Transformation is sweeping across healthcare in the United States at a rapid rate. Healthcare organizations, regardless of size, need to embrace new technologies in order to keep up with the quickly changing landscape and comply with evolving regulatory requirements.
The solutions to these challenges have one thing in common, the need for accurate information. In some cases, the information required can be sourced from a single system, but in many situations, the need requires information from a wide range of systems that could include Electronic Medical Records (EMR), Claims, Financial and Human Resources.
The solution for many organizations starts with the creation of an enterprise wide data warehouse (EDW) that serves as their “single version of truth”. At the foundation of the data warehouse is the need for a data model that accurately organizes the data in meaningful ways. Many organizations will build their own data model while others will look to leverage an industry proven data model from an experienced vendor. This choice to buy vs. build, can be one that causes great debate within organizations both large and small.
At a high level, the pros to building your own enterprise data model will come down to flexibility and control. If you choose to build your own customized model, you will get to make each and every design decision based on how your organization operates, this can be very tempting.
The main advantage to buying a data model is the time to implementation. Many of the tough decisions are made for you, based on years of experience across a wide range of customers; purchased models are often much faster to implement.
As the debate continues you will need to weigh factors like experience, time to value, risk, integration accelerators and impact on your staff. Each of these topics needs to be considered as your organization decides whether to buy or build your enterprise data model.
Interested in more information on how to weigh the pros and cons of this critical enterprise decision? Join Perficient on November 18th for a complimentary webinar. We will examine critical factors that need to be evaluated when deciding whether to build or buy an enterprise data model. We will explore real-life client stories and discuss how they benefited from their decisions.
Upcoming Webinar: Healthcare Enterprise Data Model: The Buy vs Build Debate
Tuesday, November 18, 2014 @ 2:00 PM CT
Interoperability between different electronic health record (EHR) systems is one of the most important requirements that hospitals and physicians must meet as they prepare their systems for attestation in Meaningful Use Stage 2.
1) To make sure “information follows the patient regardless of geographic, organizational, or vendor boundaries”
2) To have at least one or more instances in which providers exchange an electronic summary of care with all the clinical data elements between different EHRs. Establishing this connectivity does not insure the real goal of collaborating across the continuum of care for the patient’s benefit.
The debate still rages on the role of the patient in this interoperability process as well. We have all, as patients, had our medical files spread across a family doctor, multiple hospitals, specialists, health plans and today, even multiple pharmacies. The prospect of creating a complete picture is staggering, let alone having all of those healthcare providers really collaborate on our behalf. Is it the patient’s responsibility in this ever-changing healthcare electronic revolution to compile this electronic mess into a coordinated whole or will the industry magically create it as a result of Meaningful Use Stage 2?
It is worth arguing that interoperability in Meaningful Use Stage 2 only creates a baseline of connectivity between two or more systems to exchange information and puts in place the ability of those systems to use the information that has been exchanged. It does not create collaboration on behalf of patients within the healthcare provider community, especially between competing players like local hospital systems or healthcare providers versus payers. Having the ability to connect only trades fax machines for electronic transactions, if tools aren’t employed for physicians for example to collaborate over a single patient.
In advocating for collaboration, let’s examine the reality of an exchange of a set of electronic transactions about a patient versus where the process would need to be for genuine care coordination. Today, a fax from the hospital to the family physician is the notification that the patient was hospitalized and needs follow-up in coming weeks. Based on the type of hospitalization, a call between the attending physician and family physician may be warranted, and a potential referral to a subsequent specialist may be in order. Simply communicating electronic documents doesn’t address the interaction between key people in the decision-making process and the assumption that the inclusion of unstructured physician notes will suffice may be optimistic.
This means that health information exchange is different than health information interoperability. Exchange is necessary for interoperability, but it is not sufficient by itself to achieve health information interoperability, especially to streamline real collaboration on behalf of patients. It is time to examine an expanded view of both interoperability and health information exchange to promote ease of collaboration between the parties involved, including secure physician to physician communications – electronic or instant message, for example, and secure physician to patient communications. As an individual patient having to deal with multiple patient portals today for communicating with my healthcare providers, there is a real concern to address this issue sooner rather than clean up confusion later.
Can we define collaboration in a way that traverses healthcare’s landscape of emerging connectivity?
There has been a lot of debate around the challenges within the healthcare industry. Much of the discussion stems from the fee-for-service model and the focus on services and reimbursement rather than the patient. Health information technology has its own set of challenges when it comes to addressing healthcare issues.
