Family health history: underused for actionable risk assessment

doi:10.1016/S0140-6736(19)31275-9

The Lancet

Volume 394, Issue 10198, 17–23 August 2019, Pages 596-603

https://doi.org/10.1016/S0140-6736(19)31275-9 Get rights and content

Summary

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.

Introduction

A detailed family health history (FHH) is the most useful tool for risk assessment for common chronic diseases. The relative risks and odds ratios (ORs) for various cancers, stroke, type 2 diabetes, and cardiovascular diseases exceed 2 for people with an affected first degree relative, and exceed 4 for many of these diseases if there is more than one affected first degree relative.¹ Although the Human Genome Project, genome-wide association studies, genome sequencing, and polygenic risk scores all portend a similar ability, FHH has remained the gold standard for risk assessment. The goals of precision health care and the capture and use of a high quality FHH are highly aligned. Precision health care aims to gather environmental, molecular, and social information from a person to make decisions that are tailored to that individual. FHH contains information relevant to these spheres of risk. Furthermore, FHH can help with decisions early in life to mitigate risks of diseases that might present later, such as adoption of better dietary habits in the face of the risk of heart disease or of diabetes. An FHH can be added to and passed on to future generations, providing a foundational risk profile for immediate family and their progeny for generations to come.

Section snippets

FHH and health risk assessment

In 1961, Kannel and colleagues² first used the term “factors of risk,” indicating that male sex, diabetes, high serum cholesterol, high blood pressure, and a positive FHH of early heart disease could inform a model for predicting heart disease, which is now widely known as the Framingham Risk Score.³ These same risk factors have now become the basis for health risk assessments (HRAs) for heart disease. HRAs are an essential component of establishing an individual's risk for developing common

Using FHH tools versus conventional acquisition of FHH

FHH is underused by practitioners and represents a missed opportunity for risk stratification.²⁰ A systematic review²¹ found a 46–78% improvement in data recording by FHH tools as compared with the use of standard practice. FHH tools show excellent concordance with structured pedigree interviews and the gold standard three-generation pedigree.²² In a study²³ of 1124 primary care patients, medical record documentation was insufficient in two-thirds of charts for FHH assessment of six common

Clinical validity and clinical utility of FHH

If FHH is to be collected more systematically and patients are to become a major source of data entry for their FHH, then questions of analytic validity; clinical validity; clinical utility; and ethical, legal, and social issues should be examined. A useful framework for examining these questions is the analytic validity, clinical validity, clinical utility, ethical issues (ACCE) framework.²⁶ Initially developed as a way for policy makers and clinicians to investigate genetic testing

FHH and population health

If applied across the general population, systematic FHH-based risk assessment has the potential to have a substantial effect on population health management. Up to 44% of people meet criteria for increased risk for at least one hereditary condition based on current guidelines, so the potential for impact on health is huge.⁴⁰ Scaled to a population, FHH becomes a means of assessing the true risk and potential costs that a health system might use to better manage its financial risk. When

Future directions

FHH has the potential to become a key platform for risk assessment, precision health care, and population health management. Genome sequence data combined with FHH, lifestyle, and environmental data will provide the most robust means to identify individuals at risk and clear actions to reduce the risk of common complex diseases. With the advent of global digitisation of medicine and patient and consumer empowerment, health systems around the globe should adopt patient-facing FHH applications

References (88)

M Inouye et al.
Genomic risk prediction of coronary artery disease in 480 000 adults
J Am Coll Cardiol
(2018)
RA Stockley
Alpha1-antitrypsin review
Clin Chest Med
(2014)
KC Kent et al.
Screening for abdominal aortic aneurysm: a consensus statement
J Vasc Surg
(2004)
TM Joergensen et al.
Abdominal aortic diameter is increased in males with a family history of abdominal aortic aneurysms: results from the Danish VIVA-trial
Eur J Vasc Endovasc Surg
(2014)
N Qureshi et al.
The current state of cancer family history collection tools in primary care: a systematic review
Genet Med
(2009)
SM O'Neill et al.
Familial risk for common diseases in primary care: the Family Healthware Impact Trial
Am J Prev Med
(2009)
PW Yoon et al.
Research priorities for evaluating family history in the prevention of common chronic diseases
Am J Prev Med
(2003)
FM Facio et al.
Validation of My Family Health Portrait for six common heritable conditions
Genet Med
(2010)
KJ Jørgensen et al.
Elementary flaws in the FH01 study
Lancet Oncol
(2011)
R Moonesinghe et al.
The contribution of family history to the burden of diagnosed diabetes, undiagnosed diabetes, and prediabetes in the United States: analysis of the National Health and Nutrition Examination Survey
Genet Med
(2018)

WS Rubinstein et al.

