Moving from Volume to Value: How Do We Get There?

volume to valueListen to any healthcare pundit or industry observer longer than their opening paragraph and you’ll hear them use the current buzz phrase: Healthcare needs to move from volume to value.  See, there it is already.

We pretty much know where the volume comes from.  If a buyer, any buyer, agrees to pay an acceptable fee for each unit of a needed service, the service provider will soon recognize that the delivery of more units of those services to satisfied buyers yields more payments.  Simple enough, and healthcare service providers have responded as one would expect in this environment.  The fees paid for each unit of service motivate the healthcare provider to maximize throughput – to the limits of their capacity to deliver a satisfactory service – and this leads to an increased volume.  Yes, there’s also quality and necessity and regulation, but right now we’re talking about volume.

So, what about the value part?  What is going to drive value?  And value to whom?  And who is going to measure the value?  And decide how much to pay for it?  Unfortunately, several tenets of basic economics that ordinarily drive value (and operate in virtually every other transactional setting) are disrupted in the healthcare marketplace as payers and providers of every shape and size, employer- and other group-inspired benefit plans, preferred provider and referral networks, watchdog quality and safety groups – as well as the inherent complexity of the subject matter – all serve to distance the patient from a free and informed buying decision.

By the time the ultimate treatment decision is made, it has been framed and prodded by so many ancillary parties that the patient, sitting alone with the provider, can almost feel the other observers in the room; those who will decide after the fact, or who have decided well before the fact, whether this decision is appropriate and how each party in the transaction will be compensated, billed, measured, rewarded or penalized according to a growing litany of performance measures.  If the patient doesn’t feel all of this, the provider often does.

The complexity and confusion arise in part because each of the above fundamental elements has been intermediated – to one degree or another.  The patient – the ultimate target of the treatment – is not the only buyer.  Buying decisions affecting this single transaction were defined, negotiated and contracted months or years in advance, and are being monitored against a wide range of both clinical and financial measures before, during and after the single transaction between a given patient and a given provider.  The terms of these agreements can and do influence the chain of decisions that culminate in the choice of treatment and in the cascade of financial events that will promptly follow.  No wonder it’s confusing.

So then, how does value get defined?  Several common themes emerge as both payer and provider organizations strive to identify the appropriate fundamentals, define a useful and informative notion of value, and introduce that notion of value into the decision processes they share with their patients.

The common elements that lead to a determination of value seem to go something like this:

  • Who are my patients?  A fundamental question, but not always trivial to answer accurately or in a useful way that enables and extends visibility over a population.  Providers need to be able to identify each patient that is legitimately under their care and they must have access to a complete record of the care these patients have received as a baseline for measuring future performance.  Once this record is assembled the pattern of problems, interventions and care relationships can be discerned and used to both characterize and engage each patient.

Providers need to identify the core characteristics of their panel of patients so they can both tailor individual treatments and evaluate patient experiences and outcomes comparatively against similar patients they are treating or that are being treated by other providers.

In an accountable care world, if providers are assigned responsibility for patients retrospectively using a plurality of care or other statistical model, it doesn’t mean they have control over the care those patients are receiving. They can hardly be measured fairly on the outcomes those patients have experienced. They need to know the specific treatments these patients have received, their level of compliance, and what other providers they have seen, at what locations, and with what frequency. This increased understanding of their basic patient panel will begin to reveal the true nature of the relationships they (or others) have with these patients and will often constitute the first wave of relevant analytics into the value being delivered.

  • What outcomes are we targeting for these patients?  What are the care plans that will get them there?  How long have these targets and plans been in place, for which patients, and what results are we seeing?The segmentation analytics that was started with the patient panel can now be extended, as specific performance targets are defined for individual patients and the projection of these targets is aggregated into clinically coherent segments, yielding outcomes and results that perhaps for the first time give visibility and insight into how well the relevant population is being managed.

Care teams and practice management can now monitor the clinical, operational and financial performance measures of the segments that drive significant costs and consume substantial resources, enabling the exploration of new deployment models.

