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Scheduling patterns: Time for a change?
Bob Wachter, MD, created buzz in March 2016 when, at the SHM annual meeting in San Diego, he displayed a slide titled “What did we get wrong?” The slide contained the copy, “Hospitalist shifts run 7 a.m.-7 p.m.; 10 a.m.-10 p.m. 7on/7off” circled in bold red.
Over the last several years, thought leaders in the hospital medicine field have expressed concern that this one-size-fits-all schedule model is a threat to the well-being of many physicians and, by extension, the sustainability of their hospital medicine groups. Despite this, the 2016 State of Hospital Medicine Report reveals relatively little change in the way hospital medicine groups schedule their physicians.
Night shifts echo this trend. There is an even greater number of groups utilizing the 12- to 13.9-hour shift length (79%), which has also varied less at just approximately 5% in either direction over the last two surveys. It is likely very hard to be creative with the shift length for your night physicians when the group is structured predominately around a 12-hour day position.
The 12-hour shift scheduled in long blocks is straightforward to employ for the scheduler, limits hand offs of care, and maximizes number of days off. So, why are Wachter et al. calling for change? Seven day stretches off may seem attractive when you are just starting out, but, as physicians mature, the very long day competes with family time that cannot be made up on weekday mornings when others are at school and work. Furthermore, the very long hours for 7 days straight lead to burn out and eventually retention issues as well. Some argue that this design promotes disengagement. It sets the expectation that, during “off” weeks, physicians might be unavailable for email responses, committee meetings, or participation in quality improvement initiatives, which disrupts integration into the larger hospital community and perhaps even our own career advancement.
Some groups are trying to address these concerns with innovative approaches to block scheduling. While the hallmark hospital medicine schedule of 7on/7off blocks remains the predominant model – 38.1% of all groups – this represents a drop of approximately 15%, compared with the prior survey. A new large contingent of groups entering the survey this year utilize a Monday-Friday model with rotating moonlighter/weekend coverage. This lifestyle and family-friendly model predominates in the Midwest. It is also found more in smaller groups, which may employ this model to keep the most system-knowledgeable worker around during high volume times, as well as to preserve the well-being and retention of their limited physician work force.
Of note, reconfiguring the 7on/7off model does not necessarily translate into more time off. The median number of shifts per year is also relatively stable at 182 which is the exact number of shifts per year in a strict 7on/7off schedule. This number does not vary by region of the country, group size, or teaching status. Some might argue that working 182 annual shifts is ideal, giving hospitalists a “vacation” every other week. However, this line of thought does not take into account the very long workdays, nor the 52 weekend days spent in the hospital – far more than most specialty peers who serve fewer weekend calls often with more limited in-house hours. In addition, one might argue that defining ourselves as available only during our 182 clinical “on” days is not in our own best interest, as it is the important nonclinical quality and committee service activities that are likely to lead to professional recognition and advancement.
Our hospital medicine group has deviated from this scheduling mainstay and requires only 160 shifts per year. We have set this number based on removal of the number of shifts equivalent to the vacation hours received by our medical group peers. The model poses a challenge in terms of matching our productivity up to benchmarks when talking to system leaders. This challenge pales in comparison to the increased buy-in from our physicians, as they feel equitable vacation time signifies respect from the medical group leadership.
In addition, our group has had success in being flexible around the number of days worked in a continuity stretch. We utilize everything from a 3-day block over holidays to a 7-day block. In general, we allow physicians to select their desired block length. The scheduler then works to accommodate that stretch as much as is feasible. The upfront work in this system is significant, but the downstream effect is decreased turnover costs. Even our own entrenched standard of 7on/7off schedules for house staff services (designed to protect continuity for the learner) have been the target of change. A pilot of alternating 4 and 5 day runs in a 4-week stretch has been implemented over the last few months. The number of days the residents are exposed to a given attending is the same in this model, but there is one additional switch day. The additional switch day puts the residents at risk of managing a change in care plan related to change in attending, but this was mitigated by paring attendings with very similar teaching and patient management styles. For our group, the extra administrative effort needed to work around the 7on/7off model has always paid off in terms of provider satisfaction and retention.
