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  • Research article
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Patient and system factors associated with unassisted and injurious falls in hospitals: an observational study

Abstract

Background

Unassisted falls are more likely to result in injury than assisted falls. However, little is known about risk factors for falling unassisted. Furthermore, rural hospitals, which care for a high proportion of older adults, are underrepresented in research on hospital falls. This study identified risk factors for unassisted and injurious falls in rural hospitals.

Methods

Seventeen hospitals reported 353 falls over 2 years. We categorized falls by type (assisted vs. unassisted) and outcome (injurious vs. non-injurious). We used multivariate logistic regression to determine factors that predicted fall type and outcome.

Results

With all other factors being equal, the odds of falling unassisted were 2.55 times greater for a patient aged ≥65 than < 65 (95% confidence interval [CI] = 1.30–5.03), 3.70 times greater for a patient with cognitive impairment than without (95% CI = 2.06–6.63), and 6.97 times greater if a gait belt was not identified as an intervention for a patient than if it was identified (95% CI = 3.75–12.94). With all other factors being equal, the odds of an injurious fall were 2.55 times greater for a patient aged ≥65 than < 65 (95% CI = 1.32–4.94), 2.48 times greater if a fall occurred in the bathroom vs. other locations (95% CI = 1.41–4.36), and 3.65 times greater if the fall occurred when hands-on assistance was provided without a gait belt, compared to hands-on assistance with a gait belt (95% CI = 1.34–9.97).

Conclusions

Many factors associated with unassisted or injurious falls in rural hospitals were consistent with research conducted in larger facilities. A novel finding is that identifying a gait belt as an intervention decreased the odds of patients falling unassisted. Additionally, using a gait belt during an assisted fall decreased the odds of injury. We expanded upon other research that found an association between assistance during falls and injury by discovering that the manner in which a fall is assisted is an important consideration for risk mitigation.

Peer Review reports

Background

Up to 1 million hospitalized patients fall annually in the United States [1]. National benchmarks indicate a rate of 3.44 falls/1000 patient days on general medical, surgical, and medical-surgical units [2]. Approximately one-fourth of inpatient falls are injurious [3], with estimated costs exceeding $7000 per injury [4]. Injurious falls are one of 14 hospital-acquired conditions for which hospitals are not reimbursed under the inpatient prospective payment system [5]. Regardless of injury, patients who fall often require a greater length of stay [6,7,8], are more frequently discharged to a nursing home [7], and may restrict activity due to fear of falling [9]. Risk of falling while hospitalized increases with age [7, 10, 11], as does risk of fall-related injury [12, 13]. Given the aging population [14] and the negative impact of falls, reducing the incidence of falls and fall-related injury is a major focus of patient safety and quality improvement efforts.

Several studies have identified factors associated with inpatient falls [2, 3, 7, 11, 12, 15,16,17,18,19,20,21,22], such as impaired mobility or cognition [7, 17, 20], unit type [2, 3, 12, 20, 21], and staffing characteristics [17, 18, 21, 22]. Further, several studies have identified factors associated with fall-related injury [2, 3, 12, 13, 15, 16, 23]; for example whether or not a fall was assisted [2, 13], and lack of interprofessional teamwork [16]. Many of these studies were conducted in large urban hospitals [7, 11, 12, 15, 17, 20, 23] or used data from the National Database of Nursing Quality Indicators (NDNQI) [2, 3, 18, 21, 22] with samples that underrepresented small hospitals [18, 21] or reported results based on dichotomized bed-size categories of greater or less than 300 beds [2, 22]. Few studies have described risk factors for falls and fall-related injury in rural hospitals [13, 19], and specifically critical access hospitals (CAHs) [16]. CAHs are licensed for up to 25 beds, are located at least 35 miles from another hospital with some exceptions, and receive cost-based reimbursement from the Centers for Medicare and Medicaid Services [24]. CAHs less frequently report or benchmark falls to external organizations [16], despite the value that these processes may provide for quality improvement [25]. CAHs are also less likely than larger hospitals to use a standard fall definition [16]. Therefore, less is known about risk of falls and fall-related injury in rural hospitals including CAHs, compared to larger hospitals.

