Clinical and nonclinical factors associated with potentially preventable hospitalizations among nursing home residents in New York State

J Am Med Dir Assoc. 2011 Jun;12(5):364-71. doi: 10.1016/j.jamda.2010.03.006. Epub 2010 Oct 2.


Objective: Identify clinical and nonclinical factors associated with potentially preventable ambulatory care sensitive (ACS) hospitalization among nursing home residents.

Methods: Residents (n=26,746) of 147 randomly selected nursing homes in New York State. Data included sociodemographics and clinical and nonclinical related factors. Multivariate linear regression quantified the association between potential determinants and ACS hospitalization.

Results: Four factors significantly associated with reduction in ACS hospitalization included nursing staff trained to communicate effectively with physicians regarding a resident's condition (P < .0001), physicians treat residents within the nursing home and admit to hospital as a last resort (P < .0001), provide better information and support to nurses and aides surrounding end-of-life care (P < .0001), and easy access to stat lab results in <4 hours on weekends (P < .0001). Two factors significantly associated with increased ACS hospitalization are: perceived likelihood illness will cause death (P < .0001) and perceived inadequate access to medical history/lab/EKGs (P < .0001).

Conclusion: Preventable ACS hospitalization reduction depends on effective communication between physicians and nursing staff, providing physicians with easy access to stat results in <4 hours on weekends, and easy access to medical records/lab/EKGs. Use of electronic medical records and providing training to nursing staff on how to communicate effectively with physicians and how to articulate about a resident's condition may minimize preventable ACS hospitalizations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Ambulatory Care
  • Communication
  • Female
  • Hospitalization*
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • New York
  • Nursing Homes* / organization & administration
  • Nursing Staff / supply & distribution
  • Physician-Nurse Relations
  • Quality of Health Care
  • Risk Assessment*
  • Risk Factors