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Characteristics of the middle-age adult inpatient fall
Applied Nursing Research 31 (2016) 65–71
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Original Article
Characteristics of the middle-age adult inpatient fall Donna Guillaume, PhD, RN a,⁎, Sybil Crawford, PhD, MS b, Patricia Quigley, PhD, MPH c a b c
Graduate School of Nursing, University of Massachusetts, 55 Lake Ave North, Worcester, MA, 01655, USA Division of Preventive and Behavioral Medicine, Department of Medicine, and Graduate School of Nursing, University of Massachusetts, 55 Lake Ave North, Worcester, MA, 01655, USA VISN 8 Patient Safety Center of Inquiry, James A. Haley VAMC, Tampa, FL, 33637-1022, USA
a r t i c l e
i n f o
Article history: Received 3 October 2015 Revised 24 December 2015 Accepted 14 January 2016 Available online xxxx Keywords: Falls Middle-age Inpatient Comorbidities Risk factors
a b s t r a c t Purpose: The purpose of this study is to describe characteristics of middle-age inpatients' (ages 45–64) fallers and their fall and fall injury risk factors. Background: Middle-age falls were 42–46% of inpatient falls. Studies related to inpatient falls have not targeted this population. Methods: A 439 retrospective chart review was performed. Middle-age fall and injury rates were compared with ages 21–44 and 65–90. Results: The mean age was 55.75 years (SD 5.26). 28.7% (n = 126) of falls resulted in injury. Individual fallers (n = 386) had a mean of four comorbidities (SD 1.843), including hypertension (46.5%), anxiety/depression (40.2%), and alcohol and drug abuse (32.9%). There was no significant difference (p = .637) in fall rates per 1,000 patient days between ages 45–64 and 65–90. Conclusion: Middle-age inpatients' acute illness makes them as vulnerable for fall and injury as the older population. They should not be overlooked for fall prevention measures. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Falls with injuries remains one of the most reportable, serious, and costly type of adverse events that occur in United States (U.S.) hospitals, resulting in detrimental morbidity and mortality outcomes (Agency for Healthcare Research and Quality (AHRQ) [AHRQ], 2012; Centers for Medicare and Medicaid Services (CMS) [CMS], 2012; Mion et al., 2012; Oliver, Healey, & Haines, 2010; Quigley & White, 2013). In acute care hospitals, an estimated 1,000 falls occur per hospital each year regardless of size, with over one million inpatient falls reported annually at the national level (Oliver et al., 2010; Shorr et al., 2008). Inpatient injuries also occur in 30–51% of all fall-related events (Bradley, Karani, McGinn, & Wisnivesky, 2010; Oliver et al., 2010; Quigley & White, 2013). The hospital care provided as a result of an inpatient fall has been reported at an estimated cost of $3,500 for a non-injury to $27,000 for a single serious injury (Apold & Quigley, 2012; Halm & Quigley, 2011; Quigley & White, 2013). National agencies such as the National Quality Forum (NQF), the Joint Commission, and the CMS have identified falls as a major quality concern that should not occur during hospitalizations (Quigley & White, 2013). The Joint Commission (2015) found that an inpatient fall with injury or death was the second most frequently reviewed ⁎ Corresponding author at: 267 Rumonoski Drive, Northbridge, Massachusetts, 01534. Tel.: +1 508 736 9137 (Mobile); fax: +1 774 443 7373. E-mail addresses: [email protected], [email protected] (D. Guillaume). http://dx.doi.org/10.1016/j.apnr.2016.01.003 0897-1897/© 2016 Elsevier Inc. All rights reserved.
sentinel event in 2014. Falls were also noted as the leading reported adverse event in the hospital setting (Spoelstra, Given, & Given, 2012). 2. Background and Significance Although it has been well documented that inpatients age 65 and older are at greater risk for falls and injury, middle-age adults (45–64 years of age) have been noted recently to have higher fall rates (Mion et al., 2012; Williams, Szekendi, & Thomas, 2014). In their seminal study, Hitcho et al. (2004) revealed that of 183 adult inpatients who fell, 47% (n = 86) were under age 65. The recent fall study by Williams et al. (2014) also identified that middle-aged inpatients 51–60 years old (n = 5,561) had the highest reported fall rates, followed by patients age 61–70 years (n = 4,699). The middle-age population, according to the U.S. Census Bureau, makes up 27% of the inpatient census, which has increased by 31% since the 2000 census (U.S. Census Bureau, 2012). The National Health Interview Survey (NHIS) 2004–2007 report, which looked at selected health characteristics of adults over age 55, found that 22.9% were identified as in fair-to-poor health; including 19.6% age 55–64 (Schoenborn & Heyman, 2009). Fall monitoring at one academic teaching hospital in Central Massachusetts supported these similar findings by noting that 42% of inpatients who fell were between the ages of 45 and 64. In addition, the randomized control trial of Dykes et al. (2010), using an electronic fall prevention toolkit (FPTK) with 192 patients, revealed that those in the middle-age group were less likely (p = .003) to adhere to the recommended fall prevention interventions. While predictors of falls and
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injuries have been studied across all adult inpatients (Mion et al., 2012; Oliver et al., 2010), research has not specifically addressed the fall risk characteristics in the middle-age. This knowledge will be important for informing nursing and the multidisciplinary team's decisions on implementation of interventions for fall and injury prevention in this age group. 3. Purpose of the Study
The multifactorial and interactive nature of these fall risk factors increases the risk of a patient fall and the potential for injury. Our adapted framework suggests also that Fawcett's (1984) metaparadigm of nursing be used as the foundation for nursing and the multidisciplinary team identification and prevention for falls and associated injuries.
5. Study Design and Methods
The purpose of this study was to describe the characteristics of middle-age adult inpatients' that fall, along with their fall and fall injury risk factors. The aims were to (a) describe falls and fall injury risk factors; (b) describe unit-specific data, fall numbers with type of falls, injuries from falls, and prevention strategies; and (c) compare the incidence of fall and fall injury rates of the middle-age (45–64) patients with the hospital adult age groups (21–44 and 65–90). 4. Conceptual Framework The study framework (see Fig. 1) was adapted from the World Health Organization's (WHO), “Risk factor model for fall in older age,” The WHO Global Report on Fall Prevention (WHO, 2007). This framework was adapted with permission for use in the inpatient setting. Extrinsic and intrinsic variables from four risk factor groupings of biological, socioeconomic, behavioral, and environmental and their related outcomes were used to describe characteristics of the middleage inpatient's fall and fall injury risk. Demographics and characteristics from an earlier prospective descriptive study of inpatients from ages 17–96 by Hitcho et al. (2004) were used for identification of variables to collect in the four risk factor groupings.
5.1. Design This study was a secondary analysis of falls that occurred between January 1, 2012 and July 31, 2014. The retrospective review took place August 1, 2014–December 31, 2014. The research took place in a large academic teaching hospital in Central Massachusetts and used incident-reporting data, electronic medical records (EMR), and hospital staffing and financial data. The conceptual framework was used to identify the discrete variables collected for aims 1–3 (Fig. 1). This academic teaching hospital has about 36,690 hospital discharges yearly, with an average daily inpatient adult census of 404 patients. For this study, patient falls were reported from adult medical (n = 6), surgical (n = 4), mixed medical/surgical (n = 4), critical care (n = 8), and other specific type units (n = 4) such as post-anesthesia care, procedural areas, and the emergency department (ED).
5.2. Protection of human subjects Institutional review board (IRB) approval was obtained prior to conducting the study.
RISK FACTOR MODEL FOR INPATIENT FALLS Health
Biological Risk Factors
Environment Risk Factors Wet, Ripped Floors Lighting Clutter Commodes Time of Day Location Activity
Outcomes Fall Rates, Age, Unit Interventions Types of Fall Accidental, Anticipated Physiological Unanticipated Physiological
Level of Injury
Socioeconomic Risk Factors Marital Status Language Insurance Type
Patient
Environment
Age, Gender, Race Comorbidities, Surgery Chronic Illness Cognitive, Dizziness Mobility, Balance Elimination Needs Medication
None, Minor Moderate, Major, Death
Behavioral Risk Factors Alcohol/Drug Use Call Light Footwear History Previous Falls Physical Limitations Autonomy
Nursing & Multidisciplinary Team
Fig. 1. Risk factor model for inpatient falls. Adapted with permission from the World Health Organization (WHO) (WHO), 2007.
