The Health Care Manager Volume 34, Number 4, pp. 359–366 Copyright # 2015 Wolters Kluwer Health, Inc. All rights reserved.
Lower Nurse Staffing Levels Are Associated With Occurrences of Inpatient Falls at a Large Pediatric Hospital Joseph Hagan, ScD; Angela Jones, MN, RN No previous research has been published regarding the relationship between nurse staffing levels and inpatient pediatric falls, and previous research in the adult population has yielded conflicting results, probably due in many instances to suboptimal study design. The objective of this study was to examine the relationship between nurse staffing levels and pediatric patient falls in a large children’s hospital. A case-control study design was used to compare the nurse staffing level during the shift of patient falls to the staffing level in the same units on shifts when patient falls did not occur. Nurse staffing levels were significantly lower in units when patient falls occurred, particularly during night shift. Targeted nurse staffing interventions in high-risk units could reduce the incidence of inpatient pediatric falls. Key words: case-control study, nurse staffing, patient falls
T
HE COST OF health care is an area of everincreasing concern in the United States. Hospital administrators are always looking for ways to decrease costs while maintaining quality of patient care. Nurse staffing consumes a large proportion of every hospital’s budget, and a shortage of qualified nurses makes appropriately staffing hospitals a challenge.1 Numerous studies have shown a link between nurse staffing and the quality of patient outcomes.2 In the United States in 1999, in an effort to ensure that hospitals maintain an adequate nurse staffing level, the California legislature passed Assembly Bill 394 requiring California’s State Department of Health Services to develop minimum licensed nurse-topatient staffing ratios in acute care hospitals.3 Inpatient falls are considered to be a nursesensitive quality outcome by the National Quality Forum. In acute care hospitals, patient falls
Author Affiliations: Texas Children’s Hospital, Houston, Texas. The authors have no conflict of interest. Correspondence: Joseph Hagan, ScD, Texas Children’s Hospital, Houston, TX ([email protected]). DOI: 10.1097/HCM.0000000000000083
occur more than any other type of adverse event and often result in a longer hospital stay due to complications from the fall.4,5 More than 1 million hospitalized patient falls per year are reported in the United States,6 but the Centers for Medicare & Medicaid Service does not reimburse hospitals for care related to injuries that result from inpatient falls.7 In the pediatric population, the incidence rate of inpatient falls has been observed to range from 0.77 to 1.37 falls per 1000 patient-days, with 32% to 36% of these falls resulting in injury.8,9 The early developmental stage of children renders them susceptible to falling, but physical illness and injury and being in an unfamiliar environment can further increase the probability that a hospitalized child will fall.10 In addition, Razmus et al11 identified episodes of disorientation and a history of falls as factors that increase the risk of falling for hospitalized children. Despite the relatively common incidence of pediatric inpatient falls and the unique risk factors of falling for this population, no published studies could be identified that specifically investigated the relationship between nurse staffing and pediatric falls. Although inpatient falls are considered to be a nurse-sensitive outcome, previous research in the adult population has yielded conflicting 359
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results regarding the relationship between nurse staffing and patient fall risk, with the majority of studies failing to demonstrate a significant relationship between nurse staffing and patient falls.12-14 But as elaborated on below, many of these studies have been limited by poor study design, inappropriate variable measurement, suboptimal sampling methodology, lack of adjustment for confounding variables, and use of hospital-level data that do not capture patient-specific factors at the time of the fall.15 When analyzing observational data from 232 acute care hospitals in California, Cho et al16 found no evidence to support a relationship between nurse staffing and patient falls, although significant associations were found between nurse staffing and odds of pneumonia and pressure ulcers. McGillis Hall et al17 did not observe a relationship between nurse staffing and patient falls in a descriptive correlational study of 19 teaching hospitals. BreckenridgeSproat et al,18 Blegen and Vaughn,19 and Blegen et al20 did not see a relationship between nurse staffing and patient falls when analyzing unit-level data aggregated over 1-month, 1-quarter, and 1-year periods, respectively. On the other hand, Sovie and Jawad21 analyzed data from 29 teaching hospitals summarized over a 1-year period and found that more nursing hours per patient-day (HPPDs) were associated with lower fall rates. To further blur the picture, Staggs and Dunton22 and Dunton et al23 found increased nursing HPPDs to be protective against patient falls only on some types of units, whereas Staggs et al24 made the counterintuitive observation that units with the lowest staffing levels actually had below-average fall rates! Schubert et al25 found no relationship between nurse staffing and falls when analyzing nurse survey data, whereas Donaldson et al26 saw no relationship between staffing level trends and patient fall rates over time in California hospitals. On the other hand, Unruh27 conducted a hospital-level analysis of Pennsylvania hospital data and found that hospitals with more licensed nurses had significantly lower fall rates. He et al28 analyzed hospital data at the unit level in the National Database of Nursing Quality Indicators (NDNQI)
database aggregated over 1-year time intervals and found that higher nursing HPPDs were associated with lower fall rates. Likewise, Dunton et al29 analyzed NDNQI data summarized by quarter at the hospital unit level and concluded that increasing nursing HPPDs corresponded with lower fall rates. The relationships between nursing staffing levels and fall rates observed in all of the aforementioned studies are highly susceptible to confounding due to other factors, because data are aggregated and analyzed over long periods (1 month to 1 year) and therefore are not able to investigate the effects of nurse staffing at the time of the fall. Krauss et al30 did use nurse staffing data at the time of the patient falls; however, their statistical methods did not appropriately accommodate their case-control matching. Patrician et al31 was the only study located, without glaring study design or analytical flaws, that analyzed nurse staffing level data during the actual shift that the patient falls occurred, and this study showed that units with a higher number of nursing hours per patient had a lower risk of patient falls. But this study was conducted among adult patients. Although a recent study concluded that many inpatient pediatric falls are preventable, and nurse vigilance is required to maintain a safe environment, risk factors for pediatric inpatient falls have not been satisfactorily delineated by the relatively small amount of research conducted in the pediatric population.32 We are aware of no prior study showing a relationship between nurse staffing and pediatric inpatient falls. The purpose of this study is to determine if there is a relationship between nurse staffing levels and occurrence of patient falls at a large pediatric hospital. METHODS Effective in 2009, the Texas legislature passed Senate Bill 476, which included the addition of Chapter 257 to the Texas Health and Safety Code requiring hospitals to ‘‘establish a nurse staffing committee’’ whose purpose includes identifying ‘‘the nurse-sensitive outcome measures the committee will use to evaluate the
