Structured and templated reporting: An overview

pdf path

The American Recovery and Reinvestment Act (ARRA) and the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 provide for significant investments in electronic health records (EHR). Electronic health records are being pushed in the belief that capturing and analyzing structured information will improve medical decision making, with an associated improvement in patient outcomes.1 However, most radiology reports are currently free-text documents, much like clinical narratives. Interest is growing in transitioning from free-text reports to structured reports.

This article provides an overview of structured reporting in radiology, first defining the term itself, and then discussing its pros and cons. Current efforts will also be highlighted and implementation considerations—including future technologies—will be discussed.

Structured reporting defined

It is helpful to clarify what is meant by “structured reporting” in radiology. Three progressively structured tiers are generally recognized.2 The first and simplest tier relates to the presence of common headings, such as “Indication” and “Impression”.2,3 The second tier, sometimes called “itemized reporting,” includes sub-headings specifying categories such as organs and organ systems within the “Findings” section. Like the first tier, itemized reporting is relatively easy to implement.2

The third tier of reporting requires the use of standardized language. To enforce consistency, this tier uses pick lists, buttons, and other form elements. This last tier is orders of magnitude more difficult to implement than the first two, but it is what “structured reporting” really means. Leveraging standardized and constrained language is how most benefits of structured reporting are realized. This type of reporting is already becoming increasingly prevalent in other areas of medicine to satisfy various Meaningful Use criteria, such as problem list maintenance.4

Pros of structured reporting

Structured reporting provides many benefits. First, structured reports are relatively uniform between radiologists and use a consistent vocabulary, which reduces ambiguity.5 For example, the terms “Barium Swallow,” “Modified Barium Swallow,” “Cookie Swallow,” “Speech Swallowing Evaluation,” and “Swallowing Function Assessment” may or may not refer to the same exam, depending on the institution. Such variability can easily lead to confusion and medical errors.

Ambiguous language causes even more confusion for computers. Structured reports that use terms consistently can be more effectively analyzed, creating opportunities for research, clinical decision support, and quality improvement. For example, imagine if CT pulmonary angiogram results could be grouped automatically into “positive” and “negative” studies. One could rapidly calculate positivity rates for ordering providers and benchmark the providers against other institutions in a method similar to that utilized by mammography registries.

Structured reports also enable radiologists to provide consistently complete and useful reports. When encountering infrequent conditions, radiologists often find it difficult to remember all the required elements that referring providers care about. Take, for example, the diagnosis of a new pancreatic adenocarcinoma. A structured template would remind the radiologist to report all pertinent observations, including extent of both venous and arterial vascular involvement as well as nodal location.6

Structured reports also promote adherence to guidelines,4 which is particularly important in the current healthcare environment. Guidelines are seen by healthcare reformers as an effective way to reduce costs and improve quality, and are expected to become an increasingly large part of medical practice. Of concern, however, is that even relatively well-known and simple existing guidelines are difficult to follow. One study revealed that radiologists at a major academic center achieved only 60.8% conformity to Fleischner Society pulmonary nodule guidelines.7 Structured reports may improve these numbers and could potentially automatically calculate recommendations based on appropriate inputs.8

Perhaps most compelling, there are also new financial incentives for complete reporting. Adherence to guidelines already affects radiology reimbursement via the Centers for Medicare and Medicaid Services’ (CMS) Physician Quality Reporting System (PQRS) measures. Meeting these measures now provides a bonus payment that will become a financial penalty if not met in 2015.4 For example, the now-retired PQRS measure #10 required documenting the presence or absence of hemorrhage, mass, and acute infarction in radiology reports for possible stroke.9 One study showed that only 58.1% of reports complied with this measure.10 It is reasonable to expect that guideline adherence will increasingly affect reimbursement, and that practices not using structured reports will be at increased risk of losing money.

Cons of structured reporting

While the merits of structured reporting are commonly touted, current literature also contains questions, warnings, and comments regarding challenges to implementation.