Because every fall has potential for injury, many hospitals aim to prevent all falls. However, a goal of preventing all falls may incentivize underreporting of non-injurious and assisted falls and discourage patient mobilization [2, 26, 27]. An assisted fall is one in which hospital staff is present and able to control a patient’s descent to the ground [28]. A more appropriate goal than preventing all falls may be to specifically prevent unassisted falls [2], which are more likely to be injurious than assisted falls [2, 13]. Despite numerous studies identifying risk factors for falls in general (without assistance differentiated), and the risk of injury with unassisted falls, we know of only one research group who has studied risk factors for falling unassisted [2, 21, 22]. The focus of two of those studies was on nurse staffing [21, 22], rather than factors more readily modifiable by staff providing direct patient care on a daily basis. Further, those studies that found unassisted falls were more likely to be injurious did not address the method of how a fall may be best assisted [2, 13]. The fields of physical and occupational therapy emphasize techniques to keep both patients and staff safe during patient mobilization, including the use of tools such as gait belts to assist patients with mobility [29,30,31]. As such, staff from those professions may be well suited to collaborate with others in increasing the proportion of hospital falls that are assisted, and therefore less likely to be injurious.

The purpose of this study was to describe fall events and identify risk factors for unassisted and injurious falls in rural hospitals. We report patient and system factors that increase the likelihood of (1) whether the fall was unassisted and (2) whether it resulted in injury. Identification of risk factors for unassisted falls and fall-related injury may guide interventions to reduce unassisted and injurious fall rates.

Methods

Design and setting

We conducted an observational analysis of 353 fall events reported by 17 rural hospitals in Nebraska from August 1, 2012 through July 31, 2014. Sixteen of the 17 hospitals were CAHs. The average number of licensed beds was 25.2 ± 6.1. According to the 2010 United States Census, 18.7% of the population of the counties served by the hospitals in this study was ≥65 years of age as compared to 12.7% of the population of the United States [32].

The hospitals reported fall events as part of a research demonstration and dissemination project funded by the Agency for Healthcare Research and Quality (AHRQ). The purpose of this funding mechanism was to: (1) implement safe practices that demonstrate evidence of reducing medical errors, risks, and harms associated with the process of healthcare and (2) inform AHRQ, providers, patients, and payers about implementation of safe practices in diverse settings. Our project, Collaboration and Proactive Teamwork Used to Reduce (CAPTURE) Falls [33, 34], sought to decrease risk of falls and fall-related injury in rural hospitals by implementing a multi-team system [35] to address fall-risk reduction. Each hospital’s multi-team system was led by an interprofessional fall-risk-reduction team that coordinated their fall-risk-reduction program and reported fall-event data to us.

Variables and measurements

A fall was defined as “a sudden, unintended, uncontrolled downward displacement of a patient’s body to the ground or other object” [36]. This definition included unassisted and assisted falls (when a patient is assisted to the ground by staff). Our definitions for assisted falls and levels of injury were consistent with those used by the NDNQI [28]. For analysis, falls were categorized according to type (unassisted or assisted) and outcome (non-injurious or injurious). Injury included minor harm such as a hematoma, moderate harm such as the need for sutures, major harm such as fracture, or death.

We developed a standard reporting form (Additional File 1) to collect data about fall events. In addition to categorizing fall events according to type and outcome as described above, other data collected using our reporting form were patient factors, such as age and gender, or system factors, such as when the patient was last assessed and alarm usage. Many of our data elements regarding fall events were from the AHRQ Common Formats [36]. We also added fields to record whether a gait belt was used during an assisted fall, and the patient medical record number for tracking repeat falls for a patient within the same admission.

We educated each hospital’s fall-risk-reduction team regarding the rationale for collecting all data elements on the reporting form to improve reliability and validity of the data. This education occurred during Fall 2012 during site visits to each hospital followed by a conference call with all hospitals. As falls occurred, hospitals returned completed reporting forms to the research team via encrypted email or US mail, and data were entered into a Microsoft® Access database. We clarified inconsistencies and missing data in fall-event reports with each fall-risk-reduction team. We provided feedback about accuracy and completeness of reporting during quarterly conference calls with each fall-risk-reduction team throughout the study. Lastly, two members of the research team (DV and KJ) verified fall-event data entered into the database were internally consistent with the description of the fall and externally consistent with our definitions for fall type and outcome.

To calculate fall rates, we requested patient days for acute, skilled, and hospice patients, and hours patients were under observation from each hospital. These data were collected for 2013 and through the end of the project. Patient days was the sum of acute, skilled, and hospice days plus observation hours divided by 24. Total, unassisted, and injurious fall rates were expressed per 1000 patient days. Total falls included assisted, unassisted, injurious, and non-injurious falls.