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Nurse Staffing Levels and Occurrence of Inpatient Falls effectiveness of the official nurse services staffing plan.’’ The data analyzed for the current study were collected as part of the effort to comply with this legislation by using a datadriven evaluation of the relationship nurse staffing and nurse-sensitive outcomes. No a priori power analysis was performed because the data analyzed and presented here are routinely collected on an ongoing basis for quality improvement purposes. The hospital’s institutional research council reviewed and approved the study (protocol 14-912), including dissemination of the results. The requirement for documentation of informed consent was waived because the research posed minimal risk and does involve any procedures that require consent outside the research context. The hospital event reporting system was used to identify all inpatient falls occurring from July 1, 2013, and through March 31, 2014. For all falls reported during this period, the nurse staffing level on the unit during the shift of each patient fall was calculated. The unit’s ‘‘nurse staffing level’’ for the shift was computed as follows: nurse staffing level = (actual number of RNs working on unit during the shift / target number of RNs on unit for the shift) 100%. Units’ electronic staffing logs were used to ascertain the actual number of RNs working on the unit each shift. The target number of RNs is computed by the hospital’s commercial automated patient acuity system, which considers a combination of factors including patient census and patient acuity. Some measure of nurse staffing level when falls do not occur was needed for comparative purposes in order to determine if there is a relationship between nurse staffing level and patient falls. To this end, a case-control study design was implemented, where ‘‘control’’ nurse staffing levels are defined as the nurse staffing level exactly 7 days prior to the actual ‘‘case’’ (fall), on the same unit and same shift as the ‘‘case’’ (fall). Data on patient falls were accumulated from July 1, 2013, through March 31, 2014. Staffing level data for all ‘‘cases’’ and ‘‘controls’’ were entered into an Excel spreadsheet in a format suitable for statistical analysis. The Excel spreadsheet
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was imported into SAS 9.3 (SAS Institute Inc, Cary, North Carolina), which was used for all data analysis. To examine the relationship between nurse staffing and patient falls, a difference in staffing level was computed for each case-control dyad (difference = case staffing level control staffing level). The Wilcoxon signed rank test was used to determine if there is a significant difference between nurse staffing levels when patient falls occurred compared with when patient falls did not occur (ie, cases vs controls). RESULTS There were 111 falls documented, yielding a fall rate of 1.7 falls per 1000 patient-days during the period for which data were available (July 1, 2013, through March 31, 2014). Forty of the 111 falls (36%) resulted in injury, so the injury fall rate was 0.6 injury falls per 1000 patient-days. The greatest number of falls occurred on medical units (Table 1), and physical/ psychological falls were the most common fall category (Figure). The fall categories are defined in Table 2.8 Overall, the mean nurse staffing level was lower when falls occurred compared with control shifts (Table 3). When a stratified analysis was performed to compare the case versus control staffing levels separately on day shift and night shift, on night shift the staffing Table 1. Number and Percentage of Falls Occurring on Each Type of Unit Type of Unit Medical Cardiology Hematology/oncology Neurology Mother baby unit Inpatient rehabilitation Surgery Bone marrow transplant Progressive care Perioperative Short stay observation Cardiovascular intensive care Pediatric intensive care Inpatient research
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n (%) of Falls 21 14 14 12 11 10 8 6 6 2 2 2 2 1
(19) (13) (13) (11) (10) (9) (7) (5) (5) (2) (2) (2) (2) (1)
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Figure. Pareto chart of fall categories observed from July 1, 2013, through March 31, 2014.
level was significantly lower when falls occurred, but on day shift there was not a significant difference in case versus control staffing levels (Table 3). DISCUSSION The present study finds that lower nurse staffing levels are associated with increased incidence of falls among patients at a large pediatric hospital. This relationship was statistically significant when all data combined were analyzed. However, when the analysis was stratified by shift, significantly lower nurse staffing levels were observed when
patient falls occurred on night shift, but the association was not significant for day-shift falls. No previous study has shown such a relationship in the pediatric population. An Ovid MEDLINE search for publications containing the words ‘‘pediatric,’’ ‘‘falls,’’ ‘‘nurse,’’ and ‘‘staffing’’ yielded no matching records. Creative searches using other databases also produced no published studies specifically investigating the relationship between nurse staffing and pediatric inpatient falls. Therefore, the ensuing discussion compares the study design and findings of the present study to published studies in the adult population. The present study is unique in that it uses shift-specific
Table 2. Definition of Fall Categories Fall Category
Definition
Developmental Environmental Family attentiveness
Horseplay Modesty Other Physical/psychological Response to treatment Unknown
Fall common to toddlers (1-4 y of age) learning to walk, pivot, or run Fall resulting from a contribution of the environment or equipment Fall resulting from lack of family member attentiveness. Only used if a family member is present and could have reduced fall risk, and the fall is not described by any other category Fall associated with rough play activity (eg, running, wrestling, climbing, or jumping) Fall related to not seeking assistance due to modesty or desire for privacy Unique fall not described by another category Fall related to new or previously diagnosed seizures, developmental delay, confusion, or occurring during physical therapy due to known unsteady gait Fall resulting from response to surgery, medication, or medical intervention Not enough detail to categorize the fall
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Nurse Staffing Levels and Occurrence of Inpatient Falls Table 3. Comparison of Nurse Staffing Levels for Cases and Controls on the Day Shift, Night Shift, and Overall for Both Shifts Combined
Mean Staffing Level Shift Day Night Overall
n
Shift of Fall
Control Shift
64 47 111
98.3% 100.4% 99.2%
100.3% 106.5% 102.9%
Mean Difference 2.0% 6.1% 3.7%
P 0.172 0.010a 0.007a
a
Indicates a statistically significant difference ( = .05).