  • What is our baseline? For the patients’ and other payers’ expenditures for our services and for the actual costs we incur to deliver those services?  Virtually all risk-based contracts establish a baseline of expenditures using some form of statistical measure (e.g., weighted average) over a defined historical time frame.  Projecting the dynamics of patient mix, service mix, fee structures and delivery resources over the anticipated life of the contract provides a segment-able baseline for measuring and tracking contract performance and assessing value. From this foundation, organizations can apply complementary analytics so that under-performing practice areas or population segments can be localized and improvement programs can be appropriately focused and funded.  Over-performing segments can be examined and highlighted as potential sources of best practices targeted for broader dissemination.
  • Who is accountable, and for what?  As the payment structure for many conditions moves to more of an episode-based model, the deployment and coordination of care delivery resources takes on added significance.  Roles and responsibilities must be defined for the delivery of episode-focused clinical services across the network of care settings. Proactive coordination of transitions in care and the associated communications, hand-offs and follow-ups must be defined and written into performance contracts along with explicit adherence measures.

These metrics will begin to form the basis for concrete and measureable accountability models and will likely be a consideration when shared gains and losses are assessed retrospectively.  Evolution toward more proactive accountability models is likely to follow.

Accountability models based on the actual outcomes realized, as distinct from adherence to best practices, can be differentiated through analytics, enabling some flexibility for care redesign (potentially including patient choice) or other measured innovations undertaken by providers.

  • Are we correctly and accurately reconciling the various activities, billed services, payments, resource alignment and costs with our agreed-upon models for accountability?  This is non-trivial even within a single enterprise.  And now we have various ACO or ACA models where new participants are collaborating at levels they have never attempted before, and entering into risk agreements based on shared performance metrics.  Some organizations are experimenting with formal value stream maps where benefits and costs are explicitly modeled.  Others are punting any envisioned gains (or losses) to an aggregate ‘shared benefit’ to be ‘addressed later.’One key consideration is implementing at least some accounting (defining and tracking) of the revenues and the actual costs associated with care delivery to specific segments with different characteristics (e.g., populations, locations, groups, payers, service partners or venues).  These costs must not be (but often are) confused with the amounts the provider would like to charge; or the allowed amounts the payer will agree to; or the actual payment amounts received from all parties; or even the various provisional ratios used to approximate the real costs.  Accountability models will need to evolve much further if they are to offer any real operational decision-making value.

No one disputes that the changes underway in healthcare have the potential to be transformational, to varying degrees.  The complexity and diversity of the responses that will be required by various organizations is still taking shape and there are many variables that will determine the success that any given enterprise will achieve.

The core principles outlined here are being adopted and applied in diverse healthcare organizations to answer a few fundamental questions about the value they offer that, ironically, have been posed and answered for all time in other industries and economic settings.  Who is our customer?  What do they need or want?  Why are we the best organization to meet their needs?  How can we communicate the benefits and costs to all the parties who are involved in the decision to buy?  Can we deliver?  How can we measure these factors both as a baseline and on an ongoing basis so we can provide convincing evidence that we offer the best proposition of value to all concerned?  Healthcare organizations that can answer these questions and address the numerous issues that arise in their pursuit will have a leg up on everyone else and will both deliver the best value and enjoy the greatest success.

What I learned at HFMA’s Revenue Cycle Conference at Gillette Stadium

(…while the Patriots prepared to get their butts kicked)

Right from Jonathan Bush, the co- founder and CEO of athenahealth [the keynote speaker]: “Make Hospitals Focus on What They’re Good At – Everything Else, “Seek Help!” I can help define “everything else”. For now, I will keep it generally confined to the world of healthcare data – because I would argue more time, money, and effort is wasted on getting good data than almost any other activity in a hospital.

If you are a Chief Quality Officer, or Chief Medical Informatics Officer, or Chief Information Officer – what would you rather spend your budget on?

data analysisYour analysts collecting data – plugging away, constantly, all-day into a spreadsheet?

