Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division

Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Mo...
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Autor*in:	Naringrekar, Haresh V. [verfasserIn] Dave, Jaydev [verfasserIn] Akyol, Yakup [verfasserIn] Deshmukh, Sandeep P. [verfasserIn] Roth, Christopher G. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Productivity Relative value unit (RVU) Workflow Turnaround time (TAT)

Anmerkung:	© The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021

Übergeordnetes Werk:	Enthalten in: Abdominal radiology - [Boston, MA] : Springer US, 2016, 46(2021), 6 vom: 12. Jan., Seite 2908-2912
Übergeordnetes Werk:	volume:46 ; year:2021 ; number:6 ; day:12 ; month:01 ; pages:2908-2912

Links:	Volltext

DOI / URN:	10.1007/s00261-020-02942-4

Katalog-ID:	SPR044310161

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520			\|a Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times.
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allfields	10.1007/s00261-020-02942-4 doi (DE-627)SPR044310161 (SPR)s00261-020-02942-4-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE Naringrekar, Haresh V. verfasserin aut Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. Productivity (dpeaa)DE-He213 Relative value unit (RVU) (dpeaa)DE-He213 Workflow (dpeaa)DE-He213 Turnaround time (TAT) (dpeaa)DE-He213 Dave, Jaydev verfasserin aut Akyol, Yakup verfasserin aut Deshmukh, Sandeep P. verfasserin aut Roth, Christopher G. verfasserin aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 46(2021), 6 vom: 12. Jan., Seite 2908-2912 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912 https://dx.doi.org/10.1007/s00261-020-02942-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 6 12 01 2908-2912
spelling	10.1007/s00261-020-02942-4 doi (DE-627)SPR044310161 (SPR)s00261-020-02942-4-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE Naringrekar, Haresh V. verfasserin aut Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. Productivity (dpeaa)DE-He213 Relative value unit (RVU) (dpeaa)DE-He213 Workflow (dpeaa)DE-He213 Turnaround time (TAT) (dpeaa)DE-He213 Dave, Jaydev verfasserin aut Akyol, Yakup verfasserin aut Deshmukh, Sandeep P. verfasserin aut Roth, Christopher G. verfasserin aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 46(2021), 6 vom: 12. Jan., Seite 2908-2912 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912 https://dx.doi.org/10.1007/s00261-020-02942-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 6 12 01 2908-2912
allfields_unstemmed	10.1007/s00261-020-02942-4 doi (DE-627)SPR044310161 (SPR)s00261-020-02942-4-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE Naringrekar, Haresh V. verfasserin aut Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. Productivity (dpeaa)DE-He213 Relative value unit (RVU) (dpeaa)DE-He213 Workflow (dpeaa)DE-He213 Turnaround time (TAT) (dpeaa)DE-He213 Dave, Jaydev verfasserin aut Akyol, Yakup verfasserin aut Deshmukh, Sandeep P. verfasserin aut Roth, Christopher G. verfasserin aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 46(2021), 6 vom: 12. Jan., Seite 2908-2912 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912 https://dx.doi.org/10.1007/s00261-020-02942-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 6 12 01 2908-2912
allfieldsGer	10.1007/s00261-020-02942-4 doi (DE-627)SPR044310161 (SPR)s00261-020-02942-4-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE Naringrekar, Haresh V. verfasserin aut Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. Productivity (dpeaa)DE-He213 Relative value unit (RVU) (dpeaa)DE-He213 Workflow (dpeaa)DE-He213 Turnaround time (TAT) (dpeaa)DE-He213 Dave, Jaydev verfasserin aut Akyol, Yakup verfasserin aut Deshmukh, Sandeep P. verfasserin aut Roth, Christopher G. verfasserin aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 46(2021), 6 vom: 12. Jan., Seite 2908-2912 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912 https://dx.doi.org/10.1007/s00261-020-02942-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 6 12 01 2908-2912
allfieldsSound	10.1007/s00261-020-02942-4 doi (DE-627)SPR044310161 (SPR)s00261-020-02942-4-e DE-627 ger DE-627 rakwb eng 610 ASE 610 ASE Naringrekar, Haresh V. verfasserin aut Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. Productivity (dpeaa)DE-He213 Relative value unit (RVU) (dpeaa)DE-He213 Workflow (dpeaa)DE-He213 Turnaround time (TAT) (dpeaa)DE-He213 Dave, Jaydev verfasserin aut Akyol, Yakup verfasserin aut Deshmukh, Sandeep P. verfasserin aut Roth, Christopher G. verfasserin aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 46(2021), 6 vom: 12. Jan., Seite 2908-2912 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912 https://dx.doi.org/10.1007/s00261-020-02942-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 6 12 01 2908-2912
