DNP-810 Topic 3 DQ 1: A multigenerational family health history can facilitate the management of a patient’s disease. What model would you use to create a multigenerational family health history for a patient? Explain. Support your rationale with a minimum of two scholarly sources.

DNP-810 Topic 3 DQ 1: A multigenerational family health history can facilitate the management of a patient's disease. What model would you use to create a multigenerational family health history for a patient? Explain. Support your rationale with a minimum of two scholarly sources.

DNP-810 Topic 3 DQ 1: A multigenerational family health history can facilitate the management of a patient’s disease. What model would you use to create a multigenerational family health history for a patient? Explain. Support your rationale with a minimum of two scholarly sources.

There are multiple tools available to evaluate a family health history. Some are person-facing meaning the patient controls and initiates the profile. Others are clinician-based where the data is managed and screened by the clinician. Some are web-based while others are not. Healthcare consumers have a multitude of health apps to select from. According to Singh et al. (2016), there are more than 165,000 health apps available in app stores for various smartphone operating systems, including the popular iTunes and Google Play. This can be daunting for a healthcare consumer to select an effective app to manage or mitigate chronic disease risk. There are numerous factors to consider as well. Some apps will allow families to contribute to the family health history while others do not. Some apps are collaborative with healthcare providers as well. Savy and prudent clients should review apps to ensure the resource is reliable as well. It is, for this reason, I would recommend the Family Healthware™.

Family Healthware™ is the only family history tool to be cleared by the Food and Drug Administration (Singh et al., 2016). It is web-based and can look at common life-threatening illnesses including heart disease, stroke, diabetes, colorectal cancer, breast cancer, and ovarian cancer (Center for Disease Control and Prevention (CDC), 2022). While this is not an all-inclusive list, it is a comprehensive list of common life-altering ailments. The risk of developing these diseases is twice that for people who have a first-degree relative with these specific conditions (Ginsburg et al., 2019). Because of this increased likelihood, it is a meaningful and concise tool to use. In using this program, the pedigree is reviewed, a risk assessment is completed, a health score is given along with screening recommendations, and a prevention plan (Welch et al., 2018).

Using a multigenerational family health history should involve both the patient, family, and provider to be effective. Using a tool that can assess risk and recommend personalized prevention makes it meaningful to the patient. An ideal model is incorporated into an electronic health care system to allow information flow between the individual and the healthcare team. Conducting a thorough family health history can be a complex endeavor that the healthcare team needs to partner with the patient and family in order to deliver precision patient-focused care.

References

Centers for Disease Control and Prevention. (2022, May 25th). Family Healthware™ . https://www.cdc.gov/genomics/famhistory/famhist_healthware.htm

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Get your assignment on DNP-810 Topic 3 DQ 1: A multigenerational family health history can facilitate the management of a patient’s disease. What model would you use to create a multigenerational family health history for a patient? Explain. Support your rationale with a minimum of two scholarly sources. done on time by medical experts. Don’t wait – ORDER NOW!

Ginsburg, G. S. Wu, R. R. & Orlando, L. A. (2019). Family health history: underused for actionable risk assessment. Lancet, 394 (10198), 596-603. Doi: 10.106/S0140-6736(19)31275-9

Singh, K., Drouin, K., Newmark, L. P., Filkins, M., Silvers, E., Bain, P. A., Zulman, D. M., Lee, J. H., Rozenblum, R., Pabo, E., Landman, A., Klinger, E. V., & Bates, D. W. (2016). Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review. JMIR mHealth and uHealth4(4), e136. https://doi.org/10.2196/mhealth.6445

Welch, B. M., Wiley, K., Pflieger, L., Achiangia, R., Baker, K., Hughes-Halbert, C., Morrison, H., Schiffman, J., & Doerr, M. (2018). Review and Comparison of Electronic Patient-Facing Family Health History Tools. Journal of Genetic Counseling27(2), 381–391. https://doi-org.lopes.idm.oclc.org/10.1007/s10897-018-0235-7

Thank you, Angela, for your discussion post. I see you mentioned your preference for using Family Health ware app In evaluating family health history. Evaluation of family health history is essential for establishing an individual’s risk for certain conditions. You mentioned that the Family health ware tool helps identify common chronic illnesses among relatives. I agree that risk assessment is fundamental for establishing prevention measures for a particular condition (Marcoux et al., 2017). The health ware as a risk assessment tool can help develop ways to avoid those conditions.

