Residents Who Will Benefit
The present project aims to contribute to the well-being and health of residents in long-term care facilities. These residents might include elderly persons, persons with disabilities, as well as persons with various chronic diseases. The project will be especially beneficial for residents with impaired balance and gait, as they are at a higher risk for falls (Ambrose, Paul, & Hausdorff, 2013).
Types of Clinical and Administrative Staff, Suppliers, etc. Involved
The project will involve various administrative and clinical staff, including the facility’s management, staff managers, and staff.
Problem/Opportunity Statement
Patient falls are a major healthcare concern, both in Canada and in other parts of the world. They are particularly widespread among older patients, who are the primary residents of long-term care facilities. According to Accreditation Canada, the Canadian Institute for Health Information, and the Canadian Patient Safety Institute (Accreditation Canada, CIHI, & CPSI, 2014), fall-related hospitalization rate was at 16 per 1,000 seniors in 2013, with 17% of hospitalizations resulting from falls in residential institutions. Apart from hospitalizations and health complications, patient falls also create a burden on Canada’s healthcare system. Accreditation Canada et al. (2014) note that the estimated annual cost of falls is $2 billion. Reducing patient falls is thus a major opportunity for improving quality of care and patient outcomes, as well as reducing costs of health care.
Aim Statement
The project will try to accomplish a considerable reduction in the incidence of patient falls. A 60% decrease in patient falls within one year is the target outcome of the study. The rationale for this target is based on two factors. Firstly, the project only targets falls that occur near the bed, and thus falls in other areas could still contribute to the overall incidence. Secondly, the plan does not include additional interventions for preventing patient falls. As shown by Sahota et al. (2014), in the absence of a comprehensive approach to fall prevention, the effect of bed sensor alarms may be limited. A period of one year will be sufficient to judge the outcomes of the intervention.
Measures
As with any institutionalized interventions, the project will require several measures for determining the results. Although the focus will be on patient falls as the primary outcome of the intervention, it will be necessary to include process and balancing measures to track the progress.
Outcome Measures
The main outcome measure is the incidence of patient falls in a given period. This is a numerical measure that can be evaluated based on patient’s medical records and institution’s records. The project will require medical staff to document cases of patient falls, as well as their location and consequences (hospitalization or on-site treatment), which will help to obtain a clear picture of the outcomes.
Process Measures
The two main process measures in the proposed project would be the number of alarms triggered by the sensors and the number of falls prevented as a result of alarms. According to Moore et al. (2015), quantitative process measures help to control the effect of the intervention on outcome variables. In the present case, for instance, patient falls would depend on the staff’s response to alarms. By collecting data on the number of alarms triggered by the bed sensors, as well as the number of falls effectively prevented after an alarm, it would be possible to determine potential obstacles to effectiveness.
Balancing Measures
Balancing measures are an essential concern since they help to ensure that the intervention can be applied in the long term. Quigley and White (2013) explain that balancing measures assess the effect of the project on areas besides the target outcomes. For example, in the present case, the focus is on patient falls. However, when implementing an intervention, it is essential to ensure that it does not affect other aspects of care provided in the facility. Staff and patient satisfaction would thus be the key balancing measures in the proposed intervention.
A patient satisfaction survey is required to ensure that the quality of care and service provided did not decrease as a result of the intervention. Staff satisfaction with the intervention, on the other hand, would determine whether there were any organizational problems triggered by the intervention, such as unmanageable workload, poor coordination among staff, and more. As shown by Eakin, Ugbah, Arnautovic, Parker, and Needham (2015), increased staff workload is a common barrier to clinical interventions. When designing a survey for the staff, it would be useful to add a qualitative component by including a box for additional comments. In this way, the staff will be able to highlight the benefits or drawbacks of the intervention, which could be taken into account for future development.
Change Ideas
The proposed change is the use of bed sensor alarms that will alert the staff when the patient is at risk for falling. The sensors will be located on patient beds and connected to an electronic watch worn by the staff. When the patient is at risk of falling, the watch will buzz and indicate the room number, so that the nearest staff member could reach the patient on time. Numerousstudiesin America, Europe, and Asia investigated the use of bed alarms in reducing patient falls (Wong Shee, Phillips, Hill, & Dodd, 2014; Wolf, Hetzer, Zu Schwabedissen, Wiese, & Marschollek, 2013; Kim & Mariano, 2014). Researching the application of this method in Canada could provide a feasible solution to the problem, improving patient outcomes and reducing healthcare costs.
Business Case
Addressing the problem of patient falls will reduce the health system costs associated with it. By preventing patient falls, the intervention will also help to avoid the costs related to the management of injuries, such as X-Ray, computer tomography, and hospitalization. A study of fall prevention programs performed by Trepanier and Hilsenbeck (2014) showed that, over a 2-year period, hospitals implementing a fall prevention program saved about $776,064 on injury treatment and diagnostics. However, as noted by Spetz, Brown, and Aydin (2015), in order to achieve a significant cost reduction, it is essential to ensure that the costs of the intervention are adequate. In the present case, project costs will be minimal compared to anticipated benefits associated with it.
