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How client-reported data can help care workers make better health care decisions

The voice of a client is essential to understanding whether home care services are making a difference. Client-centered care has taken the spotlight when it comes to discussions of quality. Home care agencies are now adapting to providing care that is responsive and respectful of individual client preferences and values, which guides clinical decisions.  

Agencies now have the potential to generate and capture a significant amount of meaningful data on client-reported outcomes. With advanced technology, it can be used to provide a higher quality of care.  

For client-centered care to flourish, agencies rely heavily on communication.  

Client-reported information gives providers access to insights into the effectiveness of their care from the client’s perspective. This enables them to adjust their methods to maximize the quality of care. By transforming the voice of a client into meaningful, valuable information, relationships can improve, as well as the overall outcomes.  

With electronic health records, managing client-reported outcomes and activities of daily living tracking has become much more efficient. Caregivers can now effortlessly submit information via tablets and mobile devices resulting in copious amounts of data and enhanced communication.  

While there is no shortage of data, many agencies lack the capability to analyze these records.  

Only 3% of potentially useful data is tagged and even less is analyzed within home care and health care organizations, and 95% of CEOs in this space are exploring better ways to harness, manage and analyze data [1].  

The potential for client-reported outcomes and big data analytics in home health care to lead to better outcomes exist across many scenarios, for example:  

  1. applying analytics to client profiles such as segmentation or predictive measures to identify clients who would benefit from specific treatments or care plans;  
  2. analyzing client outcomes to identify predictive events and support care worker decisions or prevention initiatives. [2] 

Imagine clients could ask, “How will this treatment decision affect someone like me?” and caregivers could respond with, “Based on the outcomes of one hundred clients who are the same age with a similar condition, so-and-so treatment would be a suitable approach for you.”  

AlayaCare has taken active steps in tackling data analytics with machine learning and advanced algorithms. Algorithms “learn” from data in an iterative fashion and produce reliable, repeatable alerts to aid caregivers in their decision-making processes.  

Read our blog, Embracing evolution: 4 ways AI and automation are driving change in home care. Learn more about how machine learning technology is driving positive change in the home care industry.  

For home health care providers, amongst the vast amount and array of data, is opportunity. 

While there are logistical challenges associated with implementing and interpreting valuable client-reported data, it is the most direct approach to gaining insights from clients that can improve the quality of care and the way home care is delivered.  

See how Acclaim Health manages to deliver better outcomes for their clients with data-driven decisions: 




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