Recently, Datamark, a provider of digital mailroom, data entry and document processing services, sponsored a webinar hosted by Creative Healthcare, a provider of performance improvement solutions including Six Sigma, Lean and ISO 9001, who gathered together several healthcare leaders to discuss data management and the use of electronic health records and how those systems are changing the way their hospitals practice and administer care.
Though the group shared a variety of experiences about the use of EHRs, the comments – both good and bad – seemed to reach a consensus among the group. As such, each of the comments about ease of use and even innovation are hard to ignore. Nor can we dismiss the fact that the issues shared by this group are not experienced by many of their colleagues at hospitals throughout the country.
However, there were some surprising candor from the participants of the roundtable. One of the most surprising opinions expressed was by Shawn Shianna, MD of FHN Healthcare, of Freeport, Ill.: “Most of us feel we’re being forced to this (implement and use EHRs).”
Guest post by Paddy Padmanabhan is senior vice president of healthcare analytics for Symphony Analytics.
As healthcare continue to become more “democratized” and patients start taking control of their own medical and healthcare information, the emergence of new healthcare entities like ACOs and HIEs are making huge amounts of data available. As new products and care delivery models start pulling previously underinsured and uninsured members of the population into the healthcare system. Given this new healthcare landscape, recent reports have estimated the market size of healthcare analytics to be $10 billion by 2018. At the same time, a significant shortage of healthcare technology professionals is being forecast, with clinical informatics being one of the most sought-after skills in the coming few years.
In this democratized healthcare environment, previously ignored data sources, such as demographic data and individual credit histories, are now important aspects of analyzing patient profiles. And as we go deeper into internal environments, healthcare companies will start looking at machine data to understand patient and provider behavior
As the complexity of data sources multiplies, health insurance companies are faced with new challenges to manage member engagement, making it difficult for primary care physicians to provide care based on the limited patient information and insights they have from their internal systems alone.
In my conversations with senior healthcare executives, I get a sense that they recognize the situation but are understaffed for even their most basic reporting and analytical needs. Take, for example, the ACO marketplace. Meeting the needs of compliance reporting on thirty-three core quality measures alone requires these entities to invest in and establish a reporting infrastructure, in addition to all the other management information and dashboards they need to manage their businesses successfully and qualify for the shared savings.
Yet, traditionally, healthcare has focused on the “volume” end of analytics, namely data management and governance, and some degree of descriptive analytics. Unlike other markets, such as retail or banking, very little is happening in the area of advanced analytics and predictive modeling.
But there is a new way of approaching the relationships between the “3 P’s” (patient, provider, payer). Traditional parts of healthcare, namely the payers and the providers, have been used to doing business on a fee-for-service model for many years, and all of their information systems are set up to operate in this paradigm. The nature of the relationship was largely adversarial, with the focus being claims and payments, and a constant analysis of care delivery utilization for the purpose of contract negotiations between provider and payer. The new thinking now focuses on the patient as well — a collaborative relationship for improved outcomes and lower costs, and a solid analytical foundation becomes essential to track and manage clinical and financial outcomes.
Take the case of penalties on preventable readmissions. Many hospitals across the nation have been penalized up to 1 percent of their Medicare reimbursements for failing to comply with readmissions thresholds. Hospitals are scrambling to understand the root causes of readmissions, and prevent or minimize these from occurring. Hospital executives are concerned not just with the bottom line impact but the reputational damage that accompanies being on a list of offenders. Payers, on the other hand, are looking at their member populations and their provider networks at a macro level to identify patterns that will help them address the readmissions problem at a cohort level that goes beyond clinical analysis at an individual patient level. New tools and risk-scoring models are required to tackle this problem effectively.
The healthcare system has developed fairly mature analytical capabilities in traditional areas, such as claims and actuarial analysis in the traditional employer-based health insurance model. However they are in the very early stages of understanding how to work in a marketplace that is shifting toward individual members. Internal data alone will no longer cut it, and the risk-management models of employer-based insurance will no longer suffice.
Providers have spent huge sums of money implementing EHR systems and demonstrating meaningful use, to qualify for incentives. Yet the million-dollar questions remains: what to do with the data? Clinical analytics and informatics has never been a focus in the fee-for-service model, so a major change of mindset is required.
There’s no question that there is a huge need for analytics, and the capacity and capabilities required to meet those needs do not exist today within the healthcare system. There also are just not enough data scientists out there to go around, and it cannot be addressed by throwing the next new piece of technology that comes along at the problem.
The solution lies in prioritizing the areas of focus, developing a multi-year roadmap, and determining which areas are core to the business and which ones can be delivered using a combination of technology and consulting support. It’s also worthwhile considering global talent, especially from places like India where there is strong talent with backgrounds in science and applied math to take on at least some of the “heavy-lifting” aspects of an analytics program so that scarce and valuable internal resources can be focused on the domain-intensive aspects of analytical work.
It’s time for the healthcare sector to make bold, disruptive moves and embrace analytics whole-heartedly as a strategic tool for growth and profitability.
Paddy Padmanabhan is senior vice president of healthcare analytics for Symphony Analytics ( www.symphony-analytics.com), a division of Symphony Teleca. He can be reached at firstname.lastname@example.org.
According to a recent study by Towers Watson — an organization I’m very familiar with for having worked with them on a major healthcare project — there is a health IT employee shortage and healthcare providers need to rethink their approach to hiring and retaining the experienced information technology professionals they need in the new healthcare environment.
