Anales de la RANM

102 A N A L E S R A N M R E V I S T A F U N D A D A E N 1 8 7 9 INTEGRATED DIAGNOSIS: EARLY EXPERIENCE Pablo R. Ros An RANM · Año 2019 · número 136 (02) · páginas 99 a 102 Integrated Diagnosis affords a myriad of innovative ideas generated on a daily basis. A natural one is the establish- ment of a Molecular Diagnosis Program integrating the existing and already individually successful programs of molecular genetics, molecular pathology and molecular imaging. Another innovative idea is to integrate the ima- ge quantification efforts occurring in the three discipli- nes. The creation of hybrid disciplines such as Radiomics and Radiogenomics combine in a systematic fashion the core diagnostic specialties. Since the basis of ID and thus of a Diagnostic Institute is the current computational revolution it is natural to fo- cus on a COE dedicated to Computational Sciences pro- grams: 1) applications of AI to Diagnostics, 2) integration of diagnostic analysis of Radiology and Pathology images and reporting systems, and 3) development of analysis, query and autonomous learning systems to enable cross- disciplinary research and data pattern recognition (1). The reluctance to embrace a Diagnostic Institute as a ve- hicle for an ID rests primarily in the resistance to change by many physicians from radiologists, pathologists and referring physicians and sometimes hospital administra- tors. Fear to workload increases, commoditization of ra- diology and pathology reads and a thread to lose ma- nagement prerogatives by some referring physicians are frequently mentioned. We believe the integration of the core diagnostic special- ties of Radiology. Pathology and Genetics in the form of a Diagnostic Institute offers a great opportunity, recently made possible due to technology advances, mainly in com- putational sciences. The integration of diagnostic informa- tion results primarily on better patient care and brings va- lue lowering costs. In addition, affords unique collabora- tions in novel research and educational programs. 1. Lundstrom CF, Gilmore HL, Ros PR: Integrated Diagnosis: The Computational Revolution Catalyzing Cross-Disciplinary Practices in Radiology, Pathology and Genomics. Radiology 2017; 285:12-15 2. Murphey MD, Madewell JE, Olmsted WW, Ros PR, Neiman HL{ A History of Radiologic Pathology Co- rrelation at the Armed Forces Institute of Pathology and Its Evolution into the American Institute for Ra- diologic Pathology. Radiology , 2012; 262: 623-634 3. Sorace J, Aberle DR, Elimam D, Lawvere S, Tawfik O, Wallace WD. Integrating pathology and radiolo- gy disciplines: an emerging opportunity? B MC Med 2012; 10: 100. 4. Stump, E: Columbia’s Neurological Institute Celebra- tes its Centennial Neurology Today 2009; 9, 23: 1-4 5. Braunwald, E: Departments, Divisions and Centers in the Evolution of Medical Schools. AM J Med 2006; 119, 6: 457-462 6. Elrod JK, Fortenberry JL. Centers of excellence in healthcare institutions: what they are and how to as- semble them. BMC Health Serv Res 2017; 17(Suppl 1): 425. 7. Muroff LR: Implementing an effective organization and governance structure for a radiology practice. JACR 2004; 1,1: 26–32 8. Sanfilippo F, Burns KH, Borowitz MJ, Jackson JB, Hruban RH. The Johns Hopkins Department of Pathology Novel Organizational Model: a 25-year-old ongoing experiment. Acad Pathol 2018; 5. INNOVATION COE COMPUTATIONAL SCIENCES COE BARRIERS FOR INTEGRATED DIAGNOSIS CONCLUSION BIBLIOGRAFÍA DECLARACIÓN DE TRANSPARENCIA El autor/a de este artículo declara no tener ningún tipo de conflicto de intereses respecto a lo expuesto en la presente revisión. Si desea citar nuestro artículo: Ros-R. P. Integrated Diagnosis: Early Experience ANALES RANM [Internet]. Real Academia Nacional de Medicina de España; An RANM · Año 2019 · número 136 (02) · páginas 99– 102 DOI: 10.32440/ar.2019.136.02. rev01

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