The application of computer-based tools in obtaining the genetic family history

The value of parental medical records for the prediction of diabetes and cardiovascular disease: a novel method for generating and incorporating family histories

OBJECTIVE

To determine whether data-driven family histories (DDFH) derived from linked EHRs of patients and their parents can improve prediction of patients' 10-year risk of diabetes and atherosclerotic cardiovascular disease (ASCVD).

MATERIALS AND METHODS

A retrospective cohort study using data from Israel's largest healthcare organization. A random sample of 200 000 subjects aged 40-60 years on the index date (January 1, 2010) was included. Subjects with insufficient history (<1 year) or insufficient follow-up (<10 years) were excluded. Two separate XGBoost models were developed-1 for diabetes and 1 for ASCVD-to predict the 10-year risk for each outcome based on data available prior to the index date of January 1, 2010.

RESULTS

Overall, the study included 110 734 subject-father-mother triplets. There were 22 153 cases of diabetes (20%) and 11 715 cases of ASCVD (10.6%). The addition of parental information significantly improved prediction of diabetes risk (P < .001), but not ASCVD risk. For both outcomes, maternal medical history was more predictive than paternal medical history. A binary variable summarizing parental disease state delivered similar predictive results to the full parental EHR.

DISCUSSION

The increasing availability of EHRs for multiple family generations makes DDFH possible and can assist in delivering more personalized and precise medicine to patients. Consent frameworks must be established to enable sharing of information across generations, and the results suggest that sharing the full records may not be necessary.

CONCLUSION

DDFH can address limitations of patient self-reported family history, and it improves clinical predictions for some conditions, but not for all, and particularly among younger adults.

Patient Interactions With an Automated Conversational Agent Delivering Pretest Genetics Education: Descriptive Study

Background

Cancer genetic testing to assess an individual’s cancer risk and to enable genomics-informed cancer treatment has grown exponentially in the past decade. Because of this continued growth and a shortage of health care workers, there is a need for automated strategies that provide high-quality genetics services to patients to reduce the clinical demand for genetics providers. Conversational agents have shown promise in managing mental health, pain, and other chronic conditions and are increasingly being used in cancer genetic services. However, research on how patients interact with these agents to satisfy their information needs is limited.

Objective

Our primary aim is to assess user interactions with a conversational agent for pretest genetics education.

Methods

We conducted a feasibility study of user interactions with a conversational agent who delivers pretest genetics education to primary care patients without cancer who are eligible for cancer genetic evaluation. The conversational agent provided scripted content similar to that delivered in a pretest genetic counseling visit for cancer genetic testing. Outside of a core set of information delivered to all patients, users were able to navigate within the chat to request additional content in their areas of interest. An artificial intelligence–based preprogrammed library was also established to allow users to ask open-ended questions to the conversational agent. Transcripts of the interactions were recorded. Here, we describe the information selected, time spent to complete the chat, and use of the open-ended question feature. Descriptive statistics were used for quantitative measures, and thematic analyses were used for qualitative responses.

Results

We invited 103 patients to participate, of which 88.3% (91/103) were offered access to the conversational agent, 39% (36/91) started the chat, and 32% (30/91) completed the chat. Most users who completed the chat indicated that they wanted to continue with genetic testing (21/30, 70%), few were unsure (9/30, 30%), and no patient declined to move forward with testing. Those who decided to test spent an average of 10 (SD 2.57) minutes on the chat, selected an average of 1.87 (SD 1.2) additional pieces of information, and generally did not ask open-ended questions. Those who were unsure spent 4 more minutes on average (mean 14.1, SD 7.41; P=.03) on the chat, selected an average of 3.67 (SD 2.9) additional pieces of information, and asked at least one open-ended question.

Conclusions

The pretest chat provided enough information for most patients to decide on cancer genetic testing, as indicated by the small number of open-ended questions. A subset of participants were still unsure about receiving genetic testing and may require additional education or interpersonal support before making a testing decision. Conversational agents have the potential to become a scalable alternative for pretest genetics education, reducing the clinical demand on genetics providers.

Constructing data-derived family histories using electronic health records from a single healthcare delivery system

BACKGROUND

In order to examine the potential clinical value of integrating family history information directly from the electronic health records of patients' family members, the electronic health records of individuals in Clalit Health Services, the largest payer/provider in Israel, were linked with the records of their parents.

METHODS

We describe the results of a novel approach for creating data-derived family history information for 2 599 575 individuals, focusing on three chronic diseases: asthma, cardiovascular disease (CVD) and diabetes.

RESULTS

In our cohort, there were 256 598 patients with asthma, 55 309 patients with CVD and 66 324 patients with diabetes. Of the people with asthma, CVD or diabetes, the percentage that also had a family history of the same disease was 22.0%, 70.8% and 70.5%, respectively.

CONCLUSIONS

Linking individuals' health records with their data-derived family history has untapped potential for supporting diagnostic and clinical decision-making.

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.

