In recent years, the healthcare industry has seen an unprecedented rise in the use of big data and analytics in an effort to enhance personalized care for patients and residents. As technologies have improved and become more accessible, healthcare professionals have gained access to vast amounts of patient information, from their medical histories to lifestyle, dietary needs and exercise regimes. This wealth of data has enabled professionals to develop personalized care plans for a wide range of conditions.
Today—thanks to the use of big data—organizations are focusing more on the individual patient experience and outcome, rather than just their operational efficiency. A consistent patient or resident experience is the key to providing personalized care and building patient and provider relationships.
Residents need nurses and physicians most during sickness or in a health scare. During these times, they are often extremely stressed and in their most vulnerable state of mind. Long-term care organizations can use big data and an effective elder care software to plan and make this as seamless and as stress-free as possible.
But this is only the beginning; big data has even greater potential when it comes to nursing care. With information about everything from medication adherence to stress levels, nurses can use big data not just to make decisions about treatment plans, but to also proactively manage their residents’ well-being.
By using real-time analytics displayed on a KPI dashboard, in conjunction with their observational skills and medical training, nurses can provide truly personalized care that is tailored specifically for each individual patient’s needs. As such, it is clear that big data represents a true game-changer in healthcare today and is poised to transform nursing in exciting new ways in the coming future.
4 Applications of Personalized Care Technologies: Big Data in Healthcare
Big data in healthcare continues to play an increasingly important role in the field of healthcare. By analyzing large data sets, physicians and nurses are able to better understand how diseases progress and how residents respond to different treatments, allowing them to create personalized care plans for each individual resident.
Additionally, big data can help healthcare providers save money by identifying waste and inefficiency. There are a range of applications of big data in long-term care, but we want to pay specific attention to the examples of personalized care technologies made possible by the application of big data in healthcare.
1. Electronic Health Records (EHRs)
Long-term care EHRs are great for keeping resident charts accurate and up-to-date, but they also store a wealth of data. Utilizing this data can help diagnose and even predict health problems. It can also enable nurses to provide personalized care for residents in their facilities.
From the resident’s and their family’s perspective, anything health-related is incredibly personal, which means getting away from the one-size-fits-all mindset is a must for any long-term care organization. A huge step to achieving this is by using insights from data to improve the resident and provider relationship and, most importantly, health outcomes.
2. Real-time alerts
In order to be effective, personalized care must be proactive. This is where real-time alerts come in. By monitoring data 24/7, nurses can be alerted the moment a resident’s health changes, even if it’s just a small change. These alerts allow nurses to take action quickly and prevent problems from getting worse.
Senior care software, such as Experience Care’s electronic Kardex system, come equipped with a daily alert system, which is a great way for nurses to be proactive in providing personalized care for their residents. By flagging and saving specific resident items, nurses are notified when they log into the Kardex system at the start of a shift, and also when a resident’s health condition changes.
An electronic Kardex allows nurses to take action quickly and prevent any potential problems from getting worse. Additionally, a daily alert system can help nurses keep track of residents’ progress and provide personalized care over time.
3. Staff management and scheduling
The long-term care staffing crisis has made staff management all the more vital. With so few nurses available, now more than ever, nurses must be able to effectively manage their time. This means that nurses need to be able to quickly and easily access resident information, including medical history, medications, and allergies.
With an effective elder care software system in place, big data can be automatically sorted for use in a nursing home. This means that nurses can spend less time looking for and organizing information and more time providing personalized care for their residents. For this reason, Experience Care partnered with SchedulePop to integrate this staff scheduling software in its NetSolutions EHR, making staff management that much easier.
Better staff management means more efficient workflows in a facility, with the benefit of residents not only enjoying an increased quality of care but also receiving more personalized care and developing meaningful relationships with their caregivers.
Telemedicine is an emerging field of medicine that utilizes big data together with remote diagnosis and treatment to provide personalized care. Thanks to the vast amount of information collected by nursing home software and other software systems, physicians are able to gain a better understanding of their patients’ individual conditions and needs without having to be there personally.
Telemedicine can be particularly beneficial, especially in cases where a traditional diagnosis may not be effective, such as in the quick management of chronic illnesses or identifying early warning signs of more serious conditions. By analyzing a patient’s or resident’s history, treatment progress, and other relevant data, healthcare professionals are able to develop personalized care plans that take into account their unique status and circumstances.
In addition to improving medical outcomes for individuals, this personalized approach can also help reduce medical costs, as residents no longer need to commute to visit physicians. Experience Care’s long-term care pharmacy software is a great example of the value telemedicine. The software allows for paperless ePrescribing, reducing errors and saving time for nurses.
Contact us here if you would like to test our long-term care EHR that comes with big data analytics capabilities for your facility.
Benefits of Healthcare Personalization
We have mentioned some of the healthcare personalization technologies that make use of big data. We have also noted the role that big data plays in the creation of personalized care plans. Here we will answer the question, why is personalized care important, by looking at some of the benefits of healthcare personalization in long-term care. These benefits include:
- Improved patient and resident outcomes: The use of big data in healthcare and personalized care plans can lead to improved patient and resident outcomes. By taking into account a resident’s individual circumstances, physicians can develop treatment plans that are tailored specifically for them. This personalized approach is more likely to result in successful outcomes, as it takes into account the unique needs of each resident in a skilled nursing facility.
- Increased patient satisfaction: In addition to improved outcomes, personalized care can also lead to increased patient satisfaction. When long-term care residents feel that their individual needs are met, they are more likely to be satisfied with their care. This personalized approach can also help build trust between residents and their care providers.
- Reduced medical costs: Personalized care can also help reduce medical costs. By using big data analytics in healthcare to develop personalized care plans, healthcare professionals are able to prevent and manage chronic illnesses more effectively. This can lead to fewer hospitalizations and doctor’s visits, which can save money for both patients and healthcare providers.
- Increased revenue: The personalized approach to healthcare can also lead to increased revenue for long-term care facilities. When patients are satisfied with their care, they experience improved outcomes, making them more likely to recommend the facility to others. This word-of-mouth marketing can help increase occupancy rates and boost profitability.
By taking into account a resident’s individual circumstances and using effective senior care software, physicians are able to develop treatment plans that are tailored specifically for long-term care residents. This personalized approach is more likely to result in successful care outcomes, as it considers each resident’s unique needs.
The Role of AI in Personalized Care
As personalized care becomes more important in the healthcare industry, it is likely that artificial intelligence (AI) will also play a larger role. AI provides physicians with personalized recommendations for treatments and helps predict and prevent health problems in residents.
By using big data analytics, AI can develop personalized care plans that are tailored specifically for each individual. This approach is more likely to result in successful outcomes, as it takes into account the unique needs of each resident. Additionally, AI can be used to monitor patients and identify early warning signs of more serious conditions. This allows for timely intervention and treatment, which can prevent or mitigate the consequences of a health problem.
An example of an AI application is Experience Care’s upcoming PDPM Maximizer. This software employs the use of predictive AI to analyze a newly admitted resident’s file and recommend any missing diagnoses. These diagnoses can then be reviewed by the resident’s physician for approval, maximizing a facility’s reimbursements.
One can expect that, in the future, AI will play an even larger role in personalized care. As technology advances, AI will become better at understanding and predicting the needs of patients and residents.
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