Business Intelligence for Healthcare

The healthcare industry is on the brink of transformation.

Over half of all healthcare organizations plan to replace or buy a new business intelligence system over the next three years, according to a KLAS report, BI Perception.

There are many reasons for that. Growth in the healthcare industry is at an all-time high, and healthcare organizations are seeking new ways to improve operating efficiency and reduce costs.

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The big data revolution has left those in the healthcare industry with massive amounts of information that they have never had access to before. Electronic health records are in the process of being centralized. Health apps and personal fitness tools are a new source of downloadable patient data. And social media has provided a unique window into patient opinion and sentiment.

From this seemingly overwhelming mass of information, business intelligence tools can generate key insights to improve patient outcomes, cut expenses, and analyze treatment plans and drug effectiveness.

The Perfect Climate: The Data Revolution

The time has never been riper for business intelligence in the healthcare community.

A perfect storm of new technologies, lower prices, and greater availability of patient data has created unprecedented opportunity for healthcare organizations.

Healthcare executives are well aware of the coming changes. A 2014 PriceWaterhouseCoopers study showed that 95% of healthcare CIO’s are actively seeking out better ways to harness their data.

Predictive Analytics

As more people become insured and the burden on medical groups grows, there is an increasing need for technology that can better predict patient costs.

Predictive analytics tools can assess patient risk of illness, potential costs, analyze clinical data, and guide providers in their billing process.

The Predictive Analytics World Healthcare Conference was also established in 2014, a nod to the growing importance of this specific business intelligence tool in the industry.

Centralization of Electronic Health Records (EHR’s)

From hospitals to doctor’s offices and clinics, patient health records are now required to be stored electronically. The federal government has made $27 billion in incentives available to organizations that can demonstrate “meaningful use” of the data.

This mandated adoption has forced healthcare’s hand into big data, and potential incentives make business intelligence more critical than ever before. Until organizations find the right tools to draw actionable insights from this heap, EHR’s represent untapped potential.

It’s why Galen Metz, CIO and IS Director for Group Health Cooperative of South Central Wisconsin, told a panel of BI healthcare experts at WTN’s Digital Healthcare Conference: “I’m ready to declare the era of business intelligence.”

Personal Health Apps and Devices

New technologies like wearable fitness trackers and smartphone health apps are driving medical insights and encouraging the adoption of tools that can gain value from big data.

The industry is booming. Spending on such devices is on track to reach $59 million by 2019.  In 2014 alone, it is expected that 42 million wearable fitness devices that include downloadable data will be sold around the world.

Some of the devices, such as the FitBit, can be wirelessly accessed by doctors.

The Social Media Wave

Patient data is also emerging from an unlikely source – social media.

Studies show that growing numbers of doctors and healthcare professionals are using Facebook and Twitter to track everything from customer satisfaction to lifestyle management.

Some organizations were also using social media to investigate and fight against insurance fraud.

The use has given rise to the term “social business” to describe how social media impacts consumer relations, data analysis, and even product development.


Unlike five years ago, the technology needed to take advantage of big data is no longer cost prohibitive.

An expanding business intelligence market and advances in existing technologies has made software within reach of smaller and mid-sized companies that could not afford it five years ago. Data warehousing, for example, was once restricted to major companies with significant capital.

Today, even small healthcare practices are likely to find a tool that is in their price range.

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Empowering Smarter Decision Making

Healthcare spending is on the rise, yet insurance plans, practices, and hospitals compete in a sink-or-swim marketplace. Business intelligence software helps organizations stay ahead by uncovering trends and insights that can be acted upon quickly.

BI software allows organizations to address four foundational questions: what is happening, why is it happening, what should be done about it, and what the future will look like.

BI provides a framework that helps organizations track fiscal performance and operational standards while giving decision makers a picture of the future.

Financial Data Analysis

BI tools can help healthcare organizations make better financial decisions through budget management, tracking inventory and supply costs, and monitoring other key metrics.

BI software can monitor revenue, and provide numbers on performance at any level.

Key performance indicators and financial goals can easily be tracked, like return on net assets or profitability. Insights can then be visualized for busy decision makers in easy-to-understand dashboards.

Clinical Analytics

Clinical analytics provide hospitals with measurements across all functions of an organization, from lab test results and the rate of unfilled prescriptions to the average wait time in the emergency room.

This information can inform decision making at the operational level in a variety of ways. It can help nurses prioritize their care activities during a shift, or it can help a public health official identify medically underserved neighborhoods.

Clinical analytics are divided between retrospective and prospective insights.

Retrospective analytics involve performance measurement systems that gather and analyze patient or organizational data to help them make decisions about their performance or health. They usually gather extensive records from multiple patients, or facilities, to create models. Prospective analytics prescribe guidance for future planning and care, and generally analyze individual patient information.