Outcomes: Stale data in a static spreadsheet…that probably needs to be double/triple-checked…that probably is different than what the other department/analyst from down the hall gave you…that you probably wouldn’t bet your house on is accurate.

Or your analysts analyzing data and catalyzing improvement with front line leaders?

Outcomes: Real time data in a dynamic, flexible multi-dimensional reporting environment…that can roll up to the enterprise level…and drill down to the hospital → unit → provider → patient level.

Here’s a hint – this isn’t a trick question. Yet, for some reason, as you read this, you’re still spending more money on analysts reporting stale, static, inaccurate data than you are on analysts armed with real time data to improve the likelihood of higher quality and patient satisfaction scores and improved operational efficiency.

The majority of the speakers at this year’s HFMA Revenue Cycle conference seemed to accept that providers are NOT good at collecting and analyzing data, or using it as an asset to their advantage. They also seemed to align well with other speakers I’ve heard recently at HIT conferences. If you’re like 99% of your colleagues in this industry, you probably don’t understand your data either. So do what Jonathan Bush said and GET HELP!

Are you “ACO IT-Ready”?

First things first, I believe the push for accountable care is here to stay. I do not think that it is a fad that will come and go as many other attempts at healthcare reform have. Having said that, I also strongly believe that very few organizations are positioned to start realizing the benefits that will come from this reform any time soon. It’s not for lack of trying, as many organizations are already recognized as Pioneer ACO’s. But the hard part is not being established as an ACO – it’s proving you’re reducing costs and improving quality for targeted patient populations.

The first step will being January 1st, 2013. Some ACO’s will be required to start reporting quality measures – for instance the Shared Savings program from CMS for both the one-sided and two-sided models require reporting 33 quality measures. Notice I said “reporting”. So for the first year, it’s “pay for reporting”. Years 2 and 3 is when the rubber really meets the road and it becomes “pay for performance”. “Don’t just show me you are trying to reduce costs and improve quality, actually reduce and improve or realize the consequences.“

With ACO’s come reporting requirements. We in healthcare are used to reporting requirements. And those of us willing to publicly acknowledge it, more reporting means more waste. Why? Because there is job security in paying people to run around and find data…and to eventually do very little with it other than plug it in a spreadsheet, post it to a SharePoint site, email it to someone else, or well, you get my drift. Regardless of your view on these new requirements, they’re here to stay. So the $64,000 question is, are you ready to start reporting?

There is a wide range of both functional and technical requirements that healthcare providers and payers will need to address as they start operating as an ACO.  Many of the early and emerging ACOs have started the journey from a baseline of targeted patient panels to the optimized management of a population, progressing through a model with some or all of the following:

These are 7 simple questions you must be able to answer and report on DAY 1:

  1. Can you define and identify your targeted patient populations?
  2. Are you able to measure the financial and quality performance and risks of these patient panels and populations?
    1. Can you quickly, easily and consistently report quality and financial measures by Physician, Location, Service, or Diagnosis?
  3. Can you baseline your expenditures and costsassociated with various targeted patient populations?
    1. How will you benchmark your “before ACO” and “after ACO” costs?
  4. Can you accurately monitor the participation, performance and accountability of the ACO participants involved in coordinated, collaborative patient care?
  5. Will you be able to pinpoint where and when the quality of care begins to drift, so as to quickly intervene with care redesign improvements to limit the impacts on patients and non-reimbursable costs?
    1. Are you able to detect “patient leakage and provide your organization the information for its’ management? (Patient leakage is when a patient that you are treating as an ACO for a bundled payment, leaves the network for their care)
      1. Is a particular provider/provider group sending patients outside of the ACO?  If so, is it for a justified reason?
      2. Does the hospital need to address a capacity issue?
  6. Can you reconcile your internal costs of care with bundled reimbursements from payers?
  7. Are you positioned for population health management and achieving the Triple Aim on a continuing basis?