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5.3. Sample Included in the study sample were middle-age inpatients (45–64) who fell either one-time or had a repeat fall during the study period. A repeat fall may have occurred during the same admission or during another admission in the study period. Exclusion criteria included (a) an adult patient fall on a psychiatric unit; (b) an adult patient fall during an outpatient appointment in the ambulatory department; and (c) a fall by visitors, students, and staff members. 5.4. Data collection Patient falls that met study criteria between August 1, 2014 and December 31, 2014 were identified through querying of the hospital incident-reporting database. Falls were reported by clinical staff using an incident report form that is entered into a secured risk-management database. Data not captured in the incident-reporting database were collected through additional retrospective EMR chart review. If additional falls that met study criteria were identified during this review, those falls were also included in the study. The principal investigator (PI) performed the data collection and data cleaning throughout the study. The PI who was familiar with hospital incident reports on falls had a strong clinical background related to patient safety and navigation of the EMR. Data were downloaded into an EXCEL sheet. Each variable collected was reviewed manually for accuracy using the EMR, and missing data elements were extracted if available. For aim 3, data were queried from the hospital analytic database sets to determine census and 1,000 patient days. The fall occurrence data sets were used to compare fall and fall injury rates of inpatients identified in the middle-age population (45–64) with fallers in age groups of 21–64 and 65–90. This resulted in a slight disparity from the retrospective chart review of aims 1 and 2. 5.4.1. Fall event To determine what is a fall, the National Database of Nursing Quality Indicators® (NDNQI®;, 2013) description of a fall was used: “An unintentional descent to the floor or extension of the floor with or without injury, including assisted falls and physiological falls (i.e., fainting)” (NDNQI, p. 2). Falls also included patients found on the floor or who self-reported a fall. For this study, a fall may have occurred in areas outside of the nursing unit (e.g., emergency department, bone marrow unit, radiology, surgical admissions). The type of fall as defined by Morse (1997) was classified as either accidental, anticipated physiological, or unanticipated physiological. Accidental falls occur due to environmental extrinsic risk factors, often where the patient may not have been identified at risk to fall (e.g., trip or slip on the floor, or fall out of bed when reaching for an object). Anticipated physiological falls may result from known intrinsic (i.e., altered gait and balance, impaired vision, multiple diagnoses) and extrinsic (i.e., medications and IVs) risk factors. Unanticipated physiological falls are from unexpected medical conditions such as heart attack, fainting, or seizure, and are considered unpreventable (Morse, 1997). The Morse Fall Scale (MFS) screening tool was used by the organization to identify the risk of an anticipated physiological patient fall. Through use of this validated scale used for fallers and non-fallers, patients were screened based on six risk factors: history of falling, secondary diagnosis, ambulatory aide, IV therapy/heparin lock, gait, and mental status. A score based on outcome helped to identify the level of risk for one type of fall, anticipated physiological fall (b25 low risk; 25–45 moderate risk; and N 45 high risk; Morse, Morse, & Tylko, 1989). The MFS result documented closest to the time before the fall was used in this study. Kim, Mordiffi, Bee, Devi, and Evans (2007) evaluated the validity of the MFS. Their studies of various populations showed a predictive validity sensitivity that ranged between 72% and 83%, a specificity range between 29% and 83%, and inter-rater reliability
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of 96%. A consensus validation process to correlate actual fall risk factors to the actual fall event was performed to determine type of fall. 5.4.2. Fall injury When a fall occurs, depending on the severity of injury, it can change a patient's recovery and discharge. The NDNQI (2013) identified injuries based on five categories as follows: none (e.g., no injury reported, includes diagnostics test to rule out injury); minor (e.g., pain, abrasion, bruises); moderate (e.g., muscle/joint strain requiring splinting, laceration requiring suturing, staples, or steri-strips); major (e.g., fractures where treatment included surgery, casting, traction, internal head injury); and death (falls that result in death due to the trauma of the fall, not including patients who died due to their initial diagnosis; NDNQI, 2013, pp. 5–6). Halm and Quigley (2011) recommended a population-specific approach to identify fall injury. The screening tool referred to as “A, B, C, S” factors (age, ≥85 years or frailty not applicable for this study; bones/fracture risk or history; anticoagulated or bleeding disorder; and post-surgery) was reviewed to capture if patients had increased risk for injury when a fall occurred. 5.5. Data management and analysis line All data were de-identified and exported into IBM© SPSS v21 data software for analysis. Characteristics of the 386 fallers and of the 495 individual falls, including all falls per patient, were summarized. Descriptive statistics for categorical variables included frequencies, mean, standard deviation, median and range, and crosstabs to describe relationship of age with other study variables. Variables included fall and injury rates, level of injury prevention interventions, and type of falls. To examine shift-related differences in falls, a chi-square test assessed whether the observed number of falls in each of the three shifts differed significantly from the null distribution of equal numbers of falls in each shift. Similarly, chi-square tests were used to determine whether observed distributions of falls across gender differed significantly from corresponding distributions of all patient days across gender. The proportion of falls resulting in an injury was compared for the three age groups using chi-square testing as well. Poisson regression was used for comparing rates of falls per 1,000 patient days across units in mid-aged patients, and across the three age groups (21–44, 45–64, and 65–90). 6. Results 6.1. Population A total of 444 individual falls based on the study criteria were identified in the hospital-occurrence database. The EMR review identified nine falls not meeting study eligibility criteria. Falls removed from the study included incorrect age (n = 2), same fall reported twice (n = 2), and not meeting location criteria (n = 5). During the EMR review, four additional falls were identified as repeat falls that had not been reported, and were then added to the study sample. This resulted in a final sample of 439 inpatient falls. Of the 439 falls reviewed, 94 (21.4%) falls were repeat falls including 32 as repeat for the same admission and 21 as repeat for a different admission. There were 386 unique inpatients that experienced a fall. Of this population, 41 unique inpatients had repeat falls either during the present admission or in future admissions during the study time period. The number of repeat inpatient falls included the majority (n = 36) with two falls. Five different inpatients incurred a range from three to six repeat falls. The 439 falls were evenly distributed over the 2.5 year calendar year (CY) period of time: 2012–2014. 6.2. Characteristics of individual fallers and falls Table 1 shows the demographics and characteristics specific to the 386 individual middle-age inpatients that fell. The characteristics
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Table 1 Frequency distribution of demographics and study variables.
Table 2 Description of fall.
Demographics/Variables
N = 386 individual patients
Variable
Male Female Non-Hispanic Marital status Single/Separated/Divorced/Widow Married/Living as married Insurance status Private Federal/State State Uninsured Other (automobile, workers comp) Admit diagnosis⁎ Respiratory a Cancer b ETOH/Drugs Sepsis c Cardiac d Ortho e Admit chief complaint⁎ AMS GI f Respiratory Fall Cardiac Neuro g Admit comorbidities⁎ HTN Anxiety/Depression ETOH/Drugs Diabetes Cardiac Respiratory Discharge status Rehab/Facility Home with services Home no services Other Death
223 (58%) 163 (42%) 362 (94%; missing data = 2)
⁎Age (years) mean = 55.75 (SD 5.26) 45–49 50–54 55–59 60–64 Male Female Characteristic Alert & oriented MFSa Void at night Abnormal gait MFSa Fall history 3 months Assistive devices MFSa Confused at time of fall Dizzy at time of fall Area of fall Inpatient room Bathroom Other (hallway, procedure area) In patient room Found on floor From chair From commode Patient room (patient reported) Fell OOB b Reported activity Walking Getting OOB Lost balance Reaching Incontinent Urinal 24 hours after procedure Within 4 hours of transfer Gait Normal Weak Impaired Non-ambulatory Last toileted b15 min 16–60 min 1–2 hr N2 hrs Catheter/Incontinence Medications None Narcotic/Sedative Anti-psych Lax/Diuretic Relief chemo SX c
252 (65%) 134 (35%) 122 (32%) 123 (32%) 114 (30%) 19 (5%) 8 (2%) 43 (11%) 42 (10%) 37 (10%) 37 (10%) 31 (8%) 28 (7%) 59 (15%) 52 (14%) 46 (12%) 33 (9%) 29 (8%) 27 (7%) 178 (46%) 155 (40%) 127 (33%) 110 (29%) 98 (25%) 90 (23%) 173 (45%) 101 (26%) 68 (18%) 28 (7%) 16 (4%)
Note. Percentages do not total 100%, due to rounding. Discharge status: Other: NH, Psych, VA, Hosp. Group Home, Hospice and Other Hospital. No deaths were from a fall. ⁎ The six most frequently identified variables were identified. Included but not limited to each category: a Asthma, bronchitis, cardiopulmonary disease (COPD), lobe infiltrate, pneumonia. b Brain, breast, lung myleoma, spine, stem cell, thyroid. c Bacteremia, blood stream, C-difficile, meningitis septic. d Chest pain, congestive heart failure (CHF), coronary artery disease (CAD), myocardia infraction (MI). e Abnormal gait, amputation, arthroplasty, fractures, knee replacement. f Bowel obstruction, colitis, diarrhea, dysphagia, diverticulitis, nausea, vomiting. g Aphasia, altered mental status, cerebral aneurism, dizziness, Guillain Barre, seizure, stroke, syncope, numbness, tingling.
include the top six admitting diagnoses; chief complaints, comorbidities, and discharge status. Of the 386 inpatients, 94% (n = 362) were Caucasian, the remaining 6% identified were 5.6% (n = 22) Hispanic, 2% (n = 8) African, and 5.9% (n = 23) other. Only 3.1% (n = 12) of this population were hospitalized for elective admissions, and a small percentage (17.6%, n = 68) were discharged home with no services. Characteristics of the 439 total falls are shown in Table 2. The majority of the 439 falls, 85.9% (n = 377) were screened as anticipated physiologic falls (including behavior-related falls), followed by 10.7% (n = 47) accidental falls, and 3.4% (n = 15) as unanticipated physiologic falls, and 5.8% (n = 22) were not screened for a risk score. Of the 377 anticipated physiologic falls, using the MFS, nurses rated 66.3% (n = 250) inpatients as either high risk (48%, n = 181) or medium risk (18.3%, n = 69) to fall. Of the 439 individual falls recorded, 28.7% (n = 126) resulted in some level of injury from minor (21.8%, n = 96), moderate (5.9%, n = 26), and major that resulted in four (1%) fractures that included rib, ankle, fibula, and hip. Of the four falls resulting in major injuries,
Value, N = 439 56 (13%) 131 (30%) 120 (27%) 132 (30%) 251 (57%) 188 (43%) 232 (52.8%; missing data =11) 226 (51.5%; missing data = 60) 224 (51%; missing data = 33) 131 (30%; missing data = 50) 76 (34%) 33 (8%) 12 (3%) 296 (67%) 127 (29%) 16 (4%) 193 (44%) 42 (10%) 28 (6%) 22 (5%) 21 (5%) 84 (19%) 73 (17%) 61 (14%) 26 (6%) 12 (3%) 11 (3%) 57 (13%) 25 (8%) 182 (42%) 126 (29%) 78 (18%) 20 (5%) 78 (18%) 99 (23%) 142 (32%) 51 (12%) 66 (15%) 314 (72%) 72 (16%) 24 (6%) 22 (5%) 6 (1%)
Note. “Found on floor” no documentation where fall was initiated. Missing variables: gait n = 33 (8%), toileting n = 3 (0.7%). Percentages do not total 100% due to rounding. Narcotics/Sedative: Oxycodone, Dilaudid, Percocet, Morphine, Haldol, Phenobarbital; antipsych: Valium, Ativan, Effexor, Zyprexa; laxative/diuretic: Lactose, Colace, Dulcolax, Lasix. ⁎ NEISS. (2001–2013). Patient room (either reported/assisted falls). a Variable identified using MFS (Morse Fall scale. b OOB (out of bed). c SX (symptoms).
