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July 15, 2013 Readers Write 4 Comments

The Enterprise Content Management Adoption Model
By Eric Merchant

7-15-2013 6-21-31 PM

There have been numerous publications recently about the amount of unstructured content that exists (80 percent of all content) in a non-discrete format outside of the electronic medical record. This unstructured content exists as digital photos, scanned documents, clinical images, and faxes and e-mails.

The challenge of capturing this information as close to the source as possible — managing it effectively and ultimately delivering it to the necessary physician, nurse, or other provider in a timely manner at the point of need — is a continuous uphill battle. There are varying degrees of being able to manage unstructured content and make it available to decision makers in a meaningful way to improve patient care, drive operational efficiencies, and improve financial performance in the healthcare market.

In developing a content strategy, the challenge is greater than simply buying a software suite and thinking your problems are over. As content grows in volume and complexity, the strategic plan needs to be flexible to be able to grow and adapt accordingly.

To do this, a reference is needed to determine where we were, where we are now and where we want to be. I began creating an Enterprise Content Management (ECM) adoption model as an internal point of reference, but also as a strategic guide for the industry. In practice, it would function similarly to the seven stages of the EMR adoption created by HIMSS Analytics.

ECM Adoption Model

Stage 10

Vendor Neutral Archive (VNA) Integration: Ability to seamlessly integrate with VNA.

Stage 9

Federated Search: Ability to search content across the enterprise.

Stage 8

Information Exchange: Ability to share/publish content with external entities, social media, etc.

Stage 7

Analytics: Meaningful use of content.

Stage 6

Image Lifecycle Management (ILM): Ability to purge and archive.

Stage 5

Capture, Manage and Render Digital Content: Ability to capture photos, videos, audio, etc.

Stage 4

Intelligent Capture: Ability to use OCR and other techniques to extract/use data.

Stage 3

Integration: Ability to render content inside ERP, EMR, etc.

Stage 2

Workflow: Ability to use automated workflow to streamline processes.

Stage 1

Capture and Render Documents: Ability to scan/upload and retrieve documents.

Stage 0

All Paper: No document management system (DMS).

This adoption model can serve the healthcare industry well by allowing us to keep focused on the outcomes we want to achieve and the systems that would provide them. The adoption model also intertwines patient care initiatives (capture content and deliver within the EMR), operational efficiencies we need to achieve (federated search and analytics) and outcomes that will directly benefit healthcare organizations’ financial performance (intelligent capture, VNA and Image Lifecycle management).

In addition, this strategy also delivers on the commitment to support Meaningful Use and IHE data-sharing initiatives with the ability to share and publish unstructured content to information exchanges.

EMR systems have received the bulk of the attention the past few years due to the value they bring and the public policy and reimbursement implications of getting them successfully implemented. However, as the healthcare market becomes more electronically mature, we cannot lose focus on the larger picture and the bigger challenge and ultimately the patient. This picture is incomplete without bringing together both the unstructured content created outside the EMR and the discrete information within the EMR.

To do this, the ECM adoption model, in conjunction with the EMR adoption model, must both be used as a roadmap to reach that goal. ECM vendors must take the same approach that EMR vendors have taken and work hand in hand with healthcare organizations to provide the solutions to achieve Stage 10 of the ECM adoption model and ultimately move closer to a complete patient record, which subsequently creates better health outcomes delivered efficiently and in a financially solvent manner.

Eric Merchant is director of application services, health information technology, for NorthShore University HealthSystem of Skokie, IL.

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Currently there are "4 comments" on this Article:

  1. I am very happy to read that the Enterprise Content Management (ECM) system / concept is being considered by a provider organization to help with the 80% of unstructured data that make up the Electronic Health Record system. (See Mr.HIStalk Readers Write, June 12, 2013, “Accent on Objects”). However, I would challenge some of the author’s ECM Adoption Model steps to incorporate more of the unstructured data from the get-go. This is because 99% ECM vendor industry does not.