On the other hand, although I lead a large academic group, we have not yet developed flexibility around the shift length. Only one of the 29 roles our providers fill each 24-hour period is not a 12-hour shift. Over the years, I have tried to offer alternate models with shorter shifts to improve flow, reduce burn out, and increase family time. No matter how eloquent the reasoning, the response from the group was always the same: a resounding “no.” Most providers felt that they would wind up with a very similar work load and not actually leave the hospital earlier. Other reasons included not wanting to come in more days per month and concerns about increased handoffs/cross coverage.
There is some reason to think change may actually come. For one, burnout is high and may lead physicians to try a new model even with fear of the unknown. Our practice may be reconsidering this one-size-fits-all shift length in the very near future as an increasing percentage of candidates seeking to join our group express a strong interest in finding more accommodating hours.
Overall, I am hopeful that, in the coming years, my hospital medicine group, as well as many others, will heed the thoughts expressed by Dr. Wachter. Finding the flexibility to break out of these rigid scheduling models will be a first step in promoting both physician and system well being.
Dr. Eisenstock, MD, FHM, is clinical chief, division of hospital medicine, at the University of Massachusetts Memorial Health Care, Worcester.
Bob Wachter, MD, created buzz in March 2016 when, at the SHM annual meeting in San Diego, he displayed a slide titled “What did we get wrong?” The slide contained the copy, “Hospitalist shifts run 7 a.m.-7 p.m.; 10 a.m.-10 p.m. 7on/7off” circled in bold red.
Over the last several years, thought leaders in the hospital medicine field have expressed concern that this one-size-fits-all schedule model is a threat to the well-being of many physicians and, by extension, the sustainability of their hospital medicine groups. Despite this, the 2016 State of Hospital Medicine Report reveals relatively little change in the way hospital medicine groups schedule their physicians.
Night shifts echo this trend. There is an even greater number of groups utilizing the 12- to 13.9-hour shift length (79%), which has also varied less at just approximately 5% in either direction over the last two surveys. It is likely very hard to be creative with the shift length for your night physicians when the group is structured predominately around a 12-hour day position.
The 12-hour shift scheduled in long blocks is straightforward to employ for the scheduler, limits hand offs of care, and maximizes number of days off. So, why are Wachter et al. calling for change? Seven day stretches off may seem attractive when you are just starting out, but, as physicians mature, the very long day competes with family time that cannot be made up on weekday mornings when others are at school and work. Furthermore, the very long hours for 7 days straight lead to burn out and eventually retention issues as well. Some argue that this design promotes disengagement. It sets the expectation that, during “off” weeks, physicians might be unavailable for email responses, committee meetings, or participation in quality improvement initiatives, which disrupts integration into the larger hospital community and perhaps even our own career advancement.
Some groups are trying to address these concerns with innovative approaches to block scheduling. While the hallmark hospital medicine schedule of 7on/7off blocks remains the predominant model – 38.1% of all groups – this represents a drop of approximately 15%, compared with the prior survey. A new large contingent of groups entering the survey this year utilize a Monday-Friday model with rotating moonlighter/weekend coverage. This lifestyle and family-friendly model predominates in the Midwest. It is also found more in smaller groups, which may employ this model to keep the most system-knowledgeable worker around during high volume times, as well as to preserve the well-being and retention of their limited physician work force.