three were by females. Although 70.6% (n = 310) of the falls that occurred lacked an inpatient screening of “A, B, C, S” for risk of injury, of the inpatient falls screened 23.5% (n = 103) of the fallers were identified as on anticoagulation, 8.7% (n = 38) at risk due to surgical procedures, and 2.3% (n = 10) were identified with fracture risk/bonerelated problems. The majority (67.4%) of middle-age inpatient falls occurred in the patient's room, followed by 28.9% in the patient's bathroom, with a small percentage (3.6%) occurring in the hallway or other areas (see Table 2). An abnormal gait was identified by the MFS screening in 51% (n = 224) of the falls and 52.8% (n = 232) of the fallers were identified as alert and oriented to person, place, and time. Of these falls, 58.9%
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(n = 259) of the patients were last toileted more than an hour prior to the fall. In 71.5% (n = 314) of falls there were no documented narcotics, sedatives, laxatives, diuretics, or anti-psychotic medications 4–6 hours before the fall (see Table 2). A somewhat higher percentage of falls occurred in the evening and night shifts (37.6% and 32.6%, respectively) than in the day shift, although this breakdown was not statistically significantly different from equal proportions in each shift (p = .131). The mean number of days to fall after admission was 8.22 days (SD 9.91) with a median of 5.00 days (range 1–90). The total length of stay (LOS) of the patients who fell was a mean of 17.70 days (SD 35.35) with a median of 10 days (range of 1–390 days). Reported falls included 87.7% (n = 385) as unwitnessed and 4.8% (n = 21) as self-reporting or claiming not falling but “sat down,” or “was doing push-ups,” or “praying.” 6.3. Unit-type fall rate Fall rates per 1,000 patient days were slightly higher on medical surgical floors at 2.63, followed by medical units at 2.57 falls per 1,000 patient days, surgical with 2.33, and critical care with 2.28 falls per 1,000 patient days, but these differences were not statistically significant (p = .791). 6.4. Fall reduction interventions A set of basic interventions for fall reduction on acute care and ICU units included N 90% use of the call bell, adequate lighting (87–92.1%), bed in low position (77.8–90.7%), verbal reminders (69.9–84.1%), and non-skid footwear (11.4–77.8%). Interventions specific to the patient included being placed close to the nurse's station (50.0–68.2%), frequent checks (24.7–50.0%), and the use of tab alarms (11.4–25.1%). 6.5. Population comparison During the study period, 1,055 falls were reported for ages 21–90. The oldest age group of 65–90 accounted for the highest percentage of falls (44.8%, n = 473), closely followed by the middle-age group of 45–64 (41.9%, n = 442), then ages 21–44 (13.3%, n = 140). The mean age was 61.8 (STD 15.85) with a median age of 62 (ages 21–90). Fall rates per 1,000 patient days required exclusion of 55 inpatient falls that occurred in non-inpatient units with no patient days (N = 1,000; see Table 3). A significant pairwise difference was noted between ages 45–64 and ages 21–44 (p = .000), but there was no significant difference (p = .637) in rate of falls between age group 45–64 and age group 65–90. In the total population females had significantly fewer falls than expected based on the gender breakdown of inpatient discharges (p b 0.0001; see Table 4). Females had only 43% of the falls, but accounted for 54% of all inpatient discharges. Of the 28.5% of falls (n = 301) resulting in an injury (see Table 5), there were no statistically significant differences in the percentage of falls with an injury (overall p = .237) by age group. The percentage of falls resulting in an injury was 31.3% for age group 65–90, 30.4% for the middle-age group, and 24.8% for ages 21–44. There were 12 total major injuries from falls, occurring in 1.8% (n = 8) of the older age group 65–90, and 1.0% (n = 4) of the middle-age group, each of them
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Table 4 Gender breakdown per 1,000 patient days.
Male Female
% (N) of inpatient discharges
% (N) of inpatients with falls
46 54
57 43
Note. x2 p–value = b.0001.
a fracture. There were no major fall-related injuries for the age group 21–44. 7. Discussion The first aim of this research was to describe the characteristics of fall and fall injury risk factors specific to middle-age inpatients. The major findings revealed that the incidence of falls and many of the characteristics in middle-aged inpatients are similar to older inpatients in the current research (Bradley et al., 2010; Fischer et al., 2005; Mion et al., 2012). Despite the age, the majority of these inpatients were admitted with serious acute and chronic illnesses involving respiratory, cancer, ETOH/drug abuse, sepsis and cardiac diagnosis and having three or more comorbidities including hypertension, anxiety/depression, diabetes and history of ETOH. Chief complaints included altered mental status, nausea and vomiting, pneumonia, exasperation of chronic obstructive pulmonary disease, a fall prior to hospitalization, congestive heart failure, and acute coronary symptoms. This population experiences intrinsic illnesses and comorbidities similar to previous studies in older adult inpatients (Currie, 2008; Tzeng & Yin, 2013). Although the Morse Fall Scale is useful as an evidence-based screening tool, nursing clinical judgment (Oliver et al., 2010) continues to be as important in evaluating fall and fall injury risk and in the implementation of individualized plans of care. Table 1 demographics show that males had more falls, similar to the findings by Oliver et al. (2010). Further research may be important on understanding if nurses address fall safety differently for males than females when developing a plan of care. Another significant characteristic included the number of middle-age patients diagnosed on admission with altered mental status or alcohol/ drug abuse. Alcohol use has been identified as a risk for unintentional falls in the outpatient middle-age adult population (Kool, Ameratunga, & Jackson, 2009). No specific research exists regarding alcohol withdrawal and fall risk for inpatients especially in the middle-age adult who often does not acknowledge their risk to fall. Opiates and anticoagulants (Bradley et al., 2010; Hitcho et al., 2004; Shuey & Balch, 2014) are known risk and injury factors in the older population. 28% of this studies middleage inpatient population that had medication-related factors for falling. Other characteristics identified that increased fall risk included getting up at night to void (51.5%), a history of a fall in the last 3 months (29.8%), and repeat falls (21.4%). This study did not look at how characteristics differ in the repeat faller. A suggestion for future research includes study of the differences of middle-age inpatient that have repeat falls. This population fell more during the evening (37.6%) and night (32.6%) hours, similar to the Hitcho et al. (2004) report of a higher percentage of falls (59%) occurring during the evening/overnight. The important message to staff based on these findings includes that falls do occur regardless of the shift. The majority of these middle-age falls Table 5 Age-group comparison of % of falls with injury.
Table 3 Falls by age group per 1,000 patient days. Age group
Falls
Patient days
Rate
21–44 45–64 65–90
129 414 457
75,487 163,293 174,562
1.71 2.54 2.62
Note. Excluded were total 55 falls that occurred outside inpatient units. Age group 21–44 excluded 11 falls; age group 45–64 excluded 28 falls; and age group 65–90 excluded 16 falls.
Age group
% (N) of falls with injury
Total falls
21–44 45–64 65–90 Total
24.8% (32) 30.4% (126) 31.3% (143) 28.5% (301)
129 414 457 1,000
Note. Overall x2 p–value = .237. Pairwise comparisons: 45–64 vs. 21–44 p = .2668. 45–64 vs. 65–90 p = .8257.
