How can Health Care Leverage, Big Data for Better Health Care?
By 2015 in America, people are expected to spend $3.3 trillion for total health care. Today, the health care industry is moving towards value-based health care models. Soon we will see accountable-care organizations (ACOs) and patient-centered medical homes. To accomplish these goals data-driven technologies are helping to bend the cost curve and play an important role in the industry. Therefore, big data analysis can save Americans $300 to $450 billion each year in health care expenses.
Big data and data-driven technologies can help healthcare organizations address problems in population health and decision support. It is predicted that patient adherence, hospital readmission rate, and care coordination will be the top money saver next year. The health care industry has started to look at risk-bearing entities and now realize the value of data analytics tools to reduce health care expenses. The industry has started to really understand the value of the data they have collected and started to make it count when it comes to care. Therefore, hospitals can now access critical patient information and immediately administer the right care to their patients at the right time.
How is the industry using health data to turn it into actionable insights and improve health care?
1. Gather patient data from disparate sources.
In the health care industry organizations have to use numerous systems such as claims processing, EHRs, and administrative systems. It is necessary that organizations capture data and store it in one centralized location.
2. Combine unstructured data with structured data.
Hospital admission notes, physician notes, and patient history make up 80 percent of unstructured data. To have a more accurate and complete view of the patient’s health care needs you have to combine unstructured data with structured data.
3. Look at patient history and not just clinical data.
Understanding your patient’s data history outside clinical data can offer valuable insights into the way you treat and care of this person. You need to understand environmental, psycho-social, and socioeconomic factors. Also understand the patient’s sleeping patterns, marital status, employment status, and living situation will give you a full picture of your patient.
4. Identifying patient’s high risk medical problems.
In health care it is important to use advanced rules and predictive model data to classify each patient. This enables healthcare organizations to identify patients who need intervention and also helps to fill in the gaps in medical care. Therefore, this method to identify high risk patients can have an impact on health care. Especially, for high risk patients who have a high risk for hospital readmission.
5. Use a dashboard to view patient’s data.
A dashboard is important in the medical field to view stratified patient data. Therefore, using a unified dashboard your data is classified by cohorts. This allows clinicians to access target scarce resources. Also, it allows doctors to deliver the right treatment to the right patient.
About Julie Sinclair
Julie is a retired school teacher who loves writing, gardening, Internet research, crafts, and being with her family. After retirement Julie has kept up her skills in computing by taking classes at the College near by.