Preventing Patient Falls in Medical Care Setting

Introduction

Patient falls are a serious problem in the modern health care setting. The current paper provides the results of a previously planned study that was aimed at finding out the nurses’ perceptions about the efficacy of several anti-fall measures. After a succinct literature review, the methods of the study are explained; then, its results are provided; a discussion of the study’s limitations follows, and a brief conclusion is supplied.

Literature Review

A review of the literature shows that falls have a profoundly adverse impact on the health of the patients; for instance, it is the most common reason for injury deaths and for emergency department visits due to trauma among individuals aged 65 or older (Stevens & Phelan, 2013). Therefore, it is paramount to identify the possible measures of fall prevention and determine which of them may be more effective.

Multiple methods for preventing falls exist; some of the most widely used are bed alarms, rounds, and the care of sitters (Shever, Titler, Mackin, & Kueny, 2011). In addition, such measures as ambulation, relocating the patient closer to the nursing station, engaging them in physical exercise, and so on are also used (Sherrington et al., 2016; Shever et al., 2011).

Methods

For the current study, nurses from several local hospitals and clinics were surveyed. The permissions of the administrations of these clinics were gained. The respondents gave their informed consent.

36 nurses (33 females, 3 males) were interviewed; only individuals who had sufficient nursing experience (at least 5 full years of working as a nurse) were surveyed.

The participants were given questionnaires, which can be found in Appendix 1. The results were entered into the computer and processed using the IBM SPSS software. A one-way repeated measures ANOVA was run to find out whether the participants considered the three measures (bed alarms, hourly rounds, the care of sitters) equally effective for fall prevention (Laird Statistics, n.d.).

In addition, the participants were given one open-ended question where they were asked to name several fall prevention measures which they considered to be effective. The results were gathered and summarized.

Results

Quantitative Analysis

The data gathered from the survey can be found in Appendix 2.

Of the demographic characteristics of the respondents, only their gender and age were measured. Such variables as race or social status were not measured, for race was not judged to be important for the current study. As for social status, it was also not perceived to be important; in addition, all the participants were either registered nurses (RNs) or advanced practice registered nurses (APRNs), so certain similarities in social status probably existed.

As was noted, 36 nurses (33 females, 3 males) were surveyed. Mean age was 38.94 years (standard deviation = 9.027); mean, the experience of working as a nurse was 16.50 years (standard deviation = 7.934).

The descriptive statistics for the three types of measures were as shown in Table 1 below.

Descriptive Statistics
Mean Std. Deviation N
bed_alarms 3.53 1.028 36
h_rounds 3.00 1.069 36
sitters 4.39 .688 36

Table 1. Descriptive statistics for the assessment of the three measures’ effectiveness.

The results of the repeated measures ANCOVA were as displayed in Table 2 below:

Tests of Within-Subjects Effects
Measure: MEASURE_1
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
prev_measure Sphericity Assumed 35.389 2 17.694 21.133 .000 .376
Greenhouse-Geisser 35.389 1.948 18.171 21.133 .000 .376
Huynh-Feldt 35.389 2.000 17.694 21.133 .000 .376
Lower-bound 35.389 1.000 35.389 21.133 .000 .376
Error(prev_measure) Sphericity Assumed 58.611 70 .837
Greenhouse-Geisser 58.611 68.163 .860
Huynh-Feldt 58.611 70.000 .837
Lower-bound 58.611 35.000 1.675

Table 2. Results of the ANOVA.

Because Mauchly’s test of sphericity was non-significant (p=.628), the “Sphericity Assumed” option was chosen from Table 2. There were significant differences between the respondents’ assessments of different fall prevention measures: F(2, 70)=21.133, p<.0005, effect size as measured by partial η2=.376.

A pairwise comparison of the assessments can be found in Table 3 below; numerical labels are displayed in Table 4. It should be noted that the Bonferroni adjustment was used for multiple pairwise comparisons (Laird Statistics, n.d.).

Pairwise Comparisons
Measure: MEASURE_1
(I) prev_measure (J) prev_measure Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Difference
Lower Bound Upper Bound
1 2 .528 .231 .085 -.052 1.108
3 -.861* .200 .000 -1.364 -.359
2 1 -.528 .231 .085 -1.108 .052
3 -1.389* .216 .000 -1.931 -.847
3 1 .861* .200 .000 .359 1.364
2 1.389* .216 .000 .847 1.931
Based on estimated marginal means
*. The mean difference is significant at the.05 level.
b. Adjustment for multiple comparisons: Bonferroni.

Table 3. Pairwise comparisons of the assessment of different prevention measures.

Within-Subjects Factors
Measure: MEASURE_1
prev_measure Dependent Variable
1 bed_alarms
2 h_rounds
3 sitters

Table 4. Labels for variables.