Of note, reconfiguring the 7on/7off model does not necessarily translate into more time off. The median number of shifts per year is also relatively stable at 182 which is the exact number of shifts per year in a strict 7on/7off schedule. This number does not vary by region of the country, group size, or teaching status. Some might argue that working 182 annual shifts is ideal, giving hospitalists a “vacation” every other week. However, this line of thought does not take into account the very long workdays, nor the 52 weekend days spent in the hospital – far more than most specialty peers who serve fewer weekend calls often with more limited in-house hours. In addition, one might argue that defining ourselves as available only during our 182 clinical “on” days is not in our own best interest, as it is the important nonclinical quality and committee service activities that are likely to lead to professional recognition and advancement.
Our hospital medicine group has deviated from this scheduling mainstay and requires only 160 shifts per year. We have set this number based on removal of the number of shifts equivalent to the vacation hours received by our medical group peers. The model poses a challenge in terms of matching our productivity up to benchmarks when talking to system leaders. This challenge pales in comparison to the increased buy-in from our physicians, as they feel equitable vacation time signifies respect from the medical group leadership.
In addition, our group has had success in being flexible around the number of days worked in a continuity stretch. We utilize everything from a 3-day block over holidays to a 7-day block. In general, we allow physicians to select their desired block length. The scheduler then works to accommodate that stretch as much as is feasible. The upfront work in this system is significant, but the downstream effect is decreased turnover costs. Even our own entrenched standard of 7on/7off schedules for house staff services (designed to protect continuity for the learner) have been the target of change. A pilot of alternating 4 and 5 day runs in a 4-week stretch has been implemented over the last few months. The number of days the residents are exposed to a given attending is the same in this model, but there is one additional switch day. The additional switch day puts the residents at risk of managing a change in care plan related to change in attending, but this was mitigated by paring attendings with very similar teaching and patient management styles. For our group, the extra administrative effort needed to work around the 7on/7off model has always paid off in terms of provider satisfaction and retention.
On the other hand, although I lead a large academic group, we have not yet developed flexibility around the shift length. Only one of the 29 roles our providers fill each 24-hour period is not a 12-hour shift. Over the years, I have tried to offer alternate models with shorter shifts to improve flow, reduce burn out, and increase family time. No matter how eloquent the reasoning, the response from the group was always the same: a resounding “no.” Most providers felt that they would wind up with a very similar work load and not actually leave the hospital earlier. Other reasons included not wanting to come in more days per month and concerns about increased handoffs/cross coverage.
There is some reason to think change may actually come. For one, burnout is high and may lead physicians to try a new model even with fear of the unknown. Our practice may be reconsidering this one-size-fits-all shift length in the very near future as an increasing percentage of candidates seeking to join our group express a strong interest in finding more accommodating hours.
Overall, I am hopeful that, in the coming years, my hospital medicine group, as well as many others, will heed the thoughts expressed by Dr. Wachter. Finding the flexibility to break out of these rigid scheduling models will be a first step in promoting both physician and system well being.
Dr. Eisenstock, MD, FHM, is clinical chief, division of hospital medicine, at the University of Massachusetts Memorial Health Care, Worcester.
Bob Wachter, MD, created buzz in March 2016 when, at the SHM annual meeting in San Diego, he displayed a slide titled “What did we get wrong?” The slide contained the copy, “Hospitalist shifts run 7 a.m.-7 p.m.; 10 a.m.-10 p.m. 7on/7off” circled in bold red.
Over the last several years, thought leaders in the hospital medicine field have expressed concern that this one-size-fits-all schedule model is a threat to the well-being of many physicians and, by extension, the sustainability of their hospital medicine groups. Despite this, the 2016 State of Hospital Medicine Report reveals relatively little change in the way hospital medicine groups schedule their physicians.
Night shifts echo this trend. There is an even greater number of groups utilizing the 12- to 13.9-hour shift length (79%), which has also varied less at just approximately 5% in either direction over the last two surveys. It is likely very hard to be creative with the shift length for your night physicians when the group is structured predominately around a 12-hour day position.