Statistical analysis

Data used for statistical analysis are provided in Additional File 2. We used SAS/STAT software from SAS, Version 9.3 (SAS Institute Inc., Cary, NC, USA) for all analyses. We used the Pearson Chi-Square Test or Exact Pearson Chi-Square Test to determine the bivariate association between patient and system factors and fall type and fall outcome. Statistical significance was set at α ≤ .05. We used univariate logistic regression to determine significant patient or system predictors of fall type and outcome. We considered all falls as independent system events not nested by patient because of relatively small numbers of patients with ≥2 falls and the different situations in which repeat falls occurred. We used multivariate logistic regression to determine which patient or system factors best predicted fall type and outcome. We entered any variable that had a p value < .15 in the univariate analyses into the multivariate analyses on an exploratory basis to adjust the outcome for the presence of these variables in the model. We did not control for nesting of observations within hospitals because variation between hospitals was too small for the estimation procedure to converge to a solution.

Results

Three hundred sixteen patients accounted for 353 fall events reported during the study. Most were older adults with respiratory, orthopedic, or cardiovascular diagnoses (Table 1). Fall type was specified for all 353 falls, while fall outcome was specified for 352 falls. Of the 353 falls, 90 (25.5%) were assisted. Of the 352 falls with specified injury level, 113 (32.1%) were injurious. Aggregate fall rates for the study period were 4.0 total, 3.0 unassisted, and 1.3 injurious falls per 1000 patient days.

Table 1 Patient Demographic Data*

Table 2 reports bivariate associations between patient factors and fall type and outcome. Fall type was significantly associated with cognitive impairment (p < .001) and fall time (p = .048). Specifically, a higher proportion of unassisted falls occurred among patients with cognitive impairment and during 10:00 pm to 3:59 am. Fall outcome was significantly associated with age category (p = .02), fall location (p = .002), and toileting (p = .02). Specifically, the proportion of injurious falls increased with age, if the fall occurred in the bathroom, and if the fall was related to toileting, a variable that included factors beyond the patient simply being in the bathroom (see footnotes for Table 2).

Table 2 Association Between Patient Factors, Fall Type, and Fall Outcome

Table 3 reports bivariate associations between system factors and fall type and outcome. Fall type was significantly associated with identifying a gait belt as an intervention (p < .001), and location of a patient’s room (p = .02). Specifically, the proportion of unassisted falls increased when a gait belt was not identified as a fall-risk-reduction intervention for a given patient (i.e. gait belt use was not in the nursing care plan), and for patients in rooms close to the nurse’s station. Fall outcome was significantly associated with assistance during a fall (p = .004), use of alarms (p = .048), gait belt usage (p = .002), and a toileting schedule (p = .048). Specifically, the proportion of injurious falls was higher when falls were unassisted, and when alarms and toileting schedules weren’t used. Additionally, a lower proportion of injurious falls occurred when staff was providing assistance with a gait belt prior to the fall.

Table 3 Association Between System Factors, Fall Type, and Fall Outcome

Table 4 provides results of the logistic regression for patient and system factors associated with increased odds of a patient falling unassisted. Considering the adjusted odds ratios specifically, with all other factors being equal, the odds of falling unassisted were: 2.55 times greater for a patient ≥65 than one 19–64 years old (95% confidence interval [CI]: 1.30–5.03), 3.70 times greater for a patient with cognitive impairment than without (95% CI: 2.06–6.63), and nearly 7 times greater if a gait belt was not identified as an intervention for a patient than if it was identified (95% CI: 3.75–12.94).

Table 4 Odds Ratios for Patient and System Factors Associated with Increased Odds of Falling Unassisted

Table 5 provides the results of the logistic regression for patient and system factors associated with increased odds of a patient experiencing fall-related injury. Considering the adjusted odds ratios specifically, with all other factors being equal, the odds of an injurious fall were: 2.55 times greater for a patient ≥65 than one 19–64 years old (95% CI: 1.32–4.94), 2.48 times greater for a fall that occurred in the bathroom compared to one that occurred elsewhere (95% CI: 1.41–4.36), and 3.65 times greater for a fall that occurred when hands-on assist was being provided without a gait belt, compared to one that occurred when hands-on assist with a gait belt was provided (95% CI: 1.34–9.97).