If we truly want to put the patient at the center of their own healthcare experience than we need to take a step back and look at the relationship of the patient and the entire healthcare ecosystem. Healthcare should focus less on the products and services and more on the patient and provider relationship. Furthermore, health IT should support these relationships, however, by its own definition it doesn’t.
By definition, Health information technology (IT) encompasses a wide range of products and services—including software, hardware and infrastructure—designed to collect, store and exchange patient data throughout the clinical practice of medicine.
The definition does not mention the patient and provider relationship and the emphasis is on products and services, software and hardware and does not reflect on the benefits of patient data exchange.
A better health IT definition: An automated approach that facilitates the relationship between the patient and the healthcare system through the accurate and secure electronic exchange of data, ensuring the right data is available at the right time for everyone that is engaged in the patient’s care.
This definition includes 3 critical components:
A new definition will not solve the challenges of the healthcare industry, but it is a good place to start. It may be enough of a push to ensure technology developers are developing meaningful applications that improve patient outcomes, which should be the ultimate goal of health IT.
The success of translational medicine is in the data and the ability to combine multiple sources of data to enable better patient care and outcomes. Unfortunately most academic research organizations (ARO) and hospitals have multiple systems that house data creating an inability to mine through the data to identify clinical insights, disease patterns or treatment options.
Patient records, genomic data and environmental data need to be in sync to speed the process of bringing safer therapies to market and provide “bench to bedside” medicine. Combining multiple sources of data can enable complex and meaningful querying, reporting and analysis for the purposes of improving patient safety and care, boosting operational efficiency, and supporting personalized medicine initiatives. Integrated data will enable implementation and delivery of translational medicine anytime and anywhere.
To register for the webinar click here
Combining Patient Records, Genomic Data and Environmental Data to Enable Translational Medicine
Wednesday, October 15, 2014 | 1:00 PM CT
When you played baseball as a youngster, and stepped into the batter’s box, the last thing you wanted to be was an “easy out”. Ironically, today many healthcare organizations are looking for the “easy out” to rapidly develop the business intelligence reporting needed to address regulatory reporting demands, population health management and chronic condition management, to name just a few.
The pressure to quickly stand-up an enterprise data warehouse, put data governance in place, start loading and cleaning data is intense just to get to the point of creating dashboards and offering mobile BI. Overloaded Healthcare IT teams are dealing with demands to compress traditional time-frames of 18-24 months to get the BI foundation in place down to as little as 4-5 months, start to finish.
This situation begs the old saying of “do you want it fast or do you want it right?” You can bet the answer today is both. Generally, healthcare organizations develop a BI strategy that examines the current state BI architecture, envision a future state BI architecture, document the gaps and create a time phased roadmap to build out the infrastructure, software and development required to meet the business needs. Just describing the process tells us that it will be complex and time consuming, right? Read the rest of this post »
I think most healthcare entities are now moving to a more frequent budget cycle and if academic, they probably have to do a semi-annual legislative budget. They probably also at a minimum re-forecast based on updated actuals once a quarter.
Is their value though to gathering actuals daily or weekly and adjusting tactical plans based on current month trends? In today’s rapidly evolving healthcare environment, provider organizations must be able to identify financial performance gaps continuously and quickly change course when needed. As we discussed in my blog: The Role of Finance Within the Hospital has been Elevated, this requires a partnership with operations to ensure that the correct metrics are correlated within the budget process. Agility is also influenced by the mechanism the hospital uses for budgeting and whether they use a rolling forecast to replace or supplement the annual budget process.
What is a rolling forecast? The rolling forecast is usually a quarterly budget with a two to three year horizon that keeps a close eye on the organization trajectory. Typically the forecast budget is not prepared at the department level but may instead focus on divisions or even at a hospital level. Global budget drivers and assumptions will typically be the same as the annual budget but those unique to a department or division may not be line items. The forecast is built using historical trends, current conditions and future assumptions for budget drivers. Some forecasts may be primarily driven by revenue drivers with expenses flowing from ratios defined to the model. Read the rest of this post »
Is there a correlation between price transparency and cost? I read an article in the HFMA Strategic Financial Planning Newsletter recently about this and I can relate my personal experiences to it wholeheartedly. My observations are that hospitals segregate these two activities but I believe they are explicitly linked. I know there are many factors that influence price setting, not the least of which is the federal government (Medicare/Medicaid), but I suspect the reason that hospitals don’t more closely link pricing to margins is that they lack visibility into their own data.