language	English
source	Enthalten in Abdominal radiology 46(2021), 6 vom: 12. Jan., Seite 2908-2912 volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912
sourceStr	Enthalten in Abdominal radiology 46(2021), 6 vom: 12. Jan., Seite 2908-2912 volume:46 year:2021 number:6 day:12 month:01 pages:2908-2912
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Productivity Relative value unit (RVU) Workflow Turnaround time (TAT)
dewey-raw	610
isfreeaccess_bool	false
container_title	Abdominal radiology
authorswithroles_txt_mv	Naringrekar, Haresh V. @@aut@@ Dave, Jaydev @@aut@@ Akyol, Yakup @@aut@@ Deshmukh, Sandeep P. @@aut@@ Roth, Christopher G. @@aut@@
publishDateDaySort_date	2021-01-12T00:00:00Z
hierarchy_top_id	847023133
dewey-sort	3610
id	SPR044310161
language_de	englisch
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Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. 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author	Naringrekar, Haresh V.
spellingShingle	Naringrekar, Haresh V. ddc 610 misc Productivity misc Relative value unit (RVU) misc Workflow misc Turnaround time (TAT) Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division
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topic_title	610 ASE Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division Productivity (dpeaa)DE-He213 Relative value unit (RVU) (dpeaa)DE-He213 Workflow (dpeaa)DE-He213 Turnaround time (TAT) (dpeaa)DE-He213
topic	ddc 610 misc Productivity misc Relative value unit (RVU) misc Workflow misc Turnaround time (TAT)
topic_unstemmed	ddc 610 misc Productivity misc Relative value unit (RVU) misc Workflow misc Turnaround time (TAT)
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title	Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division
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title_full	Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division
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author_browse	Naringrekar, Haresh V. Dave, Jaydev Akyol, Yakup Deshmukh, Sandeep P. Roth, Christopher G.
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title_sort	comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division
title_auth	Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division
abstract	Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021
abstractGer	Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021
abstract_unstemmed	Purpose To evaluate the productivity difference between teaching and non-teaching workflow models in an abdominal imaging division in an academic radiology department. Methods and materials RVU data were compiled for six faculty members from the abdominal imaging division over a six-month period. Modalities included ultrasound and CT of the abdomen and pelvis. The relative RVU productivity for faculty members by workflow was compared individually and the composite data for the workflow models were compared. The relative RVU productivity for each faculty member was compared individually and in aggregate to study the effect of the workflow models on RVUs using factorial ANOVA. Turnaround times (TAT) were compared for each attending under both models. TAT data were analyzed using paired t-tests with Bonferroni corrections for multiple comparisons. Results Daily RVU data from 387 instances were analyzed. Daily RVUs for faculty members ranged from 23.5 ± 2.3 (mean ± standard error) to 46.2 ± 2.4 with non-teaching and from 29.8 ± 2.2 to 54.4 ± 2.7 with teaching workflow, respectively. There was a significant main effect of the workflow model on RVU productivity (p < 0.05). A significant increase of 27.8% in RVUs was noted with teaching workflow (42.8 ± 0.9) relative to non-teaching workflow (33.5 ± 1.7; p < 0.05). Teaching workflow resulted in significantly higher view-final and complete-final TATs (593 ± 112 min, mean ± SE and 841 ± 96 min, mean ± SE, respectively) compared to the non-teaching workflow (385 ± 124 min). Conclusion Teaching workflow improves abdominal imaging productivity with an increase in report turnaround times. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021
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container_issue	6
title_short	Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division
url	https://dx.doi.org/10.1007/s00261-020-02942-4
remote_bool	true
author2	Dave, Jaydev Akyol, Yakup Deshmukh, Sandeep P. Roth, Christopher G.
author2Str	Dave, Jaydev Akyol, Yakup Deshmukh, Sandeep P. Roth, Christopher G.
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doi_str	10.1007/s00261-020-02942-4
up_date	2024-07-04T00:02:39.752Z
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Comparing the productivity of teaching and non-teaching workflow models in an academic abdominal imaging division

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