In order to answer these questions you must have a highly integrated data infrastructure. It seems I’m not the only one who agrees with this tactical first step:

  • The Cleveland Clinic Journal of Medicine agreed as it listed as one of its’ 5 Core Competencies Required to be an ACO “Technical and informatics support to manage individual and population data.”
  • Presbyterian Healthcare Services (PHS) has been a Pioneer ACO for over a year. Tracy Brewer, the lead project manager was recently asked by Becker’s Hospital Review, “What goals did you set as an ACO in the beginning of the year and how have you worked to achieve them” and her answer – “One of the major ones [goals] was updating our administrative and IT infrastructure. We had to make sure we had all the operational pieces in place to function as ACO. We also completed some work on our IT infrastructure so that once we received the claims data from CMS, we could begin analysis and really get value from it.”

The ACO quality measures require data from a number of different data sources. Be honest with me and yourselves, how confident are you that your organization is ready? Is your data integrated? Do you have consistent definitions for Providers, Patients, Diagnosis, Procedure, and Service? If you do, great you don’t have much company. If you don’t, rest assured there are organizations that have been doing data integration for nearly two decades that can help you answer the questions above as well as many more related to this new thing they call Accountable Care.

What I Learned at Health Connect Partners Surgery Conference 2012: Most Hospitals Still Can’t Tell What Surgeries Turn a Profit

What I Learned at Health Connect Partners Surgery Conference 2012: Most Hospitals Still Can’t Tell what Surgeries Turn a Profit

As I strolled around the Hyatt Regency at the Arch in downtown St. Louis amongst many of my colleagues in surgery and hospital administration, I realized I was experiencing déjà vu. Not the kind where you know you’ve been somewhere before. The kind where you know you’ve said the same thing before. Except, it wasn’t déjà vu. I really was having many of the same conversations I had a year ago at the same conference, except this time there was a bit more urgency in the voices of the attendees. It’s discouraging to hear that most large hospitals STILL can’t tell you what surgeries make or lose money! What surgeons have high utilization linked to high quality? What the impact of SSI’s are on ALOS? Why there are eight orthopedic surgeons, nine different implant vendors and 10 different total hip implant options on the shelves? It’s encouraging, though, to hear people FINALLY admit that their current information systems DO NOT provide the integrated data they need to analyze these problems and address them with consistency, confidence, and in real time.

Let’s start with the discouraging part. When asked if their current reporting and analytic needs were being met I got a lot of the same uninformed, disconnected responses, “yeah we have a decision support department”; “yeah we have Epic so we’re using Clarity”; “oh we just <insert limited, niche data reporting tool here>”. I don’t get too upset because I understand in the world of surgery, there are very few organizations that have truly integrated data. Therefore, they don’t know what they don’t know. They’ve never seen materials, reimbursement, billing, staffing, quality, and operational data all in one place. They’ve never been given consistent answers to their data questions. Let’s be honest, though – the priorities are utilization, turnover, and volume. Very little time is left to  consider the opportunities to drastically lower costs, improve quality, and increase growth by integrating data. It’s just not in their vernacular. I’m confident, though, that these same people are currently, more than ever, being tasked with finding ways to lower costs and improve quality – not just because of healthcare reform, but because of tightening budgets, stringent payers, stressed staff, and more demanding patients. Sooner or later they’ll start asking for the data needed to make these decisions – and when they don’t get the answers they want, the light will quickly flip on.

Now for the encouraging part – some people have already started asking for the data. These folks can finally admit they don’t have the information systems needed to bring operational, financial, clinical and quality data together. They have siloed systems – they know it, I know it, and they’re starting to learn that there isn’t some panacea off-the-shelf product that they can buy that will give this to them. They know that they spend way too much time and money on people who simply run around collecting data and doing very little in the way of analyzing or acting on it.

