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Don't Delay on ICD-10 Training

icd10 7

The delay of ICD-10 is an opportunity for coders to improve their knowledge of ICD-10 as well as share this knowledge and insight with physicians. Health Data Vision encourages health plans, along with their coding/audit managers, to work together to offer ICD-10 training materials to their internal staff. This will keep everyone concerned knowledgeable and ready for the 2015 implementation date.   

A considerable amount of time, effort and money has been spent preparing for ICD-10 preparing for the Oct 1, 2014 implementation date, without extensions or exceptions. Now the implementation date has been extended until at least Oct 1, 2015. We believe that just like any other skill, if you don’t use it you lose it. With the delay in the implementation, for at least another year, coder’s should make efforts to remain proficient. In order to do so, coders must practice. We suggest that health plans, physician offices and coders take advantage of all ICD-10 training resources being offered by industry leaders such as AAPC and AHIMA.

Physician Education
This is the perfect time and opportunity to express the importance of detailed and necessary diagnostic documentation with physicians. ICD-10’s specificity of the reporting comes as a significantly expanded code set, 69,000 compared to 14,000 in ICD-9, and a higher responsibility to be clear in documentation. Coding managers and health plans need to take this additional time to provide physician education on proper documentation necessary for ICD-10.   

Better Documentation
Please keep in mind that this should not only be left up to the health plan, coders should also step forward and help their physicians’ by offering advice on how to better document their patient visits. The choices will be much more specific and require more detail in the medical record when assigning the appropriate code for the patient’s condition. Training physicians to know their choices now will make the ICD-10 transition easier for all parties involved. 

As we all know, change is not easy, but how we react to the change determines how successful we are. Regardless of how we feel about the delay of ICD-10, what we must do is embrace the change, keep preparing ourselves as coders and educate our physicians.

HEDIS Season Mid-Year Point: Eliminate Surprises


describe the imageAt Health Data Vision we realize most Health Plans are at about the halfway point, or hopefully a little beyond, for their 2014 HEDIS data collection projects.  This is when it gets fun and it is truly the last time to really be able to address problems before it’s too late.  Here are a few things a plan can do to make sure they are on track at the HEDIS season mid-year point and eliminate surprises in May.

Convenience Sample

Whether you have an experienced review team or long standing relationship with your vendor, it is beneficial to take advantage of the convenience sample.  Even if it is just a couple of charts from each of the measure groups, the convenience sample can help you in ways beyond verifying abstractors understanding of the measure.  It provides a test run for your chart retrieval processes before the actual MRRV. It also ensures that all necessary chart meta data is pulling over correctly and it allows your auditor to provide some feedback that could in fact make the MRRV process less stress inducing.

Data downloads from your vendor

If you haven’t done so yet, you should be getting at least their first data download.  Once a project has been in the field four to six weeks, a sufficient amount of positive hits should be in place for each measure. Then your plan can begin to assess how they are tracking toward goals, and evaluate if they are ahead or behind the pace of prior years.  By week eight, weekly to semi-weekly downloads are advisable.

Reset daily throughput targets and assess staffing level

Slow starts or delays in getting projects to the field can still be overcome, but the time to act is now.  The most important thing to know is what your daily throughput needs to be for all project steps -  from scheduling to chart overread.  If you are going to need to add staff to get the work done, don’t hesitate to escalate that request to your senior management.  Any grouchiness that you will encounter now, for having to tap resources from other parts of the organization for the next three weeks, will be nothing compared to the outrage that is likely to be vented if your plan falls short of goals for preventable reasons.

CMS Audit: Verify or Delete Plus Add


Rise Nashville

On March 9-11 Health Data Vision, Inc. (HDVI) attended and exhibited at the 8th Annual Rise Summit in Nashville, TN. With over 600 in attendance there were many common issues brought up in seminars and in conversations, such as the 2015 CMS regulations, concerns around ICD 10 later this year and the importance of proactively mitigating risk of inaccurate submissions.

