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Roadblocks to Value-Based Health care

By January 21, 2022May 16th, 2024No Comments

Patient-reported data effectively contributes to the value-based health care model. The “value” in a value-based health care system is derived from measuring health outcomes against the cost of delivering those outcomes. Research is increasingly showing that health outcomes are significantly impacted by the social and economic factors making up the environment in which an individual lives. Therefore, providers are increasingly turning to online survey and assessment tools to capture accurate patient-reported data.

Lots of patient-reported data, yet little gains

Data is only as powerful as its accuracy and when poor quality data is collected, results are compromised. Current means of collecting information, such as paper-based surveys or generic digital surveys, show low completion rates and a lack of meaningful data. For instance, the HCAHPs survey used to measure patient experience has a response rate of just 34 percent. Inadequate information along with low-quality data leads to financial loss, poor health outcomes, and missed value-based healthcare goals.  

Research also shows that a one-size-fits-all approach to communicating with each unique individual is not working. The diversity of patient populations in terms of health literacy, language, and culture is often ignored when building surveys. Instructions for completing surveys are not always clear; questions are sometimes difficult to understand, and they don’t take into consideration low literacy levels. 

Another issue is the lack of flexibility in administering surveys. Different age groups respond differently to how they are engaged. Surveys sent by mail are largely ignored as they fail to engage respondents and result in poor response rates. 

Add to that, many health screening assessments ask for sensitive personal health information in a manner that many patients may feel stigmatizing. Patients can also be reluctant in sharing information when the intent of the survey is not clear, impacting the fidelity of the data. 

Finally, poor survey designs characterized by poor user experience design, lack of visual accessibility, and high literacy levels also result in low engagement, providing clinicians with both low quality and quantity of data. 

This is the first of a three-part blog series on “Unlocking the value of patient-reported data in achieving value-based healthcare system.” This blog discusses the importance and challenges of collecting patient-reported data.  Stay tuned for our next blog where we will discuss how the Digital Empathy Design Framework can be used to build surveys that create a level of trust with respondents, resulting in higher response rates, and higher quality and quantity of patient-reported data for better health outcomes.