So – what now?! For most of the attendees, it’s back to the same ol’ manual reporting, paper chasing, data crunching, spreadsheet hell. Stale data, static reports, yawn, boring, seen this movie a thousand times. For others, they’re just starting to crack the door open on the possibility of getting help with their disconnected data. And for a very few, they’re out ahead of everyone else because they already are building integrated data solutions that provide significant ROI’s. For these folks, gone are the days of asking for static, snapshot-in-time reports – they have a self-service approach to data consumption in real time and are “data driven” in all facets of their organization. These are the providers that have everyone from the CEO down screaming, “SHOW ME THE DATA!”; and are the ones I want to partner with in the journey to lower cost, higher quality healthcare. I just hope the others find a way to catch up, and soon!

BIG DATA in Healthcare? Not quite yet…

AtlasLet’s be honest with ourselves. First –

“who thinks the healthcare industry is ready for Big Data?”

Me either…

Ok, second question,

“who thinks providers can tackle Big Data on their own without the help of healthcare IT consulting firms?”

Better yet,

“can your organization?”

Big data” seems to be yet another catch phrase that has caught many in healthcare by surprise. They’re surprised for the same reason I am which was recently summed up for me by a VP of Enterprise Informatics at a 10 hospital health system – “how can we be talking about managing big data when very few [providers] embrace true enterprise information management principles and can’t even manage to implement tools like enterprise data warehouses for our existing data?” Most people in healthcare who have come from telecommunications, banking, retail, and other industries that embraced Big Data long ago agree the industry still has a long way to go. In addition vendors like Informatica who have a proven track record of helping industries manage Big Data with their technology solutions, still have yet to see significant traction with their tools in healthcare. There are plenty of other things that need to be done first before the benefits of managing Big Data come to fruition.

Have we been here before? Didn’t we previously think that EMR’s were somehow going to transform the industry and “make everything simpler” to document, report from, and analyze? Yes we now know that isn’t the case, but it should be noted that EMR’s will eventually help with these initiatives IF providers have an enterprise data strategy and infrastructure in place to integrate EMR data with all the other data that litters their information landscape AND they have the right people to leverage enterprise data.

Same can be said of Big Data. It should be relatively easy for providers to develop a technical foundation that can store and manage Big Data compared to the time and effort needed to leverage and capitalize on Big Data once you have it. For the significant majority of the industry the focus right now should be on realizing returns in the form of lower costs and improved quality from integrating small samples of data across applications, workflows, care settings, and entities. The number of opportunities for improvement in the existing data landscape with demonstrable value should be top priority to mobilize stakeholders to action. Big Data will have to wait…for now.

The Unknown Cost of “High Quality Outcomes” in Healthcare

“You were recently acknowledged for having high quality outcomes compared to your peers, how much is it costing you to report this information?”

I recently read an article on healthcareitnews.com, “What Makes a High Performing Hospital? Ask Premier”. Because so many healthcare providers are so quick to tout their “quality credentials” (yet very few understand how much it costs their organization in wasted time and money running around to collect the data to make these claims) and this article sparked the following thoughts…

The easiest way to describe it, I’ve been told after many times trying to describe it myself, is “the tip of the iceberg”. That is the best analogy to give a group of patient safety and quality executives, staffers, and analysts when describing the effort, patience, time and money needed to build a “patient safety and quality dashboard”  with all types of quality measures with different forms of drill down and roll up.

What most patient safety and quality folks want is a sexy dashboard or scorecard  that can help them report and analyze, in a single place and tool, all of their patient safety and quality measures. It has dials and colors and all sorts of bells and whistles. From Press Ganey patient satisfaction scores, to AHRQ PSIs, Thomson Reuters and Quantros Core Measures, TheraDoc and Midas infection control measures, UHC Academic Medical Center measures….you name it. They want one place to go to see this information aggregated at the enterprise level, with the ability to drill down to the patient detail. They want to see it by Location, or by Physician, by Service Line or by Procedure/Diagnosis. This can be very helpful and extremely valuable to organizations that continue to waste money on quality analysts and abstractors who simply “collect data” instead of “analyze and act” on it. How much time do you think your PS&Q people spend finding data and plugging away at spreadsheets? How much time is left for actual value-added analysis? I would bet you very little…

So that’s what they want, but what are they willing to pay for? The answer is very little. Why?