The Importance of Verify or Delete plus Add and the 2015 CMS rules

vdaHealth plans should make sure they are taking every precaution around avoiding overpayment refund, which would be discovered in a RADV Audit or other imminent audits. A proven method to address this is to review all submitted diagnoses and make sure to delete those that are not truly supported in the chart documentation, instead of only adding. “It may hurt to remove a diagnosis during a Verify or Delete cycle, but it’s nothing compared to what can happen if it gets picked up as an apparent systematic occurrence through RADV,” cites Kristen Joyce, Senior Director of Risk Adjustment at HDVI. If inaccuracies are not identified and removed, then subsequently discovered during a RADV, the cost to the plan in penalties will be much higher than any potential payment the plan may have received for that diagnosis.  During his presentation at the conference, Anker J. Goal (a partner at McDermott Will & Emery), identified four methods to affect validation rate, these include:

• Provider education – documentation and coding
• Identify and delete unsupported codes
• Prospective visits
• Audit readiness: record retrieval and review procedures  

HDVI’s has developed a set of tools within the MRCS platform designed specifically to help health plans proactively mitigate risk, including our Verify Delete or Add Module and our RADV and Mock RADV Modules, as well and as analytics that will allow for the identification of specific error type trends that can be useful input to provider education efforts and care management efforts.

HDVI Responds to the Proposed 2015 CMS New Rule


PROPOSED RULE - Issued January 10, 2014

What is it?

According to CMS the proposed rule would revise the Medicare Advantage (MA) program (Part C) regulations and prescription drug benefit program (Part D) regulations to implement statutory requirements; strengthen beneficiary protections; exclude plans that perform poorly; improve program efficiencies and clarify program requirements. The proposed rule also includes several provisions designed to improve payment accuracy.

deliborateTo achieve all of this, CMS is proposing several changes which necessitate timelier monitoring of beneficiaries chronic conditions.  The proposed rule would require Health Plans to remove erroneous diagnostic data from the Risk Adjustment database, with strong incentives to accomplish this prior to reconciliation (no more “deliberate ignorance”). The proposal also includes requirements for plans to make reportable efforts to improve beneficiary’s health outcomes (no more “reckless disregard”). CMS is further proposing that these new requirements be tied to STARS, thereby rewarding Health Plans that pursue improved health outcomes for Medicare Advantage members.

CMS is also proposing a 6-year look-back window, in conjunction with the new mechanism for over-payment reporting, on any errors found after the reconciliation submission (“constant diligence”).  This process (already established) requires a plan to detail the operational flaws that allowed the error to occur, the number of beneficiaries it affects, the estimated total over-payment and what corrective actions the plan will take to prevent it from recurring.

What does it mean for health plans?

It would seem that CMS expects Health Plans to review all Medical Records, identify and remove all errors, and most importantly identify and close all gaps in care prior to reconciliation.  If resources and physician tolerances were limitless this would be achievable, but we all know neither is.   

So this means that Health Plans will need to revise chart audit targets. Gone are the days of suspecting to capture dropped or missed HCC diagnoses in an effort to maximize revenue.  Instead, plans are expected to focus audits on potential errors and potential gaps in care. 

However, plans shouldn’t expect that medical record documentation and encounter data will improve simply because CMS has strengthened the program reliance on it.  Therefore, there will still be the same need to audit charts to obtain comprehensive diagnostic profiles where encounter data implies a documentation gap.  The change here is that when plans identify assessment or documentation deficiencies in this process, CMS is expecting efforts in operational improvements to insure that the member’s care is not deficient and that errors are removed.  

The “timely” requirement is the larger challenge.  Plans are expected to: analyze lagged encounter data; target errors, deficiencies and gaps; review targeted charts, and react to the results optimally in the same data collection period.  

The silver lining here is that identifying gaps in care should inspire follow-up, managed and coordinated care.  This effort should not only close any gaps in care, but will also trigger appropriate revenue for any HCC conditions assessed and treated, as well as improve STARS ratings. 

risk chartWhat should plans be doing to get ready?

