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Analytics Magazine

Analytics & Healthcare: Radiology and revenue cycle management

November/December 2013

Examination of two promising areas for analytical opportunities in the healthcare industry.

Rajib GhoshBy Rajib Ghosh

In a previous article, I wrote about some significant challenges in the healthcare industry to adopt and leverage analytics. Barriers range from siloed data to a lack of incentives among the major stakeholders. However, there are signs of hope, especially when we look at the large payer organizations that are beginning to embrace and promote analytics.

In the recently concluded Strata Rx 2013 conference, many discussions were centered on the future of healthcare analytics and the impending tsunami of big data in healthcare. However, the true potential of analytics in healthcare won’t be unleashed until the key barrier of data liquidation, i.e. interoperability, is resolved. While quite a bit of work needs to be done on interoperability, several areas in the healthcare value chain are either well-suited for analytics with a tangible return on investment or are already experiencing quick uptake.

Radiologists: Key CollaboratorS in Care Delivery

A great imaging explosion is coming, and providers and vendors need to get ready for it. Imaging technology is advancing very rapidly with several modalities useful for various medical areas (Figure 1). According to Imaging Technology News, medical imaging procedures are expected to increase by 13.6 percent, which translates to 61 million more procedures annually [1]. With 32 million Americans are expected to enroll into the healthcare system in the next couple of years [2], this number is going to grow further, creating an explosion of data. Frost and Sullivan predict that diagnostic imaging alone will produce 1 Exabyte (1 Exabyte = 1 billion gigabyte) of data by 2016 [3]. Sharing images between different healthcare IT systems, mostly with the electronic health record system, will also increase. Images will no longer be locked into the traditional picture archiving and communication system (PACS) but will be shared through vendor neutral archive (VNA) systems. Several health IT startups are already targeting this growing opportunity.

 analytics healthcare radiology
Figure 1

Another area that has not contributed much in the growth of images so far but will do so in the future is homecare. Dermatology and diabetic wound care organizations have historically used images taken remotely at home for making intervention decisions. However, we are yet to see an established practice of images captured at a patient’s home transferred to the electronic medical record system to support clinical follow-up or preventive intervention. This, however, is expected to change, further adding to the imaging explosion with the popularity and proliferation of telemedicine.

Radiologists are no longer a siloed service provider; instead, they are key nodes of care collaboration with multiple medical specialties. It is important that radiologists have a better understanding of a patient’s medical history at the time of studying images. Today, downstream implication of a radiologist’s contribution to the care delivery process and patient outcome is generally not visible to radiologists. If the data on what treatment is rendered by the referring physician becomes available, radiologists can improve their work with appropriate fine-tuning. Analytics on a large volume of patient data and images can produce recognizable patterns for radiologists to review and can certainly improve future care delivery and service.

Emergence of ‘Automated Residents’

Radiologists in academic medical centers have access to residents and fellows, but those who are in other practices do not have that luxury. As the amount of images explode, radiologists with specialized skills and experience will need assistance to review old images and will need to be prepared with intelligent, insightful synopsis before they meet with patients. That way they will be able to spend more time with patients to explain medical conditions and answer questions. This can be accomplished with smart analytical tools, which Eliot Siegel, M.D., diagnostic radiology and nuclear medicine professor and associate vice chairman for informatics at the University of Maryland, calls “automated residents” [4].

Predictive Maintenance of High-Cost Equipment

“Internet of Things” is the new mantra for big industrial giants such as GE or Cisco. The promise of every machine talking to each other via a universal service backbone generating petabytes of data is surely quite intriguing. More intriguing, however, is the possibility that powerful analytics working on those big datasets can create insightful and actionable information, which if acted upon can change the future. Pundits label this the “Industrial Internet” [5] – powered by tiny sensors, powerful software platforms and insightful analytics – will revolutionize how various industries work.

A small part of this grand vision can be applied to improve upkeep and utilization of expensive equipment in hospitals. Imaging equipment typically costs hospitals between $1 million and $10 million, depending on the type of equipment. The Medicare Payment Advisory Commission (MedPAC) recommends that machines costing more than $1 million need to run at 90 percent utilization rate. Vendors have started to add sensors in the machines, and, based on the data collected from the machines, they can predict when maintenance is required to prevent longer outages and frantic service calls.

Smarter Revenue Cycle Management

Based on a February 2013 HealthLeaders Media Intelligence Report, 62 percent of healthcare organizations plan to increase their spending on financial analytics over the next three years, while only 3 percent plan to spend less. Healthcare providers are going to witness a new wave of patient traffic by 2014. Many of those patients will be new to the health insurance market without the full knowledge of “patient responsibility.”

The unanticipated surge in consumer activity on the federal health insurance exchange on and immediately after Oct. 1, 2013 indicates that people are ready to take advantage of the Accountable Care Act (ACA) and get insured. This will put additional burden on healthcare providers to keep their revenue leakage or revenue loss under tight control.

At the same time ACA also exposes providers to the risks of the pay-for-performance payment model. Those risks were non-existent in the world of fee-for-service. Providers will have to invest in analytics to understand both the operational and financial aspects of their business. In the short term this will be a big opportunity for vendors with appropriate products to find interested buyers in the provider community. Given the sluggish nature of procurement cycles in healthcare, this is very good news for analysts.

In my next article I will discuss another immediate opportunity – population health management – where adoption of analytics has been talked about for a long time. Given the ongoing healthcare reform movement in the United States, I expect both entrepreneurs and established companies to make solid commitments in this area in the coming years.

Rajib Ghosh (rghosh@hotmail.com) is an independent consultant and business advisor with 20 years of technology experience in various industry verticals where he had senior level management roles in software engineering, program management, product management and business and strategy development. Ghosh spent a decade in the U.S. healthcare industry as part of a global ecosystem of medical device manufacturers, medical software companies and telehealth and telemedicine solution providers. He’s held senior positions at Hill-Rom, Solta Medical and Bosch Healthcare. His recent work interest includes public health and the field of IT-enabled sustainable healthcare delivery in the United States as well as emerging nations. Follow Ghosh on twitter @ghosh_r.

References

  1. “Exploding imaging volume could taint radiology,” www.itnonline.com/content/exploding-imaging-volume-could-taint-radiology
  2. http://strataconf.com/rx2013/
  3. www.frost.com/prod/servlet/press-release.pag?docid=268728701
  4. http://www.diagnosticimaging.com/pacs-and-informatics/data-mining-and-analytics-radiology
  5. http://en.wikipedia.org/wiki/Industrial_Internet

Figure 1.

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