Consequently, this helps provide patient-centered care, which improves health outcomes. Integrating results into the Electronic health records allow interprofessional collaboration to share patient health information. With the data, the clinicians can provide patient-centered care that improves quality and safety.

Reference

Marcoux, V., Chouinard, M., Diadiou, F., Dufour, I. and Hudon, C., 2017. Screening tools to identify patients with complex health needs at risk of high use of health care services: A scoping review. PLOS ONE, 12(11), p.e0188663.

Thanks for your posting, Angela. I agree that a family history reflects genetic, environmental, and behavioral factors and is a significant risk factor for various diseases, including coronary artery disease, cancer, and diabetes. I also agree that Family Healthware is a family risk assessment tool for diseases such as coronary heart disease, stroke, diabetes, colorectal cancer, breast cancer, and ovarian cancer. I would like to point out it provides a prevention plan with individualized lifestyle changes and screening recommendations. In addition, the tool collects data on the health behaviors of first- and second-degree parents, screening tests, and medical history. Algorithms in the software analyze the family history data and assess familial risk based on the number of relatives affected, their age at disease onset, their sex, how closely related the relatives are to each other and the user, and the combinations of diseases in the family. The second set of algorithms uses the data on familial risk levels, health behaviors, and screening to generate personalized prevention messages(Zazove et al., 2015). 

Reference

Zazove, P.I A., Uhlmann, W. R., & Ruffin, M. T. (2015). Prompting primary care providers about increased patient risk due to family history: Does it work? The Journal of the American Board of Family Medicine28(3), 334–342. https://doi.org/10.3122/jabfm.2015.03.140149

A multigenerational medical family history also known as a pedigree or family tree is a cost-effective tool in preconception counseling to identify couples at risk to have offspring with inherited disorders and to identify if either partner has a personal risk for a disorder with a genetic etiology. Interpretation of a medical family history can provide risk assessment for reproductive planning and choices, inform a diagnosis to help identify a patient’s medical screening needs and clinical management, and build rapport with the patient or couple. The use of standardized pedigree is paramount to healthcare delivery.

The use of family health history tools to analyze individual patient risk can be complex. The ability to predict risk is limited to the accuracy and completeness of the information available to

those completing the history. Hence, there has been a lot of effort in improving the format of family health history data collection. Pedigree workbooks and online interactive software have been identified as potential solutions to improve the accuracy of each person’s data entry (Lin, Myers, Koehly & Marcum, 2019). Family health history that is obtained from multiple family members will have better accuracy and when available to clinicians, they can improve the prediction and risk assessments due to the higher degree of completeness and accuracy of the family health history report. Information from multiple family members can provide cross-validation of information and improve the prediction of risk. (Lin, Myers, Koehly & Marcum, 2019). Additionally, the status of family members whom others are reporting may be inaccurate,

incomplete or false-positive or false-negative. Hence, multifamily entry of personal or individual health information into a database is helpful to determine accurate levels of individual risk (Lin, Myers, Koehly & Marcum, 2019). Since there are barriers to collecting detailed family health history, tools such as MeTree that is computer-based with a clinical decision support system helps to streamline the process and allow for more accurate data entry, risk reports and recommendations (Buchanan et al., 2015). A personalized pedigree that represents family morbidity for diseases such as diabetes, heart disease and cancer are able to be produced and provide a risk assessment and behavioral strategies to modify risk (Wilson et al., 2016)

References

Buchanan, A., Christianson, C., Himmel, T., Powell, K., Agbaje, A., Ginsburg, G., Henrich, V., &

Orlando, L. (2015). Use of a Patient-Entered Family Health History Tool with Decision Support

in Primary Care: Impact of Identification of Increased Risk Patients on Genetic Counseling Attendance. Journal of Genetic Counseling, 24(1), 179-188.

