The Causes of Variations in Healthcare

Variations in healthcare which is also referred to as clinical variations are kind of a hard to hard to define as its meaning are used are spread across the healthcare industry and multilayered. To carefully define it, we can say that Variations in healthcare is:

 

“a gradual change in an inherited characteristic across the geographic range of a species, usually correlated with an environmental transition such as altitude, temperature, or moisture”

 

Because of problems that arise in the healthcare industry, clinical variations or variations in healthcare start to occur. In summary, clinical variations cause poor quality and outcomes and there are several reasons why clinical variations occur. And this is why healthcare organizations constantly seek to employ solutions that can help them in Reducing Variations in Healthcare.

 

Variation in clinical practice is substantial and is associated with poorer health outcomes, increased costs, and disparities in care. Substantial attention has been given to reducing unnecessary differences in practice patterns. Despite these efforts, practice variation has been difficult to overcome. Challenges to reducing variation include heterogeneity and gaps in clinicians’ knowledge; economic incentives for undesired clinical behaviors; concerns about malpractice risk; physicians’ value of autonomy and personal preference; inadequate communication and decision support tools; and imbalances between clinical demand and resource capacity. Another fundamental barrier to practice standardization is that good clinical practice must sometimes vary to reflect a patient’s specific social, environmental, and biological situation. Sometimes a standard practice would not be best for a given patient. Hence, efforts to legislate or establish policies governing care have been limited because they impede the common sense that there are nearly always exceptions to a given rule.

 

Based on research professionals have identified some major reasons that lead to clinical variations. One of those reasons is:

The lack of valid clinical knowledge

 

This sounds ironic because one of the major areas that seem to be growing in the healthcare and medical industry is the availability and growth of big data. However, quantity doesn’t always mean quality and in this case also validity. Also if healthcare practitioners cannot access this big data and loads of information in a timely manner that aids medical care provision and decision making than it’s as good as not having it at all. There have been three published studies looking at the percentage of clinical care that is based on published scientific research. These studies have concluded that only between 10 and 20 percent of routine medical practice has a basis in scientific research. Thus, much of what we do in routine clinical practice is based on tradition or opinion. That doesn’t necessarily mean it is wrong, as much of it has likely been shown to work over time. However, it does suggest that healthcare delivery organizations should use their own data to determine the efficacy of clinical practice and to determine how to improve it over time. This implies the need to create a data-driven continuous learning environment.

 

Conclusion

Patients have the potential benefit of better outcomes due to predictive analytics.

There will be many benefits in quality of life to patients as the use of predictive analytics increase. Potentially individuals will receive treatments that will work for them, be prescribed medications that work for them and not be given unnecessary medications just because that medication works for the majority of people. The patient role will change as patients become more informed consumers who work with their physicians collaboratively to achieve better outcomes. Patients will become aware of possible personal health risks sooner due to alerts from their genome analysis, from predictive models relayed by their physicians, from the increasing use of apps and medical devices (i.e., wearable devices and monitoring systems), and due to better accuracy of what information is needed for accurate predictions. They then will have decisions to make about lifestyles and their future well being.