Clinical trial NCT03973346: Impact of Social Risk Decision Support
Official title: Improving Population and Clinical Health With Integrated Services and Advanced Analytics
Study type: INTERVENTIONAL
Overall status: WITHDRAWN
Phase: NA
Conditions: Health Social Determinant
Keywords: risk prediction
Lead sponsor: Indiana University
Sponsor class: OTHER
Collaborators: name: Robert Wood Johnson Foundation
First posted: 2019-06-04
Enrollment: 0
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Multiple observation, pre-post with a secondary data source comparison group design, and a difference-in-difference modeling approach.
Primary purpose: SCREENING

Brief summary: The purpose of this study is to determine the impact of embedding a risk-stratification tool, designed to identify patient needs for services that address social determinant of health related needs, in a commercial electronic health record system (EHR).

Detailed description: Social determinant of health related needs and social risk factors complicate care delivery and drive health and well-being. Social needs are common among undeserved patient populations, but health care providers are often not equipped to routinely identify and address patients in need.

Using a combination of health information exchange, electronic health record, and aggregate datasets the investigators developed predictive algorithms to identify patients a highest risk for a need for a referral to a social worker, dietitian, behavioral health, or other wraparound service provider. Risk scores are available to primary care providers in two ways within the electronic health record system (EHR): 1) a graphical summary of individual risk or 2) a line listing of all scheduled patients.

The investigators are introducing the risk-stratification tool in an urban safety-net primary care provider on a voluntary usage basis.

Eligibility criteria: Inclusion Criteria:

* Encounters among patients seeking primary care service at any of the 9 Eskenazi Health FQHC clinics in Indianapolis, IN from January 2017 to May 2020.
* The propensity score matched primary care encounters from non-Eskenazi facilities.

Exclusion Criteria:

* Emergency encounters or hospitalizations

Primary outcomes:
measure: ED utilization rate
timeFrame: 6 months
measure: Missed primary care appointments rate
timeFrame: 6 months
Secondary outcomes:
measure: Hospitalization rate
timeFrame: 6 months
Other outcomes:
Locations:
city: Indianapolis
country: United States
facility: Eskenazi Health
state: Indiana
Study officials:
affiliation: Associte Professor
name: Joshua R Vest, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Kasthurirathne SN, Vest JR, Menachemi N, Halverson PK, Grannis SJ. Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services. J Am Med Inform Assoc. 2018 Jan 1;25(1):47-53. doi: 10.1093/jamia/ocx130.
citation: Vest JR, Grannis SJ, Haut DP, Halverson PK, Menachemi N. Using structured and unstructured data to identify patients' need for services that address the social determinants of health. Int J Med Inform. 2017 Nov;107:101-106. doi: 10.1016/j.ijmedinf.2017.09.008. Epub 2017 Sep 20.
citation: Vest JR, Menachemi N, Grannis SJ, Ferrell JL, Kasthurirathne SN, Zhang Y, Tong Y, Halverson PK. Impact of Risk Stratification on Referrals and Uptake of Wraparound Services That Address Social Determinants: A Stepped Wedged Trial. Am J Prev Med. 2019 Apr;56(4):e125-e133. doi: 10.1016/j.amepre.2018.11.009. Epub 2019 Feb 14.