From Free Text Clinical Documentation to Data-rich Actionable Information

Hey healthcare providers! Yeah you the “little guy”, the rural community hospital; or you the “average Joe”, the few-hundred bed hub hospital with outpatient clinics, an ED, and some sub-specialties; or you the “behemoth”, the one with the health plan, physician group, outpatient, inpatient, and multi-discipline, multi-care setting institution. Is your EMR really just an electronic filing cabinet? Do nursing and physician notes, standard lab and imaging orders, registration and other critical documents just get scanned into a central system that can’t be referenced later on to meet your analytic needs? Don’t worry, you’re not alone…

Recently, I blogged about some of the advantages of Microsoft’s new Amalga platform; I want to emphasize a capability of Amalga Life Sciences that I hope finds its way into the range of healthcare provider organizations mentioned above, and quick! That is, the ability to create a standard ontology for displaying and navigating the unstructured information collected by providers across care settings and patient visits (see my response to a comment about Amalga Life Science utilization of UMLS for a model of standardized terminology). I don’t have to make this case to the huge group of clinicians already too familiar with this process in hospitals across the country; but the argument (and likely ROI) clearly needs to be articulated for those individuals responsible for transitioning from paper to digital records at the organizations who are dragging their feet (>90%). The question I have for these individuals is, “why is this taking so long? Why haven’t you been able to identify the clear cut benefits from moving from paper-laden manual processes to automated, digital interfaces and streamlined workflows?” These folks should ask the Corporate Executives at hospitals in New Orleans after Hurricane Katrina whether they had hoped to have this debate long before their entire patient population medical records’ drowned; just one reason why “all paper” is a strategy of the past.   

Let’s take one example most provider organizations can conceptualize: a pneumonia patient flow through the Emergency Department. There are numerous points throughout this process that could be considered “data collection points”. These, collectively and over time, paint a vivid picture of the patient experience from registration to triage to physical exam and diagnostic testing to possible admission or discharge. With this data you can do things like real or near-real time clinical alerting that would improve patient outcomes and compliance with regulations like CMS Core Measures; you can identify weak points or bottlenecks in the process to allocate additional resources; you can model best practices identified over time to improve clinical and operational efficiencies. Individually, though, with this data written on a piece of paper (and remember 1 piece of paper for registration, a separate piece for the “Core Measure Checklist”, another for the physician exam, another for the lab/X-ray report, etc.) and maybe scanned into a central system, this information tells you very little. You are also, then, at the mercy of the ability to actually read a physicians handwriting and analyze scanned documents of information vs. delineated data fields that can be trended over time, summarized, visualized, drilled down to, and so on.

Vulnerabilities and Liabilities from Poor Documentation

Relying on poor documentation like illegible penmanship, incomplete charting and unapproved abbreviations burdens nurses and creates a huge liability. With all of the requirements and suggestions for the proper way to document, it’s no wonder why this area is so prone to errors. There are a variety of consequences from performing patient care based on “best guesses” when reading clinical documentation. Fortunately, improving documentation directly correlates with reduced medical errors. The value proposition for improved data collection and standardized terminology for that data makes sense operationally, financially, and clinically.   

So Let’s Get On With It, Shall We?

Advancing clinical care through the use of technology is seemingly one component of the larger healthcare debate in this country centered on “how do we improve the system?” Unfortunately, too many providers want to sprint before they can crawl. Moving off of paper helps you crawl first; it is a valuable, achievable goal across that the majority of organizations burdened with manual processes and their costs and if done properly, the ROI can be realized in a short amount of time with manageable effort. Having said this, the question quickly then becomes, “are we prepared to do what it takes to actually make the system improve?” Are you?

Healthcare Analytics to the Rescue!

Why does my health insurance cost so much?

It’s that time of the year again. No, I am not talking about the holidays. It’s the time of the year, when you figure out how much more money you need to make, in order to afford the rise in your healthcare costs. It’s Annual Enrollment time! But as most folks have already realized, there probably won’t be any raises, bonuses, etc., this year to help off-set the rise in healthcare premiums. The economy is experiencing its biggest downturn since the Great Depression and yet our quoted health insurance cost for next year is rising at a double-digit pace. How is that possible?

“Over the last decade, employer-sponsored health insurance premiums have increased 131 percent”.

