Hi. Welcome to Ingram Micro.

Please choose your role, so we can direct you to what you’re looking for.

If you’d like to learn more about Ingram Micro global initiatives and operations, visit ingrammicro.com.

The New Role of Business Analytics in Healthcare

April 26, 2017

The New Role of Business Analytics in Healthcare

Healthcare providers are under more fiscal and regulatory pressure than ever before. New insurance requirements and new government rules require new strategies for compliance, which mean added costs. Passage of the Affordable Care Act (commonly called Obamacare) has placed new pressures on providers, both in recordkeeping and controlling rising operating costs. Healthcare providers need to rethink how they operate and create new systems to make care more cost-effective, and business analytics can go a long way to helping hospitals, clinics and medical practices find new ways to streamline operations.

The Healthcare Information and Management Systems Society (HIMSS) conducted a study that shows a 6 percent increase in the number of organizations using clinical and business intelligence (C&BI) since 2013. With the implementation of the HITECH Act, electronic medical records (EMRs) have become mandatory, adoption has risen to more than 90 percent of healthcare providers and 52 percent of the providers polled say they use their EMR/HIS (Hospital Information Services) vendor for C&BI: a golden opportunity for solution providers to work more closely with healthcare organizations. Fifty-two percent also said they are using embedded C&BI business tools, and they are primarily looking for analytics in population health management, accountable care, predictive analytics and revenue cycle management to improve operations.

Healthcare providers have access to more data than ever before, and they are seeking new ways to harness business analytics to put that data to work to control costs:

Business operations – Business analytics can be used to improve almost any aspect of healthcare operations. By analyzing patterns in emergency-room care, for example, hospitals can refine their staffing strategies, determining how many nurses might be needed during different shifts. The same analytics can be used to determine the need for hospital equipment, specialized care facilities or any aspect of operations.

Suppliers – Using inventory control, EMRs and other metrics, hospitals and clinics can take a closer look at suppliers and determine if they are paying too much, overstocking devices or drugs or have waste in their supply chain. For example, using analytics, Mount Sinai Medical Center in Miami Beach was able to determine that it was overpaying for pacemakers for cardiovascular care and was able to negotiate a better price with the supplier. Similar analytics can be used to manage stocking for drugs and other perishable or renewable supplies to optimize stocking costs.

Emergency Medical Services – Using geographic data, global positioning data and other metrics, emergency medical services (EMS) providers have been able to improve response time. Jersey City Medical EMS was able to cut its average response time to less than 6 minutes by using analytics (the national average is almost 9 minutes). The EMS unit uses GPS and wireless data to improve response rates and uses analytics to show where it is most likely to be needed. For example, analytics showed that most emergency calls come from residential areas in the evening and business areas during the day, so ambulances can be placed closer to where they are likely to be needed.

Preventative Patient Care – By analyzing patient records and correlating symptoms using predictive modeling, at-risk patients can be identified for preemptive care. Carilion Clinic and IBM developed a program to identify patients at risk for heart disease, which can be hard to diagnose in advance. By using structured and unstructured data from a pool of 8,500 patient records, they are able to identify at-risk patients with an 85 percent accuracy rate. Similarly, the University of Pittsburgh Medical Center was able to use patient records to create an analytics program that would model the impact of flu season, who is likely to require emergency care, the likelihood of readmission and other trends in patient care.

Predicting Insurance Costs – Analytics can be applied to predict and refine medical costs to refine healthcare plans. For example, mapping insurance provider data to patient data can refine actuarial tables and create more accurate models and healthcare plans. Hospitals working with insurance providers to promote optimal patient outcomes also will be able to recommend better wellness treatment for patients, demonstrating to insurers the savings in care. Insurance companies also will be more likely to underwrite preventative care if the analyses demonstrate the greater cost savings from promoting wellness as opposed to treatment.

These are just some of the ways that analytics will shape the future of healthcare. Solution providers need to be prepared to step in with expertise and technology to enable analytics. For example:

  • Data-gathering systems will need to be updated and implemented and new strategies developed to gather and store data before it can be correlated.
  • New protocols and procedures need to be developed to capture new data and normalize data that is already being captured.
  • Staff will have to be trained in ways to capture data for later analysis.
  • New technology will need to be deployed for data captures, such as handheld and mobile data entry systems.
  • Ongoing guidance will be required in order to help HIS professionals assimilate and analyze data.

Solution providers are in an ideal position to provide the strategies, the tools and the analytical techniques to help healthcare providers get the most from business analytics. Hospital administrators are looking for new ways to improve operations, and they need outside experts to show them how to gather and analyze the data. That’s where solution providers can become an invaluable resource.