Secondary Logo

Journal Logo

Measuring subtle cognitive decline to predict fall risks

Hensley, Linda K. DNP, RN

doi: 10.1097/01.NURSE.0000580720.25145.2b

Linda K. Hensley is an associate dean and associate professor at Point Loma Nazarene University in San Diego, Calif.

The author has disclosed no financial relationships related to this article.

NURSES FACE challenges in providing a safe environment and caring for patients with unique needs daily. Publicly reported elements of patient care that are deemed the responsibility of nurses are called nursing quality indicators.1 Patient falls are one component of nursing quality indicators and have been difficult to manage historically. In response, nursing departments have instituted many efforts to reduce falls, such as ongoing fall assessments, bed exit alarms, and frequent rounding.2

At a progressive care unit in a Southern California acute care hospital, the Schmid fall risk assessment tool (Schmid) is used to assess fall risk. It examines several elements, including the patient's mentation, to arrive at a single score. The mentation assessment measures confusion, but would cognition also be a factor for these patients?3 This article examines subtle cognitive decline as a contributing factor for fall risk, identifies a potential tool for additional information on cognition, and asks whether it could assist nurses in their assessments.

Back to Top | Article Outline


The Joint Commission has identified several strategic outcomes for patient safety, including a reduced risk of patient harm from falls.4 Reducing the number of patient falls has been a patient safety goal since its inception and has become a standard of care.5 As such, fall reduction is a permanent element of patient care that must be addressed.4 Preventing falls is a priority for nurses, with the toll on patients and families providing ample motivation and incentive to develop strategies to reduce risk.

Accidental falls are the most common inpatient safety incidents reported in hospitals, resulting in injuries ranging from inconsequential to fatal.6 Falls are defined as “an unexpected event in which the participant comes to rest on the ground, floor, or lower level.”7,8 They are also associated with increased length of stay and continued isolation from families and familiar environments, resulting in prolonged rehabilitation and additional therapies to achieve functionality that may never return to baseline.7 Patients may be affected physically, psychologically, and financially.7 Approximately 80% of patient falls are not observed.6

The effects of falls can be lasting and may never resolve. These may precipitate further functional decline and lead to an ongoing cycle of falling.2,9 According to a 2012 study, patient falls in older populations may lead to “disability, fear of falling, social isolation, loss of independence, and institutionalization.”10 In older adults, fears of subsequent falls may lead to restricted activities, limited mobility, and decreased independence.2 A study found that an increased fear of falling led to a potential 20% reduction in quality of life. This finding was specific to female patients anxious about fall risk.11

The financial cost of patient falls is well documented in the literature and is often used as a benchmark in determining successful fall management.12-14 As of 2015, the CDC reported that falls cost the healthcare industry $50 billion annually.14 It is also reported that the average additional cost to hospitalization is $17,483 per fall.15 The less tangible costs to patients and their families are not as well documented, as these consequences typically occur independently of financial spreadsheets.

Institutions have had trouble reducing fall rates and the associated negative outcomes for patients and families.1,13 The Joint Commission has mandated a falls reduction plan at all healthcare facilities. Similarly, Medicare has restricted reimbursements for falls during hospitalization and the resulting patient injuries.1 Additionally, the Centers for Medicare and Medicaid Services, The Joint Commission, and the Patient Safety Network have designated patient falls as largely preventable “never events.”16

Nationally, fall rates are reported between 3 and 5 per 1,000 patient bed days.17 Many patients who fall in healthcare facilities do not experience serious injuries. Those age 65 and older make up approximately 30% of falls each year, however, and these often result in serious injury.18 Bleeding and lacerations may occur in approximately half of falls that lead to injury, a fracture or dislocation in 16%, and a contusion or hematoma in 13%.8

Hip fractures are the most significant injury, occurring in 2% to 7% of patient falls.2,6 The complications of a hip fracture may include deep vein thrombosis, catheter-related infections, pressure injuries, myocardial infarctions, and prolonged hospitalization and length of stay at long-term-care facilities to complete rehabilitation.11 These patients can also incur additional costs of approximately $30,000.14

Falls resulting in mortality occur in less than 1% of those reported.7,14 For older adults, however, mortality rates from falls increased by 30% between 2007 and 2016. Research must be initiated to better assess patients for fall risk and take the necessary steps for prevention in acute care settings.

