451 hospital encounters in 2016. 32% hospital encounters had discrepant documentation, and 54.5% of patients had implausible changes (e.g., changes from "current smoker" to "never smoker"). Overall, only 2.9% of patients were documented as active smokers, but 36.4% were documented as "unknown" or had discrepancies in their smoking status. These results suggest that patients that smoke are not appropriately identified. Centralized documentation with clinically actionable smoking status categories and implementation of patient-facing tools that allow patients to directly record their information could improve data quality of smoking status.

Improving Utilization of the Family History in the Electronic Health Record

PURPOSE

The purpose of this article is to provide an overview of Family History in the Electronic Health Record and to identify opportunities to advance the contributions of nurses in obtaining, updating and assessing family history in order to improve the health of all individuals and populations.

ORGANIZING CONSTRUCT

The article presents an overview of the obstacles to charting Family History within the Electronic Health Record and recommendations for using specific Family History tools and core Family History data sets.

METHODS

Opportunities to advance nursing contributions in obtaining, updating, and assessing family history in order to improve the health of all individuals were identified. These opportunities are focused within the area of promoting the importance of communication within families and between healthcare providers to obtain, document, and update family histories.

FINDINGS

Nurses can increase awareness of existing resources that can guide collection of a comprehensive and accurate family history and facilitate family discussions. In this paper, opportunities to advance nursing contributions in obtaining, updating, and assessing family history in order to improve the health of all individuals were identified.

CONCLUSIONS

Aligned with the clinical preparation of nurses, family health should be used routinely by nurses for risk assessment and to help inform patient and family members on screening, health promotion, and disease prevention. The quality of family health information is critical in order to leverage the use of genomic healthcare information and derive new knowledge about disease biology, treatment efficacy, and drug safety. These actionable steps need to be performed in the context of promoting evidence-based applications of family history that will be essential for implementing personalized genomic healthcare approaches and disease prevention efforts.

CLINICAL RELEVANCE

Family health history is one of the most important tools for identifying the risk of developing rare and chronic conditions, including cardiovascular disease, cancer, and diabetes, and represents an integration of disease risk from genetic, environmental, and behavioral/lifestyle factors. In fact, family history has long been recognized as a strong independent risk factor for disease and is the current best practice used in clinical practice to guide risk assessment.

Understanding the contribution of family history to colorectal cancer risk and its clinical implications: A state-of-the-science review

Persons with a family history (FH) of colorectal cancer (CRC) or adenomas that are not due to known hereditary syndromes have an increased risk for CRC. An understanding of these risks, screening recommendations, and screening behaviors can inform strategies for reducing the CRC burden in these families. A comprehensive review of the literature published within the past 10 years has been performed to assess what is known about cancer risk, screening guidelines, adherence and barriers to screening, and effective interventions in persons with an FH of CRC and to identify FH tools used to identify these individuals and inform care. Existing data show that having 1 affected first-degree relative (FDR) increases the CRC risk 2-fold, and the risk increases with multiple affected FDRs and a younger age at diagnosis. There is variability in screening recommendations across consensus guidelines. Screening adherence is <50% and is lower in persons under the age of 50 years. A provider's recommendation, multiple affected relatives, and family encouragement facilitate screening; insufficient collection of FH, low knowledge of guidelines, and poor family communication are important barriers. Effective interventions incorporate strategies for overcoming barriers, but these have not been broadly tested in clinical settings. Four strategies for reducing CRC in persons with familial risk are suggested: 1) improving the collection and utilization of the FH of cancer, 2) establishing a consensus for screening guidelines by FH, 3) enhancing provider-patient knowledge of guidelines and communication about CRC risk, and 4) encouraging survivors to promote screening within their families and partnering with existing screening programs to expand their reach to high-risk groups. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2633-2645. © 2016 American Cancer Society.

Personalized medicine in thrombosis: back to the future

Most physicians believe they practiced personalized medicine prior to the genomics era that followed the sequencing of the human genome. The focus of personalized medicine has been primarily genomic medicine, wherein it is hoped that the nucleotide dissimilarities among different individuals would provide clinicians with more precise understanding of physiology, more refined diagnoses, better disease risk assessment, earlier detection and monitoring, and tailored treatments to the individual patient. However, to date, the "genomic bench" has not worked itself to the clinical thrombosis bedside. In fact, traditional plasma-based hemostasis-thrombosis laboratory testing, by assessing functional pathways of coagulation, may better help manage venous thrombotic disease than a single DNA variant with a small effect size. There are some new and exciting discoveries in the genetics of platelet reactivity pertaining to atherothrombotic disease. Despite a plethora of genetic/genomic data on platelet reactivity, there are relatively little actionable pharmacogenetic data with antiplatelet agents. Nevertheless, it is crucial for genome-wide DNA/RNA sequencing to continue in research settings for causal gene discovery, pharmacogenetic purposes, and gene-gene and gene-environment interactions. The potential of genomics to advance medicine will require integration of personal data that are obtained in the patient history: environmental exposures, diet, social data, etc. Furthermore, without the ritual of obtaining this information, we will have depersonalized medicine, which lacks the precision needed for the research required to eventually incorporate genomics into routine, optimal, and value-added clinical care.

Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study

Background

Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study’s protocol.

Methods/design

MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff.

Discussion

This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness.

Trial registration

NCT01956773

Implementation of health risk assessments with family health history: barriers and benefits

Health risk assessments provide an opportunity to emphasise health promotion and disease prevention for individuals and populations at large. A key component of health risk assessments is the detailed collection of family health history information. This information is helpful in determining risk both for common chronic conditions and more rare diseases as well. While the concept of health risk assessments has been around since the Framingham Heart Study was launched in the 1950s, and such assessments are commonly performed in the workplace today, the US healthcare system has been slow to embrace them and the emphasis on prevention that they represent. Before wider implementation of health risk assessments within healthcare can be seen, several concerns must be addressed: (1) provider impact, (2) patient impact, (3) validity of patient-entered data and (4) health outcomes effect. Here, we describe recent developments in health risk assessment design that are helping to address these issues.

Multi-source development of an integrated model for family health history

OBJECTIVE

To integrate data elements from multiple sources for informing comprehensive and standardized collection of family health history (FHH).

MATERIALS AND METHODS

Three types of sources were analyzed to identify data elements associated with the collection of FHH. First, clinical notes from multiple resources were annotated for FHH information. Second, questions and responses for family members in patient-facing FHH tools were examined. Lastly, elements defined in FHH-related specifications were extracted for several standards development and related organizations. Data elements identified from the notes, tools, and specifications were subsequently combined and compared.

RESULTS

In total, 891 notes from three resources, eight tools, and seven specifications associated with four organizations were analyzed. The resulting Integrated FHH Model consisted of 44 data elements for describing source of information, family members, observations, and general statements about family history. Of these elements, 16 were common to all three source types, 17 were common to two, and 11 were unique. Intra-source comparisons also revealed common and unique elements across the different notes, tools, and specifications.

DISCUSSION

Through examination of multiple sources, a representative and complementary set of FHH data elements was identified. Further work is needed to create formal representations of the Integrated FHH Model, standardize values associated with each element, and inform context-specific implementations.

CONCLUSIONS

There has been increased emphasis on the importance of FHH for supporting personalized medicine, biomedical research, and population health. Multi-source development of an integrated model could contribute to improving the standardized collection and use of FHH information in disparate systems.