https://doi-org.lopes.idm.oclc.org/10.1007/s10897-014-9753-0

Lin, J., Myers, M.F., Koehly, L.M. & Marcum, C. S. (2019). A Bayesian hierarchical logistic

regression model of multiple informant family health histories. BMC Med Res Methodol

19, 56. https://doi.org/10.1186/s12874-019-0700-5

Wilson, C. J., de la Haye, K., Coveney, J., Hughes, D. L., Hutchinson, A., Miller, C., Prichard, I.,

Ward, P., & Koehly, L. M. (2016). Protocol for a randomized controlled trial testing the impact of

feedback on familial risk of chronic diseases on family-level intentions to participate in preventive lifestyle behaviors. BMC Public Health, 16 (1), 1-11. https://doi-

org.lopes.idm.oclc.org/10.1186/s12889-016-3623-7

My agreement resided with you when you wrote that MeTree is an excellent platform that provides a clinical decision support system that helps streamline the process and allows for more accurate data entry, risk reports, and recommendations. MeTree is a web-based, patient-facing tool to collect family health history and inform clinicians of important health-related information (Davison, 2018). The creators behind MeTree analyze decision modeling and implementation science as it relates to identifying and managing individuals in clinical settings at increased risk for medical conditions (Davison, 2018). The strengths of this platform facilitate clinical decision-making, which asks patients to enter information such as diet, exercise, smoking, and family history. This information is often absent in electronic medical records or standardized forms (Davison, 2018). The panel notes that allowing patients to enter information beforehand can increase the quantity and quality of data compared with what is usually collected during a primary care visit (Davison, 2018). Although barriers continue to exist in various health screenings, MeTree is helping to promote risk management and shared decision-making by enhancing the provider-patient relationship (Davison, 2018). 

Reference

Davison, C. (2018). Genetic Data Integration: A Model for Clinical Implementation and Intervention Research.

When concerning a preferable method of organizing health information, ancestral charts, or rather pedigrees, are greatly useful when addressing inheritance patterns and possible shared environmental risk factors; interpretation of a pedigree can help identify individuals who may be at increased risk for various health problems. A pedigree shows relationships between family members and indicates which individuals have specific variants concerning genetic diseases, traits, or pathogens, coupled with a family’s vital state (Carver et al., 2018; Hickey et al., 2017). In addition, a pedigree can determine disease familial inheritance patterns and thereby serves as a visual representation of how members within one’s family are impacted or not by certain traits of inheritance. This information is essential in calculating the probability that the trait will be inherited in future offspring. We will primarily consider five significant types of inheritance: autosomal dominant (AD), autosomal recessive (AR), X-linked dominant (XD), X-linked recessive (XR), and Y-linked (Y) (Carver et al., 2018; Hickey et al., 2017).

The illustration of pedigrees can undergo considerable efficiency once proper and accurate familial patient-derived history is extracted. Thus, it can be drawn much quicker than recording the information in writing and allows patterns of a disease to emerge as the pedigree is drawn. Since the family history is continually changing, the pedigree can be easily updated on future visits. Circles represent females, and squares represent males (Carver et al., 2018; Hickey et al., 2017). By analyzing a pedigree, we can determine genotypes, identify phenotypes, and predict how a trait will be passed on in the future (Carver et al., 2018; Hickey et al., 2017). Draw any siblings in birth order from left (oldest) to the right (youngest). Siblings are connected by a horizontal line above the symbols, with vertical lines connecting the symbols to the horizontal line (Carver et al., 2018; Hickey et al., 2017). Leave space to add any partners and children. Add aunts, uncles, and grandparents in the same manner (Carver et al., 2018; Hickey et al., 2017).

References

Carver, T., Cunningham, A. P., Babb de Villiers, C., Lee, A., Hartley, S., Tischkowitz, M., … & Antoniou, A. C. (2018). Pedigrees: a web-based graphical pedigree editor. Bioinformatics, 34(6), 1069-1071.

Hickey, K. T., Katapodi, M. C., Coleman, B., Reuter‐Rice, K., & Starkweather, A. R. (2017). Improving utilization of the family history in the electronic health record. Journal of Nursing Scholarship, 49(1), 80-86.

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