Evidence-based fall risk assessment AssignmentTutorOnline | Good Grade Guarantee!
Aim: To develop and test interrater reliability of an evidence-based fall risk assessment tool for nurses and to investigate how nurses perceived the clarity and usability of the tool.
In phase 1, an evidence-based fall risk assessment tool was developed based on a literature review and expert discussion. The finalized tool assessed 11 risk factors and comprised 23 items. In phase 2, reliability testing was done. Two each participating patient on admission with the assessment tool. The nurses then provided feedback on the clarity and usability of the tool. The interrater reliability was estimated by the percentage agreement, Cohen’s kappa, and prevalence- and bias-adjusted kappa.Results: Of the 164 patients who were recruited, 114 patients participated. After adjustment for prevalence and bias, only “frequent urination” and “night-time toileting” showed a less-than-substantial interrater agreement. Assessment of the items “cognitive impairment” and “night-time toileting” were most frequently reported to be problematic.
The evidence-based fall risk assessment tool requires further modification and re-examination of interrater reliability is warranted. In particular, the cognitive impairment items need to be reconsidered in order to enable nurses to better assess patient cognition on the admission day.
Key words: accidental falls, assessment tool development, inpatients, nursing assessment, reproducible of the results, risk assessment.
Falls account for 23.1–32.3% of all adverse eventsoccurring in hospitals worldwide (Healey et al., 2008;Japan Council for Quality Health Care, 2014) and areranked among the top 10 sentinel events that arereported to the Joint Commission (2015a). Moreover,falls account for 40–61.8% of nursing care-relatedadverse events (D’Amour, Dubois, Tchouaket,Clarke, & Blais, 2014; Japan Council for QualityHealth Care). Between 26.1% and 33.6% of inpatientfalls result in an injury (Aranda-Gallardo, Morales-Asencio, Canca-Sanchez, & Toribio-Montero, 2014;Bouldin et al., 2013; Krauss et al., 2007; Mion et al.,2012; Schwendimann, Buhler, De Geest, & Milisen,2006). Of those injuries, 2.9–9.2% are classified asmajor injuries (such as fractures or intracranial hemorrhages)and ≤1.8% result in patient death.
In Japan, ~10% of reported inpatient falls result in ahigh potential for residual disability or death (JapanCouncil for Quality Health Care, 2014). Furthermore,falls and fractures are one of the top five reasons forindividuals requiring assistance with activities of dailyliving (Ministry of Health, Labour and Welfare, 2014).Japan has the world’s highest proportion of people aged ≥65 years. This proportion exceeded 25% in 2013 and is expected to increase (Cabinet Office Japan, 2014).Therefore, injuries resulting from falls must be reducedin order to prolong healthy living and to counter risinghealth expenditure. An aging population is not only anissue in Japan, but also globally. The World HealthOrganization (2015) estimated that the proportion ofthe world’s population aged >60 years will increase to22% in 2050.
The Joint Commission (2015b) recommends using astandardized and validated fall risk assessment tool, suchas the Morse Fall Scale (Morse, Morse, & Tylko, 1989)or the Hendrich II Fall Risk Model (Hendrich, Bender, &Nyhuis, 2003) to prevent patient falls; however, thesetools have not been validated in Japanese hospitals. TheSt. Thomas’s Risk Assessment Tool in Falling ElderlyInpatients (STRATIFY; Oliver, Britton, Seed, Martin, &Hopper, 1997) is another well-validated tool that is usedin many countries. In a meta-analysis by Aranda-Gallardo et al. (2013), STRATIFY showed a greater levelof validity in acute hospitals than did the Hendrich IIRisk Model or the Morse Fall Scale; however, theSTRATIFY showed limited predictive validity in a Japaneseuniversity hospital (Toyabe, 2010).
Numerous studies have been published on the predictivevalidity and reliability of fall risk assessment tools,but more have focused on the predictive validity thanreliability. When investigating the reliability of a tool,the key aspects are its stability, internal consistency, andequivalence. The method that is used to examine reliabilityshould depend on the nature of the instrumentand the most important aspect of reliability for thatinstrument (Polit & Beck, 2004). For a fall risk assessmenttool, equivalence could be a more appropriatemeasure than stability or internal consistency. Stabilityshould be assessed when examining stable characteristicsthat do not change over time (Polit & Beck). Internalconsistency would not be meaningful because theitems that are included in fall risk assessment toolsassess different aspects of the risk of a fall. Previousstudies that examined the Hendrich II Fall Risk Model(Zhang, Wu, Lin, Jia, & Cao, 2015) and the Morse FallScale (Chow et al., 2007; Morse et al., 1989) reportedpoor internal consistency.