One challenge is simply resistance to change. The prose report has been the primary product of radiology since the early 1900’s and has endured great leaps in both imaging and reporting technology.11 While it can be argued that this is the exact reason radiologists should update their reporting practices, one must recognize how entrenched prose reports have become in our profession. The prose report is part of the unique value a given radiologist brings to his or her practice of medicine; as such, there is resistance to standardization, especially among older radiologists.2,5 As a result, the Johnson et al12 study that compared a structured-reporting system against traditional free-text dictation explicitly excluded older radiologists, assuming they would be more entrenched in the practice of prose. Convincing radiologists to give up their traditional reporting style remains a very challenging task facing the implementation of structured reporting.11

Although improved accuracy is often claimed as a benefit of structured reporting, some have questioned this assertion.13,14 The largest study of a structured-reporting system found decreased accuracy of report content.12 However, this may have been due partly to limitations of the reporting system, and improved designs of new reporting technology may significantly improve accuracy.15

There are also concerns that structured reporting may negatively impact radiologists’ workflow and reasoning. The complexity of creating a structured report requires increased visual attention, decreasing the radiologist’s “dwell time” on images and increasing the potential of disrupting the search pattern.2 Also, organ system itemization may contribute to radiologist error if switching from field to field results in a disruption of cognitive reasoning.2,16,17 Moreover, it may be difficult to summarize or provide an overview of a complex, multisystem disease process if the findings are fragmented over several sections.

Similar concerns have been raised for referring providers. The same over-structuring and fragmentation that may cause a radiologist to miss the big picture could have the same effect on the reader, even when accurately reported. There is also the concept of “over-completeness,” suggesting that multiple fields with pre-populated “normal” language can hide important information regarding the pathology. Moreover, pre-populated fields are impossible to judge as just part of the template or the result of thoughtful introspection.16 Nevertheless, referring providers claim a preference for structured reports;5 these limitations further emphasize the need for continuing refinement of templates and reporting software.

Current efforts

The Breast Imaging Reporting and Data System® (BI-RADS®) is currently the best example within radiology of structured reporting and standardized language, with many realized benefits. The standardized language greatly aids in education and practice consistency;18 through BI-RADS, much is learned about breast imaging and pathology. The federal government auditing system established by the Mammography Quality Standards Act (MQSA) relies upon structured reporting. In addition, mammography research has increased, largely in the form of mammography performance evaluation. This research is made possible by the standardized imaging-outcome assessments provided in BI-RADS.19 Most notably, report impressions are clear and consistent, improving patient care and clinical practice.

Although the benefits of BI-RADS are well documented, breast imaging encompasses a relatively limited range of pathology, making it particularly well-suited to structured reporting. The same is not necessarily true of the rest of medical imaging, where applying this approach can be more challenging. One potential solution is to focus on limited ranges of pathology elsewhere in the body. The American College of Radiology (ACR) is sponsoring multiple efforts to develop tailored lexicons, such as the Liver Imaging Reporting and Data System (LI-RADS) for reporting liver masses20 and the Head Injury Imaging Reporting and Data System (HI-RADS) for traumatic brain injury.21 The Prostate Imaging Reporting and Data System (PI-RADS) is being developed and tested by the European Society of Urogenital Radiology (ESUR).22-24

Structured reporting can be successfully implemented with varying scope at the institutional level. For example, UCSF used itemized templates to report CT radiation doses in response to a 2012 California mandate.25 In contrast, Cincinnati Children’s Hospital successfully implemented structured reporting department-wide for 94% of its imaging volume.26

Implementation considerations

Implementing structured reporting within a practice poses multiple challenges. Larson et al from Cincinnati Children’s Hospital recently outlined their rigorous and effective approach.26 A key point was that the organizational hurdle was at least as challenging as the technical hurdle; the job was not complete once the template was published. Getting buy-in from all radiologists and modifying templates when appropriate, “hounding” non-users to use the templates, and basing modest bonuses on achieving usage goals all contributed to successful adoption. The team also stressed the importance of consensus building and discouraged simply copying another group’s templates without an internal discussion.26 Focusing initial efforts on a few common studies and getting them to near-universal utilization may be a reasonable first step for other institutions.

In addition to organizational challenges, the technical hurdles to implementing structured reporting are significant. First, the definition of structured reporting implies a standardized language, but that language is still being developed.27 Within radiology, the most tailored ontology is RadLex28, a lexicon created by the Radiological Society of North America (RSNA). For now, any structured reporting implementation should agree on consistent language internally, but the intent is that structured reports will eventually use RadLex or another terminology such as SNOMED-CT or LOINC. Future integration of RadLex into report templates will be essential for realizing the benefits of interoperability, including communication between institutions for patient care and research.4

In light of these challenges, the RSNA Radiology Reporting Committee is working to facilitate the report template development process. The group is actively developing a library of structured reports, freely available at http://www.radreport.org/, which are intended to serve as a starting point for internal template development.4 Currently, the reports are variable in content and structure. For example, compare the templates available for CT orbits and CT face.29,30 While the CT orbits template is highly itemized with multiple subheadings for each orbit, the CT face template simply contains default “normal” text under two subheadings: “facial bones” and “other.” Ideally this library will continue to improve. Importantly, the RSNA templates will both use and inform the development of RadLex terms,27 facilitating adoption of this lexicon.