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(87.7%) were also “unwitnessed,” which is consistent with other study findings (Bradley et al., 2010; Johnson, George, & Tran, 2011; Oliver et al., 2010). The occurrence-report descriptions of the unwitnessed falls were similar to earlier findings of a qualitative study by Carroll, Dykes, and Hurley (2010). These patients denied a fall, or stated they lost their balance, were reaching, or felt dizzy or weak during activities of toileting, washing up, or getting in or out of bed. The second aim of this study was to describe unit-specific data of fall numbers and prevention strategies. The unit data did not provide specific information to characterize falls in this population. For the middle-age population, the fall rates per 1,000 patent days had little variance between units. The fall rates per 1,000 patient days were lower than fall rates reported for all ages by Williams et al. (2014) who reported adult medical/surgical (6.26/3.67) and surgical (2.68/ 2.95) as higher but had similar lower critical care (1.66/1.69) fall rates. A study by Bouldin et al. (2013) also reported medical unit fall rates as higher at 4.03/1,000 per patient days than prior study findings. Prevention strategies were found to be a universal selection of interventions versus selected interventions that target anticipated physiological intrinsic risk factors specific to the population. For the population studied, further research is needed on fall preventative interventions to address risk factors of substance and drug abuse (31%) and known history of prior falls (30%) that may increase this population's risk to fall. The third aim, describing incidence of middle-age inpatient falls and injury rates in the middle-age inpatient compared to overall hospital adult population, revealed no significant differences for inpatients age 45–64 years who fell at almost the same rate per 1,000 patient days (2.54) as those 65 and older (2.62). In addition, this study's middleage inpatient falls resulted in injuries similar to the older age adult rates. This suggests that staff use of the screening tool of “A, B, C, S” to help identify injury risk is important and appropriate. Lack of use may be due to staff knowledge of how to incorporate it into the assessment or that it is seen as only for use of patients 85 years and older. Further education on the use of this tool, and how to incorporate interventions based on assessment for fall injury prevention requires further study. Of the overall inpatient population of falls, 72% had no injuries, similar to Cox et al. (2015) who reported 74% of hospitalized adult patients who fell with no injury but higher than Oliver et al. (2010), who reported 49% to 70% experienced non-injurious falls. This finding should not prevent the clinical staff from implementing prevention strategies to decrease falls. 7.1. Limitations Results of this study were limited to one academic hospital using retrospective data. The data extraction in the clinical chart for missing elements on the Excel spreadsheet was dependent on clinical documentation. Some documentation of falls that occurred at the beginning of the study period was found to be in paper format and, although scanned into the EMR documentation, some discrete elements were missing. Because a majority of fallers had not been profiled for fall injury risk, the injuries that resulted due to the fall event could not be discussed relative to fall injury risk. In addition, the study only included the first 6 months of CY 2014, which limited comparisons of the first-through-fourth quarters by calendar year. 8. Conclusion, Clinical Implications, and Future Research This descriptive study of inpatient falls and injury in the middle-age population provided an insight into a population with acute and chronic disease conditions, including multiple comorbidities and illnesses contributing to this population's risk for falls. The acuity of this population was also reflected in their prolonged length of stay, and the high percentage of inpatients discharged home with services or to a rehabilitation facility. This age group may overestimate their ability to function and find themselves at an increased risk for falls due to physiological reasons
and accidents in an unfamiliar environment. Although many falls were identified as anticipated physiological, a majority occurred in patient rooms and were unwitnessed, questioning the environment's influence on the fall. Cozart and Cesario (2009) and Hignett and Masud (2006) noted that the physical environment of hospital rooms and bathrooms is another contributing risk factor that needs to be evaluated when discussing implementation of fall prevention interventions. Additional clinical implications include patient education and reinforcement of fall prevention measures that are tailored to this population's medical acuity, mental status changes, physical limitations, and elimination needs. The age of this patient, should not influence staff assessment of alertness and orientation to limitations and tools such as Teach Back should be considered when educating this age group. The usefulness of the adapted WHO Risk Factor Model for Fall's in describing fall characteristics of the middle-age inpatient suggests a comprehensive approach using extrinsic and intrinsic risk factors for nursing and the multidisciplinary team to influence fall prevention outcomes. More research is needed related to the behavioral risk factors involving alcohol/substance abuse and autonomy for this inpatient population. Although not every fall is preventable, nursing's first responsibility is patient safety. This study helped to identify that it is not only the elderly who fall. Understanding of risk factors identified in this study, along with use of strong clinical patient assessment skills, is needed to implement an individualized fall prevention plan of care. For success of fall prevention and interventions to decrease falls and fall injuries, further research is needed to understand how to incorporate clinical shared decision-making to preserve autonomy and independence for this population. Acknowledgements Dr. Guillaume would like to especially thank her dissertation committee chair Jean Boucher, PhD, RN, ANP-BC, and team Carol Bova, PhD, RN, ANP, Sybil Crawford, PhD, and Patricia Quigley, PhD, MPH, ARNP, CRRN, FAAN, FAANP, for their support, mentorship, and expertise. Elizabeth Phillips for her thoughtful edits and a special thank you to Dave Vogel, without his technical assistance this research would not have been possible. References Agency for Healthcare Research and Quality (AHRQ) (2012). Never events. Patient safety primers (Retrieved from http://psnet.ahrq.gov/primerHome.aspx). Apold, J., & Quigley, P. A. (2012). Minnesota Hospital Association Statewide Project: SAFE from FALLS. Journal of Nursing Care Quality, 27(10), 299–306. http://dx.doi.org/10. 1097/NCQ.0b013e3182599d1b. Bouldin, E. L., Andresen, E. M., Dunton, N. E., Simon, M., Waters, T. M., Liu, M., ... Shorr, R. I. (2013). Falls among adult patients hospitalized in the United States: Prevalence and trends. Journal of Patient Safety, 9(1), 13–17. http://dx.doi.org/10.1097/PTS. 0b013e3182699b64. Bradley, S. M., Karani, R., McGinn, T., & Wisnivesky, J. (2010). Predictors of serious injury among hospitalized patients evaluated for falls. Journal of Hospital Medicine, 5(2), 63–68. http://dx.doi.org/10.1002/jhm.555. Carroll, D. L., Dykes, P. C., & Hurley, A. C. (2010). Patients' perspectives of falling while in an acute care hospital and suggestions for prevention. Applied Nursing Research, 23(4), 238–241. http://dx.doi.org/10.1016/j.apnr.2008.10.003. Centers for Medicare and Medicaid Services (CMS) (2012). Hospital-acquired conditions. (Retrieved from: http://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/HospitalAcqCond/Hospital-AcquiredConditions.html). Cox, J., Thomas-Hawkins, C., Pajarillo, E., DeGennaro, S., Cadmus, E., & Martinez, M. (2015). Factors associated with falls in hospitalized adult patients. Applied Nursing Research, 28(2), 78–82. http://dx.doi.org/10.1016/j.apnr.2014.12.003. Cozart, H. C., & Cesario, S. K. (2009). Falls aren't us: State of the science. Critical Care Nursing Quarterly, 32(2), 116–127. http://dx.doi.org/10.1097/CNQ.0b013e3181a27dc0. Currie, L. M. (2008). Fall and injury prevention. In R. G. Hughes (Ed.), Patient safety and quality: An evidence-based handbook for nurses (pp. 1–250). Rockville (MD): AHRQ (Publication No. 08–0043). Dykes, P. C., Carroll, D. L., Hurley, A., Lipsitz, S., Benoit, A., Chang, F., ... Middleton, B. (2010). Fall prevention in acute care hospitals: A randomized trial. JAMA, 304(17), 1912–1918. http://dx.doi.org/10.1001/jama.2010.1567. Fawcett, J. (1984). The metaparadigm of nursing: Present status and future refinements. Image–the journal of nursing scholarship, 16(3), 84–89. http://dx.doi.org/10.1111/j. 1547-5069.1984.tb01393.x.
D. Guillaume et al. / Applied Nursing Research 31 (2016) 65–71 Fischer, I. D., Krauss, M. J., Dunagan, W. C., Birge, S., Hitcho, E., Johnson, S., ... Fraser, V. J. (2005). Patterns and predictors of inpatient falls and fall-related injuries in a large academic hospital. Infection Control and Hospital Epidemiology, 26(10), 822–827. http:// dx.doi.org/10.1086/502500. Halm, M. A., & Quigley, P. A. (2011). Reducing falls and fall-related injuries in acutely and critically ill patients. American Journal of Critical Care, 20(6), 480–484. http://dx.doi. org/10.4037/ajcc2011606. Hignett, S., & Masud, T. (2006). A review of environmental hazards associated with in-patient falls. Ergonomics, 49(5-6), 605–616. http://dx.doi.org/10.1080/00140130600568949. Hitcho, E. B., Krauss, M. J., Birge, S., Claiborne Dunagan, W., Fischer, I., Johnson, S., ... Fraser, V. J. (2004). Characteristics and circumstances of falls in a hospital setting: A prospective analysis. Journal of General Internal Medicine, 19(7), 732–739. http://dx.doi.org/ 10.1111/j.1525-1497.2004.30387.x. Johnson, M., George, A., & Tran, D. T. (2011). Analysis of falls incidents: Nurse and patient preventive behaviours. International Journal of Nursing Practice, 17(1), 60–66. http:// dx.doi.org/10.1111/j.1440-172X.2010.01907.x. Joint Commission (2015). Sentinel event data summary. Sentinel event (Retrieved from http://www.jointcommission.org/sentinel_event.aspx). Kim, E. A., Mordiffi, S. Z., Bee, W. H., Devi, K., & Evans, D. (2007). Evaluation of three fallrisk assessment tools in an acute care setting. Journal of Advanced Nursing, 60(4), 427–435. http://dx.doi.org/10.1111/j.1365-2648.2007.04419.x. Kool, B., Ameratunga, S., & Jackson, R. (2009). The role of alcohol in unintentional falls among young and middle-aged adults: A systematic review of epidemiological studies. Injury Prevention, 15(5), 341–347. http://dx.doi.org/10.1136/ip.2008.021303. Mion, L. C., Chandler, A. M., Waters, T. M., Dietrich, M. S., Kessler, L. A., Miller, S. T., & Shorr, R. I. (2012). Is it possible to identify risks for injurious falls in hospitalized patients? Joint Commission Journal on Quality and Patient Safety, 38(9), 408–413 (Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23002493). Morse, J. M. (1997). Preventing patient falls. Thousand Oaks, California: Sage Publications, Inc. Morse, J. M., Morse, R. M., & Tylko, S. J. (1989). Development of a scale to identify the fallprone patient. Canadian journal on aging = La revue canadienne du vieillissement, 8(04), 366–377.
