Does Covid-19 Matter: A Growth Curve Modeling Analysis Estimating and Predicting The Growth Trends of the Accountable Care Organizations (ACOS) Preventative Quality Performance During 2016-2020 Period

Author

Christina Bocanegra-PerezFollow

Date of Degree

5-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Program

Education

Advisor

Chungling Niu

Advisor

Ashley Love

Advisor

Arthur Hernandez

Abstract

Does COVID-19 Matter: A Growth Curve Modeling Analysis Estimating and Predicting the Growth Trends of the Accountable Care Organizations (ACOs) Preventative Quality Performance During 2016-2020 Period

Christina M. Bocanegra, PhD

University of the Incarnate Word

Abstract

Introduction: CMS aggregates and reports Accountable Care Organizations (ACOs) performance each year, resulting in distributed shared savings to provider participants. The intent is to share benefits with healthcare providers to promote lower costs, better patient experience, and better outcomes. The Medicare Shared Savings Program (MSSP), in which ACO groups collect data to include the six preventative quality care measures viewed in this study, focuses include impact of the COVID-19 pandemic on preventative quality care measures from 2016 to 2020. Research Questions: Questions asked in this study are as follows: (1)What would be the growth trend pattern for ACOs in terms of the six performance measures during the 2016-2020 period? (2)Do the two-time invariant covariates (i.e., size of patient population and size of provider population) significantly predict the changes in the six DVs over the 2016-2020 period? (3) What are the time-varying predictor effects on dependent variables from 2016-2020? (4) After controlling for the effects of both time-invariant and time-varying predictors, is there a significant change in the growth trend of DVs in the 2019-2020 COVID-19 period compared to the 2015-2019 period? (5) What growth trend can be predicted over the following years, 2021-2024, considering the effects of both time-invariant and time-varying predictors and COVID-19 impact? Methods: This study's longitudinal correlational research design uses quantitative analytical methods, specifically growth curve modeling, to analyze secondary data from CMS ACO years 2016-2020. Results: Significant findings were found in four DVs, with a positive growth pattern over five years. The PT and PCP rate of increase for 2016-2020 also showed a statistically significant relationship between the dependent variable measures. It was found that low category ACOs, having low provider and patient populations, thrived the best in measuring outcome quality care. Findings include, in the COVID-19 year, the pandemic influenced patient counts, provider counts, and outcomes, and there was a decrease in preventive health measures. Lastly, all predictions trends for 2021-2024 showed increased points in preventive health measures, which shows an advancement in the ACO program. Conclusions: This study shows that the year that the pandemic started was associated with decreased preventive health measures. Addressing all patients' quality of care measures to be met at every visit is the key to capturing patient compliance in fulfilling preventative health outcomes.

Keywords: Accountable Care Organizations (ACO), The Center for Medicare and Medicaid Services (CMS), Resource Dependence Theory, COVID-19, Quality of Care, Preventative Care, Medicare, Predicting Modeling, Growth Curve Modeling

Recommended Citation

Bocanegra-Perez, Christina, "Does Covid-19 Matter: A Growth Curve Modeling Analysis Estimating and Predicting The Growth Trends of the Accountable Care Organizations (ACOS) Preventative Quality Performance During 2016-2020 Period" (2025). Theses & Dissertations. 462.
https://athenaeum.uiw.edu/uiw_etds/462

Previous Versions

Mar 13 2025
Feb 27 2025