People in patient safety and quality are experts…in patient safety and quality. What they’re not experts in is data integration, enterprise information management, meta-data strategy, data quality, ETL, data storage, database design, and so on. Why do I mention all these technical principles? Because they ALL go into a robust, comprehensive, scalable and extensible data integration strategy…which sits underneath that sexy dashboard you think you want. So, it is easy for providers to be attracted to someone offering a “sexy dashboard” that knows diddly squat about the foundation, or what you can’t see under the water, that’s required to build it. Didn’t anyone ever tell you “if it sounds too good to be true, it is!?”

Healthcare’s New Mantra

Reduce Costs;
Improve Outcomes & Quality; Increase Revenue & Growth

Everything we do for our healthcare clients’ improves these fundamental core principles – Everything! I mean it, seriously, we have a history of delivering innovative solutions to common problems and each one of them helps accomplish these goals.

REDUCE COSTS: I know you have too many people collecting and scrubbing data – patient safety data, quality data, financial data, operational data….and so on. I also know you pay these people too much money to just be data collectors. Stop wasting your money and their skill sets. Data collection should be a commodity, it’s definitely NOT a competitive advantage. We’ll integrate your data, clean it up before it’s used, and present it in a way that is intuitive and actionable. We’ve done it before and guess what happened….yup $$$$ Millions $$$$$ of dollars saved.

IMPROVE OUTCOMES: I know you spend the majority of your time collecting data, leaving very little time to analyze and act on it. Your patients don’t benefit from data collection. They benefit from your ability to take the data you’ve collected, interpret it, and embed the best practices you’ve uncovered back into the clinical workflows. They also rely on you to identify areas of improvement to educate clinicians before a small problem turns into a big lawsuit. Let us enable advanced analytics with strong data governance to improve clinical processes across the continuum of patient care.

IMPROVE QUALITY: Question: Are you quality driven or compliance driven? Ok now be honest with yourself and answer again. You can have the best processes in the world in place to massage your numbers and report out to CMS in a timely and efficient manner but guess what, that doesn’t translate into better outcomes. BUT…if you have the processes in place to ensure high quality outcomes, your quality numbers will naturally improve. Outcomes first! We’ll align your data needs with your reporting needs, automate the collection and aggregation, and put data in the hands of people who know what to do with it…(before the patients are discharged).

INCREASE REVENUE: Do you know where your high revenue drivers lie? What procedures physicians, payers, discharge service codes, and DRG’s make you the most money? Can you plan and forecast your net patient revenue based on these changing dimensions and their expected volume 3, 6, 9 months out? If you can, congratulations you’re one step ahead of your competition. If you can’t, we can help you accomplish all of these goals as well as any other need your CFO and Strategic Planners have.

GROW: Do you want to track where you patient referrals are coming from to get a better ROI on your marketing dollars? We’ve implemented healthcare XRM (the “X” is for any stakeholder group – patients, physician groups, managed care plans, you name it) to tie the marketing campaign directly to the patient visit.

The Struggle to Define Quality Measures: Do You Have the Right People with the Right Skill Set Supporting This Effort?

Standardizing the definition of quality measures is hard enough when you have the right people. Unfortunately, it is too often the case that hospitals are not armed with the right people and skills sets to address this costly, complicated issue.

Over the past 2 years, we’ve heard a lot about the shortage of primary care physicians in this country, mostly due to the public debate about how to reform healthcare. What we haven’t heard nearly enough about is the even larger shortage of clinical analysts and informaticists. I would argue that right now, hospitals and healthcare organizations need this skill set more than almost anything else. Go to any large hospitals’ website and I’d be willing to bet there is a job posting related to these roles. Here’s why.

