Application Of The Physical Mobility Scale

DOI: 02/27/2014. The patient is a 63-year-old male driver who sustained lower back injury while unloading foods and fell between the loading dock and rear trailer.

Staggs, V. S., Mion, L. C., & Shorr, R. I. (2015). Consistent Differences in Medical

Falling is a common cause of the health problem, leading to injury, hospitalization, institutionalization, and even mortality in community-dwelling older adults (1, 2). It is estimated that 30–40% of older adults experience at least 1 fall a year. This amounts to direct costs of 0.1% and 1.5%, respectively, of the total healthcare expenditures of the United States and European countries (3). Over the past few decades, a number of risk factors of falling have been identified (e.g., mobility, mental status, vision, hearing, blood pressure, hip weakness, medications, and balance control) (4-6). Prospective study also finds previous fall experience as a significant predictor of future falls (7). It is therefore important to obtain a good understanding of risk factors for falls to enable identification of targets for intervention and prevention.

Many patients admitted to the stroke and orthopedic rehabilitation unit have impaired physical mobility. The length of time in rehabilitation is ten to fourteen days. Many times nurses, patients and family members form bonds that last long after the discharge. I recently had the opportunity to take care of a patient I will never forget. Mrs. C was admitted to the rehabilitation unit following recent hip surgery. She is eighty years old and had fallen raking leaves in her front yard. Mrs. C has a history of hypertension, arthritis and gout. Medications include aspirin, metoprolol and allopurinol as needed. Prior to admission Mrs. C lived independently and has two children who checked on her routinely. No cognitive or mental deficits are noted. Key parts of this paper include the introduction, NANDA, NIC and NOC elements, data, information, knowledge and wisdom and the conclusion.

The widespread falls among the geriatric population reduce their quality of life and take away their functional independence. Lee et al (2013) state that falls leads to the rise in mortality rates and morbidity complications such as fractures and disabilities,1 out of 3 elderly persons in a community setting falls in a year. About 87% of all fractures in the elderly are due to falls. Several of the risk factors that are associated with falls are visual impairments, cognitive impairments, and health-related problems: arthritis, orthostatic, back pains, lack of balance-weakening muscles, previous falls, polypharmacy or psychoactive drugs (Lee et al, 2013).

Half of those ages over 75 years who fracture their hip as a result of a fall die within one year (Rawskey, 1998), and those who survive rarely regain complete mobility (Marotolli et al 1992). Falls are associated with major morbidity, functional decline and increased health

A study was done at a 1,300 bed urban facility over a 13-week period. The purpose of the study was to describe the causes of inpatient falls in hospitals (Hitcho, et al., 2004). All falls were reported except falls in the psychiatry service and during physical therapy sessions. During the 13-week period, a total of 183 patients at an average age of 63.4 years old fell. Of the total number of falls 79% were unassisted, 85% happened in the patient room, 59% occurred during the evening or overnight shift, 19% were while walking, and 50% were elimination related (p. 732). In this study it was identified that many patients did not use their call bell before getting up because they did not believe they needed assistance. It was stated that, “perhaps patients need to be better educated on the effects that a new environment, decreased activity, medications, tests, and treatments can have on patients’ energy and ability to ambulate safely” (p. 737). The findings of this study showed that falls not only happen in the elderly, but in the younger population as well. Patients that fall in hospitals are often unaided and are due to elimination needs. To prevent falls and decrease injury rates, more studies need to be done.

“In the United Sates, unintentional falls are the most common cause of nonfatal injuries for people older than 65 years (Hughes, 2008).” This illustrates a problem that requires addressing. “Rates of falls vary across hospitals and units however, the highest rates are found in neuroscience (6.12-8.83/1000 patient days) and medical (3.48-6.12 falls/1000 patient days) units” (Mion, 2014). Older adults are usually those most affected and their falls are

Healthcare organizations rely on incident reports for counting the frequency of falls and collecting fall-related data (Quigley, Neily, Watson, Wright, & Strobel, 2017). When a fall occurs in a healthcare organization, an incident report is completed to record the occurrence and circumstances surrounding a fall (Quigley, Neily, Watson, Wright, & Strobel, 2017). The definition of a fall is a loss of upright position (Quigley, Neily, Watson, Wright, & Strobel, 2017). A sudden, uncontrolled, unintentional, non-purposeful, downward displacement of the body to the floor, ground, or on an object (Quigley, Neily, Watson, Wright, & Strobel, 2017). When a fall occurs in a healthcare organization, an incident report is completed to record the occurrence and circumstances surrounding a fall (Quigley, Neily, Watson, Wright, & Strobel, 2017). The data might include time of day, location, activity, vital signs, and incontinence (Quigley, Neily, Watson, Wright, & Strobel, 2017). From the analysis of the data, one can determine the type of fall, such as accidental, anticipated physiological, and unanticipated physiological fall (Quigley, Neily, Watson, Wright, & Strobel, 2017). Along with the severity of the injury, minor, moderate, major, or severe, as well as to identify overall patterns and trends surrounding fall occurrence (Quigley,

