Falls, Fall Sequelae, & Healthcare Use in Community Dwelling Elderly with a History of Cancer Gerontological Society of America November 22, 2010: Symposium Sandra L. Spoelstra, PhD, RN Michigan State University College of Nursing Acknowledgements This research was supported by: NRSA Grant Award Grant Number 1F31NR011522 - 01A1 The State of Michigan Nurse Corp Fellowship The Mary Margaret Walther Behavioral Oncology Group Fellowship Blue Cross & Blue Shield of Michigan Dissertation Award MSU College of Nursing Fellowships & Scholarships MSU Graduate School Dissertation Completion Award The Schumann Family Scholarship Mentors: Drs. Barbara and Charles Given Dissertation Committee: Drs. B. & C. Given; Dr. D. Schutte; Dr. A. Sikorskii 2 Background & Significance About 1/3 of elderly >65 fall each year & falls significantly increase for those >75.
(Campbell, Borrie, Spears, Jackson, Brown, & Fitzgerald, 1990; Davison & Marrinan, 2007; Nevitt, Cummings, Kidd, & Black, 1989; Sattin, 1992; Tinetti, Speeckley, & Ginter, 1988, Sattin, 1992) Falls can lead to functional decline, hospitalization, nursing home placement, higher healthcare cost, & decreased QOL. (Campbell et al., 1990; Hill, Schwarz, Flicker, & Crroll, 1999; Tinetti, Baker, McAvay, & al, 1994; Tinetti et al., 1988;Tinetti et al., 1994) There are nearly 12 million cancer survivors. (Ries, 2007) The risk of falling may be higher for those who have had cancer. (Overcash, 2007; Pautex, Herrmann, & Zulian, 2008); Pearse, 2008) 3 Purpose To compare if falls, fractures, & use of healthcare differs in those with & without a cancer diagnosis in a vulnerable, disparate community dwelling elderly population. 4 Specific Aims To determine if patients with a cancer diagnosis experience a greater number of falls, fractures, or ER, hospital, or nursing home use compared to patients with no cancer.* To determine if there are differences in the number of falls
according to cancer site, stage, or treatment. * *After adjusting for socio-demographics, medications, & frailty (ADLs, cognition, comorbidities, weight loss, & vision). 5 Conceptual Framework Age, Sex, Race Cancer Falls Site Stage Cognition ADLs ER use Days since diagnosis Comorbidities Medications & Cancer Treatment
Fractures Hospitalization Nursing Home placement Synthesis of HRQOL (Ferrans,2005) and Life Course Aging Model (1985) 6 Methodology Longitudinal, retrospective, secondary data analysis using GEE Setting: Michigan Medicaid Home & Community Based Waiver program Sample: >65; at 300% of Federal Poverty Level ; ADL & IADL needs; 20022007 Data : Minimum Data Set-Home Care & Michigan Cancer Registry Age, sex, race/ethnicity Cancer site, stage, & days since cancer diagnosis
Medication classifications & treatments Frailty factors: ADLs, comorbidities, cognition, vision, & weight loss Outcomes: Falls, fractures, ER use, hospital admissions, & nursing home placement MSU & State IRB approval: non-human research & Data Use Agreement with the State of Michigan Using SAS 9.1, SPSS 16.0, & Mplus. 7 Study Schematic Patients >65 in Waiver Program (not HMO) 2002-2007 N=18,274 Non Cancer N= 16,035 With <2MDS, matched age/sex/ race; N=7,418 Non-Cancer Group N= 8,617 Cancer N=2,239 Other Cancers N=2,193
Diagnosed 2000-07 N=1463 With 2-MDS N=977 Comparison Cancer Group N=864 Skin Cancer N=46 Diagnosed <2000 N=730 With <2MDS N=519 Deceased within 2-months of MDS N=79 8 Characteristics Non-cancer Group (n=8617) Cancer Group (n=864) Mean age
77.04 (SD 6.57) 77.06 (SD 7.53) Female Male 6166 (71.5%) 2451 (28.5%) 539 (62.3%) 325 (37.7%) Caucasian African American Other 6372 (73.9%) 1929 (22.4%) 316 (3.7%) 638 (73.7%) 196 (22.8%) 30 (3.5%) 9 Falls in cancer compared to without cancer (Final Parsimonious GEE Model)
Odds Ratio 95% Confidence Interval Cancer vs. no-cancer 1.16 1.02 1.33 Weight loss vs. none 1.56 1.37 1.77 Short-term memory recall problems vs. none/some 1.53 1.41