How many times has your healthcare IT or data related projects failed because of these two reasons (that I hear almost once a week)?

  • [IT Perspective] – “the users can’t tell us how they want to use the system, how they want to see the data, what they need out of their clinical applications…they don’t know how to ask the right questions!”
  • [Clinical Perspective] – “our people in IT don’t know the clinical world at all. Things aren’t as cut and dry as they try and make it. It’s not 0 or 1, or Yes or No – it’s more complicated than that. I wish they could just live a day in my life and see how I operate, things would be so much easier!”

And there you have it. The conundrum that almost every hospital deals with – an inefficient, ineffective relationship between their clinical users and supporting IT department/clinical decision support (CDS). I wrote previously about the difficulties IT Projects at hospitals face when the clinical and technical stakeholders don’t even know each other. “Dr. meet IT; IT meet Dr.” What I haven’t touched on, though, is the importance of what I like to call the “translators” that every hospital needs. These folks are the Clinical Systems Analysts, Clinical Decision Support Analysts, and Healthcare Informaticists who have a clinical education and real world experience with workflows and processes, but also have a strong understanding of information technology, clinical applications, and most importantly, the data. These resources are invaluable to institutions that finally understand this fundamental principle: the fastest, easiest way to improving patient outcomes and reducing the cost of delivering care is understanding ways to identify best practices and underperformers within your organization through the use of advanced analytics. How do you do that? You have someone who understands the data and can help directors and managers or clinical units/care settings understand where there are opportunities for improvement. It is essential these people “talk the clinical talk” when discussing data trends with nurses and clinicians; and “talk the IT talk” when relaying requirements and system improvements to the IT and CDS teams.

Without resources who can “straddle the fence” that sits between clinical users and CDS staff members, you’ll continue to have a disconnect between the people collecting the data and those trying to understand and report it. It’s time to find people who can play in both worlds. It’s not rocket science…even if calculating CMS Core Measures is.

The Struggle to Define Quality Measures: Try Finding the “True Source” of Your Data First

Let’s look at one measure that is extremely important to hospitals right now: How do you calculate Patient Re-Admission rates?

  • Do you break it down by certain characteristics of a Re-Admission like where the patient came from (“Admission Source”)?
  • Do you make sure to exclude any patients that expired (“Discharge Disposition” = expired) so your numbers aren’t inflated?
  • Do you include certain patient types and exclude others (include “Patient Type” = Inpatient or Psych; exclude “Patient Type” = Rehab)?
  • Do you exclude outliers like the patient that has been in your hospital for what seems like forever but goes back and forth from home health and nursing clinics to the hospital?

Ok, let’s say you do take all these nuances into consideration when calculating your Re-Admission rate……now let me ask you this — what source are you using to collect these various data elements?

  • Your ADT / registration system?
  • Your billing system?
  • How about the patient tracking system
  •  Or the case management system?
  • How about your brand new shiny EMR?

The scenario I describe above is very real. It is highly likely that the data elements needed to calculate Re-Admission rates are scattered in multiple systems across the enterprise and to make matters worse, the same data elements like “Discharge Disposition” and “Admission Source” can be found in multiple systems! Now extrapolate this problem over nearly ALL of your quality measures and you have the conundrum that Patient Safety and Quality departments struggle with in every hospital across the country. I consistently hear:

  • “How do I know everyone is calculating infection rates [CLABSIs, VAPs, CAUTIs] the same way?”
  • “How can I be sure we’re identifying the appropriate Pressure Ulcers stages consistently across units?”
  • “How can I standardize the collection and reporting of NDNQI? PQRI? AHRQ PSIs? Across my units and entities (for multi-facility organizations)?”