nurse staffing levels to demonstrate an inverse relationship between nurse staffing level and occurrence of falls among hospitalized pediatric patients. Cho et al16 did not find a relationship between nurse staffing level and patient falls when analyzing 2 existing databases. A recent study by Staggs and Dunton22 found a statistically significant inverse relationship between nursing HPPDs and fall risk on medical-surgical units, but no significant relationship on surgical or rehabilitation units. This study quantified RN HPPDs ‘‘as the sum of nursing care hours provided by RNs during the month divided by the sum of the unit’s patient-days for the month.’’ This metric does not quantify the nurse staffing at the time of the fall, unlike the nurse staffing level measure used in the current study. McGillis Hall et al17 did not find a significant relationship between nurse staffing and risk of falls in adult patients. But McGillis Hall et al17 quantified patients’ nursing resource use as ‘‘unit producing personnel,’’ a metric that includes the sum of all paid nursing hours allocated to a patient—which again does not provide information about nurse staffing at the time of the falls. In an indirect examination of the relationship between nurse staffing level and patient falls, Donaldson et al26 observed a significant increase in the total number of nursing HPPDs in 200 units from 68 California hospitals in 2004 compared with 2002, but the rate of falls (and injury falls) did not change significantly. Blegen et al20 fit 4 linear regression models to examine the relationship between independent variables including nursing HPPDs and adverse patient outcomes including patient falls. They used unit-level data averaged over an entire year
and concluded that ‘‘rates of patient falls were not explained well by any of the models.’’ Obviously, in this study, measurement of neither the independent variables (eg, nursing HPPDs on the unit over the year) nor the dependent variables (eg, patient fall rate on the unit over the year) facilitated investigation of the relationship between fall risk and nurse staffing levels at the time of the patient falls. In addition, Poisson regression would be the appropriate statistical method to use, rather than linear regression, when the objective is to fit a statistical model for which the dependent variable is a rate.32 Although Breckenridge-Sproat et al18 initially obtained data on the number of nursing HPPDs on the unit during the shift when falls occurred, the nursing HPPD data used for their statistical analysis were ‘‘aggregated to the month level for each unit, resulting in a total number of 833 ‘unit-months’,’’ and the relationship between nursing HPPDs and fall rate was examined using these 833 data points. Thus, a direct comparison of the nurse staffing level on the shifts when falls occurred to the shifts when falls did occur was not made, which might explain why Breckenridge-Sproat et al18 did not find a relationship between units’ number of nursing care HPPDs and the fall rate. On the other hand, the current study uses staffing level measurements from the shift during which the falls actually occurred. This improvement in nurse staffing level assessment could be the reason for the observed relationship between nurse staffing and patient falls achieving statistical significance in the present study, in contrast to the aforementioned studies’ nonsignificant findings. Lake and Cheung12 identified 8 studies examining the relationship between nurse staffing
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and patient falls, only 2 of which yielded statistically significant results. It should be noted that 2 of these 8 studies—and 1 of the 2 studies27 showing statistical significance—were conducted at the hospital level, which greatly limits the ability to make inference about the relationship between nurse staffing and risk of patient falls, because information about the nurse staffing exposure for the particular patient who fell is not used. Schubert et al25 did not find a significant relationship between nurse staffing and patient falls, but for this study, patient falls were ascertained by a survey asking nurses if any of their patients had fallen over the past year. Similarly, their nurse staffing data were derived from a survey of nurses. The use of surveys to measure the explanatory variables and the outcome introduces the possibility of recall bias and other sources of bias due to the subjectivity of nurses’ self-reports. There have been a few studies demonstrating a statistically significant association between nurse staffing level and patient falls. Kalisch et al33 and Sovie and Jawad21 found that a lower number of nursing hours was associated with a higher unit fall rate, but the former study aggregated each unit’s data by month, whereas the latter study aggregated data by year. Thus, even though these studies conclude that there is a statistically significant inverse relationship between nurse staffing and risk of falls, the findings are not very compelling because the association could be explained by unobserved confounding variables because staffing levels at the time of the fall were not used in the analysis. Krauss et al30 is one of the rare studies that analyzed nurse staffing data from the actual time of patient falls, but they used logistic regression to quantify the association between patient-to-nurse staffing levels and odds of patients’ falling. This statistical method ignores the case-control pairing implemented for the study and could therefore yield biased results.34 Patrician et al31 is the only study located that measured and appropriately analyzed hospital units’ nurse staffing level each shift, and they found that the risk of falls increased significantly as the number of nursing HPPDs on a shift decreased, but the study of Patrician
et al31 was conducted among adults, so the present study was needed to investigate the pediatric population. Like the current study, Patrician and colleagues’ study design provides more credible inference that nurse staffing levels affect the risk of patient falls. He et al28 and Dunton et al23,29 found a significant negative relationship between the total number of nursing hours and patient fall rates when analyzing data in the NDNQI. But surprisingly, Staggs et al24 analyzed monthly unit-level data from the NDNQI and concluded that ‘‘units at the very lowest staffing levels tended to have lower fall rates than most units with staffing levels above the median.’’ Counterintuitive findings such as this illustrate the need to cautiously interpret results obtained from the analysis of large databases not designed for the specific purpose of the research study, particularly when data around the time of the fall are not analyzed. These studies using unit-level data summarized over a period (eg, a month) are susceptible to misleading results due to the ecological inference fallacy, because summary data were used to quantify nurse staffing levels rather than measuring the nurse staffing level exposure of the specific patients who fell and did not fall. The ecological inference fallacy results from using aggregated data to make inference about individuals. For example, with regard to the aforementioned studies that used unit-level data summarized by month, it is possible that hospital units with higher nurse staffing levels during a given month also provided other new resources or implemented interventions that might reduce patient fall risk, and the observed reduction in patient falls is actually due to the other resources/interventions rather than nurse staffing. Using a research study design similar to the current study where shift-specific staffing levels are obtained for cases and controls from the same hospital unit 1 week apart will eliminate these confounding effects and isolate effects due to the nurse staffing level, because the case and control shifts would both be exposed to the new resources and interventions. It is hoped that the previously mentioned critique of previous investigations of the relationship between nurse staffing and patient
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Nurse Staffing Levels and Occurrence of Inpatient Falls falls does not appear overly disparaging. The limitations of these studies illustrate the logistical difficulties involved with developing a valid study design to investigate the hypothesized association. Because patient falls occur at a discrete time and place, ideally nurse staffing data for the specific time and place of the fall should be analyzed, but the challenge is to obtain comparable nurse staffing data when falls do not occur. The case-control study design used for the current study allowed the analysis of nurse staffing level data from the specific shift when falls occurred, and matched control data were obtained from the same unit on the same shift exactly 1 week prior when a fall had not occurred, thereby avoiding susceptibility to confounding factors that could have biased results from the other studies discussed previously. Although nursing staff at the hospital expressed skepticism about the meaningfulness of the automated target staffing level calculations obtained from the patient acuity system, the validity of the absolute nurse staffing level measurements derived from these calculations is not relevant to the data analysis used for the current study, because only the relative differences between case and control staffing levels are considered. Also, the data analysis is quite robust to extreme values of nurse staffing levels because it uses a nonparametric statistical method that evaluates differences in terms of ranks rather than actual staffing level values, thereby avoiding the need to assume that the case-control differences in staffing levels are normally distributed—an assumption that underlies standard parametric statistical methods. The stronger relationship between nurse staffing level and patient falls observed during
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the night shift is interesting. Perhaps a reduced presence of visitors to watch children during the night explains the observed increased incidence of falling when nurse staffing levels are low at night, while the same relationship is not as consistently observed during the day shift. Sedation of patients at night could also have been a factor for some falls, although the possible influence of sedation was not investigated. Although increasing nurse staffing levels would appear to be the obvious solution, common sense dictates that there should be a threshold of nurse staffing ‘‘saturation,’’ beyond which more nurses will not reduce the risk of falling, but further research is needed to elucidate how to identify that threshold for nursing staff caring for a specific patient population. Also, certain interventions such as hourly nurse rounding, which was not being implemented at the institution during the timeframe of the current study, could potentially help to reduce patient fall risk. A limitation of the current study is that it merely considers the effect of the number of nurses working, but does not account for the characteristics of the nurses such as their duration of experience, education level, certification status, and so on. Also, theoretically, the observational nature of the current study could be improved by a prospective study involving randomizing patients to shifts with high nurse staffing levels and standard nurse staffing levels, but such a study design may not be practical to implement in reality. Further research is needed to investigate the impact that increasing nurse staffing levels has on pediatric patient fall risk, especially on the night shift for units with high-risk patients.