Table 5 Odds Ratios for Patient and System Factors Associated with Increased Odds of Fall-Related Injury

Discussion

In our study, we determined risk factors that increased the odds of a patient falling unassisted and whether the fall was injurious. We report risk factors for patient falls in rural hospitals, which are underrepresented in the literature [13, 16, 19] and in external benchmarking databases [2, 16, 18, 21, 22]. Furthermore, we complemented prior research that identified risk factors for falling unassisted [2, 21, 22], and a relationship between assistance during falls and injury [2, 13]. Patient factors of increased age and cognitive impairment, and the system factor of not identifying a gait belt as an intervention for a given patient, increased the odds of falling unassisted. The patient factor of increased age, and system factors of a fall occurring in the bathroom and hands-on assist being provided, but without a gait belt, increased the odds of fall-related injury.

Comparison with other research

Few published studies have reported risk factors for falling unassisted [2, 21, 22]. Staggs et al. [21, 22] used data from the NDNQI to explore the relationship between nurse staffing characteristics and unassisted falls. In one study, unit type, total nurse hours per patient day, skill mix of nursing staff, and average tenure of registered nurses were related to unassisted fall rates [21]. In another study, higher non-registered nurse staffing was associated with higher rates of unassisted falls on all unit types except rehabilitation [22]. In a third study, Staggs et al. [2] used NDNQI data to consider factors besides nurse staffing, and found male gender, being assessed for risk, not having a fall-risk-reduction protocol in place, and unit type increased the odds of unassisted falls. We collected data relative to fall-risk factors found in the AHRQ Common Formats [36]. While some work by Staggs et al. [2, 21, 22] highlighted the relationship between nurse staffing and unassisted falls, these studies did not advance understanding of how processes of care influence unassisted falls. The system factors we considered are evidence-based interventions more readily modifiable on an everyday basis by nurses providing direct patient care than staffing characteristics. Thus, we provide evidence regarding care processes associated with unassisted falls such as identifying when a gait belt is appropriate to use for a given patient.

Considerable research has identified factors that increase risk of fall-related injury [2, 3, 12, 13, 15, 16, 23]. Our findings agree with this research in that increased patient age was associated with increased odds of injury [12, 13], as did falls occurring in the bathroom [13]. Our findings agreed with others in that cognitive impairment was not associated with increased odds of injury [12, 13]. Unlike other researchers [2, 13], we did not find gender to significantly predict injury. Hitcho et al. [15] reported elimination-related falls as the only variable in their multivariate analysis to significantly predict injury. Our factor of “fall related to toileting” was significant only in the bivariate analysis. Mion et al. [23] reported specific medications (e.g. antidepressants, antipsychotics, opiates, and diuretics) increased risk of fall-related injury. We did not find a significant association between medication use and injury, perhaps because most patients in our sample, regardless of injury, were taking medications known to increase fall risk. Lastly, Staggs et al. [2] and Krauss et al. [13] found unassisted falls were associated with increased odds of injury relative to assisted falls. We found being unassisted during a fall was significant only in the bivariate analysis. The critical factor regarding assistance that predicted injury in our multivariate model was whether or not assistance was provided with a gait belt. Our work extends that of others [2, 13] by suggesting assisting a fall without a gait belt results in greater odds of injury than not assisting the fall at all.

Some system factors were significantly related to fall type and outcome in our bivariate analysis (use of alarms, scheduled toileting, and proximity to the nurses’ station), but were not significant in the multivariate analysis. The AHRQ [37] recommends not relying on alarms for hospital fall prevention because previous research found them ineffective [38], which is consistent with our multivariate results. Scheduled toileting, particularly as part of scheduled rounding, is considered a best practice for preventing falls [37]. We found a higher proportion of unassisted falls in patients whose rooms were close to the nurses’ station, contrary to the assumption that staff could respond quickly if a patient mobilized unaided. We discovered many falls that occurred in rooms close to the nurses’ station were repeat falls, and as such, may have occurred in patients at especially high risk for falling. Despite these factors being insignificant in our multivariate model, we do not suggest abandoning these common fall-risk-reduction interventions. Clinical judgment suggests these interventions may help staff be present before or during patient mobility. Absent staff cannot assist a patient with mobility in a safe manner, such as by using a gait belt.

