Elder Mistreatment Risk Factors Among Home Health Care Service Recipients
Author Information
Author(s): Schlag Karen, Pappadis Monique, Westra Jordan, Kuo Yong-Fang, Wood Leila, Czyz Rebecca, Raji Mukaila, Mouton Charles
Primary Institution: The University of Texas Medical Branch, Galveston, Texas, United States
Hypothesis
Can a Medicare claims-based EM risk assessment model be improved using OASIS data for home health care recipients?
Conclusion
The study found that including assessment data can enhance the predictive accuracy of elder mistreatment risk among home health care recipients.
Supporting Evidence
- Medicare dual eligibility and certain medical conditions were linked to higher elder mistreatment risk.
- Patients living alone and exhibiting disruptive behaviors were at increased risk of elder mistreatment.
Takeaway
This study looked at older people getting home health care and found ways to better predict if they might be mistreated by using more information about their health and living situation.
Methodology
Logistic regression models were used to predict elder mistreatment diagnosis based on Medicare claims and OASIS data.
Limitations
The study focused only on home health care recipients and may not generalize to other populations.
Participant Demographics
Beneficiaries aged 66 and older receiving home health care in 2016.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website