Difference between revisions of "Journal:Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology"
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==Background== | ==Background== | ||
Despite [[Digital radiography|digital imaging]], widespread adoption of [[electronic health record]]s (EHRs), and advances in precision medicine tools, [[Medical diagnosis|diagnosis]] often remains a fragmented and frustrating process for clinicians and patients. Data are still gathered and presented asynchronously, and EHRs do little to organize and synthesize [[information]]. Although team practice, such as tumor boards, is increasing, routine physician interaction is limited by clinical [[workflow]], high volumes, and information technology (IT) boundaries. Despite an abundance of relevant diagnostic data, diagnoses may be incorrect, delayed, or never made. Allegations of diagnostic errors account for 28% of malpractice cases in the United States. [1] Experts estimate a diagnostic error rate of 10% to 15%, with 40,000–80,000 preventable deaths each year. [2, 3] As physicians and diagnosticians, it is our responsibility to minimize these errors. Integrative diagnostics (ID) has been proposed as one means to reduce diagnostic errors. | |||
==Method== | |||
This paper is designed to address ID from the perspectives of radiology and our sister diagnostic specialty, [[pathology]]. The paper was developed in response to a request for proposal from the International Society of Strategic Studies in Radiology (IS3R) to its members for an annual white paper to foster its mission “to actively shape the future of [[medical imaging]] and image-guided therapies by leveraging the knowledge and influence of world leaders in these disciplines and related industries.” Proposals from self-organized writing groups were reviewed by the IS3R Publications Committee, with the final selection approved for drafting by the IS3R Executive Committee. Our writing group was designed to include departmental and institutional leaders in radiology and pathology who have interest and experience in ID. After preliminary approval by the Publications Committee, the draft paper was posted to the entire IS3R membership for comments, which were incorporated into this final document. This paper was approved for internal dissemination and publication by the IS3R Executive Committee. | |||
===What is ID?=== | |||
More than seven billion diagnostic examinations are performed each year in the United States, influencing 70% of health care decisions. [4] Although [[Medical test|diagnostic tests]] differ in personnel, infrastructure, and technology, they have a shared commonality: providing data for clinical diagnosis. [5] ID has been proposed to better manage, organize, and present diagnostic data and bridge intellectual silos. ID represents a convergence of imaging, pathology, and clinical laboratory medicine, plus advanced levels of IT. [6] In this framework, integrated (versus isolated) practices plus [[Clinical decision support system|clinical decision support (CDS) tools]] drive appropriate care. Data from the entire diagnostic arsenal are aggregated to enhance insights, and EHRs present information in a consumable way to facilitate collaborative decision making and accurate clinical diagnosis. ID uses [[medical informatics]] (in which data are data, regardless of their nature or source) to organize and analyze vast, disparate diagnostic data sets to achieve timely and accurate diagnosis, precise therapeutics, accurate assessment of prognosis, and maintenance of population health. [7] | |||
Revision as of 20:51, 3 April 2023
| Full article title | Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology |
|---|---|
| Journal | Insights into Imaging |
| Author(s) | Beauchamp, Norman J.; Bryan R. Nick; Bui, Marilyn M.; Krestin, Gabriel P.; McGinty, Geraldine B.; Meltzer, Carolyn C.; Neumaier, Michael |
| Author affiliation(s) | Michigan State University, University of Pennsylvania, Moffitt Cancer Center and Research Institute, University Medical Center Rotterdam, Weill Cornell Medicine, University of Southern California, University of Heidelberg |
| Primary contact | Email: robert dot bryan at pennmedicine dot upenn dot edu |
| Year published | 2022 |
| Volume and issue | 14 |
| Article # | 54 |
| DOI | 10.1186/s13244-023-01379-9 |
| ISSN | 1869-4101 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://insightsimaging.springeropen.com/articles/10.1186/s13244-023-01379-9 |
| Download | https://insightsimaging.springeropen.com/counter/pdf/10.1186/s13244-023-01379-9.pdf (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Enormous recent progress in diagnostic testing can enable more accurate diagnosis and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the “silo” of each diagnostic discipline, diagnostic data are fragmented, and the electronic health record (EHR) does little to synthesize new and existing data into usable information. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the EHR, are aggregated and contextualized by informatics tools to direct clinical action. Integrative diagnostics has the potential to identify correct therapies more quickly, modify treatment when appropriate, and terminate treatment when not effective, ultimately decreasing morbidity, improving outcomes, and avoiding unnecessary costs. Radiology, laboratory medicine, and pathology already play major roles in medical diagnostics. Our specialties can increase the value of our examinations by taking a holistic approach to their selection, interpretation, and application to the patient’s care pathway. We have the means and rationale to incorporate integrative diagnostics into our specialties and guide its implementation in clinical practice.