The 12-hour shift scheduled in long blocks is straightforward to employ for the scheduler, limits hand offs of care, and maximizes number of days off. So, why are Wachter et al. calling for change? Seven day stretches off may seem attractive when you are just starting out, but, as physicians mature, the very long day competes with family time that cannot be made up on weekday mornings when others are at school and work. Furthermore, the very long hours for 7 days straight lead to burn out and eventually retention issues as well. Some argue that this design promotes disengagement. It sets the expectation that, during “off” weeks, physicians might be unavailable for email responses, committee meetings, or participation in quality improvement initiatives, which disrupts integration into the larger hospital community and perhaps even our own career advancement.
Some groups are trying to address these concerns with innovative approaches to block scheduling. While the hallmark hospital medicine schedule of 7on/7off blocks remains the predominant model – 38.1% of all groups – this represents a drop of approximately 15%, compared with the prior survey. A new large contingent of groups entering the survey this year utilize a Monday-Friday model with rotating moonlighter/weekend coverage. This lifestyle and family-friendly model predominates in the Midwest. It is also found more in smaller groups, which may employ this model to keep the most system-knowledgeable worker around during high volume times, as well as to preserve the well-being and retention of their limited physician work force.
Of note, reconfiguring the 7on/7off model does not necessarily translate into more time off. The median number of shifts per year is also relatively stable at 182 which is the exact number of shifts per year in a strict 7on/7off schedule. This number does not vary by region of the country, group size, or teaching status. Some might argue that working 182 annual shifts is ideal, giving hospitalists a “vacation” every other week. However, this line of thought does not take into account the very long workdays, nor the 52 weekend days spent in the hospital – far more than most specialty peers who serve fewer weekend calls often with more limited in-house hours. In addition, one might argue that defining ourselves as available only during our 182 clinical “on” days is not in our own best interest, as it is the important nonclinical quality and committee service activities that are likely to lead to professional recognition and advancement.
Our hospital medicine group has deviated from this scheduling mainstay and requires only 160 shifts per year. We have set this number based on removal of the number of shifts equivalent to the vacation hours received by our medical group peers. The model poses a challenge in terms of matching our productivity up to benchmarks when talking to system leaders. This challenge pales in comparison to the increased buy-in from our physicians, as they feel equitable vacation time signifies respect from the medical group leadership.
In addition, our group has had success in being flexible around the number of days worked in a continuity stretch. We utilize everything from a 3-day block over holidays to a 7-day block. In general, we allow physicians to select their desired block length. The scheduler then works to accommodate that stretch as much as is feasible. The upfront work in this system is significant, but the downstream effect is decreased turnover costs. Even our own entrenched standard of 7on/7off schedules for house staff services (designed to protect continuity for the learner) have been the target of change. A pilot of alternating 4 and 5 day runs in a 4-week stretch has been implemented over the last few months. The number of days the residents are exposed to a given attending is the same in this model, but there is one additional switch day. The additional switch day puts the residents at risk of managing a change in care plan related to change in attending, but this was mitigated by paring attendings with very similar teaching and patient management styles. For our group, the extra administrative effort needed to work around the 7on/7off model has always paid off in terms of provider satisfaction and retention.
On the other hand, although I lead a large academic group, we have not yet developed flexibility around the shift length. Only one of the 29 roles our providers fill each 24-hour period is not a 12-hour shift. Over the years, I have tried to offer alternate models with shorter shifts to improve flow, reduce burn out, and increase family time. No matter how eloquent the reasoning, the response from the group was always the same: a resounding “no.” Most providers felt that they would wind up with a very similar work load and not actually leave the hospital earlier. Other reasons included not wanting to come in more days per month and concerns about increased handoffs/cross coverage.
There is some reason to think change may actually come. For one, burnout is high and may lead physicians to try a new model even with fear of the unknown. Our practice may be reconsidering this one-size-fits-all shift length in the very near future as an increasing percentage of candidates seeking to join our group express a strong interest in finding more accommodating hours.
