This study provides robust incidence data for postoperative falls that included more than 15,000 patients undergoing TKA surgery with data during a 10-year interval. The fall rate we report, 1.5% (232 falls/15,189 patients), is consistent with other previous retrospective reports of 0.7% (8 falls/1190 patients),21 1.0% (70 falls/6912 patients),11 and 2.0% (5 falls/250 patients)22 but not as high as a recent retrospective study of 2.7% (60 falls/2197 patients).17 Our results echo findings from other authors reporting that older patients (>65 years) fall more frequently.11,17,23 Patients continue to fall primarily within their own rooms, with elimination-related falls comprising a majority of cases. Notably, most patient falls in this study occurred during the intermediate portion of recovery (afternoon on POD 1 through the morning of POD 3), which aligns with systemic review evidence that fall rates are greater on POD 2 or later, occurring at a time when patient and provider vigilance may be waning.16 Perhaps unexpectedly, revision TKA was associated with a lower risk of falling compared with primary TKA in our sample. This result conflicts with a recent study reporting that patients with greater burden of comorbidity undergoing more complex surgical procedures are at a greater risk for falling.24 Memtsoudis et al.24 similarly report on incidence and patient characteristics of patient falls after total joint arthroplasty performed in the United States. These data, also retrospective, consisted of a collection of patient falls from several institutions within the United States. We believe that our results represent practice consistent with most institutions in the United States and provide data on the largest sample from a single institution to date.
In addition, our study conflicts with other risk factor associations provided by several smaller studies. Previous publications have reported independent risk factors for falling, including sex11,23 and BMI17; however, our investigation found no statistically significant relationships for sex or BMI in those who fell versus the overall TKA population. This finding was true even when normal-weight patients were compared with those who were overweight. Although it is important to focus on at-risk populations, it may prove detrimental to restrict fall-monitoring programs to any particular sex or BMI classification based on earlier evidence.
Peripheral nerve blockade may be associated with an increased risk for falling.17,21,22,25 An investigation on mechanisms of falls among volunteers undergoing isolated peripheral nerve blockade (e.g., femoral and sciatic nerve blockade) demonstrated a reduction in muscle strength that impairs leg stiffness necessary for pivoting, stair-climbing, and standing from a seated position.26 Furthermore, Wasserstein et al.17 concluded continuous peripheral nerve blockade to be an independent risk factor for falling after TKA, with a frequency of 3.1% (58/1900) attributed to continuous femoral nerve block. Femoral catheters have been a mainstay of postoperative analgesia at our institution since 2003, and without contraindications, nearly every TKA patient will have a femoral catheter in place for 48 hours. Femoral catheters were present or recently removed in a majority of our patients who fell; however, the same could be said for the patients who did not fall. Because we did not collect data on our entire study population (only those who fell), we were unable to evaluate the risk of fall associated with femoral blockade. The authors of a recent systematic review and meta-analysis, however, concluded the attributable risk of falling from continuous peripheral nerve blockade alone (1.7%) was not greater than the expected rate of falling among all patients undergoing major orthopedic lower extremity surgery.16 Furthermore, in the most recent retrospective study on inpatient falls, the frequency of falls after TKA was 1.6% (3042/191,570 patients) and was not related to peripheral nerve block.27 Our frequency of 1.5% is much less than that of Wasserstein et al.17 and similar to these more recent and larger series,16,27 which do not identify peripheral nerve block as a significant risk.
The use of a knee immobilizer may stabilize impaired quadriceps weakness after total knee replacement.26 Similarly, Jones and Stubblefield28 in a small study of 5 cancer patients with femoral neuropathy were able to show a marked reduction in number of falls with knee immobilizer use. The use of knee immobilizers among volunteers also has been shown to improve leg stiffness and stability.26 Muraskin et al.26 are among many proponents advocating the use of immobilizers until the effects of femoral nerve blockade recede; however, these authors acknowledge that, despite the use of immobilizers, patients can and do still fall.16,26,27 The use of knee immobilizers was not a formal fall-prevention strategy used at Mayo Clinic from 2003 to 2012. Although we did collect use of leg brace data on those who fell, missing information was common for this variable because the postoperative use of knee immobilizers was unpredictable among our orthopedic surgeons during the study period.