    For example, Stage 0 should be defined as an organization that not only is all “paper”, but is all “analog”. What about all the photographic film in addition to all the paper? As such, Stage 0 should include organizations with an all “analog document” environment. (A document is any analog or digital, formatted and preserved “container” of structured or unstructured data.)

    Stage 1 should incorporate the capture and rendering of all the “analog” documents, whether the documents are analog paper or analog photographic film or analog …… Don’t forget that film digitizing devices are still used to scan and digitize analog photographic film as are paper scanning devices used to scan / digitize paper.

    Stage 2 – Workflow; critical!

    Stage 3 – Scanned film (and, perhaps, PACS for digital images and other already digital systems for signal traces [fetal or heart]) and scanned paper documents integrated into EHR.

    Stage 4 – I would delete Stage 4 and incorporate it into Stage 1 with the scanning of analog paper documents, whereby OCR, ICR, bar coding, etc., can be used to correctly extract 90% of the scanned paper document data for use cases.

    Stage 5 – Here is where, as the author pointed, all the already digital document data from video, audio and other systems, such as email, web pages, etc., are incorporated into the EHR, if required.

    Stage 6 – Not just Image Life Cycle Management, but all “digital document data” Life Cycle Management must be incorporated into Stage 6. By now, most of the digital document data (the scanned paper document images, the digital structured data from the EHR, the scanned photographic film images, the digital diagnostic images, the digital text, the digital audio data, the digital video data, etc. ) have become records requiring Life Cycle Management. Records are different from documents in that all records follow a life-cycle (creation, maintenance, use, security and destruction), have retention schedules assigned, have evidentiary value, and the content is locked once declared a record. All documents are potential records, but not vice versa.

    Stages 7 through 9 – YES! In addition, perhaps some of the stages could be combined. For example, federated search and analytics.

    Stage 10 – The VNA should be able to archive every single digital record in the organization. Currently, most VNAs are focused on archiving only digital diagnostic images. However, with the recent mergers and partnerships of VNA solutions with Document Management and/or Content Management solutions, thankfully, this will be changing the course.


  2. I was very interested to read the description and discussion regarding a clinical information maturity (CIM) adoption model. Clearly the industry needs guidance in how to manage all of the competing demands for health information and analytics. I think the fact that these issues are finally coming to the forefront is a good thing.

    This topic touches me and my team closely. As background, I am a director of the CAP Consulting group of the College of American Pathologists. Over the past few years we have developed and have been using a maturity model framework, the CAP Enterprise Clinical Information Maturity (ECIM) to assess and guide provider organizations in establishing best practices and helping them to build more mature information governance, management and analytic capabilities for their electronic health information. Our model takes a slightly different approach than the model presented by Eric Merchant – which is not in any way a criticism of his approach.

    We have identified, adapted and consolidated a set of high piority information management capabilities that have been successful in other data intensive industries, and that have been proven to work in leading health institutions. Solutions for today’s content issues will require both the organizational disciplines and the intelligent leveraging of technology and analytics to enhance and support data management.

    We do assume there is a place for both unstructured data and structured data. There is also a subset of “unstructured data” which can be made more mine-able or useful by consciously placing it in organized purposeful locations where it can reliably be accessed, indexed or mined.

    The primary goal of our CAP ECIM maturity “model” is to provide a roadmap for provider organizations to help achieve actionable, analyzable information that is clinically reliable, and can be analyzed and incorporated into the fabric of health decision support, patient and population care practices. We think the approach we have outlined addresses the root causes for many of the data and content challenges we see in our provider clients. As we work with clients, it has certainly been useful.

    This week I attended the Health Data Management “Healthcare Analytics Symposium and Expo” in Chicago. There were great presentations showcasing what health systems have been able to do with their information. However, in most of the presentations, the information itself had limits or gaps that had to be overcome. Some of the presentations addressed how they overcame these pain points.

    This confirms what we find in the field – that basic foundational practicesare not commonly in place. Better practices would improve the utility of provider’s health information, and increase the speed and agility of the institutions to develop analytics that apply their information to the many different improvement opportunities and health challenges they face.

