Join us Wednesday, May 30, at 12:00 PM CDT, for the Perficient webinar, “Using Big Data for Improved Healthcare Operations & Analytics.” Register now!
Healthcare providers are faced with significant challenges due to regulatory and reimbursement requirements and the everyday pressures of managing care. Providers must be proactive to manage the health of a population for ACO, and must be able to minimize admits or re-admits. Medicine needs to be more personalized, and patients need to be monitored more effectively – whether in the hospital or at home. Providers are drowning in data and are not using all of it effectively in order to glean the insight needed to face the many daunting challenges in healthcare.
Using Big Data technologies, providers can uncover the insight they need by being able to investigate massive volumes of data, improve processes in real time based on the high velocity of data from machine-generated sources such as medical devices and sensors, and to be able to tie together data with a wide variety of formats and semantics.
Big Data offers the ability to investigate and use more of your data, including unstructured data from clinical notes, medical literature, audio and video with less expense than traditional technologies.
Register for the webinar to learn what Big Data is, how it can be used for healthcare, architecture and technologies involved (Hadoop, NoSQL, Cassandra, Semantic Web, etc.), and the impact Big Data has on data management and application development.
Now that we’ve established what a canonical data model is, let’s talk about our objectives for what we want to achieve with our Canonical Data Model and what toolsets can be applied. In my Canonical Data Modeling environment, I want to store and manage my entities and their relationships. I want support for the Conceptual, Logical, and Physical Data Models. I want support for normalization and/or dimensional modeling. I want to store and manage my business rules. I want to be able to generate XML and WSDLs for my SOA developers. I want to perform these acts in an Enterprise Model so I can be model driven. And I want to be able to modify my models and generate my supporting SOA artifacts as quickly as the business changes.
A few additional objectives for any Canonical Data Model environment should:
Finding a toolset for this effort is not easy. IBM’s Data Architect, Computer Associate’s Erwin, and Embarcadero’s ER Studio are good toolsets for modeling relational objects (rdb). As far as I know, none of them will manage the business rules, and generate the XML & WSDLs to support a SOA environment. However, these vendors are advancing their toolset towards this mean, and I think you’ll see progress in that regard in the next few years. Read the rest of this post »
ACOs are paving the way for a healthcare payment model that is based on quality and efficiency instead of volume. They were created as a response to health reform initiatives that focus on improving patient safety, quality of care and affordability. As the name suggests, ACOs are institutions that collectively share the risks associated with improving outcomes and patient satisfaction. ACOs seek to make these improvements by improving the coordination of care amongst nurses, physicians, practitioners, hospitals and health care providers.
The goals of ACOs are to successfully provide three foundational elements:
Continuum of Care: These organizations rely heavily on the transfer of data to and from different institutions and areas of care to meet its objectives.To meet each of these characteristics, organizations will put forth substantial efforts and will rely heavily on technology for help.
Role of Technology
Solutions provided by Health Information Technology (HIT) are critical to the ACO delivery of care model, because it is the solution to integrating disparate data from multiple locations and care givers. By investing in electronic medical records (EMRs), enterprise data warehouses (EDW) and health information exchanges (HIEs), data can and will be used to overcome the cost and quality healthcare hurdle.
An ACO must have an advanced HIT infrastructure to appropriately manage the entire population and connect with their members using tradition and alternative methods of communication. As a result, we can expect ACOs to lead the way to healthcare solutions and serve as examples of what technology can do for healthcare.
Spurred on by Meaningful Use, there has been an explosion in the implementation of EHRs over the last several years. This tidal wave has been sweeping through the healthcare community, sucking up much of the available bandwidth that organizations have to deal with change of this magnitude. The effect is really no different than what other industries have been through over the last couple of decades beginning with the emergence of ERP systems in the late ’80s, early ‘90s. The organizations setting up EHRs have the opportunity to look back at the experiences those industries and to glean lessons learned. One of the biggest is that there will be a second wave, which we are already starting to see. This second wave is driven by the desire for information and knowledge. Folks realize that the instillation of technology to support operating standards, policies and business procedures via EHRs provides for a great source of transactional data. Data that is just waiting to be warehoused, given meaning, aggregated, sliced, diced and analyzed. The challenge here, and a trap that many fall into, is that the data can seem so close at hand, accessible and, on a small scale, manipulatable, that the cost and effort to deploy analytics solutions to get at the data aren’t that great. Invariably, after much investment and frustration at the inability to get all of the data, many realize that what they initially focused on was just the tip of the iceberg and that the effort of managing and distributing a large amount of information and knowledge across a large organization requires a great deal planning, time, people and investment. While not quite as invasive as the rollout of the EHR, the investment in analytics is substantial, must be planned and executed over a period of time.