1.65 Pain daily versus none/some 1.45 1.32 1.59 Antidepressants vs. none 1.29 1.19 1.40 Male versus Female 1.12 1.03 1.22 Comorbidities vs. none 1.07
1.04 1.12 White vs. African American 1.03 0.83 1.28 10 Fractures in cancer compared to without cancer (Final Parsimonious GEE Model) Cancer vs. no-cancer Odds Ratio 95% Confidence Interval 0.01 0.00
0.01 Comorbidities vs. none 1.61 1.11 1.22 Pain daily versus none/some 1.28 1.17 1.40 ADL dependence vs. independence 1.01 1.01 1.02 Age >65 0.95
0.87 0.99 Short-term memory recall problems vs. none/some 0.91 0.83 1.00 Male versus Female 0.76 0.67 0.69 White vs. African American 0.36 0.26 0.51 11
ER Use in cancer compared to without cancer Odds Ratio 95% Confidence Interval Cancer vs. no-cancer 1.24 1.04 1.48 Weight loss versus none 1.54 1.29 1.84 Short-term memory recall problems vs. none/some 1.51
1.03 1.29 Pain daily versus none/some 1.39 1.21 1.60 Comorbidities vs. none 1.12 1.07 1.16 (Final Parsimonious GEE Model) 12 Hospitalization in cancer compared to without cancer Odds Ratio
95% Confidence Interval Cancer vs. none 1.89 1.55 2.16 Weight loss vs. none 2.29 2.00 2.63 Aging >65 1.96 1.46 2.63 Pain daily versus none/some
1.31 1.18 1.45 Comorbidities vs. none 1.23 1.19 1.27 Antianxiety medications vs. none 1.14 1.03 1.26 ADL dependence vs. independence 1.02 1.02 1.03
Antidepressants vs. none 0.83 0.77 0.92 13 (Final Parsimonious GEE Model) Nursing Home Placement in cancer compared to without cancer (Final Parsimonious GEE Model) Odds Ratio 95% Confidence Interval Cancer vs. no cancer 0.61 0.50 0.74
Age >65 0.99 0.98 0.99 White vs. African American 0.54 0.40 0.72 *Antianxiety & hypnotic medications vs. none; pain daily versus none/some; short-term memory recall problems vs. none/some; & vision problems vs. none/little all had OR=1.00; CI 1.00, 1.00 a weak relationship yet each factor remained in the final model. 14 Summary of Research Findings An increased rate of falls may exist in cancer survivors & the closer a person was to their date of cancer diagnosis the higher the rate of falls. No increased rate of fractures was found in cancer survivors. ER use & hospitalization rates were higher while nursing home placement was lower in cancer survivors.
No difference in falls was found by stage/site of cancer. No difference was found in frailty by stage/site of cancer. Some differences in environment exist for cancer survivors. 15 Limitations The ability of an elderly individual to recall & report a fall. The unknown severity of comorbidities. Deceased within 2 months are excluded, which may lead to an underrepresentation of advanced-stage cancers, most likely lung cancer. The limited variation in the distribution of the frailty covariates (ADLs, cognition, & comorbidities) probably due to nature of waiver program enrollment requirement of ADL & IADL needs which led to minimal differences. 16 Implications for Practice Gerontological clinicians should: Be aware that cancer survivors may fall at a higher rate . Make fall prevention a safety priority. Include fall prevention measures in the care: A fall risk assessment Evidence-based fall prevention interventions Post-fall follow-up & modification of care as needed 17 Implications for Future Research Replication of this study using a data set with wider
variation in frailty measures. (ADLs, cognition, & comorbidity) Examination of cancer site, stage, & treatment and falls after obtaining a dataset with wider variability in frailty. Research using claims & pharmacy data to drill down & extend findings. Examining falls while comparing cancer to other comorbid conditions. 18 Conclusions The additive effect of a cancer diagnosis increased falls in elderly cancer survivors supporting emerging evidence. Clinicians need to be aware that cancer survivors are more likely to fall. Fall prevention should be included in cancer survivors care plans. 19 Thank you.
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