Clinical analytics is important in the healthcare industry. The practice of Quality Clinical Analytics in a healthcare organization ensures that their big data is used to the fullest capacity and all the applications are optimized. With this, the healthcare organization runs smoothly, proper care is given and patients are happy. Big data and Quality Clinical Analytics go hand in hand as they compliment each other and the presence of big data necessitates the practice of Quality Clinical Analytics.
Why We Need Quality Clinical
Analytics In Healthcare
Quality Clinical Analytics and big data analytics is expected to eventually reduce the cost of healthcare significantly. This is a welcome solution to a serious problem of increasing cost of healthcare in the United States
“After more than 20 years of steady increases, healthcare expenses now represent 17.6 percent of GDP —nearly $600 billion more than the expected benchmark for a nation of the United States’s size and wealth.”
The cost of healthcare is currently a lot higher than it should be and continues to rise. Doing the same thing over and over again and expecting change is the definition of madness so there has to be a change in strategy. This is why using data and technology in ways they’ve never been used before to seek solutions is the best bet. Insurance companies are also trying to implement strategies that would reduce the cost of care such as switching from fee-for-service to plans that put patient outcomes and value of care first. Fee-for-service is a payment method that rewards doctors for using expensive and sometimes unnecessary treatments method and for treating lots of patients in a short time frame. This payment method, of course, does not put the needs of the patients first or the quality of care for that matter. If same insurance companies that came up with fee-for-service are now trying to reduce the cost of care and “be better” one can only wonder at their true motives and what the fate of the healthcare industry in the United States will be like.
Yes, finances do matter as doctors and healthcare practitioners need to feed themselves and their families and have a good quality of life. In the same vein, prioritizing the health and life of patients above everything else also matters. This is why finding a healthy balance is important and possibly this balance can be reached with the help of big data and new technology. There is hope after all. For example, in the past, healthcare providers had no direct incentive to share patient information with one another, which had made it harder to utilize the power of analytics. The case is different now as there is a free flow of information between and within organizations, the cloud and of course, big data. Now that more physicians and healthcare practitioners are getting paid based on patient outcomes, they have a financial incentive to share data that can be used to improve the lives of patients while cutting costs for insurance companies.
Quality clinical analytics has helped physicians become more evidence-based. This means that they rely on large swathes of research and clinical data as opposed to solely their schooling and professional opinion. A good doctor never stops learning and catching up on the latest advances, new procedures such as non-invasive surgeries and so on. As in many other industries, data gathering and management are getting bigger, and professionals need help in the matter. This new treatment attitude means there is a greater demand for big data analytics in healthcare facilities than ever before.
Big Data Examples In Healthcare
It’s no doubt that big data has transformed the healthcare industry and continues to do so. The healthcare industry slowly started adopting the new technology and innovations that were flooding the industry and now the adoption rate has quickened. The adoption of new technology is what will push health and digital health to new levels. Below is a lost of ways that technology, big data, and clinical quality analytics are contributing to healthcare:
- Predict the daily patient income to tailor staffing accordingly
- Use Electronic Health Records (EHRs)
- Use real-time alerting for instant care
- Help in preventing opioid abuse in the US
- Enhance patient engagement in their own health
- Use health data for a better-informed strategic planning
- Research more extensively to cure cancer
- Use predictive analytics
- Reduce fraud and enhance data security
- Practice telemedicine
- Integrate medical imaging for a broader diagnosis
- Prevent unnecessary ER visits
Obstacles to Quality Clinical
Analytics and Big Data
As promising as the future of big data is, it still faces some obstacles in the industry. Some of these obstacles are:
Incompatible data systems:
This is perhaps the biggest technical challenge, as making these data sets able to interface with each other is quite a feat. Different healthcare organizations use different technology platforms to store and process their data and also use different binding techniques such as late-binding and early-binding. Thus merging data sets stored in incompatible systems always proves problematic.
Patient confidentiality issues:
There are different laws state by state which govern what patient information can be released with or without consent, and all of these would have to be navigated. Patient pieces of information are sensitive and the wrong move could result in a huge lawsuit that would cost the healthcare organization more money and resources. In addition, institutions which have put a lot of time and money into developing their own cancer dataset may not be eager to share with others, even though it could lead to a cure much more quickly and improved healthcare for all.