My wife and I calculated that pre-tax, she would need to earn another $ 1,200 a year this year to off-set the rise in the monthly premiums being charged for an HMO plan with family coverage. Currently, we belong to the #1 ranked Health Plan in the country, which is increasing its rates to the tune of $100 a month for the  same level of coverage as last year. Unfortunately, we have been experiencing this trend for more than the past 20 years.

I realize its not a simple answer, and there are several external factors including rising pharmacy costs, inflation, etc. However, one could argue that since the economy is in a tail-spin, unemployment is sitting just under 10%, and the federal government is wasting time and my tax dollars trying to create a new public option for health coverage, that the best option for insurers is to hold premiums steady and to finally get a handle on what are the true drivers of cost and utilization. Thus, they would not risk losing its most important constituents, their employer groups and members, who every year are now faced with the idea of reducing their level of healthcare coverage just to make ends meet.

If the #1 health plan in the country is raising their premiums by $100 a month for a basic HMO plan, can you imagine what the lower ranking health plans will charge to their members? There are no quick-fix-it solutions for the healthcare industry. However, with so many inefficient processes, fraud, overhead, flawed reimbursement methodologies, expensive compliance and technology projects, etc., the industry is ripe for opportunities to become more analytics focused. With today’s business intelligence and data warehousing technologies available, health plans now have the ability to create high-value metrics that involve integration of disparate data sources from key areas such as: sales & marketing, operations (ex. Claims processing), and cost and utilization across members, providers, and employer groups.

Despite the quoted savings achieved by health plans from a variety of medical management programs, disease management, formularies, network discounts, etc., why is it never passed onto a subscriber’s premium? Are health plans not evaluating the right metrics? Pushing the boundaries for increasing the use of payer analytics will allow health plans to truly understand the drivers of cost and utilization and thus to migrate their business model to become more predictive in nature. Maybe this is wishful thinking, but a health plan could actually reduce their monthly premiums if they can drive out the unknown costs and inefficiencies. A futuristic but intriguing thought would be to have benefit plans that are created and priced for each member, which is based on both historical utilization and predictive analytics to determine the monthly premiums.

At a minimum, can we stop the double-digit price increases?

The Patient Centered Medical Home (PCMH)

In a recent article released by IBM, an argument is made for a transition in the U.S. healthcare system to a team-based approach based on the Patient Centered Medical Home (PCMH) model. A strong case is made from a description of the model, its’ players, technology, and benefits. The critical change that must be established first, though, is the healthcare systems’ evolution to a data-driven system. The access to, higher quality and integration of data, across disparate silos of information, will provide the foundation for this change. Only then can the position of Dr. Douglas Henley, EVP and CEO of the American Academy of Family Physicians, “ A smarter health system is one based in comprehensive patient centered primary care which improves patient/physician communication, the coordination and integration of care, and the quality and cost efficiency of care” be achieved.

The quality and cost of care is what we hear the most about in news headlines. However, the success of each piece of Dr. Henley’s statement is based on the ability of a team of providers to access accurate and updated patient data across care settings and over time in order to proactively suggest lifestyle improvements and reactively diagnose and recommend appropriate treatments.  Fundamentally, each decision maker and operating entity needs a data strategy for how it will achieve the ambitious and often ambiguous goals it likes to claim.

I’ll recite a popular management mantra I’ve heard numerous times, “you can’t manage what you can’t measure.” The healthcare system is a data rich environment. Cleaning, manipulating, and leveraging  the huge volume of data available will become the critical success factors that will enable the linkage between education, research, the delivery of care and its outcomes, to benchmark and monitor the performance of the continuous improvements necessary to bring costs down and quality up.  

Players in the healthcare world will soon find out (if they haven’t already) a principle all those in the data world already know:

• Good data, appropriately aggregated and manipulated, drives accurate information;
• Accurate information is not a luxury that most decision makers have;
• The executives, managers, physicians, nurses, nurse practitioners, educators, pharmacists, researchers, and other stakeholders that do have access to accurate information are in a position to leverage and evolve this data and information from satisfying compliance and regulatory requirements to enabling an organizational knowledge-based asset.

Actionable data will drive the improvements that you see scattered across headlines and mentioned in political speeches in the past and no doubt, in the future.

Image courtesy of Texas Family Physician

ICD-10: Apocalypse or Advantage?