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National Database of Nursing Quality Indicators (NDNQI) (2013). Guidelines for data collection and submission on patient falls. (Retrieved from http://www.nursingquality. org). Oliver, D., Healey, F., & Haines, T. P. (2010). Preventing falls and fall-related injuries in hospitals. Clinics in Geriatric Medicine, 26(4), 645–692. http://dx.doi.org/10.1016/j. cger.2010.06.005. Quigley, P. A., & White, S. V. (2013). Hospital-based fall program measurement and improvement in high reliability organizations. Online Journal of Issues in Nursing, 18(2), 5. http://dx.doi.org/10.3912/OJIN.Vol18No02Man05. Schoenborn, C., & Heyman, K. (2009). Health characteristics of adults aged 55 years and over: United States, 2004–2007. National health statistics reports (Number 16), 1–32 (Retrieved from: http://www.cdc.gov/nchs/products/nhsr.htm). Shorr, R. I., Mion, L. C., Chandler, A. M., Rosenblatt, L. C., Lynch, D., & Kessler, L. A. (2008). Improving the capture of fall events in hospitals: Combining a service for evaluating inpatient falls with an incident report system. Journal of the American Geriatrics Society, 56(4), 701–704. http://dx.doi.org/10.1111/j.1532-5415.2007.01605.x. Shuey, K. M., & Balch, C. (2014). Fall prevention in high-risk patients. Critical Care Nursing Clinics of North America, 26(4), 569–580. http://dx.doi.org/10.1016/j.ccell.2014.08. 016. Spoelstra, S. L., Given, B. A., & Given, C. W. (2012). Fall prevention in hospitals: An integrative review. Clinical Nursing Research, 21(1), 92–112. http://dx.doi.org/10.1177/ 1054773811418106. Tzeng, H. M., & Yin, C. Y. (2013). Most frequently observed risk factors for adult inpatient injurious falls in hospitals. Clinical nurse specialist CNS, 6(10), 314–322. http://dx.doi. org/10.1097/NUR.ob013e3182a87271. U.S. Census Bureau (2012). Age and sex composition in the United States. (Retrieved from http://www.census.gov/population/age/data/2012comp.html). Williams, T., Szekendi, M., & Thomas, S. (2014). An analysis of patient falls and fall prevention programs across academic medical centers. Journal of Nursing Care Quality, 29(1), 19–29. http://dx.doi.org/10.1097/NCQ.0b013e3182a0cd19. World Health Organization (WHO) (2007). Risk factor model for falls in older age. WHO global report on fall prevention in older age (pp. 5). Geneva, Swizerland: Author (Retrieved from www.who.int/ageing/publications/Falls_prevention7March.pdf).
Contents lists available at ScienceDirect
Applied Nursing Research journal homepage: www.elsevier.com/locate/apnr
Original Article
Characteristics of the middle-age adult inpatient fall Donna Guillaume, PhD, RN a,⁎, Sybil Crawford, PhD, MS b, Patricia Quigley, PhD, MPH c a b c
Graduate School of Nursing, University of Massachusetts, 55 Lake Ave North, Worcester, MA, 01655, USA Division of Preventive and Behavioral Medicine, Department of Medicine, and Graduate School of Nursing, University of Massachusetts, 55 Lake Ave North, Worcester, MA, 01655, USA VISN 8 Patient Safety Center of Inquiry, James A. Haley VAMC, Tampa, FL, 33637-1022, USA
a r t i c l e
i n f o
Article history: Received 3 October 2015 Revised 24 December 2015 Accepted 14 January 2016 Available online xxxx Keywords: Falls Middle-age Inpatient Comorbidities Risk factors
a b s t r a c t Purpose: The purpose of this study is to describe characteristics of middle-age inpatients' (ages 45–64) fallers and their fall and fall injury risk factors. Background: Middle-age falls were 42–46% of inpatient falls. Studies related to inpatient falls have not targeted this population. Methods: A 439 retrospective chart review was performed. Middle-age fall and injury rates were compared with ages 21–44 and 65–90. Results: The mean age was 55.75 years (SD 5.26). 28.7% (n = 126) of falls resulted in injury. Individual fallers (n = 386) had a mean of four comorbidities (SD 1.843), including hypertension (46.5%), anxiety/depression (40.2%), and alcohol and drug abuse (32.9%). There was no significant difference (p = .637) in fall rates per 1,000 patient days between ages 45–64 and 65–90. Conclusion: Middle-age inpatients' acute illness makes them as vulnerable for fall and injury as the older population. They should not be overlooked for fall prevention measures. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Falls with injuries remains one of the most reportable, serious, and costly type of adverse events that occur in United States (U.S.) hospitals, resulting in detrimental morbidity and mortality outcomes (Agency for Healthcare Research and Quality (AHRQ) [AHRQ], 2012; Centers for Medicare and Medicaid Services (CMS) [CMS], 2012; Mion et al., 2012; Oliver, Healey, & Haines, 2010; Quigley & White, 2013). In acute care hospitals, an estimated 1,000 falls occur per hospital each year regardless of size, with over one million inpatient falls reported annually at the national level (Oliver et al., 2010; Shorr et al., 2008). Inpatient injuries also occur in 30–51% of all fall-related events (Bradley, Karani, McGinn, & Wisnivesky, 2010; Oliver et al., 2010; Quigley & White, 2013). The hospital care provided as a result of an inpatient fall has been reported at an estimated cost of $3,500 for a non-injury to $27,000 for a single serious injury (Apold & Quigley, 2012; Halm & Quigley, 2011; Quigley & White, 2013). National agencies such as the National Quality Forum (NQF), the Joint Commission, and the CMS have identified falls as a major quality concern that should not occur during hospitalizations (Quigley & White, 2013). The Joint Commission (2015) found that an inpatient fall with injury or death was the second most frequently reviewed ⁎ Corresponding author at: 267 Rumonoski Drive, Northbridge, Massachusetts, 01534. Tel.: +1 508 736 9137 (Mobile); fax: +1 774 443 7373. E-mail addresses: [email protected], [email protected] (D. Guillaume). http://dx.doi.org/10.1016/j.apnr.2016.01.003 0897-1897/© 2016 Elsevier Inc. All rights reserved.
sentinel event in 2014. Falls were also noted as the leading reported adverse event in the hospital setting (Spoelstra, Given, & Given, 2012). 2. Background and Significance Although it has been well documented that inpatients age 65 and older are at greater risk for falls and injury, middle-age adults (45–64 years of age) have been noted recently to have higher fall rates (Mion et al., 2012; Williams, Szekendi, & Thomas, 2014). In their seminal study, Hitcho et al. (2004) revealed that of 183 adult inpatients who fell, 47% (n = 86) were under age 65. The recent fall study by Williams et al. (2014) also identified that middle-aged inpatients 51–60 years old (n = 5,561) had the highest reported fall rates, followed by patients age 61–70 years (n = 4,699). The middle-age population, according to the U.S. Census Bureau, makes up 27% of the inpatient census, which has increased by 31% since the 2000 census (U.S. Census Bureau, 2012). The National Health Interview Survey (NHIS) 2004–2007 report, which looked at selected health characteristics of adults over age 55, found that 22.9% were identified as in fair-to-poor health; including 19.6% age 55–64 (Schoenborn & Heyman, 2009). Fall monitoring at one academic teaching hospital in Central Massachusetts supported these similar findings by noting that 42% of inpatients who fell were between the ages of 45 and 64. In addition, the randomized control trial of Dykes et al. (2010), using an electronic fall prevention toolkit (FPTK) with 192 patients, revealed that those in the middle-age group were less likely (p = .003) to adhere to the recommended fall prevention interventions. While predictors of falls and
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injuries have been studied across all adult inpatients (Mion et al., 2012; Oliver et al., 2010), research has not specifically addressed the fall risk characteristics in the middle-age. This knowledge will be important for informing nursing and the multidisciplinary team's decisions on implementation of interventions for fall and injury prevention in this age group. 3. Purpose of the Study
The multifactorial and interactive nature of these fall risk factors increases the risk of a patient fall and the potential for injury. Our adapted framework suggests also that Fawcett's (1984) metaparadigm of nursing be used as the foundation for nursing and the multidisciplinary team identification and prevention for falls and associated injuries.
5. Study Design and Methods
The purpose of this study was to describe the characteristics of middle-age adult inpatients' that fall, along with their fall and fall injury risk factors. The aims were to (a) describe falls and fall injury risk factors; (b) describe unit-specific data, fall numbers with type of falls, injuries from falls, and prevention strategies; and (c) compare the incidence of fall and fall injury rates of the middle-age (45–64) patients with the hospital adult age groups (21–44 and 65–90). 4. Conceptual Framework The study framework (see Fig. 1) was adapted from the World Health Organization's (WHO), “Risk factor model for fall in older age,” The WHO Global Report on Fall Prevention (WHO, 2007). This framework was adapted with permission for use in the inpatient setting. Extrinsic and intrinsic variables from four risk factor groupings of biological, socioeconomic, behavioral, and environmental and their related outcomes were used to describe characteristics of the middleage inpatient's fall and fall injury risk. Demographics and characteristics from an earlier prospective descriptive study of inpatients from ages 17–96 by Hitcho et al. (2004) were used for identification of variables to collect in the four risk factor groupings.