Overall, I am hopeful that, in the coming years, my hospital medicine group, as well as many others, will heed the thoughts expressed by Dr. Wachter. Finding the flexibility to break out of these rigid scheduling models will be a first step in promoting both physician and system well being.
Dr. Eisenstock, MD, FHM, is clinical chief, division of hospital medicine, at the University of Massachusetts Memorial Health Care, Worcester.
A prescription for heart failure success: Change the name
PARIS – Does heart failure’s name doom any progress against the disease?
That was the provocative premise advanced by Lynne Warner Stevenson, MD, who suggested that efforts to prevent, diagnose, and treat the disease would go better if it could only jettison that unfortunate word “failure,” its hard-wired albatross.
Dr. Stevenson offered several potentially superior alternatives, including cardiac insufficiency, heart dysfunction, and her favorite, cardiomyopathy.
“Is heart failure still the best diagnosis” for the entire spectrum of disease that most patients progress through ,including the many patients in earlier stages of the disease who do not have a truly failing heart? “Perhaps cardiomyopathy is the condition and heart failure is the transition,” she proposed.
To Dr. Stevenson, it’s more than just semantics.
“Words are hugely powerful,” she explained in an interview following her talk. “I think patients do not want to be seen as having heart failure. They don’t want to think of themselves as having heart failure. I think it can make them delay getting care, and it makes them ignore the disease. I worry about that a lot. I also worry that patients don’t provide support to each other that they could. Patients tend to hide that they have heart failure. We need to come up with a term that does not make patients ashamed of their disease.”
Part of the problem, Dr. Stevenson said, is that the name heart failure can be very misleading depending on the stage of the disease that patients have. Patients with stage B (presymptomatic) disease and those with mild stage C disease “don’t see themselves as having heart failure,” as having a heart that has failed them. “We need to be able to convince these patients that they have a disease that we need to treat carefully and aggressively.”
Additionally, labeling tens of millions of people as having stage A heart failure, which is presymptomatic and occurs before the heart shows any sign of damage or dysfunction, is also counterproductive, maintained Dr. Stevenson, professor of medicine at Harvard Medical School and director of the Cardiomyopathy and Heart Failure Program at Brigham and Women’s Hospital in Boston.
“So many people are at risk of developing heart failure,” she noted, including patients with hypertension, diabetes, or coronary artery disease. To label them all as already also having heart failure at that stage “tends to make them ignore the disease that we are trying to get them to pay attention to. Telling patients they have the disease that we are trying to prevent doesn’t help.”
Calling the whole range of the disease heart failure also confuses patients and others. “Patients ask me, ‘How can I have heart failure without any symptoms?’ ‘My ejection fraction improved to almost normal; do I still have heart failure?’ and ‘I don’t understand how my heart muscle is strong but my heart is failing,’ ” she said
For Dr. Stevenson, perhaps the biggest problem is the stigma of failure and the way that word ties a huge weight to the disease that prompts patients and caregivers alike to relegate it to a hidden and neglected place.
“It’s failure. Who is proud to have heart failure? Where are the marches for heart failure? Where are the celebrity champions for heart failure? We have celebrities who are happy to admit that they have Parkinson’s disease, ALS [amyotrophic lateral sclerosis], drug addiction, and even erectile dysfunction, but no one wants to say they have heart failure. We can’t get any traction behind heart failure. It doesn’t sound very inspiring,” an issue that even percolates down to dissuading clinicians from pursuing a career in heart failure care. Young people do not aspire to go into failure, she said.
“We need to call it something else.”
[email protected]
On Twitter @mitchelzoler
PARIS – Does heart failure’s name doom any progress against the disease?
That was the provocative premise advanced by Lynne Warner Stevenson, MD, who suggested that efforts to prevent, diagnose, and treat the disease would go better if it could only jettison that unfortunate word “failure,” its hard-wired albatross.
Dr. Stevenson offered several potentially superior alternatives, including cardiac insufficiency, heart dysfunction, and her favorite, cardiomyopathy.
