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Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
The transfer of information from floor to the MICU team is a very interesting process: outside of the patient record, the person performing the handoff is highly responsible in the appropriate transfer of information.
One of the challenges encountered within the project is the way in which we are categorizing agreement between groups. Previously, we created a set of categories based upon recurring themes present within the free-text provider responses, and created categories, such as “cardiac management” and “diabetes management.” Upon creating these categories, I would then group them based upon concordance. However, responses such as “bipap during the night” and “not giving her bipap” would both be coded under “respiratory management,” but those two responses would not show the providers being in concordance. Upon consulting with my mentors Dr. Vineet Arora and Dr. Juan Rojas, we decided that it would be more accurate to categorize concordance based upon the original answers, keeping the breadth of the original data intact.
As I continue to organize the data based on concordance, I have to modify my frame of thought and focus on appropriately representing the responses. There is no such thing as perfect data, and this project is no exception; in this case, not every provider was able to be reached for a response, which requires more nuance as I categorize the degree of concordance within the data and think of appropriate categories. I am very glad to learn the skill of appropriate data representation, as we want it to demonstrate both the potential lack or presence of clarity in handoffs, as well as the represented responding providers.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
The transfer of information from floor to the MICU team is a very interesting process: outside of the patient record, the person performing the handoff is highly responsible in the appropriate transfer of information.
One of the challenges encountered within the project is the way in which we are categorizing agreement between groups. Previously, we created a set of categories based upon recurring themes present within the free-text provider responses, and created categories, such as “cardiac management” and “diabetes management.” Upon creating these categories, I would then group them based upon concordance. However, responses such as “bipap during the night” and “not giving her bipap” would both be coded under “respiratory management,” but those two responses would not show the providers being in concordance. Upon consulting with my mentors Dr. Vineet Arora and Dr. Juan Rojas, we decided that it would be more accurate to categorize concordance based upon the original answers, keeping the breadth of the original data intact.
As I continue to organize the data based on concordance, I have to modify my frame of thought and focus on appropriately representing the responses. There is no such thing as perfect data, and this project is no exception; in this case, not every provider was able to be reached for a response, which requires more nuance as I categorize the degree of concordance within the data and think of appropriate categories. I am very glad to learn the skill of appropriate data representation, as we want it to demonstrate both the potential lack or presence of clarity in handoffs, as well as the represented responding providers.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
The transfer of information from floor to the MICU team is a very interesting process: outside of the patient record, the person performing the handoff is highly responsible in the appropriate transfer of information.
One of the challenges encountered within the project is the way in which we are categorizing agreement between groups. Previously, we created a set of categories based upon recurring themes present within the free-text provider responses, and created categories, such as “cardiac management” and “diabetes management.” Upon creating these categories, I would then group them based upon concordance. However, responses such as “bipap during the night” and “not giving her bipap” would both be coded under “respiratory management,” but those two responses would not show the providers being in concordance. Upon consulting with my mentors Dr. Vineet Arora and Dr. Juan Rojas, we decided that it would be more accurate to categorize concordance based upon the original answers, keeping the breadth of the original data intact.
As I continue to organize the data based on concordance, I have to modify my frame of thought and focus on appropriately representing the responses. There is no such thing as perfect data, and this project is no exception; in this case, not every provider was able to be reached for a response, which requires more nuance as I categorize the degree of concordance within the data and think of appropriate categories. I am very glad to learn the skill of appropriate data representation, as we want it to demonstrate both the potential lack or presence of clarity in handoffs, as well as the represented responding providers.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.