There is no time to be wasted.  CMS alerted MAOs this time last year that in 2014 there would be requirements for clinic follow-ups on Home Assessments to insure that all reported HCC conditions were being treated.  The message there is that CMS is not paying plans for diagnoses, but rather for managing chronic conditions. This requirement is in place now, and there is no basis to believe that the proposed chart audit requirements will not be in place this time next year.

Health Plans should be making plans now for this expectation.  If we assume that CMS will require reporting on health outcomes next year, plans will need to be ready.

Health plans should be making every effort to identify potential encounter data errors for 2011 through 2014 dates of service.  Any diagnosis not supported by assessment notes should be deleted.  Any gaps in care or documentation deficiencies identified for 2013 or 2014 should be referred for Care Management activities. 

Health plans should begin now developing new targeting strategies to maximize health outcome results and documentation. Rather than targeting members, plans should begin targeting clinical areas for enhancements.  The average plan will find Diabetes, Heart Conditions and Lung Conditions to be those with the highest drop-off rates.  This is largely due to the ability to manage these conditions pharmaceutically. These conditions may appear to be un-treated from reviewing the documentation, when in fact they are not.  

Currently at HDVI we are working with our Risk clients to review all reported HCCs and to identify cases where clinical assessments are necessary to manage the care continuum and document chronic conditions appropriately.  Additionally, our MRCS Platform has modules specifically designed to improve a health plans ability to assess the quality of documentation supporting a diagnosis and to take decisive action to ensure submissions will pass muster with CMS.

This will help to identify the unique cluster of conditions that each of our clients will need to develop enhanced Care Management activities to insure the care continuum is not broken in the future, as well as highlight documentation deficiencies to support physician education activities.

Big Data In Healthcare?


I recently participated in a panel on this topic at a Medicaid conference and gave it some more thought. This post summarizes what I took away from that discussion.

I am always skeptical of buzzwords and fads. When the hype subsides, we realize that promises were unrealistic and our expectations way too high. However, there is usually a kernel of value that can be extracted. That is true for Big Data, too. 

Before we get into Big Data in healthcare, however, let’s define the term: paraphrasing Wikipedia, Big Data is just a whole lot of data. So much, in, fact, that traditional technologies and approaches cannot keep up with processing and analyzing it fast enough. According to studies from McKinsey Gartner, and others, data is being generated at staggering rates each year, with volume reaching Exabytes (a million Terabytes) and even Zettabytes (a billion Terabytes) each year. The Kaiser Family Foundation predicts that the volume of healthcare data accumulated each year will grow 50-fold between 2013 and 2020. So much for that. 

To me, a more useful approach to the topic is to look at the technologies and tools that have evolved to manage and analyze these massive amounts of data. That is more of a Silicon valley approach, driven by having hit hard limitations of what off-the-shelf technology could handle. Google, Facebook, LinkedIn and certain research have had the most need for these technologies to date and, in my opinion, do for the most part remain most relevant to these extremely high-volume data operations.

Another way to look at the technology is by categorizing structured and unstructured data and how technology has evolved to specifically handle the latter. Historically IT has been dealing predominantly with structured data, at worst attempting to force unstructured data into a schema one form or another. Today we see a proliferation of unstructured data, a big driver for the need for new technologies and approaches. 

So what about healthcare data, then? Well, I would contend that in the realm of healthcare, we are still dealing with predominantly structured data. Even though it is sensible to argue that taking all the data from all of the many flavors of EMR can only be considered as unstructured data, if we take the data of each system individually, we return to a structured world. So it’s just inconsistently structured. Now, that does not make it less painful to deal with, but I’d like to stipulate that anyway.

Meanwhile, the challenges in healthcare remain the old ones: Quality of data, the feeds and the processes around it, defining and maintaining systems of record and reconciling all other versions of the same data around it. Now, the Big Data movement has brought us some technologies that are also very useful with structured data: new analytics tools, statistical evaluation tools and data visualization (we at HDVI are starting to use Tableau 8.1 both internally and as part of our SaaS platform). These tools are very useful, also when used with more traditional technologies. And that should really be the takeaway for us in Healthcare IT. Whether the technology is SQL , SAS or Hadoop (distributed File system) is really secondary to what should always be our primary goal: that the technology addresses a specific need when pragmatically applied to business requirements.