Another technical hurdle is the lack of a common template format. Currently, no major dictation-system vendors support importing or exporting templates between vendor systems. For some perspective, this is the equivalent of needing to recreate a PowerPoint presentation from scratch every time it must be shown on a different computer. A structured report with several pick lists would be very painstaking both to transmit and transcribe. A solution to this problem is the Management of Radiology Reporting Templates (MRRT) template format,31 which aspires to be the standard format. It was developed by the RSNA and Integrating the Healthcare Enterprise (IHE). MRRT is still in its infancy; dictation-system vendors do not yet support it, and creating or modifying MRRT templates currently requires coding in HTML. Support for MRRT by major vendors and a user-friendly authoring interface will boost template sharing and adoption.

Finally, a template library created by a panel of experts is a great start. However, identifying and sharing the best or most popular templates among practicing radiologists is also desirable. Crowdsourcing is a means for letting good ideas percolate to the top, and is well-realized in other industries.32 An open-exchange website where templates could be submitted and rated by users would be a valuable additional method for developing usable and popular templates. This is currently in development by the RSNA Radiology Reporting Committee.

Conclusion

Structured reporting provides many benefits, including decreased ambiguity and enhanced opportunities for research, clinical decision support, and quality improvement. It can also serve as an aid to clinical practice in an increasingly guideline-oriented environment. D’Orsi and Kopans said it well 20 years ago: “Without standardized terms to describe the important features ... there is no means of training or obtaining objective data to improve our specificity. There must be a concise and orderly description of the finding(s) in language understandable to both clinician and radiologist leading to a logical recommendation. Indeed, this format is important for all reports we generate, not only mammography.”33 There is little doubt that structured reporting will become more prevalent. If reimbursement becomes more tied to guideline adherence, adoption could be quite rapid. Ideally, emerging technologies and resources will make it easier to implement, use, and interpret structured reports.

Nonetheless legitimate concerns exist. Structured reporting is difficult to implement both from organizational and technical perspectives. It significantly changes well-entrenched workflows, and could result in a more distracted radiologist. There is also a danger of losing the clarity of a concise prose report in a sea of repopulated data. These concerns highlight the need for a rigorous and continuous process of consensus-building and buy-in at an institutional level.