Practical implications

Our study provides several practical implications for hospital fall-risk-reduction programs. First, we demonstrate that use of gait belts, a simple and inexpensive patient safety tool, reduces the risk of falling unassisted and the risk of fall-related injury. A person is stable when he is able to control his center of mass (the center of one’s total body mass) in relationship to his base of support (the area of one’s body in contact with the supporting surface) [39]. A gait belt is typically applied just above the pelvis, near the center of mass. By holding the gait belt, a healthcare provider can help a patient maintain his center of mass over his base of support. A gait belt can also be used to control a patient’s descent to a lower surface, should he begin to fall [29, 30]. The AHRQ recommends gait belts only for patients with cognitive impairment [37], but we found value in their use among a broad sample of patients. We discovered failure to identify a gait belt as a fall-risk-reduction intervention increased the odds of an unassisted fall. This failure may occur when a patient is not accurately identified as needing hands-on assist with mobility, or when gait belt use is not part of a hospital’s culture. We also found providing hands-on assist without a gait belt increased the odds of fall-related injury relative to providing hands-on assist with a gait belt, surprisingly more so than a fall simply being unassisted. When a gait belt is not used, a healthcare provider may grasp a patient’s arm, potentially leading to injuries such as skin tears or dislocation of the shoulder joint during a fall.

Second, our data support a role for rehabilitation therapists on hospital fall-risk-reduction teams. The use of gait belts and other strategies for safe patient mobilization are emphasized in physical and occupational therapy [29,30,31]. Although nurses and nursing assistants are trained in the use of gait belts, their training is not as robust in the mechanics of body movement and stability. Also, their daily practice does not involve routine use of gait belts in nearly every patient encounter, as occurs in physical and occupational therapy. Hoyer et al. [31] reported rehabilitation therapists received more training in how to safely mobilize patients than nurses, and nurses felt less confident than therapists in their ability to mobilize patients. Rehabilitation therapists can contribute to fall-risk-reduction teams by sharing their expertise regarding safe patient mobilization of patients. This education can occur when consulting with nursing staff on individual patients in the context of direct patient care, but also more broadly throughout the organization via staff competency training on safe patient mobilization strategies. This potential collaboration between rehabilitation therapists and other staff demonstrates an interprofessional team approach to fall-risk reduction, in which falls are considered a measure of organizational quality rather than nursing quality [16].

Third, staff knowledge of safe patient mobilization strategies may prevent unintended consequences of reduced patient mobility and subsequent functional decline due to an assumption that keeping patients from moving will prevent falls [26, 27, 40]. Growden et al. [27] suggested hospital fall-risk-reduction teams should focus on promoting the positive outcome of safely mobilizing patients rather than preventing the negative outcome of falls. We believe this suggestion relates to the findings that unassisted falls increase the odds of injury [2, 13] and that when a fall is assisted with a gait belt, the odds of injury are decreased. An unassisted fall implies staff did not accurately identify the patient needed assistance, did not reliably implement fall-risk-reduction interventions, or were simply absent when the fall occurred [2, 26]. Assisted falls and unassisted falls should not be viewed equally when considering the quality of a hospital’s fall-risk-reduction program. Rather, an assisted fall should be considered a success [2]. Staff was in the right place at the right time with the tools and knowledge to assist the patient during the fall [2, 21], which again speaks to the opportunity for collaboration between nursing and rehabilitation therapists to develop strategies for safe patient mobilization.

Finally, we demonstrated the benefit of fall-event reporting in rural hospitals by addressing barriers for benchmarking and learning from fall-event data [16]. We needed to standardize the definitions of a fall, an assisted fall, and fall-related injury as prerequisites for analyzing data and calculating valid fall rates. Prior to our project, only 3 of the hospitals used the AHRQ standard fall definition [36], and only 10 used a standard fall definition from any source. Our reporting form and database became a shared resource for organizational learning among hospitals with limited resources for quality improvement and small numbers of fall events from which to learn. We were able to aggregate data to provide a wider range of information on patient and system factors related to falls than was previously available in these hospitals.

Strengths and limitations

A strength of our study is that we examined risk factors for unassisted and injurious falls in an understudied setting of hospitals with 50 beds or less. Although our findings are specific to rural hospitals in one state, they may apply to other facilities that care for a high proportion of older adults. Our patient sample is slightly older than those of many studies addressing risk factors for falls [2, 12, 13, 15, 23], yet is similar to patients studied by others [7, 20]. A limitation is our sample size is small relative to other studies that investigated factors related to falling unassisted [2, 21, 22] and experiencing fall-related injury [2, 3, 12, 13, 15, 16, 23]. However, many of our findings agree with larger studies [12, 13], our findings about gait belt use complement studies that reported the relationship between injury and assisted falls [2, 13], and the magnitudes of our adjusted odds ratios are quite convincing. A final strength of our study is our effort to ensure reliability of reported data. We educated fall-risk-reduction teams about how to complete the reporting form, provided ongoing feedback, and followed up on missing and/or inconsistent data in fall-event reports.