With humanity coming up fast on 2012, the media is counting down to this mysterious — some even call it apocalyptic — date that ancient Mayan societies were anticipating thousands of years ago.  However, the really interesting date in healthcare will happen one year earlier. In 2011, per the mandate of Senate Bill 628, the United States will move from the ICD-9 coding system to ICD-10, a much more complex scheme of classifying diseases that reflects recent advances in disease detection and treatment via biomedical informatics, genetic research and international data-sharing. For healthcare payers and providers that have used the ICD-9 coding system for submitting and paying healthcare claims for the last 30 years, it could be apocalyptic without proper planning and execution.  Conservative estimates of the cost of switching to ICD-10 are 1.5 to 3 billion dollars to the healthcare industry as a whole and nearly $70,000 for each doctor’s practice.

Since 1900, regulators of the U.S. health care system have endeavored to give care providers a systematic way to classify diseases so that care processes could be standardized and appropriate payments made. Like many of the world’s developed health care systems, the United States follows the World Health Organization’s (WHO) International Statistical Classification of Diseases and Related Health Problems (ICD) code standard that is typically used internationally to classify morbidity and mortality data for vital health statistics tracking and in the U.S. for health insurance claim reimbursement. In 2011, technically, healthcare providers and payers will be moving from ICD-9-CM to ICD-10-CM and ICD-10-PCS.  To meet this federal mandate, it will be essential that information systems used by U.S. health plans, physicians and hospitals, ambulatory providers and allied health professionals also become ICD-10 compliant. The scale of this effort for healthcare IT professionals could rival the Y2K problem and needs immediate planning.

The challenge is that the U.S. adoption of ICD-10 will undoubtedly require a major overhaul of the nation’s medical coding system because the current ICD-9 codes are deeply imbedded as part of the coding, reporting and reimbursement analysis performed today. In everyday terms, the ICD-9 codes were placed in the middle of a room and healthcare IT systems were built around them. It will require a massive wave of system reviews, new medical coding or extensive updates to existing software, and changes to many system interfaces. Because of the complex structure of ICD-10 codes, implementing and testing the changes in Electronic Medical Records (EMRs), billing systems, reporting packages, decision and analytical systems will require more effort than simply testing data fields – it will involve installing new code sets, training coders, re-mapping interfaces and recreating reports/extracts used by all constituents who access diagnosis codes. In short, ICD-10 implementation has the potential to be so invasive that it could touch nearly all operational systems and procedures of the core payer administration process and the provider revenue cycle.

A small percentage of healthcare organizations, maybe 10 to 15 percent, will use ICD-10 compliance as a way to gain competitive advantage – to further their market agendas, business models and clinical capabilities. By making use of the new code set, these innovators will seek to derive strategic value from the remediation effort instead of procrastinating or trying to avoid the costs. An example will be healthcare plans that seek to manage costs at a more granular level and implement pay for performance programs for their healthcare providers. In addition, ICD-10 offers an opportunity to develop new business partnerships, create new care procedures, and change their business models to grow overall revenue streams. Healthcare organizations looking for these new business opportunities will employ ICD-10 as a marketing differentiator to create a more competitive market position.

There are three key areas for healthcare organizations wanting to convert regulatory compliance into strategic advantage with ICD-10 remediation:

1. Information and Data Opportunities – Healthcare entities that are early adopters of ICD-10 will be in a position to partner with their peers and constituents to improve data capture, cleansing and analytics. This could lead to the development of advanced analytical capabilities such as physician score cards, insightful drug and pharmaceutical research, and improved disease and medical management support programs, all of which create competitive advantage.
2. Personal Health Records Opportunities – Using ICD-10 codes, innovative healthcare entities will have access to information at a level of detail never before available, making regional and personal health records (PHRs) more achievable for the provider and member communities. Organizations that align themselves appropriately can provide a service that will differentiate them in the marketplace.
3. Clinical Documentation Excellence Program – Developing and implementing a Clinical Documentation Excellence (CDE) program is a critical component of organizational preparedness to respond to future regulatory changes because there could be an ICD-11 on the horizon.

Healthcare organizations need to understand the financial impact that ICD-10 will have on their bottom line and begin the operational readiness assessments, gap analyses and process improvement plans to facilitate accurate and appropriate reimbursement. Without action, a healthcare organization can expect to endure “data fog” as the industry moves through the transition from one code set to another. Now is the time to choose to gain the advantage or procrastinate on the coming code apocalypse.