References

  1. Buntin MB, Jain SH, Blumenthal D. Health information technology: Laying the infrastructure for national health reform. Health Aff (Millwood). 2010;29:1214–1219.
  2. Weiss DL, Langlotz CP. Structured reporting: Patient care enhancement or productivity nightmare? Radiology. 2008;249:739–747.
  3. Bosmans JML, Peremans L, Menni M, et al. Structured reporting: If, why, when, how—and at what expense? Results of a focus group meeting of radiology professionals from eight countries. Insights Imaging. 2012;3:295–302.
  4. Kahn CE, Heilbrun ME, Applegate KE. From guidelines to practice: How reporting templates promote the use of radiology practice guidelines. J Am Coll Radiol. 2013;10:268–273.
  5. Schwartz LH, Panicek DM, Berk AR, et al. Improving communication of diagnostic radiology findings through structured reporting. Radiology. 2011;260:174–181.
  6. Al-Hawary MM, Francis IR, Chari ST, et al. Pancreatic ductal adenocarcinoma radiology reporting template: Consensus statement of the Society of Abdominal Radiology and the American Pancreatic Association. Radiology. 2014;270:248–260.
  7. Eisenberg RL, Bankier AA, Boiselle PM. Compliance with Fleischner Society guidelines for management of small lung nodules: A survey of 834 radiologists. Radiology. 2010;255:218–224.
  8. Kahn CE. Incorporating intelligence into structured radiology reports. Presented at the SPIE Medical Imaging March 19
  9. MeasuresCodes.cms.gov.
  10. Prevedello LM, Farkas C, Ip IK, et al. Large-scale automated assessment of radiologist adherence to the Physician Quality Reporting System for stroke. J Am Coll Radiol. 2012;9:414–420.
  11. Reiner BI, Knight N, Siegel EL. Radiology reporting, past, present, and future: The radiologist’s perspective. J Am Coll Radiol. 2007;4:313-319.
  12. Johnson AJ, Chen MYM, Swan JS, et al. Cohort study of structured reporting compared with conventional dictation. Radiology. 2009;253:74–80.
  13. Sistrom CL, Honeyman-Buck J. Free text versus structured format: Information transfer efficiency of radiology reports. AJR Am J Roentgenol. 2005;185:804–812.
  14. Hawkins CM, Hall S, Hardin J, et al. Prepopulated radiology report templates: A prospective analysis of error rate and turnaround time. J Digit Imaging. 2012;25:504–511.
  15. Langlotz CP. Structured radiology reporting: Are we there yet? Radiology. 2009;253:23–25.
  16. Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: The nature of patient care information system-related errors. J Am Med Inform Assoc. 2004;11:104–112.
  17. Gawande A. The checklist manifesto: How to get things right. New York: Metropolitan Books; 2010.
  18. Berg WA, D’Orsi CJ, Jackson VP, et al. Does training in the Breast Imaging Reporting and Data System (BI-RADS) improve biopsy recommendations or feature analysis agreement with experienced breast imagers at mammography? Radiology. 2002;224:871–880.
  19. Burnside ES, Sickles EA, Bassett LW, et al. The ACR BI-RADS experience: Learning from history. J Am Coll Radiol. 2009;6:851–860.
  20. Davenport MS, Khalatbari S, Liu PSC, et al. Repeatability of diagnostic features and scoring systems for hepatocellular carcinoma by using MR imaging. Radiology. 2014:131963.
  21. Head Injury Imaging Reporting and Data System (HI-RADS) - American College of Radiology. acr.org. http://www.acr.org/Quality-Safety/Resources/HIRADS
  22. Barentsz JO, Richenberg J, Clements R, et al. ESUR prostate MR guidelines 2012. Eur. Radiol. 2012;22:746–757.
  23. Roethke MC, Kuru TH, Schultze S, et al. Evaluation of the ESUR PI-RADS scoring system for multiparametric MRI of the prostate with targeted MR/TRUS fusion-guided biopsy at 3.0 Tesla. Eur. Radiol. 2014;24:344–352.
  24. Junker D, Schäfer G, Edlinger M, et al. Evaluation of the PI-RADS scoring system for classifying mpMRI findings in men with suspicion of prostate cancer. Biomed Res Int. 2013;2013:252939.
  25. Yu J-PJ, Kansagra AP, Naeger DM, et al. Template-driven computed tomography radiation dose reporting: Implementation of a radiology housestaff quality improvement project. Acad Radiol. 2013;20:769–772.
  26. Larson DB, Towbin AJ, Pryor RM, et al. Improving consistency in radiology reporting through the use of department-wide standardized structured reporting. Radiology. 2013;267:240–250.
  27. Hong Y, Zhang J, Heilbrun ME, et al. Analysis of RadLex coverage and term co-occurrence in radiology reporting templates. J Digit Imaging. 2012;25:56–62.
  28. RadLex.rsna.org. http://www.rsna.org/RadLex.aspx
  29. CT Facial Bones Template | RadReport.org. radreport.org. http://www.radreport.org/template/0000181
  30. CT Orbits Template | RadReport.org. radreport.org. http://www.radreport.org/template/0000020
  31. Genereaux BW, Cameron G, Langlotz C, et al. Conversion of Radiology Reporting Templates to a New HTML5-Based Standard. SIIM Health 2.0 Scientific Session 2014.
  32. Howe J. Crowdsourcing: Why the Power of the Crowd Is Driving the Future. New York: Crown Business; 2008.
  33. D’Orsi CJ, Kopans DB. The American College of Radiology’s mammography lexicon: Barking up the only tree. AJR Am J Roentgenol. 1994; 162:595.
Back To Top

About the Author

Justin A. Cramer, MD, Laura B. Eisenmenger, MD, Nicholas S. Pierson, MD, Harpreet S. Dhatt, MD, and Marta E. Heilbrun, MD

Justin A. Cramer, MD, Laura B. Eisenmenger, MD, Nicholas S. Pierson, MD, Harpreet S. Dhatt, MD, and Marta E. Heilbrun, MD

Dr. Cramer, Dr. Eisenmenger, Dr. Pierson, Dr. Dhatt, and Dr. Heilbrun are with the Department of Radiology, University of Utah Medical Center, Salt Lake City, UT.

Add A Comment

Comment

Allowed HTML: <b>, <i>, <u>, <a>

Comments



Copyright © Anderson Publishing 2014