Clinical utility of family history for cancer screening and referral in primary care: a report from the Family Healthware Impact Trial

Genet Med

(2011)

LA Orlando et al.

Clinical utility of a web-enabled risk-assessment and clinical decision support program

Genet Med

(2016)

RR Wu et al.

Implementation, adoption, and utility of family health history risk assessment in diverse care settings: evaluating implementation processes and impact with an implementation framework

Genet Med

(2019)

F van Hees et al.

Personalizing colonoscopy screening for elderly individuals based on screening history, cancer risk, and comorbidity status could increase cost effectiveness

Gastroenterol

(2015)

NA Mikat-Stevens et al.

Primary-care providers' perceived barriers to integration of genetics services: a systematic review of the literature

Genet Med

(2015)

LS Acheson et al.

Family history-taking in community family practice: implications for genetic screening

Genet Med

(2000)

AF Barrison et al.

Colorectal cancer screening and familial risk: a survey of internal medicine residents' knowledge and practice patterns

Am J Gastroenterol

(2003)

WG Feero et al.

New standards and enhanced utility for family health history information in the electronic health record: an update from the American Health Information Community's Family Health History Multi-Stakeholder Workgroup

J Am Med Inform Assoc

(2008)

DO Himes et al.

Breast cancer risk assessment: calculating lifetime risk using the Tyrer-Cuzick model

J Nurse Practit

(2016)

R Moonesinghe et al.

The contribution of family history to the burden of diagnosed diabetes, undiagnosed diabetes, and prediabetes in the United States: analysis of the National Health and Nutrition Examination Survey, 2009–2014

Genet Med

(2018)

DE Levy et al.

Underutilization of BRCA1/2 testing to guide breast cancer treatment: black and Hispanic women particularly at risk

Genet Med

(2011)

J Besseling et al.

Screening and treatment of familial hypercholesterolemia—lessons from the past and opportunities for the future (based on the Anitschkow Lecture 2014)

Atherosclerosis

(2015)

M Bourbon et al.

Familial hypercholesterolaemia in Portugal

Atherosclerosis

(2008)

R Valdez et al.

Family history in public health practice: a genomic tool for disease prevention and health promotion

Annu Rev Public Health

(2010)

WB Kannel et al.

Factors of risk in the development of coronary heart disease—six year follow-up experience. The Framingham Study

Ann Intern Med

(1961)

PW Wilson et al.

Prediction of coronary heart disease using risk factor categories

Circulation

(1998)

LA Orlando et al.

Family history and health risk assessment in health care

L Minor

We don't just need precision medicine, we need precision health

AV Khera et al.

Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations

Nat Genet

(2018)

The fields of genetics and genomics have developed rapidly in the past decade

Familial breast cancer: classification and care of people at risk of familial breast cancer and management of breast cancer and related risks in people with a family history of breast cancer

(2013)

Familial breast cancer: classification, care and managing breast cancer and related risks in people with a family history of breast cancer. 2013 (updated 2017)

AM Annis et al.

Family history, diabetes, and other demo-graphic and risk factors among participants of the National Health and Nutrition Examination Survey 1999–2002

Prev Chronic Dis

(2005)

N Qureshi et al.

Effect of adding systematic family history enquiry to cardiovascular disease risk assessment in primary care: a matched-pair, cluster randomized trial

Ann Intern Med

(2012)

MB Daly et al.

Genetic/familial high-risk assessment: breast and ovarian, version 1.2014

J Natl Compr Cancer Netw

(2014)

N Qureshi et al.

Collection and use of cancer family history in primary care

Evid Rep Technol Assess

(2007)