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

Family health history (FHx) is one of the most important pieces of information available to help genetic counselors and other clinicians identify risk and prevent disease. Unfortunately, the collection of FHx from patients is often too time consuming to be done during a clinical visit. Fortunately, there are many electronic FHx tools designed to help patients gather and organize their own FHx information prior to a clinic visit. We conducted a review and analysis of electronic FHx tools to better understand what tools are available, to compare and contrast to each other, to highlight features of various tools, and to provide a foundation for future evaluation and comparisons across FHx tools. Through our analysis, we included and abstracted 17 patient-facing electronic FHx tools and explored these tools around four axes: organization information, family history collection and display, clinical data collected, and clinical workflow integration. We found a large number of differences among FHx tools, with no two the same. This paper provides a useful review for health care providers, researchers, and patient advocates interested in understanding the differences among the available patient-facing electronic FHx tools.

Compatibility of Family History Cancer Guidelines With Meaningful Use Standards

Purpose

To evaluate the potential of implementing established family cancer guidelines as clinical decision support within meaningful use (MU)-compliant health information technology systems. Methods We conducted a systematic analysis of cancer guidelines involving family health history (FHx) published before 2015. By comparing existing cancer guideline statements to current MU FHx standard requirements, we determined whether the cancer guideline statements could be implemented as clinical decision support. For guidelines that could not implemented, we determined the primary reasons for incompatibility.

Results

A total of 531 statements from 55 guidelines published by 11 different organizations were reviewed and analyzed. Overall, 18% to 66% of guideline statements could or could not be implemented in MU-compliant health information technology systems, depending on which MU standard was used. Health Level Seven (HL7) models performed better than SNOMED models. Implementability of guideline statements varied by cancer type and guideline organizations. The greatest deficiencies in implementability of statements were largely a result of the fact that MU standards required only first-degree relatives and that FHx terms used in guidelines statements were ambiguous.

Conclusion

FHx cancer guidelines and MU-based systems vary widely and are mostly incompatible. We identified sources of incompatibility and made recommendations that could improve the implementability of FHx cancer guidelines. Our findings and recommendations can enhance the use of established FHx cancer risk guidelines in routine clinical workflows.

The effect of referral for genetic counseling on genetic testing and surgical prevention in women at high risk for ovarian cancer: Results from a randomized controlled trial

BACKGROUND

Guidelines recommend genetic counseling and testing for women who have a pedigree suggestive of an inherited susceptibility for ovarian cancer. The authors evaluated the effect of referral to genetic counseling on genetic testing and prophylactic oophorectomy in a randomized controlled trial.

METHODS

Data from an electronic mammography reporting system identified 12,919 women with a pedigree that included breast cancer, of whom 625 were identified who had a high risk for inherited susceptibility to ovarian cancer using a risk-assessment questionnaire. Of these, 458 women provided informed consent and were randomized 1:1 to intervention consisting of a genetic counseling referral (n = 228) or standard clinical care (n = 230).

RESULTS

Participants were predominantly aged 45 to 65 years, and 30% and 20% reported a personal history of breast cancer or a family history of ovarian cancer, respectively. Eighty-five percent of women in the intervention group participated in a genetic counseling session. Genetic testing was reported by 74 (33%) and 20 (9%) women in the intervention and control arms (P < .005), respectively. Five women in the intervention arm and 2 in the control arm were identified as germline mutation carriers. Ten women in the intervention arm and 3 in the control arm underwent prophylactic bilateral salpingo-oophorectomy (P < .05).

CONCLUSIONS

Routine referral of women at high risk for ovarian cancer to genetic counseling promotes genetic testing and prophylactic surgery. The findings from the current randomized controlled trial demonstrate the value of implementing strategies that target women at high risk for ovarian cancer to ensure they are offered access to recommended care. CA Cancer J Clin 2016. © 2016 American Cancer Society, Inc. Cancer 2016;122:3509-3518. © 2016 American Cancer Society.

Securing and Documenting Cancer Family History in the Age of the Electronic Medical Record

Family health history is one of the least expensive, most useful, and most underused methods available to conduct assessments of the genetic aspect of a condition or to target the need for a genetic evaluation. This article introduces to the surgical oncologist the reason and process of collecting family history information. As medical records shift from paper to electronic formats, pedigree drawings are not readily available within the electronic health records. International efforts are underway to develop searchable, updatable, and interoperable formats that can collect family history information to inform clinical decision support for genetic risk assessment.

Impact of family history assessment on communication with family members and health care providers: A report from the Family Healthware™ Impact Trial (FHITr)

OBJECTIVE

This study examines the impact of Family Healthware™ on communication behaviors; specifically, communication with family members and health care providers about family health history.

METHODS

A total of 3786 participants were enrolled in the Family Healthware™ Impact Trial (FHITr) in the United States from 2005-7. The trial employed a two-arm cluster-randomized design, with primary care practices serving as the unit of randomization. Using generalized estimating equations (GEE), analyses focused on communication behaviors at 6month follow-up, adjusting for age, site and practice clustering.