    During the conference, the CAP team handed out some initial draft copies of a whitepaper that outlines our CAP ECIM framework and identifies some of the challenges we have found in the field. “Our National Rush to the EHR – An Analysis of the (New) Current State of Clinical Information Quality”. I would be happy to send this preliminary draft out to readers if they are interested. .

    Within each CAP ECIM capability “level” there are a number of goal states that describe the practices and actions that are needed. Each capability can be assessed to determine an organization’s gaps and opportunities for improvement.

    Organizations need an information strategy to identify, prioritize and appropriately and unambiguously define their content and where it lives. A data stewardship and management strategy and practices need to be developed to control priority content as it is designed for capture in the EHR data dictionaries and databases. Then, there must be audits and validation of how the EHR content is actually utilized and applied to patient records and how it is transacted across applications to assure patient documentation and records are populated in a consistent (predictable) and accurate way.

    There are many dimensions, types and forms of information to be managed. In our maturity framework, we have tried to identify the most important foundational practices that are needed if the core information is to be useful and reliable. Levels 1-3 include the basic foundational practices that are criticial for the success of Levels 4-5.

    Each organization will start with different information priorities and may be very advanced in one area, but not in another. Data structure requirements are driven by information priorities and use cases. Unstructured data may also be priority data and leaving it as “unstructured” may be strategically acceptable. There will be many acceptable variations for each organization.

    Unlike the other matuirty or adoption models, it is not entirely a ladder step approach but an iterative evolution. There is an assessment of the goals state and actual practices for each level that yields a maturity score for that level. Thus an organization may have advanced capabilities of performing complex analytics (level 4), but actually be quite immature in its practices to assure that the records are actually correct and reliable (level 3) . Of course in that scenario, the analytics are not likely to yield good actionable information, a factor considered in level 5. We think this framework allows us to tie the evaluation more closely to the realities of each organization and to identify “maturity gaps” that can be corrected. We certainly welcome comments.

    The following identifies, at the highest level, the CAP ECIM stages or levels:

    1.0 – Controlled Content Ownership: Enterprise information priorities are established, an effective governance framework is in place

    2.0 – Structured Standardized Content: Priority clinical data is strucured and standardized, terminologies and coding are accurate and managed

    3.0 – Consisten, Accurate, Data Capture: Practices are in place to assure high quality, reliable recording of patient information

    4.0 – Decision Support and Analytics – Analytics and data mining are enabled to enhance knowledge

    5.0 – Lnowledge-Driven Performance Improvement – Organization leverages and measures information for continuous improvement


    Paloma L. Hawry
    Managing Director
    CAP Consulting

  3. Great perspective and work toward developing an Enterprise Content Management System for unstructured data. In the content strategy, it’s important to consider the significant segment of unstructured information delivered by voice. Phone calls and in-person conversations that providers have with patients, physicians and payers carry critical details needed to effectively schedule, authorize and coordinate care.

    Stage 0 should expand to include the need for tools to capture and digitize unstructured information in all its formats – paper, electronic and voice. Using technology to record and index voice exchanges to the patient makes an important contribution to a complete patient record.

    Erin McCarty

  4. Re: Erin McCarty reply –

    Correct – Stage O, as I explained (above) — should be defined as an organization that not only is all “paper”, but is all “analog”. What about all the photographic film in addition to all the paper? WHAT ABOUT ALL THE ANALOG VOICE CLIP IN ADDITION TO ALL THE PAPER? As such, Stage 0 should include organizations with an all “analog document” environment. (A document is any analog or digital, formatted and preserved “container” of structured or unstructured data.) A VOICE CLIP IS A DOCUMENT!

    As such, Stage 1, as I explained (above) — should incorporate the capture and rendering of all the “analog” documents, whether the documents are analog paper or analog photographic film or analog VOICE CLIPS or analog……

    This follows that either Stage 3 or Stage 5, as I explained (above) — where, as the author pointed, all the already DIGITAL document data from video, audio, and other systems, such as VOICE, email, web pages, etc., are incorporated into the EHR, if required. NO LONGER ANALOG VOICE BUT DIGITAL VOICE!

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