Wednesday, July 2, 2025 7/2/2025

Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals

Award Number: R34MH119411
ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 12/18/2019
PERIOD OF PERFORMANCE END DATE: 11/30/2023

Group Awards By:

View Award Description

Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals - Project Summary/Abstract The main goal of this study is to build a data-driven, evidence-based organizational management system that can inform effective recruitment and retention strategies to prevent excessive turnover. High turnover rates (estimated 25-60% annually) are devastating for mental health care systems, affecting organizations (e.g., cost), employees (e.g., work well-being), and most critically, the quality of care. Human resource departments collect extensive employee data that can be useful predictors for turnover, but these data are not often analyzed to address turnover issues in mental health organizations. Computational methods have greatly evolved and can now access and analyze large and complex data. This pilot study will achieve three specific aims: Aim 1: build and test turnover prediction models by developing and applying machine learning algorithms to existing human resource data; Aim 2: generate critical questions to enhance turnover prediction through qualitative methods; and Aim 3: test the enhanced model in predicting turnover at 12 months. In Aim 1, using past human resource data and service encounters from [two mental health organizations (rural and urban locations)], we will develop machine learning algorithms to predict turnover. The algorithms will address turnover questions simultaneously (e.g., Who are the most likely to leave? What factors predict turnover at varying time points in employment?). In Aim 2, we will interview key informants: “leavers” (employees who voluntarily terminate employment during the study); “stayers” (employees with extreme longevity in the organization); and “predictees” (identified as likely to leave, based on our algorithms). The findings will be discussed in two focus groups in order to generate, refine, and validate 5-10 critical questions to enhance prediction of turnover. In Aim 3, we will conduct an on-line survey of all current employees to assess the 5-10 critical questions and link survey data with data from human resources and services to examine the improved precision between the theory-based model (predictors in the survey) and the data-driven model (machine learning algorithms) in predicting actual turnover 12 months later. Machine learning can model complex and dynamic variable relationships (e.g., handling a large number of variables, accounting for heterogeneity) and overcome limitations in traditional turnover research that often relies on small, cross-sectional, and convenience samples. Successful completion of this study will promote data-driven, evidence-based organizational management practices to address turnover, which is aligned with NIMH priorities of capitalizing on existing data structures and using technologies to improve mental health service quality. This study will be a critical step in developing highly adaptable machine learning algorithms to predict turnover; ultimately, we envision that this system will be partnered with future clinical interventions to reduce turnover in mental health.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = -$1 )
2024	2022	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	001	3	4/12/2024	SUPPLEMENT FOR EXPANSION	$0
2024	2022	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	000	3	4/12/2024	NON-COMPETING CONTINUATION	-$1
														Subtotal = -$1

Issue Date FY: 2022 ( Subtotal = $330,506 )
2022	2022	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	000	3	12/1/2021	NON-COMPETING CONTINUATION	$201,154
2022	2022	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	001	3	12/3/2021	SUPPLEMENT FOR EXPANSION	$107,000
2022	2022	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	002	3	8/9/2022	NON-COMPETING CONTINUATION	$22,352
														Subtotal = $330,506

Issue Date FY: 2021 ( Subtotal = $269,398 )
2021	2021	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	001	2	4/21/2021	NON-COMPETING CONTINUATION	$23,064
2021	2021	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	000	2	12/22/2020	NON-COMPETING CONTINUATION	$207,566
2021	2021	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	002	2	8/4/2021	SUPPLEMENT FOR EXPANSION	$16,590
2021	2021	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	003	2	9/15/2021	SUPPLEMENT FOR EXPANSION	$22,178
														Subtotal = $269,398

Issue Date FY: 2020 ( Subtotal = $244,635 )
2020	2020	TRUSTEES OF INDIANA UNIVERSITY	980 INDIANA AVE RM 2232	INDIANAPOLIS	IN	46202	MARION	USA	Mental Health Research Grants	000	1	12/18/2019	NEW	$244,635
														Subtotal = $244,635

Grand Total All Awards = $844,538

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth Professionals

Award Number: R34MH119411

ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 12/18/2019

PERIOD OF PERFORMANCE END DATE: 11/30/2023

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer