Big Data, Little Information, and the ACO Big Picture

By Michael Planchart, Perficient, Inc.

The Journey of a thousand miles towards an ACO begins with one step.
Healthcare organizations are coming to realize that the programs stimulated by the ARRA – HITECH Act, Meaningful Use (MU) and Accountable Care Organizations (ACO), require something that they don’t have in sufficient quantities, the desired type or in the right format: “Data”.

In this post we’re going to focus primarily on the ACO analytics side of things although some of the same principles are applicable to Meaningful Use at its various stages.

The Little Data We Do Have

Historically hospitals have focused on managing their data from the financial perspective. They are very good at submitting claims and receiving the reimbursements, or denials, and reconciling these. They are also very good at dealing with myriad payers which each have unique and complex processes and workflows to embrace. Government payers such as Medicare and Medicaid are very different to deal with because of complex rules that each of them has; Medicaid differs from state to state; private payers also have their disparities. Most healthcare organizations have created value based purchasing strategies that have nothing to envy the mammoth retailers. But all this data generated, stored and mined is similar to that of any other industry vertical. It’s business as usual here.

Hospital organizations have been relying on claims data for most of their financial and operational needs.

The current trend in healthcare is far beyond this type of data. Managing a patient’s health requires relevant clinical data. This is the data that is hundredfold more complex than any other industry has to deal with.

Folks that are, for the first time, entering the Healthcare Information Technology (Health IT) domain are a little perplexed and seem to perceive that we are years behind other domains. This is far from the truth. In the other verticals such as the banking, investment, retail or telecommunications ones, most of the data is of financial, logistic and operational nature. In healthcare we have to deal with this type of data as was indicated and with the other types that are not measurable with fingers alone, or an abacus.

Where’s the BIG Data

Laboratory information results are value and range based (e.g., normal, high, low), or binary (e.g., positive, negative), resulting from the chemical analysis and measurement of specimens (e.g., blood, urine, tissue); anatomical pathology results consist of the same in addition to complex interpretation narratives.

Medicines are discrete units that are being dispensed and administered (e.g., Metformin ER 500 mg tablet, Mupirocin Ointment USP, 2%) but also within a time frame, finite or infinite, and at precise intervals. And to add to the complexity; dosages may vary during the episode of care or an encounter in response to the patient’s reactions; allergies have to be taken into account; medicines may be changed; drug-to-drug interactions are evaluated prior to administering; diet has to be tracked and recorded; follow-up procedures or treatments have to be accounted for.

Imaging results from radiology contain images, discrete data, metadata and non-discrete narratives combined and packaged as a study. The non-discrete narrative is contained in report that is created by the radiologist while “reading” the images and recording into a transcription device or software which is converted from voice to text. A study can contain 1 or hundreds of images; a simple chest x-ray may contain 1-4 images (e.g., Posterior-Anterior (PA), Anterior-Posterior (AP), lateral (LAT)); a CT study may contain as many as 500 images each representing a slice.

We have complex coding systems: ICD-9 (currently migrating to ICD-10) for the classification of diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases; LOINC for the classification of laboratory and clinical observations; SNOMED as an organized categorization of clinical terms, codes, synonyms and definitions of diseases, diagnosis and procedures; RxNorm provides normalized names for clinical drugs and links its names to many of the drug vocabularies commonly used in pharmacy management and drug interaction software; etc.

Hospitals also have their own reference coding systems that have evolved throughout the years.

When a patient arrives at a provider facility and the clinicians begin with the anamnesis, many events, manual or automated, may start occurring: insurance or Medicare/Medicaid eligibility is verified; laboratory, radiology and pharmacy orders are entered; laboratory and radiology results are generated; medications are ordered, dispensed and administered, sometimes with CPOE and sometimes not; scheduling is processed and resource availability is verified; registration, admission and transfer events are triggered; billing details are validated and recorded. Behind the scenes there are disparate systems “talking” to each other in several healthcare lingos: HL7, X12 and DICOM. Hundreds or thousands of messages containing data are going from here to there and vice-versa. All these messages are sending data that is being consumed by other systems or even other external organizations.

Then, if there is so much data why is there little data?

The answer is simple: an enormous amount of data or information generated that spans from the beginning of a patient’s anamnesis, through the evolution of the episode of care and until the end of the catamnesis, is not being collected, and if it is being collected then it’s being recorded in a format that is inadequate, difficult or impossible to mine (or extract).

But didn’t we just say in one of the above paragraphs that hundreds or thousands of messages containing data are being exchanged during an encounter?

The answer is yes, but the data that is being collected is only the tip of the iceberg of what is required for many of the use cases being envisioned and which are required to manage the population’s health that belong to an ACO.

For example, from the anamnesis the clinician obtains the chief complaint and tons more of information provided entirely by the patient that may have motivated the visit or encounter. The majority of the information being provided by the patient is subject to the interpretation of the physician or the nurse. Have you ever gone to two different doctors with the same ailment and received the same interpretation? I haven’t.

The physician and nursing notes are not being transcribed into the Electronic Health Record (EHR) of the patient mostly because many providers don’t have an Electronic Medical Record (EMR) system. Maybe the provider has an EMR but the EMR doesn’t capture the information in a discrete way. These documents might be scanned and stored in an image format.

You’ve mentioned it a few times, what in the world is an anamnesis? Good question, the anamnesis is the combination of the verbal narration and written information the patient provides initially during the first encounters and it may continue throughout the entire episode of care; and since the care of a patient can depend on other people than him/herself abundant data or information may come from a heteroanamnesis, that is where relatives or caregivers narrate and provide written information about chief complaint, family history, present illness, etc.

Thinking from the End

An ACO requires the following capabilities among many others:

  • Population Health Management (PHM)
  • Chronic Disease Management (CDM)
  • Disease Registries
  • Health Information Exchanges

These capabilities require tons of data or BIG data that should be collected by clinicians and other trained healthcare professionals and not by mere source systems communicating messages between themselves.

Most of the healthcare organizations have a very difficult time knowing what the Average Length of Stay (ALOS) is for their patients at each one of their facilities. Needless to say they believe that a re-admissions management system is something required to operate effectively. Do you have to manage re-admissions or do you just have to count them? You don’t manage re-admissions you avoid them!

How much data do you need to obtain results for these two trivial indicators? All you need is the patient identifying information and the admission and discharge dates for each episode of care. Of course, you could also get fancier and try to obtain the ALOS that corresponds to a particular physician or department. But still, this data is easily obtainable.

On the other hand the capabilities listed above require data that is not easily obtainable since many times it’s not even collected. In order to succeed you would have to determine what data elements would be required for each of the capabilities and then try to map these to the origins or source systems. Not too long ago I performed a mapping for Coronary Artery Disease (CAD) and it was a daunting task. My team and myself had discovered that 80% of the data elements had to be manually abstracted since they were contained almost entirely in scanned notes or even paper notes that had never been scanned.

Yet, thinking from the end and mapping to the source will help you discover the gaps in data that is required for each use case.

The Heterogeneous Curse

Most healthcare organizations choose the “Best of Breed” model for their various systems. What this means is that each application has its own database and typically they don’t share information among each other.

Even those healthcare organizations that have chosen a single vendor for most of their needs face a similar dilemma in that the vendors generally grow their offerings by acquisition of other smaller software companies. The end result is that although the systems are under one vendor’s umbrella they generally implement different technologies and interoperability among them is as challenging as in the “Best of Breed” model.

HL7 messaging, as explained above, has been able to get most of these applications to “talk” to each other. “Talking” alone doesn’t solve the problem of “actionable” data. “Actionable” data is a requirement for many of an ACO’s requirements.

The BIG Challenge Ahead

Getting to “actionable” data is key to overcoming the heterogeneous curse. This is the BIG challenge ahead.

Taking on this challenge one step at a time can help overcome the paralysis.

The most crucial step is creating an Operational Data Store (ODS) and an Atomic Data Store (ADS) from all the available historic data, whether archived or extracted from the source systems databases. Those organizations that have taken this step have been the ones that succeeded with Business Intelligence (BI), Clinical Intelligence (CI) and near real-time use cases.

The ODS/ADS combo will help aggregate the patients data. They will also be the precursors for the Extract, Transform and Load (ETL) layer.
Unfortunately, most hospitals treat the messages that are exchanged by the myriad of systems in a “consume and discard” fashion. Most of the messages navigate through the healthcare system going through a broker or interface engine. These messages get transformed or mapped and are pushed to the consuming systems which ingest the information they need. The messages may stay in the interface engine’s data store for a short period of time; typically between 15 to 30 days before they are deleted.

The next step is fomenting a cultural shift of the clinical staff. Clinicians have been reluctant to be data clerks and many have valid reasons. Fomenting the cultural shift is not changing mindsets of the clinicians. Enabling them with novel technologies to capture a patient’s health status at all critical points of the workflows will be the real game changer. Mobile technology, natural language processing (NLP) and voice recognition should become ubiquitous in the healthcare settings.

Leverage the CCD and other CDA based documents at each point of transfer of care. This requirement alone will be the major force to put in place all the necessary gear to get to an interoperable state.

Indirect requirements will start popping up: data governance will be mandatory, and so will coming up with well-defined terminologies and coding systems. Don’t let these dissuade you since they are all good.


To succeed in the future healthcare paradigm you must start immediately. Take one step at a time, have a BIG strategic picture of the future but act tactically now. You will get there, eventually.

Michael Planchart, aka @theEHRguy is an Health IT Interoperability Consultant, Enterprise Architect for Healthcare IT, Standards Specialist:HL7, DICOM, IHE. Android and iOS Mobile Health Apps designer.


Dave Chase CEO of Avado at Health Datapalooza

By Gregg A. Masters, MPH

In the flurry of activities associated with the Health Data Forum III in Washington, DC aka (‘health datapalooza‘) I managed to corral  Dave Chase aka @ChaseDave in the Exhibition Hall at the DC Convention Center following his presentation at the ACO breakout session.

Amidst the background noise, we hear from Dave about his highlights from the event, a little about Avado and how they serve the interests of developing or operational ACOs.

During the ACO track at Health Datapalooza, there were four categories of software that have emerged as a result of ACOs. Chase argues that one of the new categories will be Patient Relationship Management (PRM) that is a superset of traditional proprietary patient portals tied to a single EHR. The PRM category does more to directly weave the patient into the process in a way that the Pioneer ACOs described.


Today on MU Live Radio: ACOs & Meaningful Use Connecting the Dots

By Gregg A. Masters, MPH

ACOs, Meaningful Use (aka MU), the persistent ‘whitewater’ of health reform and the quest for the elusive ‘triple aim’ will be at the center of our chat today on Meaningful Use: MU Live Radio.

MU Live! is a 30 minute internet talk radio show hosted by our HITECH Answers experts. Our session experts discuss breaking news and issues on meaningful use as well as other health IT topics.

For more information including past guest segments, click here. To register to listen to today’s broadcast at 11AM Pacific/2PM Eastern, click here.


Health Reform Readiness Infographic

By Gregg A. Masters, MPH

We all love infographics, right? This one caught my eye today. Kind of a clever snapshot of the crap shoot we’re in relative to the legal and political uncertainty festering in the US today. The original graphic is courtesy of @HITconsultant via his blog here.

Whether this captures the essence of our health reform readiness or not, the survey findings are summarized as follows:

  • Despite intense debate, over 80% of health plans are implementing Healthcare Reform (HCR) initiatives
  • Consumer experience tops the agenda on the 2012 priority list for health plans with a focus on member satisfaction and service
  • 80% of health plans are in the “wait and watch” mode and only in planning stages with their Health Insurance Exchange (HIX) initiative
  • Nearly 40% of health plans are already implementing Accountable Care Organizations (ACOs); more than half are in planning stages


ACO reimbursement, bundled payments, clinical quality measures and public profiles will be based on ICD-10 data

By Lynne Thomas Gordon

Healthcare leaders are juggling multiple pressures, including the consistent delivery of high-quality patient care, evaluation and development of accountable care organizations, the careful management of sensitive patient data, achieving meaningful-use criteria, making the most efficient use of the newest technology and stretching revenue to maintain end-to-end coverage of their bottom lines.

With so many priorities, it’s easy to become distracted from managing important changes such as the International Classification of Diseases, 10th Revision, or ICD-10. But there’s an urgent date on our calendars: the HHS’ final implementation date of Oct. 1, 2013, is a hard deadline that will trigger dramatic, though different, consequences for both those who will be prepared for the change and those who won’t. ACO reimbursement, bundled payments, clinical quality measures and public profiles will be based on ICD-10 data.