Michael Klotz
President & CEO

5 Commonly Missed Preparation Steps for HEDIS 2014


As we are making our final preparations for the 2014 HEDIS® season, most of us have undoubtedly taken care of the big ticket items related to HEDIS® preparation, such as—vendor selection and performance guarantees, development of measure chase logic, and notifying the network of the upcoming intrusion. There are, however, some less obvious actions that a plan can take in preparation for the upcoming HEDIS® season that can make a big difference in HEDIS® rates.

  1. Don’t get caught with unusable supplemental data. Rules for using supplemental data have tightened up for 2014. This means everyone needs to take extra care to make sure their supplemental data is auditable, has a documented QA process around it, that it’s collected in a standard way, and is mapped correctly into analysis files.
  2. Don’t be without network management support from provider relations. Avoid wasting time trying to get into resistant provider offices by articulating a clear strategy for engaging the network team to assist in gaining access.
  3. Carefully review your provider data when your chase files are generated. Take special care to scrub out specialties or locations that do not make sense for the measure. This will save you time and money, and allow you to focus limited resources on more fruitful activities.
  4. Inspect your lab data. There are critical flags that can help you quickly identify if you may be missing information. For example: what percentage of tests are for A1c and LDLs, and are they consistent?
  5. Provide your vendors with as much information as possible regarding your past performance on hybrid measures and what your goals are for 2014. This will help your vendors immediately see the delta between the goal and initial hybrid rates, and allow them to employ appropriate prioritization and retrieval strategies throughout the project.

HEDIS® Audit Made Easy: The HDVI MRRV Wizard


HDVI's CEO, Michael Klotz, and COO, Mike Curran, talk about how HEDIS® audits can be made easier with the MRRV Wizard.

HEDIS® 2013: What We Learned

HEDIS 2013

With the books closing on our 2013 HEDIS® data collection projects and with a fresh copy of the 2014 HEDIS® Technical Specs in hand (actually in both hands, this thing is getting War and Peace big!), I thought it would be a good time to reflect on the year and what we learned.

  1. Failing a Medical Record Review Validation should now be virtually impossible. Apprehension and fear abounded as the launch of HEDIS® 2013 drew near with the new deadlines and rules for the MRRV. In reality, the new rules actually improve a health plan's chances of passing the audit. True, execution and adherence to data collection and abstraction timelines are more important than ever, but even plans that start data collection as late as March should have 8-10 weeks to collect and abstract for their samples. This should be more than enough time to do a very good job on hybrid data acquisition. Knowing which measures are going to be reviewed on May 1st, plans and/or their vendors can begin the process of audit prep in parallel to the final weeks of collection. Plans with greater resources typically don’t wait for the measure list to come out as they over-read 100% of any measures they suspect might be pulled. By May 15th, plans, informed by their auditor’s input from the convenience samples, should be making decisions on which numerator hits they may want to back out of compliance due to missing or incomplete documentation before sending the lists to auditors. Once the lists are sent to auditors, there should be very little uncertainty about whether documentation exists to support numerator hits.
  2. Avoid the temptation to be too conservative. I have no doubt that thousands of perfectly viable numerator hits were backed out of rates this year due to fear of failing the audit. This was a tough year for both Compliance Auditors and Health Plans; the stakes have been raised. CMS is paying out (or not paying out) hundreds of millions of dollars in STAR Rating bonuses based largely on HEDIS® performance. The is more pressure on auditors to make sure that their audit work papers reflect a scrutiny that satisfies the NCQA and CMS that rates are valid and free of shenanigans. The convenience sample is not the only time auditors should give health plans feedback. Plans pay auditors for their services and can switch if auditors are not adding value. Have auditors review troublesome measures throughout the project. This way, plans can submit numerator lists with more confidence and less back tracking on hits due to nerves.
  3. Year-round partnerships with chart collection and abstraction vendors are more critical than ever. Points 1 and 2 above amount to very little if a plan and its vendor cannot get out of the gates fast. Both parties need to work together in the off-season to identify a network engagement strategy that will assure timely access to groups and physician offices. For example, identify special-handling groups that should be done first, EMR groups to which plans may be able to get access, or groups that may be open to block scheduling prior to the release of the samples. These are all worthwhile “off-season” activities that plans and vendors can collaborate on to ensure a fast launch in 2014.

