Advancing the Practice of Evidence-Based Medicine with Standardized Order Sets

November / December 2009

Advancing the Practice of Evidence-Based Medicine with Standardized Order Sets

A growing body of literature makes it clear that providing clinicians with access to a greater breadth of automated clinical decision support tools can improve the quality of care and patient safety. By integrating clinical guidelines, alerts and reminders, order entry, and drug information into electronic health records (EHRs) and computerized physician order entry (CPOE) for point-of-care access to evidence-based best practices, hospitals also benefit from reduced costs due to fewer medication errors and other adverse events and enhanced productivity and workflow.

Among the clinical decision support tools available today is the standardized order set, which has become fundamental in shaping patient care. Order sets improve clinical performance and regulatory compliance by establishing standards of care and advancing the practice of evidence-based medicine.

Heightened regulatory oversight and increased pressure to achieve higher levels of quality and safety have prompted a growing number of hospitals to create expansive libraries of standardized order sets. The challenge, however, is how to build and maintain that library efficiently. Achieving agreement about what constitutes the best order set is a cumbersome process, particularly when it is difficult to provide physicians with easy and convenient access to supporting literature and evidence.

Providing point-of-care access to the most current version of approved order sets is also problematic, as traditional orders sets are paper-based and rarely consistent across individual clinicians. Also, without convenient access to evidence supporting the directives specified in a given order set, physician adoption can be challenging.

Automation can help facilities implementing order sets to overcome nearly all of these obstacles. By automating the order set development process and providing reviewers with direct access to supporting evidence, hospitals can more rapidly deploy standardized order sets that integrate automatically into CPOE and EHR systems for immediate point-of-care access. Further, when links to trusted clinical resources are integrated into these order sets, clinician adoption is significantly improved.

Impact of Standardization and Automation
Evidence suggests that the use of automated tools such as notes, records and order entry, as well as advanced clinical decision support, results in fewer complications, lower mortality rates, and lower costs (Amarasingham et al., 2009).

A growing body of research indicates that the use of standardized order sets alone improves compliance with recommended care processes and patient outcomes. The use of standardized order sets has also been found to reduce overall and postoperative lengths of stay and total charges for multiple surgical procedures.

In one integrated delivery system, the deployment of a standardized order set for adult pneumonia resulted in significant reductions in in-hospital mortality, expected payment and contribution margin, and a significant increase in compliance with core measures. Severity of illness, discharge month, and reductions in in-hospital mortality remained significant even when findings were adjusted for patient and provider characteristics. The same was also true for the increase in core measures compliance (Ballard et al., 2008).

The combination of standardized order sets and intensive clinical case management has also been shown to lead to a significant reduction in length of stay, while still maintaining quality. This is driven primarily by a reduction in the time from clinical stability to discharge (Fishbane, 2007).
Additional research suggests that implementation of standardized order sets, templates, or protocols can improve compliance with recommended processes of care and improve outcomes. It can also reduce overall length of stay, postoperative length of stay, and total charges for multiple surgical procedures (Ballard et al., 2008).

These demonstrated outcomes, coupled with the changing healthcare environment, have given order sets a new place of prominence in the hospital setting, in particular as a means by which to address quality, regulatory, and accreditation issues. The goal for most hospitals is to standardize care and improve quality through the practice of evidence-based medicine.

In a survey by Renaissance Research (2008), 28% of hospital managers involved in the order set development process cited standardization of patient care as the primary objective for order set development. Twenty-three percent cited the desire to improve quality by following best practices through evidence-based care. Other common objectives were improved patient safety (12%); a reduction in medication errors (12%); improved efficiency (9%); and cost control (5%).

In terms of quality, regulatory and accreditation issues, more than 80% of survey respondents expected order set creation to address Centers for Medicare & Medicaid Services (CMS) and Joint Commission quality measures. Forty-four percent had the same expectations for meeting Agency for Healthcare Research and Quality (AHRQ) measures (Renaissance Research, 2008).

Yet despite the demonstrated value of standardized order sets, many hospitals are struggling to develop and maintain a sizable library of these critical tools. Among the primary obstacles for authoring and reviewing order sets are the time and resources associated with the process, as well as the logistics involved in bringing together all the necessary decision-makers and achieving final consensus.

Easy availability of medical content, such as evidence and best practice standards, is another significant challenge, as is identifying ongoing performance issues. Other concerns include ensuring order sets conform to hospital policies, are error-free, and that everyone is utilizing the most current version.

The Benefits of Automation
Automated order sets solutions overcome the most significant roadblocks to hospitals’ efforts to build, deploy, and maintain a sizable library of these key clinical decision support tools. By automating and streamlining the authoring, review, and maintenance processes, and by providing easy access to supporting literature, these applications enable physicians and other key decision-makers to reach consensus more efficiently.

Further, by enabling order sets to be integrated into point-of-care clinical information systems, complete with direct links to supporting evidence, automated order sets solutions encourage a higher level of physician/clinician adoption without which it would be impossible to achieve even the most limited outcomes from standardized order sets.

Most automated order sets solutions offer “starter” order sets with links to supporting evidence. They also enable the creation of custom order sets. Typically, an assigned “owner” develops the order set, links it to existing standards, best practices, and supporting literature, and identifies the appropriate reviewers. These reviewers then receive an automatic email alerting them that the order set is ready for review.

By clicking a link within that email, reviewers can open the draft order set in a web browser, add comments, review supporting literature, and notify the owner when they are finished. Once an order set has been approved, the owner releases it and the application pushes it directly into the CPOE system. This eliminates the need to recreate order sets within the EMR or CPOE to enable point-of-care access.

