What Analytics are Useful for Caregivers to Address the Challenges?

What Analytics are Useful for Caregivers to Address the Challenges?

Physical safety is one of the critical issue that caregivers need to address using appropriate text analytic mechanisms to improve the outcome of the patients. Automation of the manual record review is a significant text analytic tool which will enhance the responsiveness of the caregivers in the event of an emergency. Elderly people living alone usually embark on heavy tasks which render them vulnerable to injuries or fall without immediate attention. Without a proper mechanism of notifying caregivers promptly, the victims will receive a delayed medical care which can deteriorate their health. Automation of the manual records will shorten the time span between patient registration and adverse effects monitoring. Adopting a suitable text analytic software and technologies enable caregivers to ensure there is a thorough evaluation of the records of the patients.

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Creation of the precise patient registries is another text analytics approach which can enable caregivers to overcome the highlighted challenges. Caregiver report data, which is collected for every visit comprises of the information on medicines, health issues, well-being and the notes on the behaviors of the patients. Under this scenario, the caregivers should limit their reliance manual curated patient registries and dependence on coded data, just like it is the case with different health systems, instead, the caregivers should improve the accessibility of the text analytics tools. Current patient (registry) contains the entries such as attribute name (s_id, date, Notes), description and data types (ID, date_time, textual). These entries do not allow for the sufficient data collection needed by caregivers to cater for the patients.

Optimization of the text search is another text analytic mechanism that can be useful to the caregivers in addressing the outlined challenges. The search technology used by caregivers should be interactive and accessible to enhance solving of text analytic problems. The text search model should include elements such as a display, medical termination, and the context. This will improve caregivers to search and analyze for the specific information of the patients (seniors). For example, caregivers are supposed to deal with nutrition issues where the patient fails to prepare nutritious meals, thus resulting in health conditions or failing to receive the much-needed attention. Through optimized text search tool, the caregivers will receive prompt notifications, hence avoiding a situation where the victims receive a delayed medical care.

Medical terminologies, incorporated in the search tools and technology will provide caregivers with options and suggestions on the health conditions associated with their assigned patients. It is revealed that some of the patients were experiencing memory problems, which included Failure to turn off stoves, heaters, irons and other appliances that can cause house fires is more common in the elderly. Smokers who forget to put out cigarettes, pipes, and cigars may also be in danger. Forgetting to pay bills, perform tasks of basic hygiene, and to take medications on time and in appropriate doses are other concerns for memory-impaired people living alone. For instance, the inclusion of the terms such as 'memory loss' will enable caregivers easily search for the attributes and context of the eldercare.

Implementing of the text analytic approaches such as Automation of the manual record review, creation of the precise patient and optimization of the text search are useful in helping caregivers receive a prompt notification which can alleviate issues of delayed medical attention when delivering eldercare services. Such text analytic features are vital in facilitating representation of the patient's key attributes such as ID, date, and notes as the list of words, ultimately improving the response and timespan required by caregivers to provide elders with the needed medical attention.

What Analytics are Useful for Healthcare Professionals to Address the Challenges?

Predictive analytics can be useful to the healthcare professionals since they increase the accuracy of the diagnoses. Nutrition and memory problems are some of the challenges undermining the well-being of the senior citizens in Singapore. Nurses and caregivers have been given the task of overseeing the functionalities of the programs that support community-based personal care services which are relatively expensive. This implies that majority of the elders in the society are living alone and are prone to health-related complications emanating from memory loss and poor nutrition. Healthcare professionals can utilize text analytics such as predictive analytics to resolve issues of late notifications that often result in delayed medical attention.

The physicians and nurses assigned the task of providing healthcare to a particular group of patients can use predictive algorithms to enable them to make accurate treatment. For example, when the elderly people are brought to ER with health complications such as chest pain and malnutrition, it can be difficult to decide whether or not they should be hospitalized. Under such context, doctor's ability to make clinical judgment can be enhanced with the aid of a predictive algorithm. Text analytics is also useful in providing healthcare professionals with solutions they are seeking for particular patients. Text analytics (predictive algorithms) are the form of evidence-based medicine (EBM), which works best when the patients are seeking specified treatment. From this case, the elderly people are at increased risk of developing health complications such as physical injuries due to less medical attention. The use of appropriate text analytic tools like search and predictive algorithms will enable physicians to receive notifications promptly, thus responding quickly to the emergencies.

Health professionals can utilize the usefulness of the text analytics to improve the quality of life for the patients. According to the findings from the focus group discussions by caregivers and nurses, it is revealed that senior citizens in Singapore are experiencing multiple health care problems. Majority of the elders living at home alone have failed to recognize life-threatening medical conditions and obtain appropriate medical care. Minor medical conditions may be ignored until they become severe, thus making it hard for healthcare professionals to predict such cases with short visits. However, the integration of the predictive algorithms allows nurses and physicians to provide treatments promptly. Detection of the personal health risks will be detected sooner due to notification from the genome analysis done by the adopted predictive models.

The usefulness of the text analytics for the healthcare professionals will aim at improving the accuracy of diagnoses and prompt response to the medical emergency as part of the eldercare initiatives in Singapore. A senior citizen who lives alone is prone to different health complications and challenges. Some are exposed to nutrition problems, life-threatening conditions such as pneumonia and chest problems. Reliance on manual records leads to late notification and time wastage when seeking for appropriate prescription and treatment for the patients. It follows that the use of the predictive analytics will enable healthcare professionals to be prompt in their service delivery and the making of clinical judgments, ultimately improving the well-being of elderly people in Singapore.