When I first started working in healthcare in the late 90’s, my only prior exposure to revenue cycle automation came from the airline industry where pricing is tightly linked to both demand and yield. I was part of the team that helped Continental Airlines transition into the era of de-regulation. It didn’t take industry leaders very long to identify the metrics that truly informed pricing once the government was taken out of the equation. This taught me very valuable lessons about analytics and instilled in me a drive to use data to improve operations.
To understand and achieve sufficient transparency and maintain a proactive approach to maintaining margins, hospitals must be capable of correlating costs for supplies and drugs, etc. with the cost of providers and overhead costs. Then they must compare this with the payments from payers, individuals and other purchasers. While we certainly can’t take the federal government out of the equation for hospitals, recent expectations have been set for quality performance that may help the affected organizations begin to take a more margin focused view of pricing. Bringing together the necessary data is not simple and definitely should be approached iteratively using a configurable set of analytic tools that can provide the right data to the right individuals in the organization who manage operations and continue or create new services. Read the rest of this post »
I’m having a good laugh at all of the memes floating through social on the “hugeness” that is the new iPhone 6. Apple even wisely predicted the size sentiment (℅ super user research) and landed a spot featuring Jimmy Fallon and Justin Timberlake that provides a few laughs.
So, while size-by-size comparisons are even a thing in my household (husband has the new phone while I’m skipping a version), I’ve found that my favorite features of the new release are actually a part of iOS8, and, therefore, I don’t need to get the new phone, and the extra inch of screen size that provides, to have them.
Let me explain. I’m a big fan of the Quantified Self, and, as a runner and biking enthusiast, I like apps that help me track my progress. I especially like when those apps are extensible and connect to provide an entire Quantified Self experience. I’m not here to talk about HealthKit, though. I’m here to talk about a lack of functionality I have found in these apps when it comes to safety. I’m a woman running or cycling alone, and sometimes, if my work day creeps into the evening, the sun goes down before I get started. I’ve combed the app store trying to find an answer, and there really aren’t good answers out there. What I need is:
The iOS answers to these problems:
So, there you have it. If you know of any alternative options for exercise safety, then I’d love to hear about them!
Healthcare costs are rising at a faster pace than the economy is growing. Hospitals are often the focus of this concern, because they constitute the largest single component of healthcare spending. When looking at hospital costs, it is important to keep in mind that there are both direct and indirect expenses that contribute to the total cost of care.
How do we understand total cost of care? Our team of experts leverages a proprietary technology for our clients called the Perficient High-Performance Costing Expressway, which enables transparency of fully burdened margin by service, patient and procedure. For decades, spreadsheets and costing software have been the best alternatives in determining cost of care. It is now more important than ever to transform these methods and leverage administrative, clinical and financial data in order to gain control of healthcare costs. Creating transparent costing models to indicate profitability across multiple dimensions of data is the key to driving healthcare costs down.
Embracing data-driven decision making in a provider setting requires agile thinking to pinpoint and respond to the short- and long-term needs of the organization. This shift requires finance departments to transcend from the typical focus on aggregating data to a value-added analytical view of hospital data. This new approach will provide greater visibility into changes in variables and assumptions and will require organizations to fully understand and ensure transparency exists for key performance indicators.
In evaluating supplies, labor, productivity or clinical effectiveness, the quality/cost/value equation requires an organization to truly understand its data. This includes not only considering the right product at the right place but also applying a broader perspective on clinical evidence for resources used and approaches employed. Data by itself doesn’t make a company successful; organizations must act on information and filter what is useful, appropriate, and above all else actionable. Those few organizations that are able to transform data into decisions and harness the power of insightful and timely analytics are ahead of their competition.
Perficient will be on hand to demonstrate the High-Performance Costing Expressway on display at OpenWorld 2014. Stop by and visit with our Healthcare experts at the Healthcare Solutions in Industry Central (Marriott Hotel 2nd floor).
Not attending #OOW14? Learn more about our costing solution here.
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In recent years, dramatic advances in molecular biology, genomics, and related technologies have resulted in greater understanding of cancer at the molecular level. It is now possible not only to identify the genetic and molecular variations in each patient’s cancer cells, but to apply the results from the tumor profile, in some circumstances, to begin to inform treatment strategies that target the molecular underpinnings of the specific disease in each patient.