Link to LTC Organizational Strategy
LTC organizational strategy requires the use of evidence-based practices and innovation for improving the quality of service provided to residents. It is also concerned with reducing costs in the long-term. The present project applies to the LTC organizational strategy, as it will provide an evidence-based foundation for using a new intervention, which, in turn, would reduce health care costs for the facility.
Term of Project
Start Date: August 1, 2018
End Date: September 31, 2019
Project Budget
The budget of the project will be approximately $8500, which includes:
- Watch and alarm cost – $700 per staff (10 per shift)
- Training – $200
- Maintenance and replacement (if needed) – $1300
However, the estimated benefits of the project will be higher than the costs involved. In case of an injury, the cost of one X-Ray is $500, the cost of a CT scan is $1200, and the treatment of a broken hip could be up to $20,000. Thus, the project will ensure cost savings by preventing expenditures associated with injuries from falls.
Anticipated Milestones
- Installation of alarms;
- Purchase of electronic watches;
- Pre-intervention staff and patient surveys;
- Training of staff;
- Collection of results at 6 months and 1 year;
- Post-intervention staff and patient surveys;
- Data analysis;
- Publication of results.
Estimated Time Required for Staff Participation
Staff participation will be required during the preliminary, intervention, and data collection stages of the project. Thus, the maximum time necessary for staff participation will be 14 months. However, during the preliminary and data collection stages, minimal staff involvement will be required, and it will not affect their workload.
References
Accreditation Canada, Canadian Institute for Health Information and Canadian Patient Safety Institute (Accreditation Canada, CIHI, & CPSI). (2014). Preventing falls: From evidence to improvement in Canadian health care. Web.
Ambrose, A. F., Paul, G., & Hausdorff, J. M. (2013). Risk factors for falls among older adults: A review of the literature. Maturitas, 75(1), 51-61.
Eakin, M. N., Ugbah, L., Arnautovic, T., Parker, A. M., & Needham, D. M. (2015). Implementing and sustaining an early rehabilitation program in a medical intensive care unit: A qualitative analysis. Journal of Critical Care, 30(4), 698-704.
Hempel, S., Newberry, S., Wang, Z., Booth, M., Shanman, R., Johnsen, B.,… Ganz, D. A. (2013). Hospital fall prevention: A systematic review of implementation, components, adherence, and effectiveness. Journal of the American Geriatrics Society, 61(4), 483-494.
Kim, T. E., & Mariano, E. R. (2014). Developing a multidisciplinary fall reduction program for lower-extremity joint arthroplasty patients. Anesthesiology Clinics, 32(4), 853-864.
Kosse, N. M., Brands, K., Bauer, J. M., Hortobágyi, T., & Lamoth, C. J. (2013). Sensor technologies aiming at fall prevention in institutionalized old adults: A synthesis of current knowledge. International Journal of Medical Informatics, 82(9), 743-752.
Moore, G. F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W.,… Baird, J. (2015). Process evaluation of complex interventions: Medical Research Council guidance. BMJ, 350(1), 1258-1264.
Quigley, P., & White, S. (2013). Hospital-based fall program measurement and improvement in high reliability organizations. OJIN: The Online Journal of Issues in Nursing, 18(2). Web.
Sahota, O., Drummond, A., Kendrick, D., Grainge, M. J., Vass, C., Sach, T.,… Avis, M. (2013). REFINE (REducing Falls in In-patieNt Elderly) using bed and bedside chair pressure sensors linked to radio-pagers in acute hospital care: a randomised controlled trial. Age and Ageing, 43(2), 247-253.
Spetz, J., Brown, D. S., & Aydin, C. (2015). The economics of preventing hospital falls: Demonstrating ROI through a simple model. Journal of Nursing Administration, 45(1), 50-57.
Trepanier, S., & Hilsenbeck, J. (2014). A hospital system approach at decreasing falls with injuries and cost. Nursing Economics, 32(3), 135-141.
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.
Wolf, K. H., Hetzer, K., Zu Schwabedissen, H. M., Wiese, B., & Marschollek, M. (2013). Development and pilot study of a bed-exit alarm based on a body-worn accelerometer. Zeitschrift für Gerontologie und Geriatrie, 46(8), 727-733.
Wong Shee, A., Phillips, B., Hill, K., & Dodd, K. (2014). Feasibility, acceptability, and effectiveness of an electronic sensor bed/chair alarm in reducing falls in patients with cognitive impairment in a subacute ward. Journal of Nursing Care Quality, 29(3), 253-262.