Avoid the Trap
There are a couple of tell-tale signs that you’ve fallen into the trap. The first is the 80/20 rule, where you end up spending 80% of your time collecting, cleaning, organizing and making data available, leaving only a small amount of time to analyze and act upon it. The second sign is the executive dashboard, the situation where a large number of people spend a great deal of time every month, sourcing from the new EHR and other transactional platforms, aggregating, calculating and making available, with very little automation, to a select few (ie., the senior management team). A dashboard that others in the organization don’t have access to, nor, due to its highly aggregated level, is it of much value to, although I’m sure it’s been a source of many “fire-drills.” The “fire-drill” being painful in that the lengthy and manual manner, in which the particular dashboard measure is deduced, must be dissected in order to determine was there really an issue or is it related to the calculation and aggregation process. Then, if there is an issue, where? Typically, you’re already 45-90 days out from the occurrence of the negative event.
It’s Not Just About the Transactional System
What can health organizations do about this? First, they must realize that the implementation of the EHR creates both a great source of data and a need within the organization to aggregate that data, combining with other information from across the organization and from third parties. With this awareness, the EHR effort should be shadowed by one focused on developing a strategy, objectives and plans supported by milestones to deploy analytics in a controlled and deliberate manner. To successfully do so, it will be quickly realized that there are dependencies that must be addressed. Such as the need for data governance, inclusion of any master data management activities already underway and the need for an infrastructure that enables the transactional, analytical and other systems and devices to access and exchange data, whether an HL7 transaction, X12 out-going batch file, an EHR feeding the analytics store or a patient portal via SOA. Third are awareness, education and training. Analytics unleashed upon the employee population all at once can be analogous to drinking from the fire-hose. The effective use of analytics is driven by the ability of the organization, department, teams and individuals to clearly articulate a specific need for information, putting into the context of the particular business process(es), activity(ies) and task(s). Ideally, analytics are doing two things for us; 1) reinforcing that we’re meeting or exceeding the desired performance level, as we all need that periodic feedback that everything is ok and 2) an exception is occurring, which is where we’ve defined what it is to be operating normally and an event or occurrence has arisen that is outside the box, so the appropriate people must be alerted and have the ability to drill down into abnormal event to immediately begin identification and resolution of the issue.
What Does It Mean to Me?
How does all of this relate to Utilization and Population Health? Over the last few months, there has been a noticeable increase in activity amongst health systems around the desire to understand more about the dynamics of the marketplace they do business in and the population they serve. They are more aggressively pursuing sources of information outside the organization that can be combined with internal information to begin to paint a picture of not only the morbidity of the local population they serve, but the usage patterns the population is following in seeking out care. Seeking care isn’t as consumer-friendly as many would hope and most health coverage leaves the choice of access to the consumer. Health systems can begin to identify and track those patterns of utilization, situations of network leakage, repeat visits, begin to stratify the local population for risk, predict demand on facilities and impact to case-mix. To the extent the health system is pursuing community outreach and educational programs; this information can be input into designing these programs as well as way to measure their impact. The outreach and education can occur in conjunction with the PCPs and, potentially, the health insurance companies servicing that same membership. The unspoken objective of all is to better understand and improve on the outcome of care.
Dan Bowman, in a recent article, quotes a family physician who feels social media has no place in healthcare. He asserts busy physicians don’t have time to add yet another technology to their already busy schedules. I see his point, but I have to challenge this.
Social media, including Facebook, Twitter, LinkedIn, and many other sites has drastically changed the way people (a.k.a patients) communicate with each other. Accountable care, population management, and chronic disease management activities are all about enhanced communication with patients. It would be borderline negligent to ignore social media as a vehicle to enhance this communication.
Patients have been trained from birth to delegate their healthcare decisions to their physicians. Most completely ignore healthcare issues and activities until they get too sick to overlook their healthcare trajectories. Reaching and training these patients before their disease becomes chronic is needed desperately to improve outcomes.
