# Improving cancer family history collection through social networking and artificial intelligence

> **NIH NIH K07** · MEDICAL UNIVERSITY OF SOUTH CAROLINA · 2020 · $173,453

## Abstract

PROJECT SUMMARY 
The  activities  proposed  in  this  NCI  K07  application  are  designed  to  advance  the  career  development  and 
research  independence  of  Dr.  Brandon  M.  Welch.  Family  health  history  (FHx)  is  one  of  the most important 
resources available to help clinicians identify disease risks. By knowing a patient's FHx, clinicians can quickly 
identify  disease risks and initiate risk-reducing strategies such as increased screening, prophylactic surgery, 
risk-reducing  therapeutics,  and  lifestyle  changes.  FHx  is  also  the  foundation  of  genomic  medicine. 
Unfortunately,  the  collection  and  use  of  FHx  by  patients  and  clinicians  is  suboptimal.  To  improve  the 
collection and use of FHx among the general population, a better FHx tool that is easier and more convenient 
to  use  than  current  FHx  tools  is  needed.  A  new  FHx  web  tool,  called  ​ItRunsInMyFamily.com,​  incorporates 
artificial intelligence and social networking to improve user engagement with FHx collection.Utilizing artificial 
intelligence  based  chat  entity  can  improve  the  collection  of  FHx  information  by  making  it  easier  and  more 
engaging to record FHx information, likewise social networking allows users to tap into the collective wisdom 
and  knowledge  of  the  family  to  correct  inaccuracies  and  overcome  gaps  in  FHx  knowledge.  This research 
study  will  first  identify  enhancements  to  ​ItRunsInMyFamily.com  ​that  will  further  promote  user  engagement, 
with  particular  focus  on  rural and underserved patients (Aim 1). We will then evaluate whether this new FHx 
tool can improve collection of cancer FHx in comparison with current FHx tools (Aim 2). Finally, we will assess 
the impact of ​ItRunsInMyFamily.com ​on the clinical settings (Aim 3). To implement the research plan, it will be 
critical  to  apply,  skills  obtained  through  K  award  learning  objectives,  namely  clinical  oncology  (learning 
objective  1),  iterative  patient-centered  design  (learning  objective  2),  and  health  technology  assessment 
(learning  objective  3).  To  fulfill  these  learning  objectives,  an  interdisciplinary  group  of  mentors  will  direct  a 
comprehensive training plan. The training plan includes coursework, seminars, workshops, journal clubs, and 
conferences,  covering clinical oncology, patient engagement, health disparities, user-centered development, 
human-computer  interaction,  clinical  research  methodologies,  health  technology  assessment,  and  ethical 
conduct  of  research.  The  strong  support  of  an  excellent  team  of  mentors,  and  the  vast  resources  of  the 
Medical  University  of  South  Carolina,  create  an  optimal  training  environment.  Collectively,  the  integrated 
learning  objectives  and  research  plan  are  critical  to  establishing  a  successful,  innovative,  and  meaningful 
academic career focused on developing patient-centric informatic...

## Key facts

- **NIH application ID:** 10008996
- **Project number:** 5K07CA211786-05
- **Recipient organization:** MEDICAL UNIVERSITY OF SOUTH CAROLINA
- **Principal Investigator:** Brandon M Welch
- **Activity code:** K07 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $173,453
- **Award type:** 5
- **Project period:** 2016-09-15 → 2021-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10008996

## Citation

> US National Institutes of Health, RePORTER application 10008996, Improving cancer family history collection through social networking and artificial intelligence (5K07CA211786-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10008996. Licensed CC0.

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