RESULTS

A significant interaction was observed between study arm and baseline communication status for the family communication outcomes (p's<.01), indicating that intervention had effects of different magnitude between those already communicating at baseline and those who were not. Among participants who were not communicating at baseline, intervention participants had higher odds of communicating with family members about family history risk (OR=1.24, p=0.042) and actively collecting family history information at follow-up (OR=2.67, p=0.026). Family Healthware™ did not have a significant effect on family communication among those already communicating at baseline, or on provider communication, regardless of baseline communication status. Greater communication was observed among those at increased familial risk for a greater number of diseases.

CONCLUSION

Family Healthware™ prompted more communication about family history with family members, among those who were not previously communicating. Efforts are needed to identify approaches to encourage greater sharing of family history information, particularly with health care providers.

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.

Acceptability and feasibility of a virtual counselor (VICKY) to collect family health histories

PURPOSE

To overcome literacy-related barriers in the collection of electronic family health histories, we developed an animated Virtual Counselor for Knowing your Family History, or VICKY. This study examined the acceptability and accuracy of using VICKY to collect family histories from underserved patients as compared with My Family Health Portrait (MFHP).

METHODS

Participants were recruited from a patient registry at a safety net hospital and randomized to use either VICKY or MFHP. Accuracy was determined by comparing tool-collected histories with those obtained by a genetic counselor.

RESULTS

A total of 70 participants completed this study. Participants rated VICKY as easy to use (91%) and easy to follow (92%), would recommend VICKY to others (83%), and were highly satisfied (77%). VICKY identified 86% of first-degree relatives and 42% of second-degree relatives; combined accuracy was 55%. As compared with MFHP, VICKY identified a greater number of health conditions overall (49% with VICKY vs. 31% with MFHP; incidence rate ratio (IRR): 1.59; 95% confidence interval (95% CI): 1.13-2.25; P = 0.008), in particular, hypertension (47 vs. 15%; IRR: 3.18; 95% CI: 1.66-6.10; P = 0.001) and type 2 diabetes (54 vs. 22%; IRR: 2.47; 95% CI: 1.33-4.60; P = 0.004).

CONCLUSION

These results demonstrate that technological support for documenting family history risks can be highly accepted, feasible, and effective.

Veterans' experience in using the online Surgeon General's family health history tool

AIM: To assess veterans' experience and satisfaction in using the Surgeon General's (SG) online family health history (FHH) tool, and determine the perceived facilitators and barriers to using the online SG-FHH tool. MATERIALS #ENTITYSTARTX00026; METHODS: A mixed-method using both qualitative and quantitative approaches was employed in this study. A total of 35 veterans at the VA Medical Center in San Antonio, Texas, USA were invited to enter their FHH information using the online SG-FHH tool, complete the study's satisfaction survey and participate in a short semi-structured interview. The goal of the semi-structured interviews was to assess participants perceived facilitators and barriers to using the online SG-FHH tool. All participants were also provided with a printed copy of their pedigree, which was generated by the SG-FHH tool and were encouraged to share it with their relatives and providers. RESULTS: The majority of participants (91%) said that they had access to a computer with internet capability and 77% reported that they knew how to use a computer. More than two-thirds of the participants felt that items on the SG-FHH tool were easy to read and felt that FHH categories were relevant to their family's health. Approximately 94% of participants viewed the SG-FHH tool as useful, and the majority of participants (97%) indicated that they were likely to recommend the tool to others. Content analysis of the semi-structured interviews highlighted several barriers to veterans' use of the SG-FHH tool and their FHH information. These included: lack of patients' knowledge regarding their relatives' FHH, and privacy and confidentiality concerns. CONCLUSION: This study provides information on the performance and functionality of an inexpensive and widely accessible method for FHH collection. Furthermore, our findings highlight several opportunities and challenges facing the utilization of FHH information as a clinical and genomic tool at the Veterans Health Administration (VHA). The results suggest that strategies that improve veterans' knowledge regarding the importance of their FHH information and that address their concerns about privacy and confidentiality may enhance the successful implementation of FHH information into VHA clinical practice. IMPLICATIONS: identifying a locally accepted method for FHH collection and documentation which can be conducted outside of the patient visit will reduce time burdens for providers and patients and allow for a focus on other important topics during clinic visits. Improvement in familial risk screening and assessment will enable the VHA to be prepared for personalized medicine and focus their resources on promoting critically important health behaviors for populations with the highest risk of developing chronic diseases and their complications.

Electronic medical records and personalized medicine

If the dream of personalized medicine is to be realized, tremendous amounts of data specific to each individual must be captured, synthesized and presented to clinicians at the time this information is needed to make care decisions for the patient. This can only be accomplished through the use of sophisticated electronic medical record (EMR) systems that are designed to support this function. This article will define two important aspects of a fully functional EMR the ability to: present patients or clinicians with high quality context specific information at the point of care (so-called "just-in time" education) and to combine clinically relevant information from disparate sources in order to guide the clinician to the optimized intervention for a given patient (clinical decision support). Personalized medicine examples are used to illustrate these concepts. As implemented most EMR systems are not being used to assimilate the information needed to provide personalized medicine. A description of necessary enhancements to currently available systems that will be needed to create a "personalized medicine enabled" EMR is provided.