I can see a scenario where Facebook threads between the care team and the patient are used as reminders, updates, and information gathering tools for patient data. There is far less cost to train one or five care providers than to encourage hundreds of patients to learn a new system. Facebook is sticky. Today’s model is to build a patient portal site that requires patients to actively connect, sign-on, and interact. Most of them only do this when they have a specific need. Since they are already actively using Facebook, why not build sites that meet them on their own turf? This can still be done securely, easy to use, and relatively quickly.
Physicians have a great opportunity to market their services and reach their patients if they embrace Twitter. The key here is to build a following. Twitter is based on sending small sound bites to a group of followers. Followers are people who have chosen to listen to what the sender has to say. This is a marketer’s dream that the healthcare industry should consider embracing. Once a physician has built a group of followers, they should post links to wellness and diet tips, new practice offerings, and other general health improvement ideas. These posts will be immediately received by a list of patients who want to receive this kind of information.
Physicians who are too busy to learn about social media are missing a giant opportunity to educate and reach patients on their terms. The good news is some of this can be delegated. Hire an intern who already knows these tools and let them build an outreach. Assign this to a computer savvy administrator.
Social media has the potential to make a huge impact on healthcare. With some creative thinking, they not only mix, but can be a catalyst to drastically change patient motivation and interaction.
In Part II of this blog series on the Patient Protection and Affordable Care Act (PPACA), I will explore the following statement: “Adults with pre-existing conditions became eligible to join a temporary high-risk pool, which will be superseded by the healthcare exchange in 2014.To qualify for coverage, applicants must have a pre-existing health condition and have been uninsured for at least the past six months. There is no age requirement. The new program sets premiums as if for a standard population and not for a population with a higher health risk. Allows premiums to vary by age (4:1), geographic area, and family composition. Limit out-of-pocket spending to $5,950 for individuals and $11,900 for families, excluding premiums.”
In addition, the premiums (effective September, 2010) for this high-risk pool were set as follows:
What is disturbing about this premium scheme is that individuals who cannot control their age are required to pay much more than individuals who can control their tobacco-related habits. Does this seem disturbing to anyone else?
While there is a limit on out-of-pocket spending, there is no ceiling on premiums (yet) and no floor for benefits. There is a 40% excise tax on premiums greater than $27,500 for families and $10,700 for individuals. However, this tax on health insurance companies does not go into effect until 2018. In addition, the healthcare exchange mentioned in the provision does not take effect until 2014.
The healthcare exchange is a government subsidy that will be provided to families based on size and annual income as a percentage of the federal poverty line. For instance, a family of 4 whose income is 400% above the poverty line (in other words, $88,200) will have a maximum out-of-pocket premium of $8,379 (9.5% of income). However, for another two years there is no premium ceiling, and for another six years there is no penalty for charging high premiums. Further, there is no premium ceiling at all for families whose annual income is above $88,200. What can this mean for a middle-class family in the US?
In the same year as the healthcare exchange takes effect, the government will also begin imposing a $2,000 tax per employee on employers who do not offer health insurance and employ more than 50 individuals. Thus, in two years, a family of four making $90,000 annually can lose its health benefits and be forced to purchase its own insurance for which there will be no subsidy and no premium ceiling.
What if the primary breadwinner of this family loses his job but has a pre-existing condition that may not be insured for 6 months to 10 years by a new healthcare package, based on the state in which the family resides? Even if he finds a new job right away, will he have to refuse healthcare for six months in order to enter the temporary high-risk pool of individuals, some of whom may have to pay up to four times the standard premium because they are older? Will this individual be able to afford this high premium when combined with insurance costs for his family? How will he insure his family during those six months? I have yet to find answers to these questions in the PPACA. I hope I am missing something.
Farzad Mostashari , in a meeting with the National Quality Forum in late April, says, “In 2016, it’s going to be rare to find a doctor without EHRs.” He went on to say we need to “… find people who have done it, who understand deeply what it takes and not just the challenges but how to overcome those challenges.” He finished by reminding us to “put patients at the center.” Before we can populate the EHR, we must capture this information in a form that is usable in the EMR.
