


The Quality Improvement Program for Missouri's Long - Term Care Facilities (QIPMO) is committed to Missouri's Elderly.
The "Aging-in-place" model allows older adults to receive health care in their preferred place of living, eliminating the need for a more restricted living space, such as a nursing home.
TigerPlace is a specially designed elder housing project initiated by the MU Sinclair School of Nursing, working to provide elders a better quality of life.
Interdisciplinary research is a major focus for MU faculty and many have come together to focus their research expertise on improving the lives of older people. There are several large research projects funded by the National Institutes of Health (NIH), National Science Foundation (NSF), and Agency for Healthcare Research and Quality (AHRQ) underway developing and applying technology to help the residents of TigerPlace age in place. Research teams are pursuing multiple ways to measure physical function, detect falls, and early illness recognition. Grant proposals to NIH, NSF, AHRQ, and other funding agencies are continuously under development with PIs from our multidisciplinary team.
Our team has developed a technological innovation that detects changes in health
status that indicate impending acute illness or exacerbation of chronic illness before usual assessment methods or self-reports of illness. We successfully used this information in a 1-year prospective study to alert health care providers so they could readily assess the situation and initiate early treatment to improve functional independence. Intervention participants showed significant improvements (as compared with the control group) for the Short Physical Performance Battery gaitspeed score at Quarter 3 (p = 0.03), hand grip-left at Quarter 2 (p = 0.02), hand gripright at Quarter 4 (p = 0.05), and the GAITRite functional ambulation profile score at Quarter 2 (p = 0.05). Technological methods such as these could be widely adopted in older adult housing, long-term care settings, and in private homes where older adults wish to remain independent for as long as possible.
Background: Effectiveness of clinical information systems to improve nursing and patient outcomes depends on human factors including system usability, organizational workflow, and user satisfaction.
Objective: The specific aim of this research is to examine to what extent residents, family members, and clinicians find a sensor data interface used to monitor elder activity levels usable and useful in an independent living setting.
Methods: Three independent expert reviewers conducted an initial heuristic evaluation. Subsequently, 20 end users: 5 residents, 5 family members, 5 registered nurses, and 5 physicians participated in evaluation. During the evaluation each participant was asked to complete three scenarios taken from three residents. Morae recorder software was used to capture data during the user interactions.
Results: The heuristic evaluation resulted in 26 recommendations for interface improvement; these were classified under the headings content, aesthetic appeal, navigation, and architecture which were derived from heuristic results. Total time for elderly residents to complete scenarios was much greater than other users. Family members spent more time than clinicians, but less time than residents to
complete scenarios. Elder residents and family members had difficulty interpreting clinical data and graphs, experienced information overload, and did not understand terminology. All users found the sensor data interface useful for identifying changing resident activities.
Discussion: Older adult users have special needs that should be addressed when designing clinical interfaces for them, especially information as important as health information. Evaluating human factors during user interactions with clinical information systems should be a requirement before implementation.
The paper describes the evolution of an early illness warning system used by an interdisciplinary team composed of clinicians and engineers in an independent living facility called TigerPlace. The early illness warning system consists of algorithms which analyze resident activity patterns obtained from sensors embedded in residents’ apartments. The engineers designed an automated reasoning system to generate clinically relevant alerts which are sent to clinicians when significant changes occur in the sensor data, for example declining activity levels. During January 2010 through July 2010 clinicians and engineers conducted weekly iterative review cycles of the early illness warning system to discuss concerns about the functionality of the warning system, to recommend solutions for the concerns, and to evaluate the implementation of the solutions. A total of 45 concerns were reviewed during this period. Iterative reviews resulted in greater efficiencies and satisfaction for clinician users who were monitoring elder activity patterns.
Key Words: Human Factors, Information Technology, Patient Safety, Patient Care, Gerontology
It appears that implementation and use of bedside electronic medical record (EMR) in nursing homes can be a strategy to improve quality of care and staff like using the bedside EMR and believe it is beneficial. Information gleaned from this qualitative evaluation of 4 nursing homes that implemented complete electronic medical records (EMRs) and participated in a larger evaluation of the use of EMR will be useful to other nursing homes as they consider implementing bedside computing technology. Nursing home owners and administrators will need to be prepared to undertake a major change that will take many months of planning to successfully implement. Direct care staff will need support as they learn to use the equipment, especially for the first 6 to 12 months post-implementation. There needs to be a careful plan for continuing education opportunities so that staff learn to properly use the software and can benefit from the technology. After 12 to 24 months, almost no one wants to return to the era of paper charting.