Many interventions can be used to prevent falls.17,19 For example, patients may be asked to notify the nursing staff when they would like to leave their bed, rather than trying to ambulate independently and overestimating their ability. This relates to a patient's decision-making ability and may be influenced by his or her cognitive function.

Back to Top | Article Outline

Assessment tools

Fall risk assessments describe the process of identifying patients with a combination of individual factors that may increase the likelihood of a fall.20 Additional factors can influence falls, but these are difficult to assess.6 Examples include any risky or impulsive behaviors from patients, which may not be defined clearly in the literature but are still viewed as factors in determining patient risk. The patient's mental state and cognition have also been identified as factors related to falls; however, these are not specifically assessed on the Schmid.7

This improvement project incorporated the Schmid, nursing assessments, and the Mini Mental State Examination (MMSE). The Schmid provides a broad assessment, separating patients into two broad categories: “fall risk” and “not fall risk.” It was developed in response to unacceptable fall rates at a large naval hospital as a tool for better assessments. It consists of five components weighted to achieve a final score: mobility, mentation, elimination, fall history, and current medications.3 Scores range between 0 and 6 with higher numbers indicating an increased fall risk. While a maximum score of 6 is possible, a score of 3 indicates increased risk for a fall.3

The Schmid includes several additional considerations, such as age 65 years or older, orthostasis, hypotension, hypoglycemia, and medications associated with fall risk. These undefined measures are anecdotally considered at the discretion of the nurse and may influence the total Schmid score, but they are not supported in a quantifiable or consistent manner.3

This project focused on the patient mentation component of the Schmid and asserted subtle cognitive change as an influencing factor for fall risks. To determine patient mentation, nurses are presented with with four choices:3

  • alert and oriented
  • periodic confusion
  • confusion at all times
  • comatose and/or unresponsive.

From its inception, the Schmid has not provided descriptive definitions or criteria for each mentation item.3 Without guidance, decisions regarding what constitutes confusion have ultimately been left to the discretion of individual nurses. As nurses may have varying experiences and backgrounds influencing their assessment, this lack of objective criteria could be potentially problematic.

Confusion is considered a separate scored item on the Schmid and a significant factor contributing to fall risk.3,21 A systematic retrospective review of the literature found the validity and reliability of the Schmid to be well established.9 However, subtle cognitive decline is a different phenomenon.21 While many assessment tools identify confusion as a factor in fall risks, none of these assess for subtle cognitive decline as well.22

A complete nursing assessment, including a neurologic exam, was also conducted by nurses on each shift. The neurologic exam included the assessment of cranial nerve function, mobility and motor deficits, and simple orientation questions such as “What day is it?” and “Where are you?” to provide an overall impression of patient status. This exam was completed as a separate assessment from the mentation component on the Schmid. Additionally, the nurses evaluated other factors, including symptomatic orthostatic hypotension and hypoglycemia or difficulty managing blood glucose. These items were combined with the Schmid score to achieve a final fall risk assessment.

TheMMSE is a known, validated, reliable, and quantifiable method typically used to screen for dementia or Alzheimer disease.23 It is an 11-question test that measures five areas of cognitive functioning: orientation, registration, attention and calculation, recall, and language.23

A less common application of the MMSE is the assessment of subtle cognitive decline. Cognitive decline is associated with known fall risk factors, including medical conditions, balance and gait, strength, and visual ability.25 The MMSE is scored from 1 to 30, and patients who score between 24 and 28 may exhibit signs of subtle cognitive decline and have an increased risk of falling.24

Three ranges were identified and evaluated in this project:24

  • 29 to 30: without cognitive decline
  • 24 to 28: with cognitive decline
  • less than 24: associated with dementia.

A secondary analysis of a previously conducted randomized clinical study on the relationship between subtle cognitive decline and increased fall risk found a predictive relationship between fall rates and MMSE scores between 24 and 28.24 Additionally, patients who scored below 28 were at almost a threefold increased risk for falls compared with those who scored 30 in this study.

Combining the MMSE and the Schmid may benefit healthcare facilities as a strategy for increased accuracy in evaluating patients for fall risks. This project was designed to identify patients who may be at risk for falls but are objectively difficult to identify due to the absence of previously diagnosed dementia.