REFERENCES 1. Paul JA, MacDonald L. Models using the benefits of cross training policies to tackle nurse shortage crisis. Int J Prod Econ. 2014;140:83-95. 2. Brennan CW, Daly BJ, Jones KR. State of the science: the relationship between nurse staffing and patient outcomes. West J Nurs Res. 2013;35: 760-794. 3. Coffman JM, Seago JA, Spetz J. Minimum nurse-topatient ratios in acute care hospitals in California. Health Aff (Project Hope). 2002;21:53-64.
4. Center for Disease Control and Prevention. National Center for Injury Prevention and Control. Web-Based Injury Statistics Query and Reporting System (WISQARS). 2011. http://www.cdc.gov/injury/wisqars. Accessed September 29, 2014. 5. Lancaster AD, Ayers A, Belbot B, et al. Preventing falls and eliminating injury at Ascension Health. Jt Comm J Qual Saf. 2007;33:367-375. 6. Mion LC, Chandler AM, Waters TM, et al. Is it possible to identify risks for injurious falls in hospitalized
Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
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7.
8. 9.
10.
11. 12.
13.
14.
15.
16.
17.
18.
19.
20. 21.
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patients? Jt Comm J Qual Patient Saf. 2012;38: 408-413. Bouldin ED, Andresen EM, Dunton NE, et al. Falls among adult patients hospitalized in the United States: prevalence and trends. J Patient Saf. 2013;9:13-17. Kingston F, Bryant T, Speer K. Pediatric falls benchmarking collaborative. J Nurs Adm. 2010;40:287-292. Jamerson PA, Graf E, Messmer PR, et al. Inpatient falls in freestanding children’s hospitals. Pediatr Nurs. 2014;40:127-135. Cooper CL, Nolt JD. Development of an evidencebased pediatric fall prevention program. J Nurs Care Qual. 2007;22:107-112. Razmus I, Wilson D, Smith R, Newman E. Falls in hospitalized children. Pediatr Nurs. 2006;32:568-572. Lake ET, Cheung RB. Are patient falls and pressure ulcers sensitive to nurse staffing? West J Nurs Res. 2006;28:654-677. Lake ET, Shang J, Klaus S, Dunton NE. Patient falls: association with hospital Magnet status and nursing unit staffing. Res Nurs Health. 2010;33:413-425. Harris A, McGillis Hall L. Evidence to Inform Staff Mix Decision Making: A Focused Literature Review. Report for the Canadian Nurses Association. Ottawa, Canada: Canadian Nurses Association; 2012. Clarke SP, Donaldson NE. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville, MD: Agency for Healthcare Research and Quality; 2008 Chapter 25. Cho SH, Ketefian S, Barkauskas VH, Smith DG. The effects of nurse staffing on adverse events, morbidity, mortality and medical costs. Nurs Res. 2003;52:71-179. McGillis Hall L, Doran D, Pink GH. Nurse staffing models, nursing hours, and patient safety outcomes. J Nurs Adm. 2004;34:41-45. Breckenridge-Sproat S, Johantgen M, Patrician P. Influence of unit-level staffing on medication errors and falls in military hospitals. West J Nurs Res. 2012;34: 455-474. Blegen MA, Vaughn T. A multisite study of nurse staffing and patient occurrences. Nurs Econ. 1998;16: 196-203. Blegen MA, Goode CJ, Reed L. Nurse staffing and patient outcomes. Nurs Res. 1998;47:43-50. Sovie MD, Jawad AF. Hospital restructuring and its
22.
23.
24.
25.
26.
27. 28.
29.
30.
31.
32.
33.
34.
impact on outcomes: nursing staff regulations are premature. J Nurs Adm. 2001;31:588-600. 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;26:87-92. Dunton N, Gajewski B, Taunton RL, Moore J. Nurse staffing and patient falls on acute care hospital units. Nurs Outlook. 2004;52:53-59. Staggs VS, Knight JE, Dunton N. Understanding unassisted falls: effects of nurse staffing level and nursing staff characteristics. J Nurs Care Qual. 2012;27: 194-199. Schubert M, Glass TR, Clarke SP, et al. Rationing of nursing care and its relationship to patient outcomes: the Swiss extension of the International Hospital Outcomes Study. International J Qual Health Care. 2008;20:227-237. Donaldson N, Bolton LB, Aydin C, Brown D, Elashoff JD, Sandhu M. Impact of California’s licensed nursepatient ratios on unit-level nurse staffing and patient outcomes. Policy Polit Nurs Pract. 2005;6:98-210. Unruh L. Licensed nurse staffing and adverse events in hospitals. Med Care. 2003;41:142-152. He J, Dunton N, Staggs V. Unit-level time trends in inpatient fall rates of US hospitals. Med Care. 2012;50: 801-807. Dunton N, Gajewski B, Klaus S, Pierson B. The relationship of nursing workforce characteristics to patient outcomes. Online J Issues Nurs. 2007;12:Manuscript 3. Krauss MJ, Evanoff B, Hitcho E, et al. A case-control study of patient, medication, and care-related risk factors for inpatient falls. J Gen Intern Med. 2005;20: 116-122. Patrician PA, Loan L, McCarthy M, et al. The association of shift-level nurse staffing with adverse patient events. J Nurs Adm. 2011;41:64-70. Kleinbaum DG, Kupper LL, Nizham A, Muller KE. Applied Regression Analysis and Other Multivariable Methods. 4th ed. Boston, MA: Cengage Learning; 2007. Kalisch BJ, Tschannen D, Lee KH. Missed nursing care, staffing, and patient falls. J Nurs Care Qual. 2012;27:6-12. Allison PD. Logistic Regression Using SAS: Theory and Application. Cary, NC: SAS Institute Inc; 2001.