Real Time Analysis

BI tools can monitor the effectiveness and quality of physician care.

Some software offers real-time analysis of the health and treatment plans prescribed by physicians. This gives administrators of healthcare organizations the ability to ensure doctors are adhering to best practices, evidence-based standards, and other quality metrics, like those laid out by the National Committee for Quality Assurance.

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BI in Action: 6 Real World Use Cases

1) Predicting Patient Needs

University of Pittsburgh Medical Center (UPMC), a provider and insurer which operates 22 hospitals and 400 outpatient sites, deals with a massive amount of data.

Dr. Pamela Peele, Chief Analytics Officer at UPMC Health Plan, Insurance Services Division, said there was so much that it could “cripple” the organization.

Implementing business intelligence tools allowed UPMC to organize that data and turn a liability into an advantage.

Two of their member organizations were able to use the software to predict the impact of flu season on patients. They’ve also been able to figure out which patients will require the most services from their facilities, which ones are likely to require emergency care, and forecast readmission rates.

Predicting patient needs not only led to more efficient care and better service, but helped UPMC hospitals save money from regulatory fines by reducing the number of readmissions.

2) Reporting Efficiency

The United Kingdom’s National Health Services began implementing “natural analytics,” a user-friendly type of analytics intended to work with the natural way the human brain operates. It works to give users answers to the questions they asked and the context surrounding them.

One of their member centers, Colchester Hospital, used natural analytics to drastically reduce its reporting time from 231 hours a month to 54 hours a month.

Colchester reported that the resulting productivity saved over $77,000 in the first year of implementation.

3) Improving Response Rates

Improving response rates is at the top of any EMS priority list, and that’s exactly what a business intelligence allowed the Jersey City Medical EMS to do.

To help handle the volume of incoming calls, they created the Mobile Area Routing and Vehicle Location Information System (MARVLIS). The system utilizes wireless communications and GPS and GIS technology to bring EMS to their destinations more quickly.

Real-time analytics help position ambulances in areas where they are more likely to be needed. The success has been resounding. Jersey City EMS lowered their response rate below six minutes, well under the national standard of eight minutes and 59 seconds.

Moreover, since MARVLIS, half of cardiac arrest victims have recovered a pulse. Previously, that rate was only one in five.

4) Mining Data to Treat Diseases

Seeking to improve the treatment of respiratory disease, Deloitte partnered with Intermountain Healthcare and New York City pharmaceutical company Forest Labs to conduct outcomes-based research.

Outcomes research focuses on the complete results of the treatment process: the experiences, preferences, and values which patients came away with.

The collaborative effort utilized software from Deloitte to analyze data in Intermountain’s electronic health records. The group identified several areas where treatment can be improved, noting trends such as unmet needs, and common successful treatment paths, which describe the entire route leading to full recovery.

5) Identifying At-Risk Patients

Virginia’s Carilion Clinic successfully deployed predictive analytics to identify those among their 8,500 patients that were most at-risk for heart disease.

The mined data included both traditional structured data and unstructured data, such as doctors’ notes and opinions.

The software was 85% accurate in predicting potential heart failure, and led to both improved care and saved money.

The condition, which is notoriously difficult to diagnose and which strikes over 5 million Americans per year, costs the nation about $5 billion annually.

6) Reducing Adverse Events

The Keystone Health Center in Michigan turned to their data to address a growing epidemic of adverse events, such as patients falls, accidents, or other negative turns in health. They also sought to reduce harmful accidents and falls,

The Center used BI tools to gather obstetrics data from 60 Michigan hospitals, and analyzed the information for warning signs, common indicators, and other trends.

Using the data to improve its practices, Keystone Center has seen a significant drop in adverse events.

What’s Holding Healthcare BI Back

Despite the success of many organizations across the healthcare spectrum, some are still reluctant to invest in business intelligence.

A recent survey released by TEK Systems indicated that thirty-two percent of workers in the healthcare industry believed that a lack of skilled users was the reason that BI tools had not yet been implemented.

In some cases, available resources have already been committed to other technologies. And even where resources are available, some organizations still find data complexity to be a challenge, especially organizations that lack a unified data structure.

As BI takes hold across the industry, these groups will have to work to find ways to seek out user-friendly and cost-effective ways to use their data.


In the healthcare industry, having access to the right information at the right moment is critical.

Without business intelligence tools capitalizing upon the stockpiles of operational and patient data, healthcare organizations are not using all of the information at hand to make informed decisions.

And it is more than just business efficiency that hangs in the balance. Patient care and outcomes are directly impacted by these decisions.

There is an unprecedented amount of data available to medical professionals today, and nearly limitless opportunities to leverage that data. With today’s affordable software, it has never been so important or so easy for healthcare to invest in business intelligence.

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