Back to Top | Article Outline

Implementation and analysis

This performance improvement project incorporated elements of a cross-sectional design. It compared the Schmid, the MMSE, and nursing assessments to determine what combination would yield optimal results in assessing for fall risk.26,27 Each patient was evaluated once within 24 hours of admission, and data collection occurred over 7 weeks. Institutional Review Board approval was obtained from the hospital facility in accordance with subject protection.

Patients received the current standard of care according to their score on the Schmid. Per facility protocol, a fall prevention plan was implemented for patients with a score of three or higher on the Schmid. The MMSE was utilized as a screening tool administered to an identified patient population.

Back to Top | Article Outline


The project proposed that patients with subtle cognitive decline are at an increased risk for falls. It examined 100 patients and medical records related to fall risk documentation and MMSE scoring. Subtle cognitive decline may have an influential role, but further research is required.

Upon examination, the data demonstrated that patients who were not designated as at risk for falls according to Schmid scoring demonstrated an MMSE score of 27/30, which is close to normal cognitive status. While an MMSE score between 24 and 28 is recognized as subtle cognitive decline, this range may be overly sensitive in determining fall risk correlating to cognitive status alone. If most patients are designated as at risk for falls, it becomes a nursing challenge to enhance interventions for those truly at risk.

Some studies recognize cognitive decline at the cutoff score of 23/30 or 24/30 of the MMSE assessment and base recommendations on this score.28 Accordingly, patients were considered at risk for falls if they had an MMSE score of less than 23/30. These same patients scored somewhere between “alert and oriented” and “periodically confused” on the Schmid. If all the other elements were within normal limits on the Schmid, however, being periodically confused alone would not designate patients as at risk.

This project indicated that nurses were twice as likely to assess patients as at risk for falls compared with the Schmid. The nursing staff may have incorporated unspecified data into their assessments that were not present on the Schmid but may be reflected in the MMSE. These data, which cannot be quantified objectively, leave decisions up to individual nurses and may lead to inconsistencies.

Back to Top | Article Outline


The MMSE and the Schmid are well-recognized tools, and each evaluates important aspects of patient status. The MMSE is specific to cognitive assessment only and lacks the breadth of assessment categories found in the Schmid assessment. The Schmid includes a score on mentation, but it assesses only whether a patient is awake and alert and the different levels of confusion. It does not assess for cognition beyond the element of confusion. Nursing assessments included multiple pieces of data, such as a neurologic evaluation, the nurse's impression, and adjunctive factors such as hypotension and medications.

During this project, the Schmid identified the least number of patients to be at risk for falls. Surprisingly, the MMSE identified almost all patients to be at some level of cognitive decline within the first 24 hours of admission. Finally, nursing assessments found patients to be at risk twice as often as the Schmid alone. How does this happen? If nurses assess patients based on unscored or anecdotal data, healthcare organizations must consider the specific indicators nurses may notice that are not captured in current fall assessment tools.

Back to Top | Article Outline


Implementing fall risk measures for every patient may not represent the best use of clinical resources. Increasing numbers of patients being assessed as at risk for falls are a natural consequence when nurses use data that cannot be quantified. Nurses often indicate that they know a patient is at risk despite the assessment score.

The results indicated that the Schmid identified at-risk patients, but the nursing staff was able to recognize additional patients anecdotally. The nurses identified mentation as the most common risk factor for falls, but their assessments were subjective. Conversely, the MMSE objectively assessed patients for cognitive decline, which was correlated to the mentation component. In adding to nursing assessments on admission, several elements must be considered. The MMSE takes approximately 15 minutes to complete, the scoring is straightforward, and staff education and implementation costs less than one hip fracture, the most common significant injury related to patient falls.2,6

Many fall risk and cognitive assessment tools are available. This project investigated the implementation of the MMSE as a supplementary fall risk assessment within 24 hours of admission and proposes reassessment with a change in patient condition. Additional recommendations would include the auto population of previous falls onto the fall risk assessment from the electronic health record, as well as any known sedatives or antiepileptic drugs for convenience without a time-consuming review of the medication record or shift report.

Back to Top | Article Outline


Unfortunately, no single tool addresses every aspect of fall risk. Although the Schmid is a respected method that evaluates broad categories of fall assessment, the mentation category is limited in providing a detailed patient assessment. The MMSE offers a more detailed and comprehensive assessment of overall cognition, which may complement the Schmid in assessing for fall risk. Further research may help fill this gap in assessment accuracy.