Multiple intervention strategies, including provider and patient education, use of fall-assessment tools, fall-alert signs and bed alarms, and the use of patient lifts, appear to be collectively effective for fall prevention, as evidenced by a reduction in postoperative falls during the time period of implementation at our institution. Interestingly, we found more than 60% of falls occurred among patients determined at “no risk” of fall according to the HFRMII, which may indicate identifying those at risk requires a more vigorous diagnostic tool. In 2007, the HFRMII was determined to be the best assessment tool for fall prevention.29 A recent systematic review and meta-analysis30 comparing fall-assessment instruments, however, determined that the St. Thomas Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) may be the best tool with more sensitivity and specificity and ease of use for detecting falls among hospitalized acutely ill adult patients. In addition, STRATIFY compared with HFRMII accounts for fall as the presenting complaint for hospital admission or falls that have occurred on the ward since admission. This inclusion of history of falling may make for a better assessment tool, considering those patients with a history for fall are known to be at high risk.6,8 We considered applying STRATIFY to a subset of patients; unfortunately, the subjective questioning necessary for assessment would make it difficult, if not impossible, to retrospectively score information within our fall database. Because the behavior of various fall instruments varies considerably based on environment or population, future studies should check whether there is a difference between STRATIFY and HRFMII in the ability to predict falls among patients undergoing TKA.
This study is strengthened by the largest sample size to date, but it is important to recognize the retrospective nature of this study has limits, including selection bias, responder, diagnostic, and reporting bias. However, fall often is characterized as a well-defined and serious event with fall occurrences unlikely to go unreported. We also acknowledge that our results may be limited by changes in surgical, rehabilitation, and anesthesia practice during the 10-year interval. Finally, these study results may not be generalizable to populations markedly different from this single institution known for caring for patients undergoing complex primary and revision knee joint arthroplasties.
In conclusion, our data demonstrate a reduction in fall incidence coinciding with the implementation of a multi-intervention fall-prevention strategy. The relative contribution of each single intervention is still unknown. Despite prevention efforts, patients of advanced age, elimination-related falls, and patients in the intermediate phase of recovery (afternoon on POD 1 through morning of POD 3) are at high risk for falling. Until an authoritative fall-assessment tool emerges, fall-prevention strategies should continue with education provided to all; but, in particular, initiatives should focus on further reducing falls in elderly patients and reinforce practices that will monitor patients within their hospital rooms.
Standardized Fall-Assessment Tool Descriptions
- Hendrich II Fall Risk Model (HFRMII)1
- Validated screening tool used to assess inpatient fall risk based on 8 independent risk factors and has been collected on all patients undergoing total joint arthroplasty at Mayo Clinic since 2005.
- A risk score ≥5 correlates to a high risk for fall (sensitivity 74.9% and specificity 73.9%).
- St. Thomas Risk Assessment tool in Falling Elderly Inpatients (STRATIFY)2
- Tool used in conjunction with clinical assessment and a review of medications to determine if a patient is at risk for falls.
- STRATIFY total score calculation (Yes = 1, No = 0)
- Hendrich AL, Bender PS, Nyhuis A. Validation of the Hendrich II Fall Risk Model: a large concurrent case/control study of hospitalized patients. Appl Nurs Res 2003;16:9–21
- Oliver D, Britton M, Seed P, Martin FC, Hopper AH. Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: case-control and cohort studies. BMJ 1997;315:1049–53
The authors would like to extend their appreciation to Joan Henely, Patti Bieber, Ann Halverson, and Brooke Hakanson, members of the Department of Nursing at Mayo Clinic for their expertise in standardized fall assessment tools and for providing assistance with fall data collection. Also, they extend their sincere gratitude to Youlonda Loechler, member of the Department of Orthopedics Research, for her contributions to total joint arthroplasty data collection and analyses.
Dr. Terese Horlocker is the Section Editor for Regional Anesthesia for Anesthesia & Analgesia. This manuscript was handled by Dr. Sorin J. Brull, Section Editor for Patient Safety for the journal, and Dr. Horlocker was not involved in any way with the editorial process or decision.
Name: Rebecca L. Johnson, MD.
Contribution: This author collected data, analyzed data, and prepared the manuscript.
Attestation: Rebecca L. Johnson approved the final manuscript, attests to the integrity of the original data and the analysis reported in this manuscript, and is the archival author.
Name: Christopher M. Duncan, MD.
Contribution: This author collected data, analyzed data, and prepared the manuscript.
Attestation: Christopher M. Duncan approved the final manuscript.
Name: Kyle S. Ahn, MD.
Contribution: This author helped design the study, collected data, and reviewed the manuscript.
Attestation: Kyle S. Ahn approved the final manuscript.
Name: Darrell R. Schroeder, MS.
Contribution: This author helped analyze data, revise tables and figures, and prepared the revised manuscript.
Attestation: Darrell Schroeder approved the final manuscript.
Name: Terese T. Horlocker, MD.
Contribution: This author helped design the study, analyzed data, and prepared the manuscript.
Attestation: Terese T. Horlocker approved the final manuscript.
Name: Sandra L. Kopp, MD.
Contribution: This author helped design the study, collected data, analyzed data, and prepared the manuscript.
Attestation: Sandra L. Kopp approved the final manuscript.
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© 2014 International Anesthesia Research Society
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