Apparently, providers are at a disadvantage when it comes to hiring IT staff in part because of competition from IT consultancies that can afford to pay top dollar for experienced IT professionals.
The Towers Watson survey of more than 100 healthcare providers, including hospitals, found that two-thirds (67%) are having problems attracting experienced IT employees, and 38% reporting retention issues. The attraction problem is even greater for Epic-certified professionals, with nearly three-quarters (73%) of the respondents reporting difficulty hiring these individuals, whose specialized skills are essential to meet new electronic medical record requirements under health care reform.
What keeps health IT leaders up at night? It’s a simple question with millions of different responses. For each one of us, it’s something entirely different. For me, I toss and turn because of a few fairly simple reasons: ensuring my start-up company is bringing in revenue to cover the bills and building it into a sustainable first-class organization, not the mention making sure my family is healthy and secure.
Most likely what keeps me up, keeps health IT leaders up, too, but they likely face a few more complexities than I given the huge responsibility they bear keeping their products in compliance with reform and regulation, and the large number of people their products touch. With all of the activity and rapid change in the ever evolving world of health IT, I decided to ask a few folks what in fact keeps them up at night.
Some of the following responses you might expect; others are a bit surprising.
Guest post by Aaron Weiss, director of marketing for HP LaserJet Enterprise Solutions.
Throughout my career, I’ve worked with many small-to medium-sized businesses (SMBs) to improve workflows and efficiency by using technology. Across all of the SMBs in various industries that I’ve helped, healthcare offices often experience the most debilitating pain points, resulting from an overflow of documents like patient and medication information.
From scheduling appointments and providing medication information to keeping track of patient history records, employees of office-based physician practices are expected to meet high demands. In the midst of diagnosing illnesses and managing administrative responsibilities, disorganization, security issues and time management often become pain points for practices.
With increasing financial pressure on the industry, healthcare is being redefined to focus on quality outcomes at lower costs. Providers in particular need to look to new ways to utilize data to improve outcomes, while taking into account the rapid changes that can occur during a case. No matter how prepared physicians may be before surgery, the situation can shift dramatically on the operating table and physicians need evidence-based support to make the smartest real-time decisions.
While the accumulated experience and skill of physicians allows them to make gut calls based on instinct, there is no substitute for data-backed, evidence-based information to support these calls. Many hospitals and physicians currently do not have the tools or technology to leverage the inordinate amount of data they produce to assist in making decisions in real time.
The ability of consumers and healthcare providers to access information and streamline processes using mobile devices is having a profound impact on healthcare.
For the first time this year, sales of smartphones are expected to surpass sales of traditional cell phones. More than 800 million smartphones are expected to be sold worldwide in 2013, according to Canalys. In addition, IDC predicts that more than 170 million tablets will be sold this year, surpassing laptop sales.
All these mobile devices in the hands of consumers means that the mobile app market will continue its torrid pace, and this is true in healthcare too. The market for mobile healthcare apps is expected to reach $400 million by 2016, according to ABI Research.
With the consumerization of healthcare, both doctors and hospitals have a vested interest in delivering an experience that will build patient loyalty. At the same time, new healthcare laws also are putting patients in a position of being more responsible for their own care. Healthcare providers who give patients the tools they need to simplify information and make informed choices will build stronger and longer relationships with patients. Mobile apps will be the heart of these tools.
While most of the worrisome news about transitioning to ICD-10 is correct, the most daunting of tasks are actually the easiest to accomplish. Yet unwittingly, most healthcare providers, following the various help forums and articles, have focused on chalking out a complete ICD-10 transition plan before all else. Then, the plan is too often delayed or scrapped altogether.
The trick to a successful transition starts at the grass-root level: analysis before planning the transition effort and timelines. A detailed impact analysis is critical, and since it is based on historical data, it can never be too early to get this done. Moreover, with comprehensive historical data analysis, the planning effort can be drastically reduced. Consider that NIIT’s research, which analyzed the historical data of multiple providers, has revealed that up to 90 percent of claims utilize less than 5 percent of the ICD codes used by providers. Thus, by focusing on the accurate mapping of 5 percent of the code subset being utilized, 90 percent of the risk can be mitigated.
So, we’ve finally done it – we’ve reached the sticking point in the battle of electronic health records. Apparently, as of April 2013, more than half of all office-based physicians and other eligible professionals received their meaningful use incentive payments for successfully using and adopting EHRs.
Which means … you guessed it – more than 50 percent of eligible professionals successfully used a certified EHR (of course the number is higher if you calculate the number of physicians not using a certified system).
According to Modern Healthcare, in April 191,305 physicians and EPs received EHR incentive payments from Medicare, and 88,903 have received payments from Medicaid and 11,117 from Medicare Advantage under programs created by the American Recovery and Reinvestment Act of 2009.
Guest post by Sean Armstrong, Director of Product Management at AppNeta.
Today, healthcare practices run on critical applications that connect remote users (hospitals, physicians, clinics) to centralized and hosted resources. From the largest medical centers to small clinics, healthcare organizations depend on network-sensitive applications every day. Electronic Health Records (EHR), ePrescriptions, medical imaging, online medical registries, desktop virtualization, VoIP, IP storage, cloud–based system, Software-as-a-Service — all of these critical applications help keep hospitals, physicians and clinics running. When these slow down or crash, so do the healthcare providers and the offices relying on them.
Here are five main reasons why every healthcare provider needs be able to monitor and manage application and network performance: