3 Ways Data Analytics Tools Boost Patient-Centric Care

By: on October 5, 2015

With the old days of billing for services vanishing into the past, today’s health care organizations must demonstrate that the care they deliver to patients is both effective and efficient. If they cannot, then payers—whether public or private—may reduce, or even refuse to reimburse, their costs.

In short: Patient-centric care is a must. But how can this be achieved?

In this blog, we look at three practical ways business intelligence (BI) and analytics tools are being used to achieve this goal.

1. Eliminating Redundant Tests

Population health management (PHM) requires health care providers to proactively provide minimum levels of care to patients to improve their health. That all sounds good, but here’s the catch: It must be done at the lowest possible cost. Squaring that particular circle is made even more complicated by the fact that many patients visit multiple doctors.

For instance, says Jamie Oswald, associate principal data analyst at Mercy Health hospital in St. Louis, if a doctor is going to see a male diabetic patient over age 55, he should also make sure he gets a foot exam, an eye exam and, because of his age, a prostate exam—among other tests. However, some of the treatment data will be contained in EHRs he cannot access:

“They may have a Mercy primary care physician, but they may have a foot doctor who works for a different hospital and an eye doctor who works for a different hospital … and they may get their flu shot at Walgreens,” Oswald says. “So it’s really tough to tell what care they’re getting elsewhere, but we also don’t want to give them 10 flu shots a year!”

⇒ Under this model, the risk of over-prescribing treatment, or sending the patient for redundant tests, is high—which isn’t very patient-centric.

Mercy has partnered with insurance companies to access the claims data they hold on individual patients. Using BI tools, such as SAP BusinessObjects, Mercy integrates insurance claims records with its own, giving doctors a holistic view of each individual patient’s total care throughout the entire health care system.

The information, meanwhile, is easily accessed by the doctor in a display screen embedded inside the electronic health records (EHR) software. This is the very same health records software he consults throughout his ordinary working day, so the data culled behind the scenes is delivered seamlessly. As the doctor sits with his patient, he sees exactly what treatment the patient has received elsewhere and what remains to be done—all without requiring any data analytics skills on his part.

The Result:
Data analytics makes care more patient-centric, while reimbursements are now assured, as Mercy can demonstrate that it is eliminating waste and redundant treatments.

And not only that, says Oswald: “Our physicians are happier; they get to take better care of their patients.”

2: Improving Survival Rates in the ICU

Picture this: A health care provider is experiencing above-average mortality rates in its ICUs. Clearly, something has gone wrong, and the situation must be addressed quickly. However, with such complex workflows and so many contributing factors, it can be extremely difficult for care providers to identify the root causes.

With BI and analytics tools, health care providers can go beyond the limitations of manual methods and conduct a much more detailed, patient-focused analysis of who is entering their ICUs. Analysts can gather all of the information related to the treatment of all their patients across multiple ICUs, then drill deep into the data in pursuit of patterns and correlations.

For instance, says Dr. David Delaney, chief medical officer of software giant SAP, analysts could compare different ICUs within an organization. This analysis would pull information on multiple factors, including:

  • The age of the patients
  • Other medical conditions the patients may have
  • Gender and age information
  • How long it takes for patients to have their blood culture drawn
  • The length of time between ordering antibiotics to delivering them to patients
  • The nurse-to-patient ratio
  • Survival rates at different ICUs

Analysts mine the data to compare characteristics shared by the patients who survive against characteristics of those who do not. Using different statistical models to identify and rate factors related to excess mortality rates, analysts will be able to determine which subgroup within a population is most at risk, and at which ICUs.

For instance, says Delaney: “[If] the mortality [data] relates to someone who is over 75, male and has congestive heart failure—well, those three factors [equate to] three times an increased incidence of mortality.”

Delaney says that data analysis enables the hospital to go beyond a high-level view of the situation (in this case, high overall mortality rates) to pinpoint which population group is most at risk, then remedy the situation with targeted, patient-centric steps.

For instance, Delaney suggests that, in this example, the hospital may have decided to forgo a pharmacy or premix bags in certain of its ICUs as a cost-cutting measure. Instead, these ICUs send out for medications to the central pharmacy. However, for the at-risk group identified by the analytics data, the time lag puts them at a greater risk of dying—hence, the increase in mortality rates.

The Result:
Using the insights generated by the analytics tools, providers at our example hospital can now identify the most at-risk patients, then modify workflow processes to make sure these patients receive medications as quickly as possible. A relatively simple step—making sure premix bags are available—could quickly boost their chances of survival, thus decreasing overall mortality rates.

3. Boosting Preventative Care Using Wearables

Perhaps the best-known example of health care analytics technology today is the Fitbit bracelet. Users wear these bracelets to track metrics such as their sleep patterns and the number of steps they take in a day—all of which can be viewed through a dashboard.

This kind of technology represents a great opportunity for personalizing health care, says Southard Jones, VP of product strategy at cloud BI vendor Birst.

Jones cites the case of Rally Health: a website that collects data about its users’ behavior and health to deliver targeted, specific preventative care advice to them. Rally deploys the Birst BI platform to capture information and analyze data from every interaction users have with the site on every type of device. It then builds a detailed profile of the patient’s state of health based on this data, and makes dietary and exercise recommendations designed to prevent users from getting sick in the first place.

This type of service can empower patients to take more control over their own health based on detailed, personalized metrics. Meanwhile, a whole new level of wearables is emerging, which can not only gather much more information, but also deliver that information in real time to dashboards accessible via mobile devices.

For example, “smart” vests are now available that measure:

  • Heart rates and variability
  • Breathing rates and volume
  • Steps and pace
  • Sleep patterns

The Result:
Prevention is the best cure. Companies can encourage staff to use wearables to monitor their own health and take preventative steps tailored precisely to their own needs. Health care organizations could even use them among their own staff.

And Jones suggests another possible benefit of this technology: If firms can demonstrate, with the data collected from wearables, that their staff is healthy, they may be able to negotiate with insurance providers for lower premiums.


Many software tools are available that can help health care organizations transform their data into actionable insights. If you’re ready to start realizing the benefits of these tools, what can you, as a buyer, do next?

Finding a trusted resource for choosing software can help. Our team of Software Advisors has expert knowledge of over 40 BI platforms, and has assisted more than 1,000 buyers in finding solutions that are right for them.

Here are three things you can do right now:

Follow these steps and you, too, can tap into the powerful insights that BI and analytics platforms offer health care organizations.

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