5.1. Design This study was a secondary analysis of falls that occurred between January 1, 2012 and July 31, 2014. The retrospective review took place August 1, 2014–December 31, 2014. The research took place in a large academic teaching hospital in Central Massachusetts and used incident-reporting data, electronic medical records (EMR), and hospital staffing and financial data. The conceptual framework was used to identify the discrete variables collected for aims 1–3 (Fig. 1). This academic teaching hospital has about 36,690 hospital discharges yearly, with an average daily inpatient adult census of 404 patients. For this study, patient falls were reported from adult medical (n = 6), surgical (n = 4), mixed medical/surgical (n = 4), critical care (n = 8), and other specific type units (n = 4) such as post-anesthesia care, procedural areas, and the emergency department (ED).
5.2. Protection of human subjects Institutional review board (IRB) approval was obtained prior to conducting the study.
RISK FACTOR MODEL FOR INPATIENT FALLS Health
Biological Risk Factors
Environment Risk Factors Wet, Ripped Floors Lighting Clutter Commodes Time of Day Location Activity
Outcomes Fall Rates, Age, Unit Interventions Types of Fall Accidental, Anticipated Physiological Unanticipated Physiological
Level of Injury
Socioeconomic Risk Factors Marital Status Language Insurance Type
Patient
Environment
Age, Gender, Race Comorbidities, Surgery Chronic Illness Cognitive, Dizziness Mobility, Balance Elimination Needs Medication
None, Minor Moderate, Major, Death
Behavioral Risk Factors Alcohol/Drug Use Call Light Footwear History Previous Falls Physical Limitations Autonomy
Nursing & Multidisciplinary Team
Fig. 1. Risk factor model for inpatient falls. Adapted with permission from the World Health Organization (WHO) (WHO), 2007.
D. Guillaume et al. / Applied Nursing Research 31 (2016) 65–71
5.3. Sample Included in the study sample were middle-age inpatients (45–64) who fell either one-time or had a repeat fall during the study period. A repeat fall may have occurred during the same admission or during another admission in the study period. Exclusion criteria included (a) an adult patient fall on a psychiatric unit; (b) an adult patient fall during an outpatient appointment in the ambulatory department; and (c) a fall by visitors, students, and staff members. 5.4. Data collection Patient falls that met study criteria between August 1, 2014 and December 31, 2014 were identified through querying of the hospital incident-reporting database. Falls were reported by clinical staff using an incident report form that is entered into a secured risk-management database. Data not captured in the incident-reporting database were collected through additional retrospective EMR chart review. If additional falls that met study criteria were identified during this review, those falls were also included in the study. The principal investigator (PI) performed the data collection and data cleaning throughout the study. The PI who was familiar with hospital incident reports on falls had a strong clinical background related to patient safety and navigation of the EMR. Data were downloaded into an EXCEL sheet. Each variable collected was reviewed manually for accuracy using the EMR, and missing data elements were extracted if available. For aim 3, data were queried from the hospital analytic database sets to determine census and 1,000 patient days. The fall occurrence data sets were used to compare fall and fall injury rates of inpatients identified in the middle-age population (45–64) with fallers in age groups of 21–64 and 65–90. This resulted in a slight disparity from the retrospective chart review of aims 1 and 2. 5.4.1. Fall event To determine what is a fall, the National Database of Nursing Quality Indicators® (NDNQI®;, 2013) description of a fall was used: “An unintentional descent to the floor or extension of the floor with or without injury, including assisted falls and physiological falls (i.e., fainting)” (NDNQI, p. 2). Falls also included patients found on the floor or who self-reported a fall. For this study, a fall may have occurred in areas outside of the nursing unit (e.g., emergency department, bone marrow unit, radiology, surgical admissions). The type of fall as defined by Morse (1997) was classified as either accidental, anticipated physiological, or unanticipated physiological. Accidental falls occur due to environmental extrinsic risk factors, often where the patient may not have been identified at risk to fall (e.g., trip or slip on the floor, or fall out of bed when reaching for an object). Anticipated physiological falls may result from known intrinsic (i.e., altered gait and balance, impaired vision, multiple diagnoses) and extrinsic (i.e., medications and IVs) risk factors. Unanticipated physiological falls are from unexpected medical conditions such as heart attack, fainting, or seizure, and are considered unpreventable (Morse, 1997). The Morse Fall Scale (MFS) screening tool was used by the organization to identify the risk of an anticipated physiological patient fall. Through use of this validated scale used for fallers and non-fallers, patients were screened based on six risk factors: history of falling, secondary diagnosis, ambulatory aide, IV therapy/heparin lock, gait, and mental status. A score based on outcome helped to identify the level of risk for one type of fall, anticipated physiological fall (b25 low risk; 25–45 moderate risk; and N 45 high risk; Morse, Morse, & Tylko, 1989). The MFS result documented closest to the time before the fall was used in this study. Kim, Mordiffi, Bee, Devi, and Evans (2007) evaluated the validity of the MFS. Their studies of various populations showed a predictive validity sensitivity that ranged between 72% and 83%, a specificity range between 29% and 83%, and inter-rater reliability
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of 96%. A consensus validation process to correlate actual fall risk factors to the actual fall event was performed to determine type of fall. 5.4.2. Fall injury When a fall occurs, depending on the severity of injury, it can change a patient's recovery and discharge. The NDNQI (2013) identified injuries based on five categories as follows: none (e.g., no injury reported, includes diagnostics test to rule out injury); minor (e.g., pain, abrasion, bruises); moderate (e.g., muscle/joint strain requiring splinting, laceration requiring suturing, staples, or steri-strips); major (e.g., fractures where treatment included surgery, casting, traction, internal head injury); and death (falls that result in death due to the trauma of the fall, not including patients who died due to their initial diagnosis; NDNQI, 2013, pp. 5–6). Halm and Quigley (2011) recommended a population-specific approach to identify fall injury. The screening tool referred to as “A, B, C, S” factors (age, ≥85 years or frailty not applicable for this study; bones/fracture risk or history; anticoagulated or bleeding disorder; and post-surgery) was reviewed to capture if patients had increased risk for injury when a fall occurred. 5.5. Data management and analysis line All data were de-identified and exported into IBM© SPSS v21 data software for analysis. Characteristics of the 386 fallers and of the 495 individual falls, including all falls per patient, were summarized. Descriptive statistics for categorical variables included frequencies, mean, standard deviation, median and range, and crosstabs to describe relationship of age with other study variables. Variables included fall and injury rates, level of injury prevention interventions, and type of falls. To examine shift-related differences in falls, a chi-square test assessed whether the observed number of falls in each of the three shifts differed significantly from the null distribution of equal numbers of falls in each shift. Similarly, chi-square tests were used to determine whether observed distributions of falls across gender differed significantly from corresponding distributions of all patient days across gender. The proportion of falls resulting in an injury was compared for the three age groups using chi-square testing as well. Poisson regression was used for comparing rates of falls per 1,000 patient days across units in mid-aged patients, and across the three age groups (21–44, 45–64, and 65–90). 6. Results 6.1. Population A total of 444 individual falls based on the study criteria were identified in the hospital-occurrence database. The EMR review identified nine falls not meeting study eligibility criteria. Falls removed from the study included incorrect age (n = 2), same fall reported twice (n = 2), and not meeting location criteria (n = 5). During the EMR review, four additional falls were identified as repeat falls that had not been reported, and were then added to the study sample. This resulted in a final sample of 439 inpatient falls. Of the 439 falls reviewed, 94 (21.4%) falls were repeat falls including 32 as repeat for the same admission and 21 as repeat for a different admission. There were 386 unique inpatients that experienced a fall. Of this population, 41 unique inpatients had repeat falls either during the present admission or in future admissions during the study time period. The number of repeat inpatient falls included the majority (n = 36) with two falls. Five different inpatients incurred a range from three to six repeat falls. The 439 falls were evenly distributed over the 2.5 year calendar year (CY) period of time: 2012–2014. 6.2. Characteristics of individual fallers and falls Table 1 shows the demographics and characteristics specific to the 386 individual middle-age inpatients that fell. The characteristics
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Table 1 Frequency distribution of demographics and study variables.
Table 2 Description of fall.
Demographics/Variables
N = 386 individual patients
Variable
Male Female Non-Hispanic Marital status Single/Separated/Divorced/Widow Married/Living as married Insurance status Private Federal/State State Uninsured Other (automobile, workers comp) Admit diagnosis⁎ Respiratory a Cancer b ETOH/Drugs Sepsis c Cardiac d Ortho e Admit chief complaint⁎ AMS GI f Respiratory Fall Cardiac Neuro g Admit comorbidities⁎ HTN Anxiety/Depression ETOH/Drugs Diabetes Cardiac Respiratory Discharge status Rehab/Facility Home with services Home no services Other Death
223 (58%) 163 (42%) 362 (94%; missing data = 2)
⁎Age (years) mean = 55.75 (SD 5.26) 45–49 50–54 55–59 60–64 Male Female Characteristic Alert & oriented MFSa Void at night Abnormal gait MFSa Fall history 3 months Assistive devices MFSa Confused at time of fall Dizzy at time of fall Area of fall Inpatient room Bathroom Other (hallway, procedure area) In patient room Found on floor From chair From commode Patient room (patient reported) Fell OOB b Reported activity Walking Getting OOB Lost balance Reaching Incontinent Urinal 24 hours after procedure Within 4 hours of transfer Gait Normal Weak Impaired Non-ambulatory Last toileted b15 min 16–60 min 1–2 hr N2 hrs Catheter/Incontinence Medications None Narcotic/Sedative Anti-psych Lax/Diuretic Relief chemo SX c
252 (65%) 134 (35%) 122 (32%) 123 (32%) 114 (30%) 19 (5%) 8 (2%) 43 (11%) 42 (10%) 37 (10%) 37 (10%) 31 (8%) 28 (7%) 59 (15%) 52 (14%) 46 (12%) 33 (9%) 29 (8%) 27 (7%) 178 (46%) 155 (40%) 127 (33%) 110 (29%) 98 (25%) 90 (23%) 173 (45%) 101 (26%) 68 (18%) 28 (7%) 16 (4%)
Note. Percentages do not total 100%, due to rounding. Discharge status: Other: NH, Psych, VA, Hosp. Group Home, Hospice and Other Hospital. No deaths were from a fall. ⁎ The six most frequently identified variables were identified. Included but not limited to each category: a Asthma, bronchitis, cardiopulmonary disease (COPD), lobe infiltrate, pneumonia. b Brain, breast, lung myleoma, spine, stem cell, thyroid. c Bacteremia, blood stream, C-difficile, meningitis septic. d Chest pain, congestive heart failure (CHF), coronary artery disease (CAD), myocardia infraction (MI). e Abnormal gait, amputation, arthroplasty, fractures, knee replacement. f Bowel obstruction, colitis, diarrhea, dysphagia, diverticulitis, nausea, vomiting. g Aphasia, altered mental status, cerebral aneurism, dizziness, Guillain Barre, seizure, stroke, syncope, numbness, tingling.