E-Billing Expose – Part Two

In my previous post, I discussed E-Billing and its impact on a Healthcare Payer or Life/P&C/Worksite Marketing Insurer and alluded to levels of E-Billing I’ve seen in my travels.

Level One is the simplest – really just E-Bill Presentment. Sometimes this is a PDF of the bill emailed to a customer (privacy alert!), but usually it’s the customer logging into the insurance company’s web site and viewing a copy of the bill, with the ability to print. On the positive side, this approach does shorten the billing cycle by avoiding the mail.  From an IT standpoint, this is a print-driver substitution (I know, I exaggerate, as simply printing a bill is a very convoluted process for many insurance companies), but yes, many companies (and many consultants!) call this E-Billing. From a technical/transaction standpoint, this is the simple equivalent of brochureware for a web site.  There is no process efficiency gain by either the company or the customer.  The bill goes out, a check comes back.  All the manual processes stay in place.

Level Two is a step up, albeit small - E-Billing Presentment and Payment.  This method provides the same information as Level One with the ability to submit payment via Electronic Fund Transfer (EFT) or credit card.  The lockbox can be cut out and the payment processing steps bypassed, but the payment will again, never match the account by the time the two are matched.  Too many changes occur in the gap between bill generation and bill payment.

So it comes down to Level Three, the real payback generating use of technology – RECONCILIATION.  In the industry this is called E-Billing Presentment, Reconciliation and Payment.  These are the systems where I’m seeing companies and their customers make huge leaps in efficiency.  You need three ingredients for this recipe:  (1)  the back office system, (2) web self-service and (3) true system integration.

The back office system (regardless of brand, platform or computer language) must be kept sterile as the “system of record”.  It generates the bills through the application of business rules, dates and rates.  The E-Billing System, through integration and custom software, captures this bill and builds a live webpage with embedded links to portions of the bill the customer might need to change for reconciliation purposes.

The customer is notified the bill is available and logs into the company’s website to access the bill at their convenience.  Clicking on an employee’s name might bring up the ability to add a dependent to that employee record, or change their employee class, etc., etc., with each change resulting in a modified premium amount for that line item.  Links are available to add new employees along with their start dates, invoking a pro-rating routine to calculate the premium.  Each time one of the hundreds of possible reconciliation changes are made to the bill, the bill recalculates, the total changes and the change is marked for easy review.  Behind the scenes, the system builds a set of transactions representing all of the reconciliation changes.  When the customer is finished and the bill is balanced to their satisfaction, they finalize the bill by selecting a separate link.  This locks the bill and feed the changes to the back office system through the final set of integration routines.  The customer is given the opportunity to pay electronically.  The bill and the back office system are in balance and all is good in the land of E-Billing.

What doesn’t happen?  A “marked-up” bill is NOT sent back to the company to be manually reconciled.  A payment for the wrong amount is NOT posted, resulting in additional debits and credits.  Phone calls and emails do NOT fly between company and customer accounting departments.  The next bill is NOT wrong before it is generated.  Most compliance issues are avoided as the bill controls the census, thereby controlling the premium, so there are no misunderstandings about who was paid when, resulting in a much cleaner claims process.

Of course, the Level Three description above is a very simplified view of this process.  There are many, many back office systems, most have been modified since installation and some are even no longer supported by the vendor.  Legacy systems abound. 

Selecting a true system integrator with expert knowledge of the business is the key.

Image appears courtesy of weblogcartoons.com

E-Billing Expose – Part One

Designed correctly, E-Bills are a great use for the web, allowing insurance companies to communicate critical financial and census data to their customers in a controlled fashion while increasing efficiency and accuracy for the customer and themselves.

Unfortunately, it has been my experience that there’s a lot of misleading information about E-Billing “products” and “systems” on the Internet. In my upcoming posts, I’m going to wade through this morass of information and detail the approach that works – both from the company and customer standpoint.