What have you learned from the HEDIS® 2013 season?

MRRV: Part 2 - Done in 60 Minutes...


OK, we’ve actually done it in under 15 minutes. Generate the complete MRRV Response package for the auditors, that is. We used the second MRRV Wizard in MRCS (we discussed the first one last week) to accomplish this.

How It Works…

It takes a few seconds to select the numerators and exclusion categories previously used in the MRRV Prep Wizard (as determined by the auditor), which is done in the first step in the MRRV Package Wizard. In step 2, using the filter and search function, find and select the appropriate members the auditor requested to audit. Someone good at copying and pasting member names can complete this step in 1 – 2 minutes for each numerator and the exclusion category. So now, let’s say we are about 9 minutes in.

Next, is a review screen that shows all the selections made, checking this list takes a couple minutes. Once confirmed, clicking one button takes care of the rest. It triggers the system to generate one zip file with everything in it:

  • One zip file for each numerator and exclusions (6 zip files)
  • One PDF for each member within these zip files (typically 16 PDFs for each numerator/exclusion)

Those PDFs have everything in them. A cover sheet with all the member and measure information, date and time generated, user who generated the PDF and all relevant numerator (or exclusion) information on it. For each numerator value, a page reference to the appropriate chart and page number on that chart as a clickable hyperlink. 

The package automatically includes all the relevant charts (sometimes there are more than one) and each page has the chart (or Chase) ID as well as the page number on them, just to be sure.

It takes a few minutes to generate that package. One ZIP file, albeit a big one, ready to ship to the auditor, securely downloadable directly from the system. Done in 15 minutes.

So, if you take your time, double and triple check the selections and also consider the time to deliver the file to the auditor, you can be easily done in 60 minutes. Knowing that it’s complete, neat and clean.

MRRV: Part 1 – Just to Make 100% Sure…


The HEDIS® 2013 project season is coming to an end and Medical Records Review Validation is more stringent than ever, with tighter timelines leading up to it. Uncertainty remains until the auditors give an 'all clear' in the next couple weeks. Not fun.

So, what have we at HDVI done this year to assist clients with their HEDIS® Hybrid projects? Well, quite a few things, including even more stringent quality controls on abstraction, over-read and data. The latest features we rolled out just ahead of the MRRV weeks may deserve special attention because they aim to make MRRV as pain-free and anxiety-free as possible.

What we came up with are two wizards. This blog post discusses the first one. The second one will be discussed in our next blog post.

The MRRV Preparation Wizard

It is common, logical and prudent to review all the MRs and abstractions for the numerators chosen by the auditor (typically 5 numerators and all exclusions). In addition to all the QA features and over-read capabilities (for project team and/or client), the wizard allows the selection of the relevant numerators. It provides a simple yet powerful way for a targeted review of all the hybrid-positive numerators and the associated medical records, and tracks 'cleared' members and those with issues/questions/concerns.

Results: HDVI's project teams reviewed the relevant numerators in a 'beta-pass' in just a couple hours, then clients performed their own review using the wizard. Within a couple days, any members with questions were isolated and resolved (no abstraction errors were found due to prior QA working as designed). Last-minute abstractions that came in were easily identified and reviewed as well. Member lists for the relevant numerators and exclusions were created with the click of a button. Now we wait…

Return for part 2, where we discuss how the second wizard makes completing the MRRV Sample process easy.

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