include the top six admitting diagnoses; chief complaints, comorbidities, and discharge status. Of the 386 inpatients, 94% (n = 362) were Caucasian, the remaining 6% identified were 5.6% (n = 22) Hispanic, 2% (n = 8) African, and 5.9% (n = 23) other. Only 3.1% (n = 12) of this population were hospitalized for elective admissions, and a small percentage (17.6%, n = 68) were discharged home with no services. Characteristics of the 439 total falls are shown in Table 2. The majority of the 439 falls, 85.9% (n = 377) were screened as anticipated physiologic falls (including behavior-related falls), followed by 10.7% (n = 47) accidental falls, and 3.4% (n = 15) as unanticipated physiologic falls, and 5.8% (n = 22) were not screened for a risk score. Of the 377 anticipated physiologic falls, using the MFS, nurses rated 66.3% (n = 250) inpatients as either high risk (48%, n = 181) or medium risk (18.3%, n = 69) to fall. Of the 439 individual falls recorded, 28.7% (n = 126) resulted in some level of injury from minor (21.8%, n = 96), moderate (5.9%, n = 26), and major that resulted in four (1%) fractures that included rib, ankle, fibula, and hip. Of the four falls resulting in major injuries,
Value, N = 439 56 (13%) 131 (30%) 120 (27%) 132 (30%) 251 (57%) 188 (43%) 232 (52.8%; missing data =11) 226 (51.5%; missing data = 60) 224 (51%; missing data = 33) 131 (30%; missing data = 50) 76 (34%) 33 (8%) 12 (3%) 296 (67%) 127 (29%) 16 (4%) 193 (44%) 42 (10%) 28 (6%) 22 (5%) 21 (5%) 84 (19%) 73 (17%) 61 (14%) 26 (6%) 12 (3%) 11 (3%) 57 (13%) 25 (8%) 182 (42%) 126 (29%) 78 (18%) 20 (5%) 78 (18%) 99 (23%) 142 (32%) 51 (12%) 66 (15%) 314 (72%) 72 (16%) 24 (6%) 22 (5%) 6 (1%)
Note. “Found on floor” no documentation where fall was initiated. Missing variables: gait n = 33 (8%), toileting n = 3 (0.7%). Percentages do not total 100% due to rounding. Narcotics/Sedative: Oxycodone, Dilaudid, Percocet, Morphine, Haldol, Phenobarbital; antipsych: Valium, Ativan, Effexor, Zyprexa; laxative/diuretic: Lactose, Colace, Dulcolax, Lasix. ⁎ NEISS. (2001–2013). Patient room (either reported/assisted falls). a Variable identified using MFS (Morse Fall scale. b OOB (out of bed). c SX (symptoms).
three were by females. Although 70.6% (n = 310) of the falls that occurred lacked an inpatient screening of “A, B, C, S” for risk of injury, of the inpatient falls screened 23.5% (n = 103) of the fallers were identified as on anticoagulation, 8.7% (n = 38) at risk due to surgical procedures, and 2.3% (n = 10) were identified with fracture risk/bonerelated problems. The majority (67.4%) of middle-age inpatient falls occurred in the patient's room, followed by 28.9% in the patient's bathroom, with a small percentage (3.6%) occurring in the hallway or other areas (see Table 2). An abnormal gait was identified by the MFS screening in 51% (n = 224) of the falls and 52.8% (n = 232) of the fallers were identified as alert and oriented to person, place, and time. Of these falls, 58.9%
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(n = 259) of the patients were last toileted more than an hour prior to the fall. In 71.5% (n = 314) of falls there were no documented narcotics, sedatives, laxatives, diuretics, or anti-psychotic medications 4–6 hours before the fall (see Table 2). A somewhat higher percentage of falls occurred in the evening and night shifts (37.6% and 32.6%, respectively) than in the day shift, although this breakdown was not statistically significantly different from equal proportions in each shift (p = .131). The mean number of days to fall after admission was 8.22 days (SD 9.91) with a median of 5.00 days (range 1–90). The total length of stay (LOS) of the patients who fell was a mean of 17.70 days (SD 35.35) with a median of 10 days (range of 1–390 days). Reported falls included 87.7% (n = 385) as unwitnessed and 4.8% (n = 21) as self-reporting or claiming not falling but “sat down,” or “was doing push-ups,” or “praying.” 6.3. Unit-type fall rate Fall rates per 1,000 patient days were slightly higher on medical surgical floors at 2.63, followed by medical units at 2.57 falls per 1,000 patient days, surgical with 2.33, and critical care with 2.28 falls per 1,000 patient days, but these differences were not statistically significant (p = .791). 6.4. Fall reduction interventions A set of basic interventions for fall reduction on acute care and ICU units included N 90% use of the call bell, adequate lighting (87–92.1%), bed in low position (77.8–90.7%), verbal reminders (69.9–84.1%), and non-skid footwear (11.4–77.8%). Interventions specific to the patient included being placed close to the nurse's station (50.0–68.2%), frequent checks (24.7–50.0%), and the use of tab alarms (11.4–25.1%). 6.5. Population comparison During the study period, 1,055 falls were reported for ages 21–90. The oldest age group of 65–90 accounted for the highest percentage of falls (44.8%, n = 473), closely followed by the middle-age group of 45–64 (41.9%, n = 442), then ages 21–44 (13.3%, n = 140). The mean age was 61.8 (STD 15.85) with a median age of 62 (ages 21–90). Fall rates per 1,000 patient days required exclusion of 55 inpatient falls that occurred in non-inpatient units with no patient days (N = 1,000; see Table 3). A significant pairwise difference was noted between ages 45–64 and ages 21–44 (p = .000), but there was no significant difference (p = .637) in rate of falls between age group 45–64 and age group 65–90. In the total population females had significantly fewer falls than expected based on the gender breakdown of inpatient discharges (p b 0.0001; see Table 4). Females had only 43% of the falls, but accounted for 54% of all inpatient discharges. Of the 28.5% of falls (n = 301) resulting in an injury (see Table 5), there were no statistically significant differences in the percentage of falls with an injury (overall p = .237) by age group. The percentage of falls resulting in an injury was 31.3% for age group 65–90, 30.4% for the middle-age group, and 24.8% for ages 21–44. There were 12 total major injuries from falls, occurring in 1.8% (n = 8) of the older age group 65–90, and 1.0% (n = 4) of the middle-age group, each of them
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Table 4 Gender breakdown per 1,000 patient days.
Male Female
% (N) of inpatient discharges
% (N) of inpatients with falls
46 54
57 43
Note. x2 p–value = b.0001.
a fracture. There were no major fall-related injuries for the age group 21–44. 7. Discussion The first aim of this research was to describe the characteristics of fall and fall injury risk factors specific to middle-age inpatients. The major findings revealed that the incidence of falls and many of the characteristics in middle-aged inpatients are similar to older inpatients in the current research (Bradley et al., 2010; Fischer et al., 2005; Mion et al., 2012). Despite the age, the majority of these inpatients were admitted with serious acute and chronic illnesses involving respiratory, cancer, ETOH/drug abuse, sepsis and cardiac diagnosis and having three or more comorbidities including hypertension, anxiety/depression, diabetes and history of ETOH. Chief complaints included altered mental status, nausea and vomiting, pneumonia, exasperation of chronic obstructive pulmonary disease, a fall prior to hospitalization, congestive heart failure, and acute coronary symptoms. This population experiences intrinsic illnesses and comorbidities similar to previous studies in older adult inpatients (Currie, 2008; Tzeng & Yin, 2013). Although the Morse Fall Scale is useful as an evidence-based screening tool, nursing clinical judgment (Oliver et al., 2010) continues to be as important in evaluating fall and fall injury risk and in the implementation of individualized plans of care. Table 1 demographics show that males had more falls, similar to the findings by Oliver et al. (2010). Further research may be important on understanding if nurses address fall safety differently for males than females when developing a plan of care. Another significant characteristic included the number of middle-age patients diagnosed on admission with altered mental status or alcohol/ drug abuse. Alcohol use has been identified as a risk for unintentional falls in the outpatient middle-age adult population (Kool, Ameratunga, & Jackson, 2009). No specific research exists regarding alcohol withdrawal and fall risk for inpatients especially in the middle-age adult who often does not acknowledge their risk to fall. Opiates and anticoagulants (Bradley et al., 2010; Hitcho et al., 2004; Shuey & Balch, 2014) are known risk and injury factors in the older population. 28% of this studies middleage inpatient population that had medication-related factors for falling. Other characteristics identified that increased fall risk included getting up at night to void (51.5%), a history of a fall in the last 3 months (29.8%), and repeat falls (21.4%). This study did not look at how characteristics differ in the repeat faller. A suggestion for future research includes study of the differences of middle-age inpatient that have repeat falls. This population fell more during the evening (37.6%) and night (32.6%) hours, similar to the Hitcho et al. (2004) report of a higher percentage of falls (59%) occurring during the evening/overnight. The important message to staff based on these findings includes that falls do occur regardless of the shift. The majority of these middle-age falls Table 5 Age-group comparison of % of falls with injury.
