It remains one of the best ways to earn trust in the senior housing industry analytics services to ensure residents can stay as independent as possible. While balancing a safe environment with an independent one can be challenging, it can be done.
Using new devices and predictive analytics tools, senior care communities can monitor residents in a less intrusive, more targeted manner in the future. Organizations can collect huge amounts of data in an unobtrusive manner using wearable technology and connected devices, in particular.
Adverse events can be predicted by sensors and trackers
As an example, Benchmark Senior Living in Waltham, Mass., has worked with Big Cloud Analytics to analyze data gathered from seniors wearing Garmin Vivosmart HR activity trackers to assist residents in identifying changes that tend to precede adverse outcomes and guiding residents to healthy activities.
Big Cloud Analytics CEO J. Big Cloud Analytics CEO Moulay Elalamy and Benchmark Vice President of IT Moulay Elalamy attended the HIMSS 2017 annual conference in Orlando, Fla. In discussing their collaboration, Patrick Bewley stated that his team identified sleep heart rates exceeding 90 beats per minute as a warning sign for a variety of adverse conditions. It is indeed a noteworthy finding.
Analyze resource needs ahead of time
As senior living communities house a variety of residents in different health stages, their needs are more complex than those of a single resident. Developing and deploying analytics capabilities can expand the utility of devices by collecting a large volume and variety of data on residents and then targeting resources accordingly.
Analyzing large data sets can lead to more innovation in a positive feedback loop. The more diverse the data sets a facility collects, the easier it is to identify adverse events that are associated with them. Those events can then be mitigated or, in some cases, avoided entirely by senior care communities.
Additionally, technology and analytics can be used to improve staffing and workflow in communities. Care coordination and efficiency can be improved by identifying trends that suggest specific resource use at certain times, in certain locations, or around certain residents, for example.
Residents’ safety and independence must be prioritized in the senior living industry. The use of technology and analytics can transform how senior care providers achieve this goal.
The new trend for senior housing is an analytics
Despite its reputation as a relationship-based business, senior housing analytics trends provide the perfect basis for math. What do we really know about the residents of senior living communities?
With today’s new math, it’s possible to understand the factors that influence the resident quality of life, the caregiver’s quality of life, and the executive director’s quality of life. In order to do so, we need to understand the demographics of each resident.
An individual’s health issues, expectations, aspirations, interactions, and even what they eat affect how they feel, how they respond to others, and what they are willing to do to improve their health and happiness.
Data is the starting point for analytics
What kind of data should you collect? You should collect every bit of data you can. Even if you don’t know exactly what you’ll do with that data, it’s important to have it to leverage when you’re ready.
Since data storage is free, you can collect everything from the number of times your resident moves into their bed to the types and amounts of food they eat.
The process of collecting data has become much easier in recent years. By conducting interviews, taking notes, and conducting surveys, you can manually collect them. For this data to be useful, it must be consistent.
Another option is to automate the data collection process. Smoke detectors, for example, collect data about air quality.
In the middle of the night, motion sensors detect the number of times a resident gets up. Food eaten and left untouched can be captured in uploaded photographs. It is possible to monitor a resident’s weight, blood pressure, walking gait, balance, and speed of movement through biological and behavioral monitoring.
Using remote controls, you can even keep track of how many clicks it took to accomplish a task.
To build a more complete picture of a resident’s daily experience, you need data from both manual and automated sources.
Data accuracy is also crucial in order to prevent any valuable insights from being tainted. Your data integrity processes are driven by the data you collect.
The collection routines and transportation, as well as the backup and management of data, will all need to be considered. You’ll also need expert eyes to determine whether the data is valid and whether it’s delivering accurate insights.
Does the information make sense to you?
In the event of outliers, how do you handle them? What is the age at which data is no longer valid?
Data analytics tools need to be embraced, not avoided
What would your business model look like if you could predict which residents will stay the longest in your community?
Would it be possible for you and your staff to extend that same experience to other residents?
How might it affect how you train your employees?
Predictive help is the promise of data. It’s not about knowing WHEN something has gone wrong; it’s about knowing BEFORE something goes wrong.
Prevention begins with data analytics. In other words, it is the last mile in transforming a real estate investment into a true healthcare organization that manages your resident’s continuum of care from the moment they arrive until they leave.
There is no enemy in data. Our industry needs this step to move forward.
Conclusion
At Polestar Solutions and Services, we offer descriptive and predictive analytics services to senior housing analytics providers, assisted living providers, memory care facilities, and hospice providers.
We help companies set up architecture to collect useful data and build visually insightful dashboards.
As a result of these services, our clients have been able to optimize their existing processes and achieve operational efficiency.