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Lower Nurse Staffing Levels Are Associated With Occurrences of Inpatient Falls at a Large Pediatric Hospital Joseph Hagan, ScD; Angela Jones, MN, RN No previous research has been published regarding the relationship between nurse staffing levels and inpatient pediatric falls, and previous research in the adult population has yielded conflicting results, probably due in many instances to suboptimal study design. The objective of this study was to examine the relationship between nurse staffing levels and pediatric patient falls in a large children’s hospital. A case-control study design was used to compare the nurse staffing level during the shift of patient falls to the staffing level in the same units on shifts when patient falls did not occur. Nurse staffing levels were significantly lower in units when patient falls occurred, particularly during night shift. Targeted nurse staffing interventions in high-risk units could reduce the incidence of inpatient pediatric falls. Key words: case-control study, nurse staffing, patient falls
T
HE COST OF health care is an area of everincreasing concern in the United States. Hospital administrators are always looking for ways to decrease costs while maintaining quality of patient care. Nurse staffing consumes a large proportion of every hospital’s budget, and a shortage of qualified nurses makes appropriately staffing hospitals a challenge.1 Numerous studies have shown a link between nurse staffing and the quality of patient outcomes.2 In the United States in 1999, in an effort to ensure that hospitals maintain an adequate nurse staffing level, the California legislature passed Assembly Bill 394 requiring California’s State Department of Health Services to develop minimum licensed nurse-topatient staffing ratios in acute care hospitals.3 Inpatient falls are considered to be a nursesensitive quality outcome by the National Quality Forum. In acute care hospitals, patient falls
Author Affiliations: Texas Children’s Hospital, Houston, Texas. The authors have no conflict of interest. Correspondence: Joseph Hagan, ScD, Texas Children’s Hospital, Houston, TX ([email protected]). DOI: 10.1097/HCM.0000000000000083
occur more than any other type of adverse event and often result in a longer hospital stay due to complications from the fall.4,5 More than 1 million hospitalized patient falls per year are reported in the United States,6 but the Centers for Medicare & Medicaid Service does not reimburse hospitals for care related to injuries that result from inpatient falls.7 In the pediatric population, the incidence rate of inpatient falls has been observed to range from 0.77 to 1.37 falls per 1000 patient-days, with 32% to 36% of these falls resulting in injury.8,9 The early developmental stage of children renders them susceptible to falling, but physical illness and injury and being in an unfamiliar environment can further increase the probability that a hospitalized child will fall.10 In addition, Razmus et al11 identified episodes of disorientation and a history of falls as factors that increase the risk of falling for hospitalized children. Despite the relatively common incidence of pediatric inpatient falls and the unique risk factors of falling for this population, no published studies could be identified that specifically investigated the relationship between nurse staffing and pediatric falls. Although inpatient falls are considered to be a nurse-sensitive outcome, previous research in the adult population has yielded conflicting 359
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results regarding the relationship between nurse staffing and patient fall risk, with the majority of studies failing to demonstrate a significant relationship between nurse staffing and patient falls.12-14 But as elaborated on below, many of these studies have been limited by poor study design, inappropriate variable measurement, suboptimal sampling methodology, lack of adjustment for confounding variables, and use of hospital-level data that do not capture patient-specific factors at the time of the fall.15 When analyzing observational data from 232 acute care hospitals in California, Cho et al16 found no evidence to support a relationship between nurse staffing and patient falls, although significant associations were found between nurse staffing and odds of pneumonia and pressure ulcers. McGillis Hall et al17 did not observe a relationship between nurse staffing and patient falls in a descriptive correlational study of 19 teaching hospitals. BreckenridgeSproat et al,18 Blegen and Vaughn,19 and Blegen et al20 did not see a relationship between nurse staffing and patient falls when analyzing unit-level data aggregated over 1-month, 1-quarter, and 1-year periods, respectively. On the other hand, Sovie and Jawad21 analyzed data from 29 teaching hospitals summarized over a 1-year period and found that more nursing hours per patient-day (HPPDs) were associated with lower fall rates. To further blur the picture, Staggs and Dunton22 and Dunton et al23 found increased nursing HPPDs to be protective against patient falls only on some types of units, whereas Staggs et al24 made the counterintuitive observation that units with the lowest staffing levels actually had below-average fall rates! Schubert et al25 found no relationship between nurse staffing and falls when analyzing nurse survey data, whereas Donaldson et al26 saw no relationship between staffing level trends and patient fall rates over time in California hospitals. On the other hand, Unruh27 conducted a hospital-level analysis of Pennsylvania hospital data and found that hospitals with more licensed nurses had significantly lower fall rates. He et al28 analyzed hospital data at the unit level in the National Database of Nursing Quality Indicators (NDNQI)
database aggregated over 1-year time intervals and found that higher nursing HPPDs were associated with lower fall rates. Likewise, Dunton et al29 analyzed NDNQI data summarized by quarter at the hospital unit level and concluded that increasing nursing HPPDs corresponded with lower fall rates. The relationships between nursing staffing levels and fall rates observed in all of the aforementioned studies are highly susceptible to confounding due to other factors, because data are aggregated and analyzed over long periods (1 month to 1 year) and therefore are not able to investigate the effects of nurse staffing at the time of the fall. Krauss et al30 did use nurse staffing data at the time of the patient falls; however, their statistical methods did not appropriately accommodate their case-control matching. Patrician et al31 was the only study located, without glaring study design or analytical flaws, that analyzed nurse staffing level data during the actual shift that the patient falls occurred, and this study showed that units with a higher number of nursing hours per patient had a lower risk of patient falls. But this study was conducted among adult patients. Although a recent study concluded that many inpatient pediatric falls are preventable, and nurse vigilance is required to maintain a safe environment, risk factors for pediatric inpatient falls have not been satisfactorily delineated by the relatively small amount of research conducted in the pediatric population.32 We are aware of no prior study showing a relationship between nurse staffing and pediatric inpatient falls. The purpose of this study is to determine if there is a relationship between nurse staffing levels and occurrence of patient falls at a large pediatric hospital. METHODS Effective in 2009, the Texas legislature passed Senate Bill 476, which included the addition of Chapter 257 to the Texas Health and Safety Code requiring hospitals to ‘‘establish a nurse staffing committee’’ whose purpose includes identifying ‘‘the nurse-sensitive outcome measures the committee will use to evaluate the
