Big Data. Big Decisions
InformationWeek
Special Coverage Series


Meaningful Use Slowly Increases EHR Use In Hospitals

Expense and resistance to change are among reasons 75% of hospitals still aren't in advanced stages of MU, says Health Information Management and Systems Society.

9 Mobile EHRs Compete For Doctors' Attention
9 Mobile EHRs Compete For Doctors' Attention
(click image for larger view and for slideshow)
The advanced use of electronic health records is starting to accelerate in hospitals, mainly because of the government's EHR incentive program, concludes a new analysis of HIMSS Analytics' Electronic Medical Record Adoption Model (EMRAM) scale. The EMRAM scale is an eight-stage model that indicates where hospitals stand on the EHR adoption curve.

A survey by HIMSS Analytics, the research arm of the Health Information Management and Systems Society, indicates that during the five quarters ended in September 2012, the number of U.S. acute care hospitals achieving EMRAM stage 5 or 6 increased by more than 80%; the number of facilities in stage 7 rose 63%.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Nevertheless, the percentages of hospitals that are actually in these stages show that the majority of facilities have a long way to go before they realize the full potential of their EHRs. In the fourth quarter of 2012, HIMSS Analytics figures show, just 1.9% of hospitals had reached stage 7; 8.2%, stage 6, and 14%, stage 5. Three-quarters of the hospitals were not yet in stage 5.

[ Why does healthcare want to put the brakes on new MU rules? Read Docs, Hospitals Say Delay Meaningful Use Stage 3. ]

Although the EMRAM stages have no direct relationship to the stages of Meaningful Use in the federal incentive program, the current distribution of hospitals' IT capabilities raises questions about their ability to meet the requirements of Meaningful Use stage 2.

On the plus side, a hospital in EMRAM stage 4 has computerized physician order entry (CPOE) and clinical decision support, both of which are required in Meaningful Use stages 1 and 2. Facilities in stage 4 have nursing documentation, error checking, and other capabilities. But they are missing closed-loop medication administration (stage 5), physician documentation and full clinical decision support (stage 6), and the ability to exchange standardized summary documents with other providers (stage 7). All of these are required in Meaningful Use stage 2 except for physician documentation, which is an optional menu item for eligible professionals.

Health information exchange capabilities are moving slowly in the right direction as well, according to John Hoyt, executive VP of HIMSS Analytics. "Facilities moving to the upper stages of EMRAM are laying the groundwork for interoperability to occur," he said in a press release. "Stage 6 and Stage 7 hospitals are fully prepared for provider-to-provider or facility-to-facility interoperability, as well as increasing the provider or facility's ability to provide electronic health data reporting to public health and immunization registries to support population health review and syndromic surveillance."

In an interview with InformationWeek Healthcare, Hoyt said, "We still have an accelerating rate of growth in stages 5, 6 and 7. The biggest hurdle is getting physicians to enter data on their keyboards. Of course, that's required for stage 1 of Meaningful Use."

That comment referred to the Meaningful Use stage 1 requirement that clinicians enter pharmacy orders for 30% of patients with at least one pharmacy order through CPOE. Noting that HIMSS Analytics has always required medication, lab, imaging and other orders to be done electronically in stage 4, he observed that some hospitals might not achieve that level in EMRAM, yet still be able to attest to stage 1 Meaningful Use.

Providers who achieve stage 5 in EMRAM could probably meet the Meaningful Use stage 2 requirements, Hoyt said, partly because they already have full CPOE. In addition, EMRAM stage 5 requires closed-loop medication administration that matches patient IDs with bar codes on drug packages. Although the Meaningful Use regs aren't so specific, he said, they "imply" that kind of medication administration.

Asked why it takes most hospitals so long to get to advanced stages of EHR implementation, Hoyt pointed out, "It's really difficult to implement these systems with voluntary medical staffs." In a highly competitive environment, he noted, hospitals want to make private practice physicians happy, so they don't want to lean on them too heavily to enter orders through CPOE or do electronic documentation. But Meaningful Use has leveled the playing field, he said, making it easier for hospitals to seek physician participation because their competitors are doing the same thing.

In addition, he said, it's expensive and time consuming to fully implement clinical systems. "It's not just a matter of buying software, it's about process redesign. It takes leadership and access to capital. That's clearly a problem, especially for small hospitals -- not leadership, but access to capital," he said.

Many hospitals are doubtful about their ability to achieve Meaningful Use stage 2. In a recent KPMG survey, 47% of healthcare executives said they were only "somewhat confident" about their ability to satisfy these requirements. The biggest challenge, the respondents said, would be training and change management.

Clinical, patient engagement, and consumer apps promise to re-energize healthcare. Also in the new, all-digital Mobile Power issue of InformationWeek Healthcare: Comparative effectiveness research taps the IT toolbox to compare treatments to determine which ones are most effective. (Free registration required.)



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.