“Precision medicine,” also known as “personalized medicine,” is the term used for this transformative new model of health care that involves the selection of diagnostic tests that have the potential to identify changes in each individual patient’s cancer cells. The use of that knowledge may help to prevent and treat cancer through the development of treatment strategies to target these specific molecular alterations. Ultimately, the goal of precision oncology is to improve patient outcomes. 1
I attended a conference session recently on this topic where an esteemed speaker panel took the audience though their vision of a time in our future when we could have a simple blood test on the way to our doctor’s office and arrive at the appointment to find our doctor fully prepared with a diagnosis and the ideal medication would already be identified based on our genetic makeup and perfectly formulated to avoid side effects for which you we are susceptible. Imagine this on a larger scale to speed up drug development, to create more precise therapies, faster and less expensively and apply this approach to improve the lives of people worldwide, at lower cost.
Perficient is helping clients such as the University of Colorado to establish a fully integrated informatics “highway” for precision medicine using the Oracle Health Sciences Translational Research Center platform to address formidable challenges such as:
Join us at #OOW14 to hear Michael Ames, MBI, Associate Director, Health Data Compass, Center for Biomedical Informatics and Personalized Medicine, University of Colorado and my colleague Lesli Adams, MPA @LesliAdams during the session “Creating a Digital Healthcare Safety Net with EHA and OBI for Care Transitions” located at the Marriott Marquis – Salon 10/11; Wednesday, October 1, 11:30am – 12:15pm.
We are an Oracle Platinum partner and we’ve gained valuable expertise from nearly 2,000 Oracle projects with our clients the past 15 years and we have amassed vast amounts of best practices and ideas to share. Stop by and visit with our Healthcare experts at the Healthcare Solutions in Industry Central (Marriott Hotel Atrium Lobby) at the Perficient kiosk (HMH-003) for a demo of the Translational Research Center.
Not attending #OOW14? Join our webinar Combining Patient Records, Genomic Data and Environmental Data to Enable Translational Medicine Wednesday, October 15, 2014 1:00 PM – 2:00 PM CT.
2 Michael Ames, MBI, Associate Director, Health Data Compass, Center for Biomedical Informatics and Personalized Medicine, University of Colorado
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In ACA and QRS – Shoot for the Stars Part 1, I laid out the overall domains that are going to be used to score QHP plans offered through the Marketplace. In Part 2, I discussed some factors to consider for the data derived measures. In this blog, we will take a closer look at the survey derived measures and what factors a QHP issuer should consider to achieve high scores.
Again, for reference all 43 of the required measures can be found on the CMS website (click here).
Now let’s take a look at some factors to keep in mind when dealing with the Enrollee Satisfaction Survey (ESS) derived measures:
Leverage CAHPS Processes
As mentioned in Part 2, it was required to get Health Plans Accredited to offer on-market. In addition, CMS aligned required QRS ESS measures with current CAHPS measures that are typically required during accreditation. And just as an organization should leverage HEDIS for data, make sure to leverage current investments in CAHPS to keep initial costs low while jump starting ESS efforts.
Read the rest of this post »
We live in a world of information, everywhere we turn someone is collecting information about us. The technology advancements over the last 10 years are mind-boggling, but new technology is usually escorted by apprehension as our privacy continues to diminish and security is anything but secure. From cookies on the internet to a basket analysis at the supermarket, “big brother” is always watching.
The healthcare industry is no different. Healthcare organizations are surrounded by data: clinical, operational and financial; internal and external; structured and unstructured. There is so much information that healthcare providers don’t know what to do with it. The problem with healthcare is not a lack of information. The problem is healthcare organizations often have disparate systems that lack continuity. The absence of interoperability within IT infrastructures ultimately means that the right information is not available to the right people at the right time. Healthcare organizations can have all the information in the world, but if the information is not cohesive and can’t be used efficiently to improve clinical outcomes than information really doesn’t matter.
In order for healthcare organizations to improve outcomes, communication between systems is paramount. Despite industry standards such as EDI/X12, HL7 and CDA, information delivery is not effective. Most healthcare organizations understand the importance of untangling the interoperability web, but those same organizations don’t know where to begin.
Government regulations such as Meaningful Use Stage 2 (MU2) are putting additional pressure on healthcare organizations to improve the quality of care, coordination of care and population health management. A strong interoperability backbone that provides system connectivity is the key to attaining MU2. Interoperability transforms information into key insights that drive better clinical outcomes and improve the lives of individuals and communities.
Do you understand the importance of interoperability but not sure where to start? Perficient will be teaming up with technology partners IBM and Oracle to bring you 2 complimentary webinars:
Tackle Healthcare Interoperability Challenges and Improve Transitions of Care
Thursday, September 25th @ 12 CT
Learn More and Register
Engage Patients, Reduce Manual Processes and Drive Key Insights with Interoperability
Tuesday, October 2nd @ 2 CT
Learn More and Register