Back to Top | Article Outline


1. Inouye SK, Brown CJ, Tinetti ME. Medicare nonpayment, hospital falls, and unintended consequences. N Engl J Med. 2009;360(23):2390–2393.
2. Rawsky E. Review of the literature on falls among the elderly. Image J Nurs Sch. 1998;30(1):47–52.
3. Schmid NA. 1989 Federal Nursing Service Award Winner. Reducing patient falls: a research-based comprehensive fall prevention program. Mil Med. 1990;155(5):202–207.
4. The Joint Commission. Hospital accreditation. 2019.
6. Oliver D. Preventing falls and falls-injuries in hospitals and long-term care facilities. Rev Clin Gerontol. 2008;17:75–91.
7. Bemis-Dougherty A, Delaune MF. Reducing patient falls in inpatient settings. PT Mag. 2008;16(1):73–82.
8. Gray-Miceli D. Preventing falls in acute care. In: Evidence-Based Geriatric Nursing Protocols for Best Practice. 3rd ed. New York, NY: Springer Publishing Company, LLC; 2008:161–202.
9. Oliver D, Daly F, Martin FC, McMurdo ME. Risk factors and risk assessment tools for falls in hospital in-patients: a systematic review. Age Ageing. 2004;33(2):122–130.
10. Boye ND, Van Lieshout E, Van Beeck EF, Hartholt KA, Van der Cammen TJ, Patka P. The impact of falls in the elderly. Trauma. 2012;15(1):29–35.
11. Iglesias CP, Manca A, Torgerson DJ. The health-related quality of life and cost implications of falls in elderly women. Osteoporos Int. 2009;20(6):869–878.
12. The Joint Commission. Sentinel Event Alert 55: Preventing falls and fall-related injuries in health care facilities. 2015.
13. Miake-Lye IM, Hempel S, Ganz DA, Shekelle PG. Inpatient fall prevention programs as a patient safety strategy: a systematic review. Ann Intern Med. 2013;158(5 Pt 2):390–396.
14. Centers for Disease Control and Prevention. Important facts about falls. 2017.
15. Trepanier S, Hilsenbeck J. A hospital system approach at decreasing falls with injuries and cost. Nurs Econ. 2014;32(3):135–141.
16. Agency for Healthcare Research and Quality. Patient safety primer: never events. PSNet. 2019. https://psnet.ahrq.gove/primers/primer/3/Never-Events.
17. Agency for Healthcare Research and Quality. Falls. Patient Safety Network. 2019.
18. Florence CS, Bergen G, Atherly A, Burns E, Stevens J, Drake C. Medical costs of fatal and nonfatal falls in older adults. J Am Geriatr Soc. 2018;66(4):693–698.
19. Agency for Healthcare Research and Quality. Patient safety primer: falls. PSNet. 2019.
20. Haines TP, Hill K, Walsh W, Osborne R. Design-related bias in hospital fall risk screening tool predictive accuracy evaluations: systematic review and meta-analysis. J Gerontol A Biol Sci Med Sci. 2007;62(6):664–672.
21. Aird T, McIntosh M. Nursing tools and strategies to assess cognition and confusion. Br J Nurs. 2004;13(10):621–626.
22. Myers H. Hospital fall risk assessment tools: a critique of the literature. Int J Nurs Pract. 2003;9(4):223–235.
23. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–198.
24. Gleason CE, Gangnon RE, Fischer BL, Mahoney JE. Increased risk for falling associated with subtle cognitive impairment: secondary analysis of a randomized clinical trial. Dement Geriatr Cogn Disord. 2009;27(6):557–563.
25. Anstey KJ, von Sanden C, Luszcz MA. An 8-year prospective study of the relationship between cognitive performance and falling in very old adults. J Am Geriatr Soc. 2006;54(8):1169–1176.
26. Mateo MA, Kirchhoff KT, eds. Research for Advanced Practice Nurses. New York, NY: Springer Publishing Company, LLC; 2009.
27. Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract. 2004;10(2):307–312.
28. Olin JT, Zelinski EM. The 12-month reliability of the mini-mental state examination. J Consult Clin Psychol. 1991;3(3):427–432.
Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.