There has been a number of previous studies of interraterreliability of commonly used tools, including theHendrich II Fall Risk Model (Ivziku, Matarese, & Pedone,2011; Kim, Mordiffi, Bee, Devi, & Evans, 2007;Zhang et al., 2015), the Morse Fall Scale (Chow et al.,2007; Kim et al.), the modified Morse Fall Scale (Tang,Chow, & Koh, 2014), the STRATIFY (Barker, Kamar,Graco, Lawlor, & Hill, 2011; Kim et al.), and the modifiedSTRATIFY (Barker et al.; Wong, Phillips, & Hill,2012). Of these studies, all examined the total score,except Tang et al., who examined the interrater reliabilityof each item.
The interrater reliability of individual items also hasbeen investigated in other less commonly used fall riskassessment tools. However, only three studies (Hnizdo,Archuleta, Taylor, & Kim, 2013; Vu & Mackenzie,2012; Walsh, Hill, Bennell, Vu, & Haines, 2011) followedthe recommended statistical approaches andreported a combination of assessment coefficients, suchas kappa and percentage agreement (Kottner et al.,2011). Fall risk assessment tools should not be usedsolely to predict falls during hospitalization, but alsoshould be used to guide the actions of nurses to reducethat risk (National Institute for Health and Care Excellence,2013). Nevertheless, most previous studies of thereliability of fall risk assessment tools have focused ontotal scores, with few investigating the reliability of individualitems using recommended statistical measures.The university hospital where the present study wasconducted has adopted the modified Japanese NursingAssociation’s (JNA’s) fall risk assessment tool. This toolhas good predictive validity (sensitivity 0.82, specificity0.71), but only 21 out of the 35 included items showsignificant differences among the fallers, compared withthe non-fallers (Higaonna, 2015). This modified JNAtool comprises a higher number of items, comparedwith the STRATIFY (five items; Oliver et al., 1997), theMorse Fall Scale (six items; Morse et al., 1989), and theHendrich II Fall Risk Model (eight items; Hendrichet al., 2003). Fall risk assessment tools that include ahigh number of items potentially could address morerisk factors and lead to a more comprehensive riskassessment. However, tools with a high number of itemsrequire more time to complete.
There is no well-validated fall risk assessment toolthat is currently available for use in Asia, includingJapan. With the population aging throughout theworld, there is a great need for tools that accuratelyidentify the risk factors for falls and enable healthcarestaff to intervene appropriately to reduce these risk factors.Furthermore, these tools should be easy to use andquick to administer. This study aimed to develop such atool and to establish its reliability and validity. As theanalysis for predictive validity requires a larger patientsample, it was planned to first evaluate the reliabilityand then to conduct a larger study examining the validityonce the tool had achieved a clinically acceptablelevel of reliability.The present study was conducted in two phases.Phase 1 aimed to develop an evidence-based fall riskassessment tool. Phase 2 aimed to test the interrater reliabilityof the assessment tool and to investigate its clarityand usability.
PHASE 1: DEVELOPMENT OF THE EVIDENCE-BASED FALL RISK ASSESSMENT TOOL
Methods:-The evidence-based fall risk assessment tool was developedbased on an extensive review of the relevant literatureand discussions among researchers and expertnurses. The researchers conducted a search of the JapanMedical Abstracts Society electronic database for originalarticles that had been written in Japanese or Englishand published between 2002 and April 2012. Thesearch terms were fall AND assessment AND a universityhospital OR an advanced treatment hospital. Originalresearch articles with a cohort design that reporteddata on an association between individual items of a fallrisk assessment tool and the occurrence of falls wereincluded. Studies investigating hospital inpatients in asingle clinical specialty were excluded. In addition, aprevious study that had been conducted at the authors’university hospital was included in the review(Higaonna, 2015).
The most commonly used and well-validated tools inhospitals, the Hendrich II Fall Risk Model (Hendrichet al., 2003), the Morse Fall Scale (Morse et al., 1989),and the STRATIFY (Oliver et al., 1997), also wereincluded in the review. In addition, studies of tools thathad been developed for specific populations, such asolder adults (Izumi, Makimoto, Kato, & Hiramatsu,2002) and psychiatric patients (Edmonson, Robinson,&Hughes, 2011; Itou et al., 2012), were included becausecertain risk factors need to be considered for thesepatient groups.