Given the high stakes, it is imperative that healthcare leaders avoid getting so caught up in the day-to-day that we fail to prepare properly for the many important changes that the ICD-10 conversion will demand from us.

The change to ICD-10 provides the U.S. the chance to discard the technologically outdated, medically inferior ICD-9 coding system and join all other World Health Organization member nations that have been successfully using ICD-10 to manage patient data for more than 15 years. Healthcare leaders will find that the more granular ICD-10 codes will provide opportunities to improve workflows, dive into quality improvement initiatives, demonstrate the severity of conditions being treated and participate with the rest of the developed world in the meaningful exchange of patient data for matters related to public health, scholarly research and the overall advancement of global health information management.

While multiple surveys conducted by AHIMA over the past year-and-a-half show promising signs that healthcare organizations are now making progress in planning for the ICD-10 conversion (85% of respondents recently indicated that they had begun work on ICD-10 planning and implementation), much work still remains if we’re to continue meeting implementation milestones. There is very little time for any industry providers or professional communities involved in data set management to lag behind or experience untimely (cont’d).

Read complete Modern Healthcare Article, click here.

Lynne Thomas Gordon is CEO of the American Health Information Management Association.


CMS Conference Call Digest & Reaction

By Gregg Masters, MPH

Tuesday, August 23rd, 2011 CMS held an informative conference call, on the new “Bundled Payments for Care Improvement” Initiative, click here for summary and replay instructions. For those who missed, this is a ‘Tweet Digest’ of some of the salient observations, thoughts and re-tweets.

CMS Conference Call on the new ‘Bundled Payments for Care Improvement’ Initiative [Re-play]

August 23rd, 2011 – The Centers for Medicare and Medicaid Innovation today announced the Bundled Payments for Care Improvement Initiative to help improve care for patients while they are in the hospital and after they are discharged.

Doctors, hospitals, and other health care providers can now apply to participate in this new program that will align payments for services delivered across an episode of care, such as heart bypass or hip replacement, rather than paying for services separately.  Bundled payments will give doctors and hospitals new incentives to coordinate care, improve the quality of care and save money for Medicare.

To learn more, join a conference call TODAY with CMS Innovation Center Director, Dr. Richard Gilfillan, Director of the Patient Care Models Group, Valinda Rutledge and Senior Advisor Dr. Nancy Nielsen.

What:  Conference Call on the new Bundled Payments for Care Improvement Initiative

When: Tuesday, August 23rd at 3:30pm Eastern/12:30 PM Pacific

Call Information :  (800) 642.1687, Conference ID: 94307536

Background on the Bundled Payments for Care Improvement Initiative

This initiative will bundle care for a package of services patients receive to treat a specific medical condition during a single hospital stay and/or recovery from that stay – this is known as an episode of care.  By bundling payment across providers for multiple services, providers will have a greater incentive to coordinate and ensure continuity of care across settings, resulting in better care for patients.  Better coordinated care can reduce unnecessary duplication of services, reduce preventable medical errors, help patients heal without harm, and lower costs.

Released today, the Innovation Center’s Request for Applications (RFA) outlines four broad approaches to bundled payments.  Providers will have flexibility to determine which episodes of care and which services will be bundled together.  By giving providers the flexibility to determine which model of bundled payments works best for them, it will be easier for providers of different sizes and readiness to participate in this initiative.

The Bundled Payments initiative is based on research and previous demonstration projects that suggest this approach has tremendous potential. For example, a Medicare heart bypass surgery bundled payment demonstration saved the program $42.3 million, or roughly 10 percent of expected costs, and saved patients $7.9 million in coinsurance while improving care and lowering hospital mortality.

Organizations interested in applying to the Bundled Payments for Care Improvement initiative must submit a Letter of Intent (LOI) no later than September 22, 2011 for Model 1 and November 4, 2011 for Models 2, 3, and 4. For more information about the various models and the initiative itself, please see the Bundled Payments for Care Improvement initiative web site at:


Interested parties may obtain answers to specific questions by e-mailing CMS at: BundledPayments@cms.hhs.gov.

For more information about this initiative or the CMS Innovation Center, please visit: http://www.innovations.cms.gov.