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Nurse Staffing Levels and Occurrence of Inpatient Falls effectiveness of the official nurse services staffing plan.’’ The data analyzed for the current study were collected as part of the effort to comply with this legislation by using a datadriven evaluation of the relationship nurse staffing and nurse-sensitive outcomes. No a priori power analysis was performed because the data analyzed and presented here are routinely collected on an ongoing basis for quality improvement purposes. The hospital’s institutional research council reviewed and approved the study (protocol 14-912), including dissemination of the results. The requirement for documentation of informed consent was waived because the research posed minimal risk and does involve any procedures that require consent outside the research context. The hospital event reporting system was used to identify all inpatient falls occurring from July 1, 2013, and through March 31, 2014. For all falls reported during this period, the nurse staffing level on the unit during the shift of each patient fall was calculated. The unit’s ‘‘nurse staffing level’’ for the shift was computed as follows: nurse staffing level = (actual number of RNs working on unit during the shift / target number of RNs on unit for the shift) 100%. Units’ electronic staffing logs were used to ascertain the actual number of RNs working on the unit each shift. The target number of RNs is computed by the hospital’s commercial automated patient acuity system, which considers a combination of factors including patient census and patient acuity. Some measure of nurse staffing level when falls do not occur was needed for comparative purposes in order to determine if there is a relationship between nurse staffing level and patient falls. To this end, a case-control study design was implemented, where ‘‘control’’ nurse staffing levels are defined as the nurse staffing level exactly 7 days prior to the actual ‘‘case’’ (fall), on the same unit and same shift as the ‘‘case’’ (fall). Data on patient falls were accumulated from July 1, 2013, through March 31, 2014. Staffing level data for all ‘‘cases’’ and ‘‘controls’’ were entered into an Excel spreadsheet in a format suitable for statistical analysis. The Excel spreadsheet
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was imported into SAS 9.3 (SAS Institute Inc, Cary, North Carolina), which was used for all data analysis. To examine the relationship between nurse staffing and patient falls, a difference in staffing level was computed for each case-control dyad (difference = case staffing level control staffing level). The Wilcoxon signed rank test was used to determine if there is a significant difference between nurse staffing levels when patient falls occurred compared with when patient falls did not occur (ie, cases vs controls). RESULTS There were 111 falls documented, yielding a fall rate of 1.7 falls per 1000 patient-days during the period for which data were available (July 1, 2013, through March 31, 2014). Forty of the 111 falls (36%) resulted in injury, so the injury fall rate was 0.6 injury falls per 1000 patient-days. The greatest number of falls occurred on medical units (Table 1), and physical/ psychological falls were the most common fall category (Figure). The fall categories are defined in Table 2.8 Overall, the mean nurse staffing level was lower when falls occurred compared with control shifts (Table 3). When a stratified analysis was performed to compare the case versus control staffing levels separately on day shift and night shift, on night shift the staffing Table 1. Number and Percentage of Falls Occurring on Each Type of Unit Type of Unit Medical Cardiology Hematology/oncology Neurology Mother baby unit Inpatient rehabilitation Surgery Bone marrow transplant Progressive care Perioperative Short stay observation Cardiovascular intensive care Pediatric intensive care Inpatient research
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n (%) of Falls 21 14 14 12 11 10 8 6 6 2 2 2 2 1
(19) (13) (13) (11) (10) (9) (7) (5) (5) (2) (2) (2) (2) (1)
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Figure. Pareto chart of fall categories observed from July 1, 2013, through March 31, 2014.
level was significantly lower when falls occurred, but on day shift there was not a significant difference in case versus control staffing levels (Table 3). DISCUSSION The present study finds that lower nurse staffing levels are associated with increased incidence of falls among patients at a large pediatric hospital. This relationship was statistically significant when all data combined were analyzed. However, when the analysis was stratified by shift, significantly lower nurse staffing levels were observed when
patient falls occurred on night shift, but the association was not significant for day-shift falls. No previous study has shown such a relationship in the pediatric population. An Ovid MEDLINE search for publications containing the words ‘‘pediatric,’’ ‘‘falls,’’ ‘‘nurse,’’ and ‘‘staffing’’ yielded no matching records. Creative searches using other databases also produced no published studies specifically investigating the relationship between nurse staffing and pediatric inpatient falls. Therefore, the ensuing discussion compares the study design and findings of the present study to published studies in the adult population. The present study is unique in that it uses shift-specific
Table 2. Definition of Fall Categories Fall Category
Definition
Developmental Environmental Family attentiveness
Horseplay Modesty Other Physical/psychological Response to treatment Unknown
Fall common to toddlers (1-4 y of age) learning to walk, pivot, or run Fall resulting from a contribution of the environment or equipment Fall resulting from lack of family member attentiveness. Only used if a family member is present and could have reduced fall risk, and the fall is not described by any other category Fall associated with rough play activity (eg, running, wrestling, climbing, or jumping) Fall related to not seeking assistance due to modesty or desire for privacy Unique fall not described by another category Fall related to new or previously diagnosed seizures, developmental delay, confusion, or occurring during physical therapy due to known unsteady gait Fall resulting from response to surgery, medication, or medical intervention Not enough detail to categorize the fall
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Nurse Staffing Levels and Occurrence of Inpatient Falls Table 3. Comparison of Nurse Staffing Levels for Cases and Controls on the Day Shift, Night Shift, and Overall for Both Shifts Combined
Mean Staffing Level Shift Day Night Overall
n
Shift of Fall
Control Shift
64 47 111
98.3% 100.4% 99.2%
100.3% 106.5% 102.9%
Mean Difference 2.0% 6.1% 3.7%
P 0.172 0.010a 0.007a
a
Indicates a statistically significant difference ( = .05).