Risk factors for falls are categorized by intrinsic or extrinsic (Tzeng, & Yin, 2009). According to Tzeng and Yin (2008), intrinsic factors, referring to the patient themselves, are related to their health status and possibly associated with age-related changes: previous falls, reduced vision, unsteady gait, musculoskeletal system deficits, mental status deficits, acute illness, and chronic illness. Extrinsic factors are involved in the patient’s environment, including medications, lack of support equipment, furniture, bathroom designs, small patient rooms, poor lighting, and improper use of and inadequate assistive devices. Tzeng & Yin (2008; 2009) focused on the extrinsic risk factors for the basis of their studies.

The functional independence measure (FIM) was utilized to identify patients who are at a high risk for fall and found that patients who fell had a lower admission and discharge FIM scores than the ones who had not fallen; they also found that those with lower FIM scores were stroke rehabilitation patient and had the highest rate of fall. FIM is defined as a measurement of disability specific to patients in rehabilitation; it has has 18 categories broken down into motor and cognitive components with each category scored on a scale of 1 for total dependence to 7 for total independence. The authors of the research article determined that FIM score have significance in predicting patients who are at a highest risk of falls and is more appropriate to aid in implementing interventions. With the above discovery, Salamon, Victory & Bobay (2012) undertook retrospective pilot study to compare the Morse Fall Scale scores and components of the FIM. The result from the pilot study yielded several important correlations between the Morse Fall Scale and the FIM scores. The study revealed that patient with cognitive impairments, and those with decreased ability to expressed needs are more likely to fall and no correlation with comprehension was found with the

The medical chart was used to obtain information from the time of fracture to arrival at the hospital. The type of transport to the hospital (ambulance, other); length of stay in the emergency department (ED); time from inpatient admission to surgery; duration of surgery; and type of anesthesia (general anesthesia; other type) was also used to determine this study. Weight and height were abstracted from the medical chart or, when missing, were obtained by interviewing the patient or proxy. Body mass index (BMI) was calculated from weight and height (kg/m2). History of chronic cognitive deficit was assessed from the medical chart; if missing in the chart, it was assumed to be absent. Severity of illness was measured using the Rand Sickness at

Impairments can contribute to an increased risk of falls at all stages following a stroke.2,5 As a result of these impairments, stroke has been classified as the most disabling chronic disease, with about 80% of individuals falling within the first three months from loss of balance when walking.2,5 In addition, approximately 70% of individuals who have had a stroke experience ongoing difficulty with ambulation within the first year.2 One research study revealed that patients post stroke have fall rates that range from 3.8 to 22%, and the incidence of falls range from 1.3 to 6.5 times in the year after the stroke.1 Furthermore, stroke has been identified as the primary cause of disability in the United States and the third leading cause of death in people over the age of

In the case of Anne Morrell there are several normal physiologically changes that impact her quality of life. Anne is experiencing normal aging related changes to her musculoskeletal system. Changes in musculoskeletal tissue occur through the loss of muscle mass and strength which replace lean body mass which fat and fibrous tissue. These changes in tissue cause a decrease in contractile muscle force with increased weakness and fatigue (Boltz, Capezuti, Fulmer, & Zwicker, 2012). As discussed in her case study she reports back pain when standing or walking for longer than 15 minutes, needs assistance with steps, ambulates with a cane since she fell last year which affects her mobility and ability to perform her activities of daily living. This loss in Anne’s muscle function greatly increases her chance of falls and she also has an increased risk for disability.

Some how surprisingly, not only severe injured workers show a complicated recovery process, but also minor to moderate injured persons, for example workers with bruises or simple fractures. Thus, injury severity alone can be seen as a weak predictor of the individual recovery process and as a result psychosocial variables were incorporated in the prevalent models of working disability. Based on this postulated biopsychosocial nature a short screening tool is required, which incorporates various predictive psychosocial variables and is able to identify vulnerable accident victims for a complicated recovery. This screening should guide the efforts for early preventive rehabilitation interventions, which increase the efficacy of treatment and decrease the cost burden by directing treatment according to the needs of the injured persons.