This is fantastic news for all of us healthcare analytics fans. The proliferation of EMRs signals the industry movement toward installing tools that can capture discrete data that is the cornerstone of a good business intelligence strategy. Putting tools to capture this key data in everyone’s hands is a mandatory first step towards using this data to improve outcomes, save costs, and put the patients at the center.
EMRs are a giant step from paper, but they are only useful if the data captured can be reused. I urge everyone in the industry to take it just a tiny bit further. While you are training yourself and your teams to use these EMR systems, spend a little time on standardization and vernacular. Train your staff to use specific terms that are searchable and uniform. The benefits of this are hundredfold.
This is important for research. To keep them flexible, EMRs enable a lot of free-form text entries. This is a double edged sword. This flexibility enables the healthcare team to capture notes and details about patient-specific conditions. Unfortunately, if these notes are not consistent, this flexibility also encourages the entry of terms that are nearly impossible to search and group.
Recently, I did analysis at a large ED on the east coast. I was reviewing the Complaint field and I found entries including SOB, SB, hard to breathe, shortness of breath, short breath, breathing difficult, and Lungs hurt. All of these mean the patient is complaining of shortness of breath. Unfortunately, when a database engine encounters each of these terms, it assumes they are all different. In a scenario where we want to report on the number and types ED visits, it would be preferable to group all these terms under a single condition and report seven instances of SOB as opposed to a single instance using each term in the system.
There are some translation tools that use ICD, SNOMED, and UMLS to try to standardize language. These are useful and get the data a little bit more standardized. These tools are not nearly as useful as training and oversight. Just a few minutes spent during the roll-out of the EMR and a couple instances of reviewing the data and some remedial training will show a far larger return on the time invested. This approach also appeals to my motto “don’t use technology to fix a training problem.”
Perficient worked with Meriter Health Services to implement Microsoft Business Intelligence and SharePoint 2010 to work in conjunction with their Epic Electronic Medical Records system. The result of this paring has been a decrease in costs, increased efficiency across the organization, and ability to locate relevant information and data quickly.
Perficient recently paired up with Epic Systems to create the first integration of the two systems in the U.S. for DuPage Medical Group. The solution also incorporates the Microsoft Business Intelligence solution, which improves reporting accuracy to drive business efficiency.
On April 17, 2012 the Department of Health and Human Services (HHS) published a proposed rule that would delay, from October 1, 2013 to October 1, 2014, the compliance date for the International Classification of Diseases, 10th Edition diagnosis and procedure codes (ICD-10). HHS is seeking comments by May 17.
The proposed rule extends the deadline for use of ICD-10 code sets used in claims management and medical billing from October 1, 2013 to October 1, 2014, responding to providers concerned with the difficulty of implementing the new edition in the time provided. AHIMA and HIMSS are urging us to “stay the course” with our implementation planning. I agree.
Payers and Providers do not always have alignment of their own internal business and IT. Payers and Providers are not always in agreement with each other’s medical policy that will be used to defend a GEM. Payers and Providers are not always in agreement with each other’s perspective of benefit and reimbursement. Now let’s scale up from 17,000 ICD-9 codes to 155,000 ICD-10 codes…
Payers and Providers Need to Get Along
The clock is ticking, and we’re still trying to define neutrality before we can even start to build processes to verify neutrality, and then we need to re-contract…
The Workgroup for Electronic Data Interchange (WEDI), an industry advocacy organization, conducted the survey in February and has submitted results to the Centers for Medicare and Medicaid Services (CMS). Based on the premise that ICD-10 impact assessments should have been completed in 2011, the WEDI survey results find:
In order to start making sense of the ICD-9 to ICD-10 code variability risk, payers and providers must consider the following:
Internal Business and IT need to get along. This is not typical SDLC. Testing sooner rather than later will allow for the re-introduction of test results within each iteration of process refinement. Organizations need to embrace collaborative and dynamic requirements management.
Organizations need to pick partners wisely. You can’t outsource accountability for compliance through vendors and hosted solutions.
Adjudication, benefit assignment, reimbursement schedules and re-contracting can happen later. Let’s make sure we don’t miss the mark on our assessment of clinical equivalency. Medical policy will provide context for defending our GEM, but we’ll still need to verify through testing. Even though HHS has proposed a 1 year reprieve, Payers and providers need to get to the table asap.
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