Literature DB >> 28476461

Adding Social Determinant Data Changes Children's Hospitals' Readmissions Performance.

Marion R Sills1, Matthew Hall2, Gretchen J Cutler3, Jeffrey D Colvin4, Laura M Gottlieb5, Michelle L Macy6, Jessica L Bettenhausen4, Rustin B Morse7, Evan S Fieldston8, Jean L Raphael9, Katherine A Auger10, Samir S Shah10.   

Abstract

OBJECTIVES: To determine whether social determinants of health (SDH) risk adjustment changes hospital-level performance on the 30-day Pediatric All-Condition Readmission (PACR) measure and improves fit and accuracy of discharge-level models. STUDY
DESIGN: We performed a retrospective cohort study of all hospital discharges meeting criteria for the PACR from 47 hospitals in the Pediatric Health Information database from January to December 2014. We built four nested regression models by sequentially adding risk adjustment factors as follows: chronic condition indicators (CCIs); PACR patient factors (age and sex); electronic health record-derived SDH (race, ethnicity, payer), and zip code-linked SDH (families below poverty level, vacant housing units, adults without a high school diploma, single-parent households, median household income, unemployment rate). For each model, we measured the change in hospitals' readmission decile-rank and assessed model fit and accuracy.
RESULTS: For the 458 686 discharges meeting PACR inclusion criteria, in multivariable models, factors associated with higher discharge-level PACR measure included age <1 year, female sex, 1 of 17 CCIs, higher CCI count, Medicaid insurance, higher median household income, and higher percentage of single-parent households. Adjustment for SDH made small but significant improvements in fit and accuracy of discharge-level PACR models, with larger effect at the hospital level, changing decile-rank for 17 of 47 hospitals.
CONCLUSIONS: We found that risk adjustment for SDH changed hospitals' readmissions rate rank order. Hospital-level changes in relative readmissions performance can have considerable financial implications; thus, for pay for performance measures calculated at the hospital level, and for research associated therewith, our findings support the inclusion of SDH variables in risk adjustment.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  healthcare quality measurement; pay for performance; performance measure; predictive model; public reporting; risk adjustment

Mesh:

Year:  2017        PMID: 28476461     DOI: 10.1016/j.jpeds.2017.03.056

Source DB:  PubMed          Journal:  J Pediatr        ISSN: 0022-3476            Impact factor:   4.406


  14 in total

1.  Importance and Feasibility of Transitional Care for Children With Medical Complexity: Results of a Multistakeholder Delphi Process.

Authors:  JoAnna K Leyenaar; Paul A Rizzo; Dmitry Khodyakov; Laurel K Leslie; Peter K Lindenauer; Rita Mangione-Smith
Journal:  Acad Pediatr       Date:  2017-07-21       Impact factor: 3.107

Review 2.  Pediatric Hospital Readmissions: An Emerging Metric of Healthcare Quality.

Authors:  Bhavneet Bharti
Journal:  Indian J Pediatr       Date:  2019-02-11       Impact factor: 1.967

3.  Social determinants of health in electronic health records and their impact on analysis and risk prediction: A systematic review.

Authors:  Min Chen; Xuan Tan; Rema Padman
Journal:  J Am Med Inform Assoc       Date:  2020-11-01       Impact factor: 4.497

4.  Potential Impact of Initial Clinical Data on Adjustment of Pediatric Readmission Rates.

Authors:  Mari M Nakamura; Sara L Toomey; Alan M Zaslavsky; Carter R Petty; Chen Lin; Guergana K Savova; Sherri Rose; Mark S Brittan; Jody L Lin; Maria C Bryant; Sepideh Ashrafzadeh; Mark A Schuster
Journal:  Acad Pediatr       Date:  2018-11-20       Impact factor: 3.107

5.  Developing Prediction Models for 30-Day Unplanned Readmission Among Children With Medical Complexity.

Authors:  Jana C Leary; Lori Lyn Price; Cassandra E R Scott; David Kent; John B Wong; Karen M Freund
Journal:  Hosp Pediatr       Date:  2019-03

6.  Association Between Neighborhood Disadvantage and Pediatric Readmissions.

Authors:  Carrie L Nacht; Michelle M Kelly; M Bruce Edmonson; Daniel J Sklansky; Kristin A Shadman; Amy J H Kind; Qianqian Zhao; Christina B Barreda; Ryan J Coller
Journal:  Matern Child Health J       Date:  2022-01-11

7.  Leveraging Data and Digital Health Technologies to Assess and Impact Social Determinants of Health (SDoH): a State-of-the-Art Literature Review.

Authors:  Kelly J Thomas Craig; Nicole Fusco; Thrudur Gunnarsdottir; Luc Chamberland; Jane L Snowdon; William J Kassler
Journal:  Online J Public Health Inform       Date:  2021-12-24

8.  The Association of the Childhood Opportunity Index on Pediatric Readmissions and Emergency Department Revisits.

Authors:  Jessica L Bettenhausen; Clemens Noelke; Robert W Ressler; Matthew Hall; Mitch Harris; Alon Peltz; Katherine A Auger; Ronald J Teufel; Jeffrey E Lutmer; Molly K Krager; Harold K Simon; Mark I Neuman; Padmaja Pavuluri; Rustin B Morse; Pirooz Eghtesady; Michelle L Macy; Samir S Shah; David C Synhorst; James C Gay
Journal:  Acad Pediatr       Date:  2021-12-17       Impact factor: 2.993

9.  Perspectives of Parents and Providers on Reasons for Mental Health Readmissions: A Content Analysis Study.

Authors:  Sarah K Connell; Tony To; Kashika Arora; Jessica Ramos; Miriam J Haviland; Arti D Desai
Journal:  Adm Policy Ment Health       Date:  2021-04-19

10.  Adjusting for Social Risk Factors in Pediatric Quality Measures: Adding to the Evidence Base.

Authors:  Emily M Bucholz; Sara L Toomey; Charles E McCulloch; Naomi Bardach
Journal:  Acad Pediatr       Date:  2022-04       Impact factor: 2.993

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