nurse staffing levels to demonstrate an inverse relationship between nurse staffing level and occurrence of falls among hospitalized pediatric patients. Cho et al16 did not find a relationship between nurse staffing level and patient falls when analyzing 2 existing databases. A recent study by Staggs and Dunton22 found a statistically significant inverse relationship between nursing HPPDs and fall risk on medical-surgical units, but no significant relationship on surgical or rehabilitation units. This study quantified RN HPPDs ‘‘as the sum of nursing care hours provided by RNs during the month divided by the sum of the unit’s patient-days for the month.’’ This metric does not quantify the nurse staffing at the time of the fall, unlike the nurse staffing level measure used in the current study. McGillis Hall et al17 did not find a significant relationship between nurse staffing and risk of falls in adult patients. But McGillis Hall et al17 quantified patients’ nursing resource use as ‘‘unit producing personnel,’’ a metric that includes the sum of all paid nursing hours allocated to a patient—which again does not provide information about nurse staffing at the time of the falls. In an indirect examination of the relationship between nurse staffing level and patient falls, Donaldson et al26 observed a significant increase in the total number of nursing HPPDs in 200 units from 68 California hospitals in 2004 compared with 2002, but the rate of falls (and injury falls) did not change significantly. Blegen et al20 fit 4 linear regression models to examine the relationship between independent variables including nursing HPPDs and adverse patient outcomes including patient falls. They used unit-level data averaged over an entire year
and concluded that ‘‘rates of patient falls were not explained well by any of the models.’’ Obviously, in this study, measurement of neither the independent variables (eg, nursing HPPDs on the unit over the year) nor the dependent variables (eg, patient fall rate on the unit over the year) facilitated investigation of the relationship between fall risk and nurse staffing levels at the time of the patient falls. In addition, Poisson regression would be the appropriate statistical method to use, rather than linear regression, when the objective is to fit a statistical model for which the dependent variable is a rate.32 Although Breckenridge-Sproat et al18 initially obtained data on the number of nursing HPPDs on the unit during the shift when falls occurred, the nursing HPPD data used for their statistical analysis were ‘‘aggregated to the month level for each unit, resulting in a total number of 833 ‘unit-months’,’’ and the relationship between nursing HPPDs and fall rate was examined using these 833 data points. Thus, a direct comparison of the nurse staffing level on the shifts when falls occurred to the shifts when falls did occur was not made, which might explain why Breckenridge-Sproat et al18 did not find a relationship between units’ number of nursing care HPPDs and the fall rate. On the other hand, the current study uses staffing level measurements from the shift during which the falls actually occurred. This improvement in nurse staffing level assessment could be the reason for the observed relationship between nurse staffing and patient falls achieving statistical significance in the present study, in contrast to the aforementioned studies’ nonsignificant findings. Lake and Cheung12 identified 8 studies examining the relationship between nurse staffing
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THE HEALTH CARE MANAGER/OCTOBER–DECEMBER 2015
and patient falls, only 2 of which yielded statistically significant results. It should be noted that 2 of these 8 studies—and 1 of the 2 studies27 showing statistical significance—were conducted at the hospital level, which greatly limits the ability to make inference about the relationship between nurse staffing and risk of patient falls, because information about the nurse staffing exposure for the particular patient who fell is not used. Schubert et al25 did not find a significant relationship between nurse staffing and patient falls, but for this study, patient falls were ascertained by a survey asking nurses if any of their patients had fallen over the past year. Similarly, their nurse staffing data were derived from a survey of nurses. The use of surveys to measure the explanatory variables and the outcome introduces the possibility of recall bias and other sources of bias due to the subjectivity of nurses’ self-reports. There have been a few studies demonstrating a statistically significant association between nurse staffing level and patient falls. Kalisch et al33 and Sovie and Jawad21 found that a lower number of nursing hours was associated with a higher unit fall rate, but the former study aggregated each unit’s data by month, whereas the latter study aggregated data by year. Thus, even though these studies conclude that there is a statistically significant inverse relationship between nurse staffing and risk of falls, the findings are not very compelling because the association could be explained by unobserved confounding variables because staffing levels at the time of the fall were not used in the analysis. Krauss et al30 is one of the rare studies that analyzed nurse staffing data from the actual time of patient falls, but they used logistic regression to quantify the association between patient-to-nurse staffing levels and odds of patients’ falling. This statistical method ignores the case-control pairing implemented for the study and could therefore yield biased results.34 Patrician et al31 is the only study located that measured and appropriately analyzed hospital units’ nurse staffing level each shift, and they found that the risk of falls increased significantly as the number of nursing HPPDs on a shift decreased, but the study of Patrician
et al31 was conducted among adults, so the present study was needed to investigate the pediatric population. Like the current study, Patrician and colleagues’ study design provides more credible inference that nurse staffing levels affect the risk of patient falls. He et al28 and Dunton et al23,29 found a significant negative relationship between the total number of nursing hours and patient fall rates when analyzing data in the NDNQI. But surprisingly, Staggs et al24 analyzed monthly unit-level data from the NDNQI and concluded that ‘‘units at the very lowest staffing levels tended to have lower fall rates than most units with staffing levels above the median.’’ Counterintuitive findings such as this illustrate the need to cautiously interpret results obtained from the analysis of large databases not designed for the specific purpose of the research study, particularly when data around the time of the fall are not analyzed. These studies using unit-level data summarized over a period (eg, a month) are susceptible to misleading results due to the ecological inference fallacy, because summary data were used to quantify nurse staffing levels rather than measuring the nurse staffing level exposure of the specific patients who fell and did not fall. The ecological inference fallacy results from using aggregated data to make inference about individuals. For example, with regard to the aforementioned studies that used unit-level data summarized by month, it is possible that hospital units with higher nurse staffing levels during a given month also provided other new resources or implemented interventions that might reduce patient fall risk, and the observed reduction in patient falls is actually due to the other resources/interventions rather than nurse staffing. Using a research study design similar to the current study where shift-specific staffing levels are obtained for cases and controls from the same hospital unit 1 week apart will eliminate these confounding effects and isolate effects due to the nurse staffing level, because the case and control shifts would both be exposed to the new resources and interventions. It is hoped that the previously mentioned critique of previous investigations of the relationship between nurse staffing and patient
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Nurse Staffing Levels and Occurrence of Inpatient Falls falls does not appear overly disparaging. The limitations of these studies illustrate the logistical difficulties involved with developing a valid study design to investigate the hypothesized association. Because patient falls occur at a discrete time and place, ideally nurse staffing data for the specific time and place of the fall should be analyzed, but the challenge is to obtain comparable nurse staffing data when falls do not occur. The case-control study design used for the current study allowed the analysis of nurse staffing level data from the specific shift when falls occurred, and matched control data were obtained from the same unit on the same shift exactly 1 week prior when a fall had not occurred, thereby avoiding susceptibility to confounding factors that could have biased results from the other studies discussed previously. Although nursing staff at the hospital expressed skepticism about the meaningfulness of the automated target staffing level calculations obtained from the patient acuity system, the validity of the absolute nurse staffing level measurements derived from these calculations is not relevant to the data analysis used for the current study, because only the relative differences between case and control staffing levels are considered. Also, the data analysis is quite robust to extreme values of nurse staffing levels because it uses a nonparametric statistical method that evaluates differences in terms of ranks rather than actual staffing level values, thereby avoiding the need to assume that the case-control differences in staffing levels are normally distributed—an assumption that underlies standard parametric statistical methods. The stronger relationship between nurse staffing level and patient falls observed during
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the night shift is interesting. Perhaps a reduced presence of visitors to watch children during the night explains the observed increased incidence of falling when nurse staffing levels are low at night, while the same relationship is not as consistently observed during the day shift. Sedation of patients at night could also have been a factor for some falls, although the possible influence of sedation was not investigated. Although increasing nurse staffing levels would appear to be the obvious solution, common sense dictates that there should be a threshold of nurse staffing ‘‘saturation,’’ beyond which more nurses will not reduce the risk of falling, but further research is needed to elucidate how to identify that threshold for nursing staff caring for a specific patient population. Also, certain interventions such as hourly nurse rounding, which was not being implemented at the institution during the timeframe of the current study, could potentially help to reduce patient fall risk. A limitation of the current study is that it merely considers the effect of the number of nurses working, but does not account for the characteristics of the nurses such as their duration of experience, education level, certification status, and so on. Also, theoretically, the observational nature of the current study could be improved by a prospective study involving randomizing patients to shifts with high nurse staffing levels and standard nurse staffing levels, but such a study design may not be practical to implement in reality. Further research is needed to investigate the impact that increasing nurse staffing levels has on pediatric patient fall risk, especially on the night shift for units with high-risk patients.