Conclusions

This study provides information regarding risk factors associated with unassisted and injurious falls in rural hospitals. We addressed barriers to reporting, aggregating, and benchmarking fall-event data in these hospitals. We expanded upon other research that found an association between assistance during falls and injury by discovering that the manner in which a fall is assisted is an important consideration for risk mitigation. Additional research is needed to determine best practices in assessing and maintaining the competency of non-rehabilitation therapy staff to safely assist patients with mobility.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and a supplementary information file (Additional File 2). In accordance with our Institutional Review Board’s guidance, the medical record numbers were replaced with mock values.

Abbreviations

AHRQ:

Agency for Healthcare Research and Quality

CAH:

Critical access hospital

CAPTURE Falls:

Collaboration and Proactive Teamwork Used to Reduce Falls

CI:

Confidence interval

NDNQI:

National Database for Nursing Quality Indicators

References

  1. Oliver D, Healey F, Haines TP. Preventing falls and fall-related injuries in hospitals. Clin Geriatr Med. 2010;26(4):645–92.

    Article  Google Scholar 

  2. Staggs VS, Mion LC, Shorr RI. Assisted and unassisted falls: different events, different outcomes, different implications for quality of hospital care. Jt Comm J Qual Patient Saf. 2014;40(8):358–64.

    Article  Google Scholar 

  3. Bouldin EL, Andresen EM, Dunton NE, Simon M, Waters TM, Liu M, et al. Falls among adult patients hospitalized in the United States: prevalence and trends. J Patient Saf. 2013;9(1):13–7.

    PubMed  PubMed Central  Google Scholar 

  4. Agency for Healthcare Research and Quality. 2013 Annual Hospital-Acquired Condition Rate and Estimates of Cost Savings and Deaths Averted From 2010 to 2013. AHRQ Publication No. 16–0006-EF. Rockville, MD: Agency for Healthcare Research and Quality; 2015. https://www.ahrq.gov/sites/default/files/publications/files/hacrate2013_0.pdf. Accessed 14 August 2019.

  5. Centers for Medicare and Medicaid Services. Hospital-acquired conditions. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalAcqCond/Hospital-Acquired_Conditions.html.. Accessed 14 August 2019.

  6. Bates DW, Pruess K, Souney P, Platt R. Serious falls in hospitalized patients: correlates and resource utilization. Am J Med. 1995;99(2):137–43.

    Article  CAS  Google Scholar 

  7. Corsinovi L, Bo M, Ricauda Aimonino N, Marinello R, Gariglio F, Marchetto C, et al. Predictors of falls and hospitalization outcomes in elderly patients admitted to an acute geriatric unit. Arch Gerontol Geriatr. 2009;49(1):142–5.

    Article  Google Scholar 

  8. Dunne TJ, Gaboury I, Ashe MC. Falls in hospital increase length of stay regardless of degree of harm. J Eval Clin Pract. 2014;20(4):396–400.

    Article  Google Scholar 

  9. Deshpande N, Metter EJ, Lauretani F, Bandinelli S, Guralnik J, Ferrucci L. Activity restriction induced by fear of falling and objective and subjective measures of physical function: a prospective cohort study. J Am Geriatr Soc. 2008;56(4):615–20.

    Article  Google Scholar 

  10. Deandrea S, Bravi F, Turati F, Lucenteforte E, La Vecchia C, Negri E. Risk factors for falls in older people in nursing homes and hospitals. A systematic review and meta-analysis. Arch Gerontol Geriatr. 2013;56(3):407–15.

    Article  Google Scholar 

  11. Halfon P, Eggli Y, Van Melle G, Vagnair A. Risk of falls for hospitalized patients: a predictive model based on routinely available data. J Clin Epidemiol. 2001;54(12):1258–66.

    Article  CAS  Google Scholar 

  12. Fischer ID, Krauss MJ, Dunagan WC, Birge S, Hitcho E, Johnson S, et al. Patterns and predictors of inpatient falls and fall-related injuries in a large academic hospital. Infect Control Hosp Epidemiol. 2005;26(10):822–7.