Table 3 Falls by age group per 1,000 patient days. Age group
Falls
Patient days
Rate
21–44 45–64 65–90
129 414 457
75,487 163,293 174,562
1.71 2.54 2.62
Note. Excluded were total 55 falls that occurred outside inpatient units. Age group 21–44 excluded 11 falls; age group 45–64 excluded 28 falls; and age group 65–90 excluded 16 falls.
Age group
% (N) of falls with injury
Total falls
21–44 45–64 65–90 Total
24.8% (32) 30.4% (126) 31.3% (143) 28.5% (301)
129 414 457 1,000
Note. Overall x2 p–value = .237. Pairwise comparisons: 45–64 vs. 21–44 p = .2668. 45–64 vs. 65–90 p = .8257.
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(87.7%) were also “unwitnessed,” which is consistent with other study findings (Bradley et al., 2010; Johnson, George, & Tran, 2011; Oliver et al., 2010). The occurrence-report descriptions of the unwitnessed falls were similar to earlier findings of a qualitative study by Carroll, Dykes, and Hurley (2010). These patients denied a fall, or stated they lost their balance, were reaching, or felt dizzy or weak during activities of toileting, washing up, or getting in or out of bed. The second aim of this study was to describe unit-specific data of fall numbers and prevention strategies. The unit data did not provide specific information to characterize falls in this population. For the middle-age population, the fall rates per 1,000 patent days had little variance between units. The fall rates per 1,000 patient days were lower than fall rates reported for all ages by Williams et al. (2014) who reported adult medical/surgical (6.26/3.67) and surgical (2.68/ 2.95) as higher but had similar lower critical care (1.66/1.69) fall rates. A study by Bouldin et al. (2013) also reported medical unit fall rates as higher at 4.03/1,000 per patient days than prior study findings. Prevention strategies were found to be a universal selection of interventions versus selected interventions that target anticipated physiological intrinsic risk factors specific to the population. For the population studied, further research is needed on fall preventative interventions to address risk factors of substance and drug abuse (31%) and known history of prior falls (30%) that may increase this population's risk to fall. The third aim, describing incidence of middle-age inpatient falls and injury rates in the middle-age inpatient compared to overall hospital adult population, revealed no significant differences for inpatients age 45–64 years who fell at almost the same rate per 1,000 patient days (2.54) as those 65 and older (2.62). In addition, this study's middleage inpatient falls resulted in injuries similar to the older age adult rates. This suggests that staff use of the screening tool of “A, B, C, S” to help identify injury risk is important and appropriate. Lack of use may be due to staff knowledge of how to incorporate it into the assessment or that it is seen as only for use of patients 85 years and older. Further education on the use of this tool, and how to incorporate interventions based on assessment for fall injury prevention requires further study. Of the overall inpatient population of falls, 72% had no injuries, similar to Cox et al. (2015) who reported 74% of hospitalized adult patients who fell with no injury but higher than Oliver et al. (2010), who reported 49% to 70% experienced non-injurious falls. This finding should not prevent the clinical staff from implementing prevention strategies to decrease falls. 7.1. Limitations Results of this study were limited to one academic hospital using retrospective data. The data extraction in the clinical chart for missing elements on the Excel spreadsheet was dependent on clinical documentation. Some documentation of falls that occurred at the beginning of the study period was found to be in paper format and, although scanned into the EMR documentation, some discrete elements were missing. Because a majority of fallers had not been profiled for fall injury risk, the injuries that resulted due to the fall event could not be discussed relative to fall injury risk. In addition, the study only included the first 6 months of CY 2014, which limited comparisons of the first-through-fourth quarters by calendar year. 8. Conclusion, Clinical Implications, and Future Research This descriptive study of inpatient falls and injury in the middle-age population provided an insight into a population with acute and chronic disease conditions, including multiple comorbidities and illnesses contributing to this population's risk for falls. The acuity of this population was also reflected in their prolonged length of stay, and the high percentage of inpatients discharged home with services or to a rehabilitation facility. This age group may overestimate their ability to function and find themselves at an increased risk for falls due to physiological reasons
and accidents in an unfamiliar environment. Although many falls were identified as anticipated physiological, a majority occurred in patient rooms and were unwitnessed, questioning the environment's influence on the fall. Cozart and Cesario (2009) and Hignett and Masud (2006) noted that the physical environment of hospital rooms and bathrooms is another contributing risk factor that needs to be evaluated when discussing implementation of fall prevention interventions. Additional clinical implications include patient education and reinforcement of fall prevention measures that are tailored to this population's medical acuity, mental status changes, physical limitations, and elimination needs. The age of this patient, should not influence staff assessment of alertness and orientation to limitations and tools such as Teach Back should be considered when educating this age group. The usefulness of the adapted WHO Risk Factor Model for Fall's in describing fall characteristics of the middle-age inpatient suggests a comprehensive approach using extrinsic and intrinsic risk factors for nursing and the multidisciplinary team to influence fall prevention outcomes. More research is needed related to the behavioral risk factors involving alcohol/substance abuse and autonomy for this inpatient population. Although not every fall is preventable, nursing's first responsibility is patient safety. This study helped to identify that it is not only the elderly who fall. Understanding of risk factors identified in this study, along with use of strong clinical patient assessment skills, is needed to implement an individualized fall prevention plan of care. For success of fall prevention and interventions to decrease falls and fall injuries, further research is needed to understand how to incorporate clinical shared decision-making to preserve autonomy and independence for this population. Acknowledgements Dr. Guillaume would like to especially thank her dissertation committee chair Jean Boucher, PhD, RN, ANP-BC, and team Carol Bova, PhD, RN, ANP, Sybil Crawford, PhD, and Patricia Quigley, PhD, MPH, ARNP, CRRN, FAAN, FAANP, for their support, mentorship, and expertise. Elizabeth Phillips for her thoughtful edits and a special thank you to Dave Vogel, without his technical assistance this research would not have been possible. References Agency for Healthcare Research and Quality (AHRQ) (2012). Never events. Patient safety primers (Retrieved from http://psnet.ahrq.gov/primerHome.aspx). Apold, J., & Quigley, P. A. (2012). Minnesota Hospital Association Statewide Project: SAFE from FALLS. Journal of Nursing Care Quality, 27(10), 299–306. http://dx.doi.org/10. 1097/NCQ.0b013e3182599d1b. Bouldin, E. L., Andresen, E. M., Dunton, N. E., Simon, M., Waters, T. M., Liu, M., ... Shorr, R. I. (2013). Falls among adult patients hospitalized in the United States: Prevalence and trends. Journal of Patient Safety, 9(1), 13–17. http://dx.doi.org/10.1097/PTS. 0b013e3182699b64. Bradley, S. M., Karani, R., McGinn, T., & Wisnivesky, J. (2010). Predictors of serious injury among hospitalized patients evaluated for falls. Journal of Hospital Medicine, 5(2), 63–68. http://dx.doi.org/10.1002/jhm.555. Carroll, D. L., Dykes, P. C., & Hurley, A. C. (2010). Patients' perspectives of falling while in an acute care hospital and suggestions for prevention. Applied Nursing Research, 23(4), 238–241. http://dx.doi.org/10.1016/j.apnr.2008.10.003. Centers for Medicare and Medicaid Services (CMS) (2012). Hospital-acquired conditions. (Retrieved from: http://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/HospitalAcqCond/Hospital-AcquiredConditions.html). Cox, J., Thomas-Hawkins, C., Pajarillo, E., DeGennaro, S., Cadmus, E., & Martinez, M. (2015). Factors associated with falls in hospitalized adult patients. Applied Nursing Research, 28(2), 78–82. http://dx.doi.org/10.1016/j.apnr.2014.12.003. Cozart, H. C., & Cesario, S. K. (2009). Falls aren't us: State of the science. Critical Care Nursing Quarterly, 32(2), 116–127. http://dx.doi.org/10.1097/CNQ.0b013e3181a27dc0. Currie, L. M. (2008). Fall and injury prevention. In R. G. Hughes (Ed.), Patient safety and quality: An evidence-based handbook for nurses (pp. 1–250). Rockville (MD): AHRQ (Publication No. 08–0043). Dykes, P. C., Carroll, D. L., Hurley, A., Lipsitz, S., Benoit, A., Chang, F., ... Middleton, B. (2010). Fall prevention in acute care hospitals: A randomized trial. JAMA, 304(17), 1912–1918. http://dx.doi.org/10.1001/jama.2010.1567. Fawcett, J. (1984). The metaparadigm of nursing: Present status and future refinements. Image–the journal of nursing scholarship, 16(3), 84–89. http://dx.doi.org/10.1111/j. 1547-5069.1984.tb01393.x.
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