Inpatient Falls In The Elderly Health And Social Care Essay

Inpatient Falls In The Elderly Health And Social Care Essay As in common with other European countries, the population of 65 years and above in the UK is predicted to increase from 16% in 2008 to 23% by 2033 .(Statistics, 2009)With the increasing population of elderly people, falls has become a major public health problem .(Masud and Morris, 2001). Falls and its related injuries can result in considerable negative effects for example mortality, morbidity and suffering physical and mental stress for older people and social and financial burden their family.(Skelton and Todd, 2004). Falls can also increase health care costs for hospitals and social services. In 2004-05, 60% of all cases from hospitals related to falls in the UK(Oliver.D et al., 2007). Approximately 30% of people aged over 65 years (Skelton and Todd, 2004)and 50% of people over 80 years(INSTITUTE, 1998) suffer at least one fall per year. Among them, 30% of elderly falls result in physical injury with 4% to 5 % having serious injuries(Nakai et al., 2006). Moreover, falls are the commonest cause of injury-related death in people over 75 years.(Masud and Morris, 2001). Inpatient falls Interestingly, falling rates vary across different settings(Sherrington.C et al., 2001). The incidence of elderly patients falling is almost 3 times higher in hospital and health care institutions than in those living in the community(American Geriatrics Society and American Academy of Orthopaedic Surgeons Panel on Falls, 2001).According to hospital statistics, inpatient falls are the commonest adverse events in hospital reports(Terrell et al., 2009). In the UK, 98% of NHS organisations providing inpatient care reported over 200,000 falls during a year period from September 2005 to August 2006. There are approximately 4.8 falls for every 1000 bed days.(Vass.C et al., 2009) 50% of elderly patient falls occur at the bedside(INSTITUTE, 1998) .There are many intrinsic factors attributed to inpatient falls such as patients age, level of orientation, underlying disease, drug history, gait and stability, bowel and bladder problems. Extrinsic factors can also affect inpatient falls for example- hospital equipment, patients room lighting and level of staff provided etc.(Tzeng et al., 2008) Elderly in-patient falls in hospital affect both patients and health service organisations. Patients can suffer serious injuries including fractures, subdural haematoma , excessive bleeding and even death(Hitcho et al., 2004). Falls can also have psychological consequences such as fear of falling, and loss of confidence that can result in poor quality of life(Gillespie. LD et al., 2009). Falls can be costly to health sector organisations and in 1999, cost  £ 981 million in NHS and Personal Social Services (Skelton and Todd, 2004). Thus, prevention of falls in the hospital setting is a major public health issue concerning patient safety, quality and cost-effectiveness of health sectors(Nakai et al., 2006, Hitcho et al., 2004). Falls and their related injuries are complex and falling is a multifactorial phenomenon (Sherrington.C et al., 2001). .It is needed to understand more about the important risk factors of inpatient falls and see if they can be managed better on the ward. Previous researches also suggested to identify those who are at risk of falling in hospitals. Aim of the study to describe the pattern of falls among the inpatients in the Elderly wards of Nottingham University Hospital, NHS trust Objectives of the study to describe the demographic characteristics of inpatients who fall to identify the time and location of the inpatient fall to describe the nature of injury due to fall to specifically examine the movement of patients who fell (two hours before and after the incident) to identify the level of staffing at the time of when the inpatient fall occurred Methods The Data set The REFINE study is a randomised control trial which aims to reduce inpatient fall successfully and cost-effectively by using pressure sensor-pager technology. This detects pressure changes when the patient moves from the bed or bedside chair and then activates an alarm to a handled pager carried by nursing staff. Patients from five acute elderly wards in Nottingham University Hospital, NHS Trust are eligible for this study. Patients are randomised to pressure sensors or to usual care (i.e no alarm). Patients who are randomised to the intervention arm receive bedside chair and bed pressure sensors for the duration of their hospital stay. Patients who are permanently bed bound before admission, unconscious or receiving terminal care or previously participated in the study in an earlier admission are excluded from the study. This trial commenced in November 2008. From this time onwards, approximately 44 cases of inpatient falls has occurred among both arms of the study. Baseline data is collected by face to face interview or from patients medical and nursing notes and /or carer . These data involve demographic and residential details, reasons for admission, time of admission ,previous history of fall and fracture, mobility and transfer before the illness(measured by the Barthel ADL index), 30 point Mini Mental Stare examination and Health related quality of life measured using the EuroQol EQ -5D. Study population The cases of inpatient falls from the intervention arm which have already been documented in the REFINE trial from the time of commencement to January 2010 will be the study population of this study. Method 1 : For the objective 1 Demographic data of the particular fall patient including- age, sex, previous medical history, previous history of fall, reason for admission an residential detail will be used from baseline data recorded in the REFINE trial. Method 2 : For the objective 2 Time of the inpatient fall is recorded by the pressure sensor output. Both time and location of the inpatient fall are noted down in the patient safety incident form by the nurse. The author will use these incident forms of REFINE dataset to identify this. Method 3 : For the objective 3 The nature of injury due to fall in this study will be classified into abrasion, bruise, swelling, cut, laceration, dislocation, fracture or muscle sprain or strain. This information is also recorded in the patient incident form where the author will collect. Method 4 : For the objective 4 The frequency of position changes of the patients who fell including off and on the bed and bedside chair will be examined from 2 hours before and 2 hours after the fall. The sensor output will be used to obtain these data. Method 5 : For the objective 5 Number and skill mix of ward staff at the time of occurrence of the inpatient fall will be described by using the duty roster of staff. Analysis All analyses will be performed using SPSS version 16.0.Descriptive analysis will be conducted first to explore the characteristics of the study participants. Mean, standard deviation or median and IQ ranges will be used to summarise the continuous data such as age and time when fall happened. Binary variables such as sex will be summarised by proportion or percentage. Residential detail will be categorised into three groups as follows- home, nursing institutions and transfer from other wards such as surgical wards and then will be summarised by percent. Approximations of the risk of fall with P-value, Chi-square and Chi-square test for trends will be calculated among categorical variables such as sex, residential details. Fisher exact test will be used when Chi-square test is not appropriate Ethics Written, informed consent has already been obtained from the patients, or from ward staff if the patients were unable to understand the nature of consenting to research. The REFINE study was approved by Nottingham Research Ethics Committee 1 on 23rd May 2008. Time Table 21st January Peer review of the project 9th February Final protocol completed.(Landmark 2) From Landmark 2 to mid April Activity Initial Descriptive and simple analysis of data and writing literature review Output- Draft Literature review to supervisors From mid April to June 3rd Activity further analysis of dataset Output- Initial result of data analysis and poster/presentation of the project conference on 3rd June From 4th June to the end of June Activity write methods and result section , consider study findings, implications, weakness and strengths Output- First draft of method and result section to supervisors From 1st July to mid July Activity write the discussion Output- first draft of complete dissertation to supervisors From mid July to 16th August Activity Improving draft with support from supervisor Output final dissertation completed.