    Article  Google Scholar 

  13. Krauss MJ, Nguyen SL, Dunagan WC, Birge S, Costantinou E, Johnson S, et al. Circumstances of patient falls and injuries in 9 hospitals in a midwestern healthcare system. Infect Control Hosp Epidemiol. 2007;28(5):544–50.

    Article  Google Scholar 

  14. Colby SL, Ortman JM. Projections of the size and composition of the U.S. population: 2014 to 2060. Current Population Reports. US Department of Commerce, Economics and Statistics Administration, US Census Bureau; 2015. Report Number P25–1143.

  15. Hitcho EB, Krauss MJ, Birge S, Claiborne Dunagan W, Fischer I, Johnson S, et al. Characteristics and circumstances of falls in a hospital setting: a prospective analysis. J Gen Intern Med. 2004;19(7):732–9.

    Article  Google Scholar 

  16. Jones KJ, Venema DM, Nailon R, Skinner AM, High R, Kennel V. Shifting the paradigm: an assessment of the quality of fall risk reduction in Nebraska hospitals. J Rural Health. 2015;31(2):135–45.

    Article  Google Scholar 

  17. Krauss MJ, Evanoff B, Hitcho E, Ngugi KE, Dunagan WC, Fischer I, et al. A case-control study of patient, medication, and care-related risk factors for inpatient falls. J Gen Intern Med. 2005;20(2):116–22.

    Article  Google Scholar 

  18. Lake ET, Shang J, Klaus S, Dunton NE. Patient falls: association with hospital magnet status and nursing unit staffing. Res Nurs Health. 2010;33(5):413–25.

    Article  Google Scholar 

  19. Moe K, Brockopp D, McCowan D, Merritt S, Hall B. Major predictors of inpatient falls: a multisite study. J Nurs Adm. 2015;45(10):498–502.

    Article  Google Scholar 

  20. Schwendimann R, Buhler H, De Geest S, Milisen K. Characteristics of hospital inpatient falls across clinical departments. Gerontology. 2008;54(6):342–8.

    Article  Google Scholar 

  21. Staggs VS, Knight JE, Dunton N. Understanding unassisted falls: effects of nurse staffing level and nursing staff characteristics. J Nurs Care Qual. 2012;27(3):194–9.

    Article  Google Scholar 

  22. Staggs VS, Dunton N. Associations between rates of unassisted inpatient falls and levels of registered and non-registered nurse staffing. Int J Qual Health Care. 2014;26(1):87–92.

    Article  Google Scholar 

  23. Mion LC, Chandler AM, Waters TM, Dietrich MS, Kessler LA, Miller ST, et al. Is it possible to identify risks for injurious falls in hospitalized patients? Jt Comm J Qual Patient Saf. 2012;38(9):408–13.

    Article  Google Scholar 

  24. Balanced Budget Act of 1997, 42 USC §1395i-4. (1997).

  25. Moscovice IS, Casey M. Quality of care in critical access hospitals. JAMA. 2011;306:1653.

    Article  CAS  Google Scholar 

  26. Staggs VS, Davidson J, Dunton N, Crosser B. Challenges in defining and categorizing falls on diverse unit types: lessons from expansion of the NDNQI falls indicator. J Nurs Care Qual. 2015;30(2):106–12.

    Article  Google Scholar 

  27. Growdon ME, Shorr RI, Inouye SK. The tension between promoting mobility and preventing falls in the hospital. JAMA Intern Med. 2017;177(6):759–60.

    Article  Google Scholar 

  28. Press Ganey Associates I. Guidelines for data collection and submission on patient falls: Inpatient and ambulatory care areas. http://www.pressganey.com/solutions/clinical-quality/nursing-quality. Accessed 19 July 2018.

  29. Fairchild SL, Kuchler O'Shea R, Washington RD. Assistive devices, patterns, and activities. In: Principles and techniques of patient care. 6th ed. St. Louis, MO: Elsevier; 2018. p. 211–60.

    Google Scholar 

  30. Fairchild SL, Kuchler O'Shea R, Washington RD. Transfer activities. In: Principles and techniques of patient care. 6th ed. St. Louis, MO: Elsevier; 2018. p. 169–210.

