Despite its promising growth prospects, healthcare service providers are hard-pressed to find solutions to multiple complex issues including regulatory and policy changes, medicinal and technological advancements, rising costs, staff, and trained employees, maintain efficient operations and services, and support other healthcare initiatives. With increasing concerns for living healthier, longer, and lead more active lifestyles, healthcare costs have increased. Research reveals that spending and healthcare costs often rise at rates more than the rate of inflation and are expected to increase even more in the years to come.
With the rising healthcare costs, co-pays and deductibles have become expensive and employers are burdened to take a bigger cut of their employees’ wages to pay for insurance premiums. This surge in healthcare costs will soon become a big barrier to the growth of the overall healthcare industry. Therefore, leaders must find alternative methods to combat rising healthcare costs. They must do the appropriate research to find funding, grants, and contributors to help them conduct research, set up programs, and implement processes at the pace of change.
At Quantzig, we understand the impact that costs have on your business plans. And to help companies excel in an ever-competitive market space, our team of experts has highlighted four effective ways in which healthcare data analytics can reduce the rising costs of care.
Wondering how to reduce costs in the midst of rising health care spending? Healthcare data analytics can help. Speak with our analytics experts to know how you can access cost data on real-time dashboards.
How Healthcare Data Analytics Can Reduce Healthcare Costs?
#1: By Minimizing Healthcare Waste
One of the major contributing factors to increasing hospital costs is patient variation and waste associated with the delivery of care. Healthcare data analytics can help hospitals to address waste through a variety of methods such as LEAN, Six Sigma, and other healthcare quality process improvement techniques. While these methods are impactful in dealing with administrative costs, a much higher return can be obtained by focusing on patient care or clinical costs. Clinical work teams coupled with big data analytics in healthcare and healthcare data analytics reduce costs by helping your organization reduce variation, leading to lowering cost trends
#2: By Reducing Hospital Re-Admissions
Healthcare data analytics can lead to significant cost savings by preventing readmissions. Research shows that many readmissions can be avoided when better actionable information is available to both patients and their providers. Before discharge, physicians and busy nurses don’t often have the luxury to scrutinize each patient much deeply before releasing them. Here healthcare data analytics can come to rescue by providing real-time, concise, and correlated data for more effective decision support.
#3: Cost-Effective Treatment for Chronic Diseases
Healthcare data analytics can also enable doctors to treat chronic diseases more effectively. Generally, doctors are limited to the amount of patient history available to them and this hinders the treatment of a patient suffering from chronic disease with multiple symptoms. With EMRs enabling rich electronic documentation of patient information, healthcare data analytics can supply doctors with correlative information that can help them link together missing puzzle pieces in effective ways. Physicians can now easily tailor more effective treatments providing truly personalized medicine. Healthcare data analytics provides a complete picture of longitudinal diagnostic data, historical treatments, medical history, and healthcare data analytics empowers clinicians to provide more effective and efficient treatment of chronic disease patients that can cut costs while reducing the side effects and increase the quality of life.
#4: Reducing Drug Reactions
Healthcare data analytics can provide more sophisticated and comprehensive intelligence to help avoid problems with adverse effects of drugs or drug interactions proactively by analyzing a broader set of historical as well as current patient medications, contraindications, and drug allergies. In fact, predictive analytics in healthcare is proving to be very helpful in minimizing the drug reaction thereby resulting in less healthcare spending.