Automated order sets solutions also provide efficient auditing and maintenance. Comments are tracked and a historical record of the order set is maintained. This allows reviewers and owners to see what was changed, when it was changed and by whom, and how the current version compares to earlier iterations.

Orlando Health ( knows first-hand how complex the order set creation and maintenance process can be. The organization — with more than 2,000 affiliated physicians and eight hospitals including the Orlando region’s only Level One Trauma Centers for adults and pediatrics — recognized several years ago that the availability of an expansive library of standardized order sets at the point of care was vital to its mission.

Indeed, order sets coupled with good workflow and evidence-based guidelines are considered by Orlando Health’s leadership to be keystones to excellence in patient care. The challenge, one shared by most large healthcare organizations, was a backlog of resources that hampered their ability to build order sets fast enough to meet the demand.

Orlando Health faced this challenge despite an established development process that resulted in the successful creation of approximately 1,500 order sets. That process typically started with a clinical expert who developed the initial order set draft, which was then reviewed and approved by the Pharmacy & Therapeutics Committee, Risk Management and Quality Assurance before being distributed for physician input.

Depending upon the complexity of the order set, it could take days, weeks, or months for consensus to be achieved. Once it was, the order set would be deployed to the appropriate hospital’s CPOE system for point-of-care access by physicians. Once in the system, physicians could edit order sets; however approval from the appropriate department heads was required before a particular order set could be officially updated.
Orlando Health’s order set process was streamlined and fairly efficient. Yet challenges remained in several key areas: 

  • Easy access to supporting literature
  • Efficient editing
  • Deployment of order sets and updates across all facilities
  • Physician awareness of order set availability

Achieving an acceptable level of performance once deployed within the CPOE system was also problematic, particularly given that as many as 2,400 concurrent users could be signed onto the system and accessing order sets at any given time.

Faced with managing the additional 1,000 order sets already in the pipeline as well as the ongoing maintenance of its existing library, Orlando Health undertook a system-wide evaluation to identify how to accelerate the overall process. Ultimately, they determined the need to create a centralized database of standardized order sets and deployment of a tool that would automate authoring, review, deployment, and maintenance.

As one of only a handful of health systems nationwide to reach Stage 4 of the Healthcare Information and Management System Society (HIMSS) Analytics’ EMR Adoption Model, it was also imperative that the order set solution Orlando Health ultimately selected would integrate into its clinical information system.

To reach Stage 4, which had been achieved by just 2.8% of hospitals and health systems tracked by HIMSS Analytics as of the first quarter of 2009, a facility must have deployed CPOE for use by any clinician, added to the nursing and clinical data repository environment, and implemented second-level clinical decision support related to evidence-based medicine protocols.

It was also crucial that the order-set tool link supporting evidence to the draft order set, which would shorten auditing time and enable physicians to provide a higher level of input. Too, deploying finalized order sets into its existing CPOE system with the appropriate evidence attached would make it clear to physician users why a particular order set was written as it was, encouraging greater adoption.

Although automated order sets solutions are
relatively new, users are already recognizing their benefits. In the
previously cited independent survey, the majority of users reported
being “very satisfied” with the authoring (53%), reviewing (60%), and
approval (60%) functions of their application (Renaissance Research,

The key to achieving high satisfaction and
adoption rates and realizing a maximum return on the investment is to
evaluate order set applications based on the features that users
consider most important. In the survey by Renaissance Research (2008),
those features were identified as:

  • The ability to link into disease, lab, drug, and
    patient education information and ensure that everyone on the order set
    committee has access to the same information (93%)
  • Auditable history logs to track order set changes (87%)
  • Customizable library of evidence-based order sets (67%)
  • The ability to track review comments on draft versions (60%)
  • Integrated access to a comprehensive underlying repository of evidence and primary literature (53%)
  • Intuitive structure based on the facility’s review and approval process workflow (33%)
  • Innovative and unique data security controls (33%)

When properly selected and implemented, automated
order sets solutions can deliver benefits that go far beyond
streamlined development and maintenance. By providing access to
comprehensive clinical evidence at the point of care, order sets
applications can improve patient care. Through built-in
standardization, they can also increase patient safety and reduce costs
related to medication errors and hospital length of stay.

Further, by integrating standardized order sets
with existing clinical decision support systems, hospitals will be able
to put evidence-based healthcare into practice by establishing and
maintaining standards of care.

Linda Peitzman is chief
medical officer for Wolters Kluwer Health and executive vice president
of Clinical Development and Informatics for its Clinical Solutions
division. In these roles, she helps direct clinical strategy and
oversees the clinical development and informatics for Clinical
Solutions products, including structured clinical documentation, coding
and reimbursement, evidence-based order sets, order set management,
evidence-based guidelines and clinical decision support, as well as EMR
and clinical systems integration. Peitzman has more than 18 years of
healthcare experience that spans several areas of healthcare, including
direct patient care, leadership of physician care delivery, physician
management, nursing care delivery, system process improvement, access
to care initiatives, healthcare change management, care guidelines, and
evidence-based medicine. Other areas of expertise include structured
documentation, coding and reimbursement, EMR integration, and clinical
software application development and evaluation, as well as a wide
range of clinical informatics and content development. She may be
contacted at

R., Plantinga, L., Diener-West, M., Darrell, G., & Powe, N. (2009).
Clinical information technologies and inpatient outcomes: A multiple
hospital study. Archives of Internal Medicine, 169(2), 108-114.

Renaissance Research. (2008).
ProVation Order Sets Research: Report of Findings. Edwardsville:
Renaissance Research and Wolters Kluwer Health.