Sunday, 18 September 2016
Soon Young Ha, MSN, RN
College of Nursing Henderson Hall, Kent State University, Kent, OH, USA
Patricia Vermeersch, PhD, CNP, RN
College of Nursing, Kent State University, Kent, OH, USA
Background: The combination of more elderly living longer1 and needing more supportive care
means the absolute proportion of older adults in nursing homes is likely to rise.2 Nursing home
residents are more likely to fall as compared to community dwelling older adults.3 Consequently,
the absolute number of falls among nursing home residents will also increase with a concurrent
rise in falls with major injury4: bone fractures, joint dislocations, closed head injuries with altered
consciousness, and/or subdural hematoma.5 The increased falls with major injury will negatively
impact the physical and psychological health of older adults and will expand health care
spending.6 There is a significant gap in research on falls with major injury among nursing home
residents. Previous research is inconsistent and conflicting in defining and determining risk
factors for falls with major injury.
Purpose: The purpose of this study is to identify intrinsic and extrinsic factors from the Long-
Term Care Minimum Data Set (MDS) 3.0 for 2014 associated with major injury falls in elderly
nursing home residents and use these to develop a parsimonious explanatory model of falls
with major injury.
Specific Aims: The aims of the study are to answer the following questions. In elderly nursing
home residents: (Q1) What are the intrinsic and extrinsic factors that contribute to falls with
major injury?; (Q2) Do these factors interact and if so, how do they interact?; (Q3) Which factors
and/or interactions of these factors are most useful for explaining who will have a major injury
upon falling?
Methods
Design: The study design is an exploratory, retrospective, and secondary analysis of the MDS
3.0 for 2014. The national MDS 3.0 dataset from the Chronic Conditions Data Warehouse
contains about 1.4 million beneficiaries. According to Senior Health Informatics Analyst, D.
Messenger (written communication, May 2016), each beneficiary carries a maximum 655
variables.
Sample and setting: The sample is approximately 594,000 through 712,000 Medicare and
Medicaid certified nursing home residents in the United States who fell in 2014. Sample size is
estimated based on the literature.7-8 Inclusion criteria are (1) age 65 years and over; and (2) had
at least one fall in 2014. Exclusion criterion: a movement disorder diagnosis (e.g., Parkinson’s
disease, multiple sclerosis).
Variables: Intrinsic factors include: age, gender, race/ethnicity, marital status, vision, hearing,
cognitive pattern, mood, behavior, functional status, bladder and bowel continence, diagnoses,
pain management, fall history, swallowing and nutritional status, and skin condition. Extrinsic
factors include: mobility devices, corrective lenses, hearing aid, medication category,
polypharmacy, and length of stay. The outcome or dependent variable is fall with major injury
(yes or no).
Analysis: After data cleaning, at least two subsets will be created by randomly splitting the
dataset of eligible beneficiaries. One data set will be used to answer the research questions and
the other(s) will be used to test the explanatory model for cross-validation. Q1 will be addressed
using descriptive analysis to compare intrinsic/extrinsic factors of beneficiaries with no major
injury versus major injury. Next, assumptions for logistic regression and the strength of
association between each independent variable and dependent variable (falls with major injury)
will be examined. Q2 will be addressed using multiple logistic regression to examine the
strength of association between interaction of factors and dependent variable (falls with major
injury). Q3 will be addressed using multiple logistic regression to develop a model for falls with
major injury by using only statistically and/or clinically significant factors found from simple
logistic and multiple logistic regression. The final step in this study will be to test the model on
the other dataset created.
References
1. Douglas AH, Paul DP. Healthcare rationing and cost control: perspectives on the American
health care system. In: Proceedings of the 2005 Midwest Business Administration
Association Conference; 2005;21-32.
2. Harris-Kojetin L, Sengupta M, Park-Lee E, et al. Long-term care services in the United
States: 2013 overview. Hyattsville, MD: U.S. Department of Health and Human Services
Centers for Disease Control and Prevention, National Center for Health Statistics; 2013.
Series 3(7).
3. Baranzini F, Diurni M, Ceccon F, et al. Fall-related injuries in a nursing home setting: is
polypharmacy a risk factor? BMC Health Services Research. 2009;9(228).
doi:10.1186/1472-6963-9-228
4. Van Doorn C, Gruber-Baldini AL, Zimmerman S, et al. Dementia as a risk factor for falls and
fall injuries among nursing home residents. J Am Geriatr Soc. 2003;51:1213-1218.
doi:10.1046/j.1532-5415.2003.51404.x
5. Long-term care facility resident assessment instrument 3.0 user’s manual version 1.13.
Baltimore, MD: Department of Health and Human Services Centers for Medicare & Medicaid
Services; 2015. Retrieved from https://www.cms.gov/Medicare/Quality-Initiatives-Patient-
Assessment-Instruments/NursingHomeQualityInits/Downloads/MDS-30-RAI-Manual-
V113.pdf
6. Abrahamsen B, van Staa T, Ariely R, et al. Excess mortality following hip fracture: a
systematic epidemiological review. Osteoporos Int, 2009;20(10):1633-1650.
doi:10.1007/s00198-009-0920-3.
7. MDS 3.0 frequency report. Baltimore, MD: Centers for Medicare and Medicaid Services;
2012. Retrieved from https://www.cms.gov/Research-Statistics-Data-and-
Systems/Computer-Data-and-Systems/Minimum-Data-Set-3-0-Public-Reports/Minimum-
Data-Set-3-0-frequency-report.html
8. Hill-Westmoreland EE, Gruber-Baladini AL. (2005). Falls documentation in nursing homes:
agreement between the minimum data set and chart abstractions of medical and nursing
documentation. J Am Geriatr Soc. 2005;53(2):268-273. doi:10.1111/j.1532-
5415.2005.53113.x