The bill I’m speaking of is for group insurance. In the paper world, it’s that complicated, multi-page, already incorrect when it’s mailed, document that details what the insurance company believes the customer owes them. In the group insurance world (especially worksite marketing), where products may be voluntary and usually involve payroll deductions, I contend the bill is always wrong when received by customer due to the nature of the beast. By the time the bill arrives, the customer has employees who have joined the company, left the company, added dependents, etc. The poor customer then moves to try to reconcile said manual bill at a “point in time” that has nothing to do with the insurance company’s computer system used to generate the bill. The customer remits the reconciled (from their standpoint) bill, and it starts all over at the company end. There, it’s a reverse reconciliation as the company tries to figure out the entries the customer made on their end. It’s not unusual to see bills arrive at an insurance company with lines marked out, additions written in the margins, incorrect calculations, etc. How can it be right? The customer doesn’t know the insurance company’s business rules.

A statement about E-Billing products – based on the complexity of insurance billing systems (especially legacy systems), the inherent dynamic nature of the customer’s census and the integration needed to design posting for a true E-Billing System (Presentment, Reconciliation and Payment) back to the billing system after a bill is finalized, products haven’t met the mark.  I have yet to see a product that meets the needs of an insurance company requiring true branding, specific process flow, true self-service automation, and SOA compliant integration.

Contributing to this state of confusion, I’ve seen three completely different levels of E-Billing as requested by clients. All are referred to as E-Billing and in many cases, in previous engagements, the client visualized more and received a lot less.

Stay tuned for a discussion of (1) E-Bill Presentment, (2) E-Bill Presentment and Payment and (3) E-Bill Presentment, Reconciliation and Payment (true E-Billing).

Image appears courtesy of graphicalwonder.com

Actionable Healthcare Business Intelligence – 4 Key Elements

In our Business Intelligence (BI) strategy consulting with healthcare clients, we are often asked how to design a metrics program so the data that ultimately populates the dashboards and drill-downs is inherently actionable. They ask: How do we design the BI data collection and presentation systems to focus our corrective actions and other interventions most effectively?

In our experience, metrics facilitate action when they exhibit four key characteristics:

1. A clear definition – the meaning of the metric must be clear and unambiguous. In a surgical services context, the definition of a late start for a scheduled procedure must be precise, and agreed upon by everyone concerned. If three minutes past scheduled start is defined as late, there should be no haggling that four minutes is close enough to be considered on-time. When late surgical starts are aggregated up to a service line or an entire system, especially when used comparatively, the metric must represent a homogeneous population with regard to the definition of the metric.
2. Clear attribution & dimensional focus – the attributes that describe or annotate the specific metric must be clearly defined, and must allow for focused response along some dimension that makes sense to the business operation. Most often these will align with one or more of the following:
   • Organizationally-focused – staff and other aggregated resources (e.g. departments, service lines, programs, care setting) are organized and accountable in alignment with the mission of the enterprise or segment thereof. It is clear where the action is required in the organization in order to achieve the desired effect or outcome being measured.
   • Process-focused – specific processes or standard operating procedures (e.g. standard orders or order sets, care plans, clinical pathways, standard or research protocols) are implemented and tracked for performance and compliance. It is clear in which specific process or activities action is required, in order to achieve the desired effect or outcome being measured.
   • Specific Resource-focused – specific resources (e.g. individual staff or teams, facilities, materials, equipment) are monitored for performance and compliance with standards for quality, operations or regulations. It is clear with which types or instances of these specific resources action is required, in order to achieve the desired effect or outcome being measured.

   Other Primary Entity-focused – specific critical entities that exist in the operational context being measured, each described by a potentially diverse set of differentiating attributes. For example, in a clinical context, patients are critical entities. The set of clinical, demographic, diagnostic, prognostic, treatment, outcome or other differentiating characteristics on patients is routinely examined and analyzed for potential patterns, and possible interventions.

3. Timeliness – the metric must be captured and available to responders in sufficient time to allow an appropriate response. Metrics can evolve from being primarily retrospective, to real-time reporting, to predictive, each of which enables and facilitates a different type of action. At a minimum, they must be reported in sufficient time for a meaningful response to occur.
4. Accountability – with any of the above, someone in the organization must be responsible and accountable for appropriate action and assessment. The responsible party(ies) must be ready to analyze the situation and deploy the appropriate resources, to take specific needed actions in response to the position or value of each metric relative to relevant performance standards or expectations.

Other factors such as high confidence in data quality and its source, effective communications to responders, and authority to act are also critical elements. Metrics programs and BI systems with these characteristics have taken a good first step toward enabling the focus and the improvements for which they are ultimately designed.