The following overall points can be made about this research:
- Although an overall boon to clinical diagnosis, increasingly voluminous, diverse, and fragmented diagnostic data can overwhelm physicians and frustrate patients.
- Data are gathered and processed within “silos” of the diagnostic disciplines, including radiology and pathology. The EHR does little to intelligently organize and synthesize these disparate data to facilitate diagnosis.
- Integrative diagnostics envisions a process in which data from the entire arsenal of in vivo and in vitro diagnostics, together with clinical data from the EHR, are aggregated and contextualized to enhance diagnosis and direct clinical action.
Keywords: diagnostics, integrative diagnostics, radiology, pathology, informatics
Graphic abstract:
Background
Despite digital imaging, widespread adoption of electronic health records (EHRs), and advances in precision medicine tools, diagnosis often remains a fragmented and frustrating process for clinicians and patients. Data are still gathered and presented asynchronously, and EHRs do little to organize and synthesize information. Although team practice, such as tumor boards, is increasing, routine physician interaction is limited by clinical workflow, high volumes, and information technology (IT) boundaries. Despite an abundance of relevant diagnostic data, diagnoses may be incorrect, delayed, or never made. Allegations of diagnostic errors account for 28% of malpractice cases in the United States. [1] Experts estimate a diagnostic error rate of 10% to 15%, with 40,000–80,000 preventable deaths each year. [2, 3] As physicians and diagnosticians, it is our responsibility to minimize these errors. Integrative diagnostics (ID) has been proposed as one means to reduce diagnostic errors.
Method
This paper is designed to address ID from the perspectives of radiology and our sister diagnostic specialty, pathology. The paper was developed in response to a request for proposal from the International Society of Strategic Studies in Radiology (IS3R) to its members for an annual white paper to foster its mission “to actively shape the future of medical imaging and image-guided therapies by leveraging the knowledge and influence of world leaders in these disciplines and related industries.” Proposals from self-organized writing groups were reviewed by the IS3R Publications Committee, with the final selection approved for drafting by the IS3R Executive Committee. Our writing group was designed to include departmental and institutional leaders in radiology and pathology who have interest and experience in ID. After preliminary approval by the Publications Committee, the draft paper was posted to the entire IS3R membership for comments, which were incorporated into this final document. This paper was approved for internal dissemination and publication by the IS3R Executive Committee.
What is ID?
More than seven billion diagnostic examinations are performed each year in the United States, influencing 70% of health care decisions. [4] Although diagnostic tests differ in personnel, infrastructure, and technology, they have a shared commonality: providing data for clinical diagnosis. [5] ID has been proposed to better manage, organize, and present diagnostic data and bridge intellectual silos. ID represents a convergence of imaging, pathology, and clinical laboratory medicine, plus advanced levels of IT. [6] In this framework, integrated (versus isolated) practices plus clinical decision support (CDS) tools drive appropriate care. Data from the entire diagnostic arsenal are aggregated to enhance insights, and EHRs present information in a consumable way to facilitate collaborative decision making and accurate clinical diagnosis. ID uses medical informatics (in which data are data, regardless of their nature or source) to organize and analyze vast, disparate diagnostic data sets to achieve timely and accurate diagnosis, precise therapeutics, accurate assessment of prognosis, and maintenance of population health. [7]
Notes
This presentation is faithful to the original, with only a few minor changes to presentation, grammar, and punctuation. In some cases important information was missing from the references, and that information was added.