Table 3 displays that a marginally significant difference (George & Mallery, 2016) was found between the assessments of the effectiveness of bed alarms and hourly rounds (p=.085); mean difference (bed alarms – hourly rounds) =.528. However, a statistically significant difference was found between the estimation of efficaciousness of bed alarms and that of sitters: p<.0005, mean difference (bed alarms – sitters) = -.861. Also, a statistically significant difference was found between the respondents’ assessments of hourly rounds and sitters: p<.0005, mean difference (hourly rounds – sitters) = -1.389.

Qualitative Survey

The respondents also named several ways for fall prevention when completing the survey. Apart from the methods that were mentioned above, these included the alteration of physical space around the patient (e.g., using bed rails, removing objects from the floor that one may stumble over), using appropriate footwear, etc.

Limitations

The current study has several limitations. For instance, the quantitative part only compares the nurses’ perceptions of the effectiveness of anti-fall measures but does not research the clinical data pertaining to, e.g., registered falls. Also, only the three most popular (Shever et al., 2011) measures were compared. Also, the cost of these measures was not taken into account; for instance, providing the care of a sitter requires considerably more resources than using bed alarms. The qualitative, open-ended question only allowed for gathering a very limited amount of information.

Conclusion

On the whole, falls remain a serious challenge for patients, especially aged ones, and need to be addressed. It is critical that the most effective measures are used to prevent falls; however, the cost of these measures also needs to be taken into account when choosing which of them to implement.

Appendix 1

Please answer the following questions:

  1. Please indicate your gender:
  2. 1 = female, 2 = male
  3. Please indicate your age (full years): _____
  4. Please indicate your total length of nursing service (how long you have been a nurse, full years): _______
  5. Bed alarms are effective in preventing patient falls in the hospital setting.
  6. 1 = Strongly disagree
  7. 2 = Disagree
  8. 3 = Neither agree nor disagree
  9. 4 = Agree
  10. 5 = Strongly agree
  11. Hourly rounds are effective in preventing patient falls in the hospital setting.
  12. 1 = Strongly disagree
  13. 2 = Disagree
  14. 3 = Neither agree nor disagree
  15. 4 = Agree
  16. 5 = Strongly agree
  17. Sitters are effective in preventing patient falls in the hospital setting.
  18. 1 = Strongly disagree
  19. 2 = Disagree
  20. 3 = Neither agree nor disagree
  21. 4 = Agree
  22. 5 = Strongly agree
  23. Please name any falls prevention technique that you consider useful:

Appendix 2

The results of quantitative surveying:

id gender age nursingXP bed_alarms h_rounds sitters
1 1 29 7 3 3 4
2 1 32 10 4 4 5
3 1 41 10 3 3 5
4 1 37 15 4 2 4
5 1 30 9 4 4 5
6 1 57 30 3 3 3
7 1 43 21 5 4 3
8 1 29 8 3 2 4
9 1 38 16 2 1 5
10 1 39 18 1 1 5
11 1 45 24 3 4 5
12 1 52 29 5 2 5
13 1 34 13 4 3 5
14 2 33 12 3 4 5
15 1 39 17 3 3 4
16 1 38 18 4 4 5
17 1 54 33 2 4 3
18 1 42 20 5 4 5
19 1 44 23 4 5 4
20 1 47 27 3 3 4
21 1 32 10 3 4 5
22 2 35 14 4 3 4
23 1 31 10 2 2 3
24 1 64 31 3 3 4
25 2 29 9 4 2 5
26 1 38 18 3 1 5
27 1 33 12 4 2 4
28 1 44 15 5 2 5
29 1 39 13 5 3 4
30 1 30 8 4 2 4
31 1 28 6 2 4 5
32 1 27 6 5 3 5
33 1 52 29 5 3 4
34 1 49 28 3 4 5
35 1 33 12 3 5 4
36 1 35 13 4 2 4

References

George, D., & Mallery, P. (2016). IBM SPSS Statistics 23 step by step: A simple guide and reference (14th ed.). New York, NY: Routledge.

Laerd Statistics. (n.d.). Web.

Sherrington, C., Fairhall, N., Kirkham, C., Clemson, L., Howard, K., Vogler, C., & Sonnabend, D. (2016). Exercise and fall prevention self-management to reduce mobility-related disability and falls after fall-related lower limb fracture in older people: Protocol for the RESTORE (Recovery Exercises and STepping On afteR fracturE) randomised controlled trial. BMC Geriatrics, 16(1), 34.

Shever, L. L., Titler, M. G., Mackin, M. L., & Kueny, A. (2011). Fall prevention practices in adult medical-surgical nursing units described by nurse managers. Western Journal of Nursing Research, 33(3), 385-397.

Stevens, J. A., & Phelan, E. A. (2013). Health Promotion Practice, 14(5), 706-714. Web.

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