After all the studies for review had been selected, atable was constructed to compare the items included ineach fall risk assessment tool. All the items that hadbeen included in externally validated fall risk assessmenttools were assigned a score of one point. The PsychiatricFall Risk Assessment tool (Edmonson et al., 2011) wasnot externally validated but showed greater predictivevalidity than the Morse Fall Scale; therefore, items thatwere in this tool also were assigned a score of one point.Items in the fall risk assessment tools that had been validatedin single Japanese hospitals were scored one pointif they demonstrated a significant association with falls.For each risk item, the total scores were calculated bysumming up the points that had been assigned based onthe above mentioned rule. Although each of the identifiedrisk items was important in different clinical settings,the number of items had to be limited in order tomeet the needs of a brief assessment tool for acute caresettings. Thus, those items that scored three or morepoints – one-third of the maximum score – were consideredfor potential inclusion in the evidence-based tool,as these were more likely to generalize to varied patientpopulations. Once the items for possible inclusion in thetool had been selected based on the literature review,the researchers, the director and vice-director of thenursing department, and a hospital safety managementnurse discussed the relevance of each item in terms ofclinical nursing practice.
Results:-Among the 18 articles that had been identified by thedatabase search, two articles met the inclusion criteria(Suzuki et al., 2006; Tanaka et al., 2010). After theaddition of a study that had been conducted at the currentuniversity hospital, as well as the studies of sixother fall risk assessment tools, in total nine studieswere included in the review (Fig. S1). From these tools,60 risk items were identified (Table 1). The item fall historyobtained the highest score (eight points), followedby unstable standing/walking (seven points) and the useof assistive devices (seven points). Nineteen risk itemsthat scored three points and above were put forwardfor discussion among the researchers and nursingexperts (Table S1).
During the discussion phase of the selection process,two items (age and muscle weakness) were deleted, fouritems (delirium, behavioral and psychological symptomsof dementia [BPSD], anxious, and overestimation ofone’s ability) were added, two items (mobility assistanceand toileting assistance) were combined, and one itemwas changed from “frequent elimination” to “frequenturination.” The item “age” was deleted because the discussionpanel felt that the specific changes that arerelated to aging, such as physical and cognitive decline,should be individually assessed in order to identify theneed for preventative care. Muscle weakness wasdeleted because the item “unstable standing/walking”would identify any muscle weakness that is likely toincrease fall risk. Delirium, BPSD, anxious, and overestimationof one’s ability were added because they werecommonly observed among older inpatients and/or psychiatric inpatients. The items “mobility assistance” and “toileting assistance” were combined and renamed“patient requires assistance.” “Frequent elimination”was changed to “frequent urination” because there wasno relationship identified between the frequency ofbowel movements and fall risk, whereas there was a17–40% increase in fall risk associated with frequenturination (Parsons et al., 2009; Tanaka et al., 2011).The Edmonson Psychiatric Fall Risk Assessment toolincludes the use of psychotropic medication and assignsa higher score when the dose of medication has beenincreased or is administered as needed within a 24 hperiod. A number of studies has reported an increasedfall risk when psychotropic medications are newly prescribedor within 2–3 days of a dose increase (Echt,Samelson, Hannan, Dufour, & Berry, 2013; Lamis,Kramer, Hale, Zackula, & Berg, 2012; Neutel, Perry, &Maxwell, 2002; Sorock et al., 2009; Takahashi et al.,2011). Therefore, in the evidence-based fall risk assessmenttool, the use of hypnotics and/or psychotropicmedication was scored depending on whether the drugwas newly prescribed or the dose had been increasedwithin 2 days of assessment. In addition, the use of multiplepsychotropics was included because patients whoare taking a combination of benzodiazepines with otherpsychotropic medication have a higher incidence offalls, compared with patients taking only benzodiazepines or other psychotropic medications (Passaroet al., 2000).
On the recommendations of the expert nurses in thediscussion, the phrase “but not willing or unable to use acall light” was added to “patient requires assistance.”The expert nurses felt that it was important for certainitems to be more specific in order to highlight the needfor appropriate fall prevention measures, such as providinga patient movement alarm. The expert nurses confirmedthe clinical relevance of all the items that had beenincluded in the evidence-based fall risk assessment tool.The finalized evidence-based fall risk assessment tool considered11 risk factors and included 23 items (Table 2).
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