REFERENCES 1. Paul JA, MacDonald L. Models using the benefits of cross training policies to tackle nurse shortage crisis. Int J Prod Econ. 2014;140:83-95. 2. Brennan CW, Daly BJ, Jones KR. State of the science: the relationship between nurse staffing and patient outcomes. West J Nurs Res. 2013;35: 760-794. 3. Coffman JM, Seago JA, Spetz J. Minimum nurse-topatient ratios in acute care hospitals in California. Health Aff (Project Hope). 2002;21:53-64.
4. Center for Disease Control and Prevention. National Center for Injury Prevention and Control. Web-Based Injury Statistics Query and Reporting System (WISQARS). 2011. http://www.cdc.gov/injury/wisqars. Accessed September 29, 2014. 5. Lancaster AD, Ayers A, Belbot B, et al. Preventing falls and eliminating injury at Ascension Health. Jt Comm J Qual Saf. 2007;33:367-375. 6. Mion LC, Chandler AM, Waters TM, et al. Is it possible to identify risks for injurious falls in hospitalized
Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
366
7.
8. 9.
10.
11. 12.
13.
14.
15.
16.
17.
18.
19.
20. 21.
THE HEALTH CARE MANAGER/OCTOBER–DECEMBER 2015
patients? Jt Comm J Qual Patient Saf. 2012;38: 408-413. Bouldin ED, Andresen EM, Dunton NE, et al. Falls among adult patients hospitalized in the United States: prevalence and trends. J Patient Saf. 2013;9:13-17. Kingston F, Bryant T, Speer K. Pediatric falls benchmarking collaborative. J Nurs Adm. 2010;40:287-292. Jamerson PA, Graf E, Messmer PR, et al. Inpatient falls in freestanding children’s hospitals. Pediatr Nurs. 2014;40:127-135. Cooper CL, Nolt JD. Development of an evidencebased pediatric fall prevention program. J Nurs Care Qual. 2007;22:107-112. Razmus I, Wilson D, Smith R, Newman E. Falls in hospitalized children. Pediatr Nurs. 2006;32:568-572. Lake ET, Cheung RB. Are patient falls and pressure ulcers sensitive to nurse staffing? West J Nurs Res. 2006;28:654-677. Lake ET, Shang J, Klaus S, Dunton NE. Patient falls: association with hospital Magnet status and nursing unit staffing. Res Nurs Health. 2010;33:413-425. Harris A, McGillis Hall L. Evidence to Inform Staff Mix Decision Making: A Focused Literature Review. Report for the Canadian Nurses Association. Ottawa, Canada: Canadian Nurses Association; 2012. Clarke SP, Donaldson NE. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville, MD: Agency for Healthcare Research and Quality; 2008 Chapter 25. Cho SH, Ketefian S, Barkauskas VH, Smith DG. The effects of nurse staffing on adverse events, morbidity, mortality and medical costs. Nurs Res. 2003;52:71-179. McGillis Hall L, Doran D, Pink GH. Nurse staffing models, nursing hours, and patient safety outcomes. J Nurs Adm. 2004;34:41-45. Breckenridge-Sproat S, Johantgen M, Patrician P. Influence of unit-level staffing on medication errors and falls in military hospitals. West J Nurs Res. 2012;34: 455-474. Blegen MA, Vaughn T. A multisite study of nurse staffing and patient occurrences. Nurs Econ. 1998;16: 196-203. Blegen MA, Goode CJ, Reed L. Nurse staffing and patient outcomes. Nurs Res. 1998;47:43-50. Sovie MD, Jawad AF. Hospital restructuring and its
22.
23.
24.
25.
26.
27. 28.
29.
30.
31.
32.
33.
34.
impact on outcomes: nursing staff regulations are premature. J Nurs Adm. 2001;31:588-600. 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;26:87-92. Dunton N, Gajewski B, Taunton RL, Moore J. Nurse staffing and patient falls on acute care hospital units. Nurs Outlook. 2004;52:53-59. Staggs VS, Knight JE, Dunton N. Understanding unassisted falls: effects of nurse staffing level and nursing staff characteristics. J Nurs Care Qual. 2012;27: 194-199. Schubert M, Glass TR, Clarke SP, et al. Rationing of nursing care and its relationship to patient outcomes: the Swiss extension of the International Hospital Outcomes Study. International J Qual Health Care. 2008;20:227-237. Donaldson N, Bolton LB, Aydin C, Brown D, Elashoff JD, Sandhu M. Impact of California’s licensed nursepatient ratios on unit-level nurse staffing and patient outcomes. Policy Polit Nurs Pract. 2005;6:98-210. Unruh L. Licensed nurse staffing and adverse events in hospitals. Med Care. 2003;41:142-152. He J, Dunton N, Staggs V. Unit-level time trends in inpatient fall rates of US hospitals. Med Care. 2012;50: 801-807. Dunton N, Gajewski B, Klaus S, Pierson B. The relationship of nursing workforce characteristics to patient outcomes. Online J Issues Nurs. 2007;12:Manuscript 3. Krauss MJ, Evanoff B, Hitcho E, et al. A case-control study of patient, medication, and care-related risk factors for inpatient falls. J Gen Intern Med. 2005;20: 116-122. Patrician PA, Loan L, McCarthy M, et al. The association of shift-level nurse staffing with adverse patient events. J Nurs Adm. 2011;41:64-70. Kleinbaum DG, Kupper LL, Nizham A, Muller KE. Applied Regression Analysis and Other Multivariable Methods. 4th ed. Boston, MA: Cengage Learning; 2007. Kalisch BJ, Tschannen D, Lee KH. Missed nursing care, staffing, and patient falls. J Nurs Care Qual. 2012;27:6-12. Allison PD. Logistic Regression Using SAS: Theory and Application. Cary, NC: SAS Institute Inc; 2001.
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