    Google Scholar 

  31. Hoyer EH, Brotman DJ, Chan KS, Needham DM. Barriers to early mobility of hospitalized general medicine patients: survey development and results. Am J Phys Med Rehabil. 2015;94(4):304–12.

    Article  Google Scholar 

  32. United States Census Bureau. Age and sex composition in the United States: 2010. https://www.census.gov/data/tables/2010/demo/age-and-sex/2010-age-sex-composition.html. Accessed 14 August 2019.

  33. CAPTURE Falls. https://www.unmc.edu/patient-safety/capturefalls/. Accessed 14 August 2019.

  34. Jones KJ, Skinner A, Venema D, Crowe J, High R, Kennel V, et al. Evaluating the use of multiteam systems to manage the complexity of inpatient falls in rural hospitals. Health Serv Res. 2019;54(5):994-1006.

    Article  Google Scholar 

  35. DeChurch LA, Zaccaro SJ. Perspective: teams won't solve this problem. Hum Factors. 2010;52(2):329–34.

    Article  Google Scholar 

  36. Agency for Healthcare Research and Quality. Supporting Documents - Common Formats - Hospital Version 1.2. https://www.psoppc.org/psoppc_web/publicpages/supportingDocsV1.2. Accessed 14 August 2019.

  37. Ganz DA, Huang C, Saliba D, Shier V, Berlowitz D, VanDeusen Lukas C, et al. Preventing falls in hospitals: a toolkit for improving quality of care https://www.ahrq.gov/professionals/systems/hospital/fallpxtoolkit/index.html. Accessed 14 August 2019.

  38. Shorr RI, Chandler AM, Mion LC, Waters TM, Liu M, Daniels MJ, et al. Effects of an intervention to increase bed alarm use to prevent falls in hospitalized patients: a cluster randomized trial. Ann Intern Med. 2012;157(10):692–9.

    Article  Google Scholar 

  39. Shumway-Cook A, Woollacott MH. Normal postural control. In: Nobel M, Francis LG, editors. Motor control: translating research into clinical practice. 5th ed. Philadelphia, PA: Wolters Kluwer; 2017. p. 153–82.

    Google Scholar 

  40. Inouye SK, Brown CJ, Tinetti ME. Medicare nonpayment, hospital falls, and unintended consequences. N Engl J Med. 2009;360(23):2390–3.

    Article  CAS  Google Scholar 

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Acknowledgements

The authors thank Kristin Topliff, PT, DPT and Zachary Douglas, PT, DPT for their assistance in collecting and entering data for this study. We also thank the rural hospitals who participated in the study.

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Not applicable.

Funding

This project was supported by grant number R18HS021429 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. The Agency for Healthcare Research and Quality was not involved in the design of the study, data collection and analysis, interpretation of the data, or writing the manuscript.

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Contributions

DV participated in study conception and design, analysis and interpretation of data, and drafting and critically revising the manuscript for important intellectual content. AS participated in study conception and design, acquisition of data, analysis and interpretation of data, and critically revising the manuscript for important intellectual content. RN participated in interpretation of data and drafting and critically revising the manuscript for important intellectual content. DC participated in interpretation of data and critically revising the manuscript for important intellectual content. RH participated in analysis of data and drafting and critically revising the manuscript for important intellectual content. KJ participated in study conception and design, acquisition of data, analysis and interpretation of data, and drafting and critically revising the manuscript for important intellectual content. All authors approve the final version of the manuscript and agree to be held publically accountable for all aspects of the work.

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Correspondence to Dawn M. Venema.

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The University of Nebraska Medical Center Institutional Review Board approved this study (protocol number 256–12-EP), including a waiver of informed consent.

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The authors declare that they have no competing interests.

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Supplementary information

Additional file 1.

CAPTURE Falls Event Reporting Form. Standardized reporting form (.pdf) used to collect patient and system data about fall events.

Additional file 2.

CAPTURE_Falls_Data_and_Dictionary. Spreadsheet (.xlsx) of raw data used to conduct the statistical analysis presented within the manuscript. The file includes data from which fall rates were calculated; data for individual fall events, a data dictionary, and look up tables referred to in the data dictionary. In accordance with our Institutional Review Board’s guidance, the patient medical record numbers were replaced with mock values.

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Venema, D.M., Skinner, A.M., Nailon, R. et al. Patient and system factors associated with unassisted and injurious falls in hospitals: an observational study. BMC Geriatr 19, 348 (2019). https://doi.org/10.1186/s12877-019-1368-8

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