The answer to these questions often starts with knowing where the most reliable source of the individual data elements needed to calculate these measures sit. It gets trickier though because even when you find the best data source, you then have to be sure that the data is being entered consistently across your user community. That means:

  • Is the data being entered at the same time?
  • Is each data field restricted to certain values? Are the users entering these values or free-text?
  • Is the data being entered by the same person / role? With the same level of experience and expertise (this is especially critical in the case of identifying infections and pressure ulcers)?
  • Is the data being entered manually? Is it entered in multiple places?
  • Are there spreadsheets and documents that have this data that are paper sources and therefore, not able to be automatically data-mined?
  • Do your users understand the importance of standardizing this process? Do they understand the value it provides their organization and thus their patients?

The answer to the last question often eludes many clinicians I run into. It is sometimes difficult for someone who has been clinically trained their entire career to understand the power of discrete data over free-text narrative documentation.

One exercise we have found extremely helpful for our clients is creating a source-to-measure mapping document that identifies the agreed upon sources of the individual data elements (both numerator and denominators) for each quality measure being reported across the enterprise. Once this is created, get your clinicians, nursing, and analysts to bless it and finally publish it for reference so there is no ambiguity moving forward. Now everyone is reporting the same data with the same definitions. The most difficult part, though, comes as you have to hold people accountable for changing their practices to improve patient outcomes once you’re all reporting in the same language.

The Never-Ending Burden of Reporting Patient Safety & Quality Metrics

Quick: how long does it take you to collect, aggregate, and report your SCIP, PN, AMI, and HF Core Measures? How about infection control metrics like rates of CLABSI, VAP, UTI, and MRSA? Or for that matter, any patient safety and quality metric that is mandated by JCAHO, CMS, your Department of Health, or anyone else? If you answered anything less than 2 months, and if I was a betting man, I’d bet you were lying.

There is a never-ending burden strapped to the backs of hospitals to collect, aggregate, analyze, validate, re-analyze, re-validate, report, re-validate, report again….quality measures. Reporting of these quality metrics is meant to benchmark institutions across the industry on their level of care, and inform patients of their treatment options. Fortunately for the majority of institutions, it is not difficult to achieve a high rate of compliance (>80-90%) because clinicians genuinely want to provide the best standards of care. Unfortunately though, the standards for achieving the highest designation according to CMS guidelines (achieving top percentile >99%) requires hospitals to allocate a disproportionate amount of time, money, and people to increase very small increments of compliance. I sat with a SCIP Nurse Abstractor last week and we spent 90 minutes drawing out, on 2 consecutive white boards, the entire process from start to finish of reporting SCIP core measures. There are over 50 steps, 5 spreadsheets/files, 4 hand-offs, 3 committees, and a partridge in a pear tree. It takes 2.5 months. I wonder how much money that is if you were to translate that time and effort into hard money spent? I also wonder what the return on investment is for that time, effort, and money. If we’re going to start running healthcare like a business, which I argue we should, this seems like a great place to start.

STEP 1: Reduce the amount of time spent on this process by ensuring the data is trustworthy There are way too many “validation” steps. Most people do not trust the data they’re given, and therefore end up re-validating according to their own unique way of massaging the data.

STEP 2: Integrate data from multiple sources so your Quality Abstractors and Analysts aren’t searching in 10 different places for the information they need. I’m currently helping a client implement interfaces for surgery, general lab, microbiology, blood bank, and pharmacy into their quality reporting system so their analysts can find all the information they need to report infection rates, core measures, and patient safety metrics. In addition, we built a Business Objects universe on top of the quality data store and they can do dynamic reporting in near real time. The amount of time saved is amazing and we have been successful in dramatically shifting the type of work these people are responsible for. The BI Capability Maturity Model below depicts our success helping them move from left to right.

STEP 3: Empower your analysts. With much more time to actually analyze the information, these people are the best candidates to help find errors in the data, delays in the process, and opportunities for improvement.

STEP 4: Create a mechanism for feedback based on the information you uncover. Both overachievers and underperformers alike need to be recognized for the appropriate reasons. Standardize on the best of what you find, and be sure to localize your intervention where the data is inaccurate or the process breaks down. This will also demonstrate greater transparency on your part.