“Is heart failure still the best diagnosis” for the entire spectrum of disease that most patients progress through ,including the many patients in earlier stages of the disease who do not have a truly failing heart? “Perhaps cardiomyopathy is the condition and heart failure is the transition,” she proposed.
To Dr. Stevenson, it’s more than just semantics.
“Words are hugely powerful,” she explained in an interview following her talk. “I think patients do not want to be seen as having heart failure. They don’t want to think of themselves as having heart failure. I think it can make them delay getting care, and it makes them ignore the disease. I worry about that a lot. I also worry that patients don’t provide support to each other that they could. Patients tend to hide that they have heart failure. We need to come up with a term that does not make patients ashamed of their disease.”
Part of the problem, Dr. Stevenson said, is that the name heart failure can be very misleading depending on the stage of the disease that patients have. Patients with stage B (presymptomatic) disease and those with mild stage C disease “don’t see themselves as having heart failure,” as having a heart that has failed them. “We need to be able to convince these patients that they have a disease that we need to treat carefully and aggressively.”
Additionally, labeling tens of millions of people as having stage A heart failure, which is presymptomatic and occurs before the heart shows any sign of damage or dysfunction, is also counterproductive, maintained Dr. Stevenson, professor of medicine at Harvard Medical School and director of the Cardiomyopathy and Heart Failure Program at Brigham and Women’s Hospital in Boston.
“So many people are at risk of developing heart failure,” she noted, including patients with hypertension, diabetes, or coronary artery disease. To label them all as already also having heart failure at that stage “tends to make them ignore the disease that we are trying to get them to pay attention to. Telling patients they have the disease that we are trying to prevent doesn’t help.”
Calling the whole range of the disease heart failure also confuses patients and others. “Patients ask me, ‘How can I have heart failure without any symptoms?’ ‘My ejection fraction improved to almost normal; do I still have heart failure?’ and ‘I don’t understand how my heart muscle is strong but my heart is failing,’ ” she said
For Dr. Stevenson, perhaps the biggest problem is the stigma of failure and the way that word ties a huge weight to the disease that prompts patients and caregivers alike to relegate it to a hidden and neglected place.
“It’s failure. Who is proud to have heart failure? Where are the marches for heart failure? Where are the celebrity champions for heart failure? We have celebrities who are happy to admit that they have Parkinson’s disease, ALS [amyotrophic lateral sclerosis], drug addiction, and even erectile dysfunction, but no one wants to say they have heart failure. We can’t get any traction behind heart failure. It doesn’t sound very inspiring,” an issue that even percolates down to dissuading clinicians from pursuing a career in heart failure care. Young people do not aspire to go into failure, she said.
“We need to call it something else.”
[email protected]
On Twitter @mitchelzoler
PARIS – Does heart failure’s name doom any progress against the disease?
That was the provocative premise advanced by Lynne Warner Stevenson, MD, who suggested that efforts to prevent, diagnose, and treat the disease would go better if it could only jettison that unfortunate word “failure,” its hard-wired albatross.
Dr. Stevenson offered several potentially superior alternatives, including cardiac insufficiency, heart dysfunction, and her favorite, cardiomyopathy.
“Is heart failure still the best diagnosis” for the entire spectrum of disease that most patients progress through ,including the many patients in earlier stages of the disease who do not have a truly failing heart? “Perhaps cardiomyopathy is the condition and heart failure is the transition,” she proposed.
To Dr. Stevenson, it’s more than just semantics.
“Words are hugely powerful,” she explained in an interview following her talk. “I think patients do not want to be seen as having heart failure. They don’t want to think of themselves as having heart failure. I think it can make them delay getting care, and it makes them ignore the disease. I worry about that a lot. I also worry that patients don’t provide support to each other that they could. Patients tend to hide that they have heart failure. We need to come up with a term that does not make patients ashamed of their disease.”
Part of the problem, Dr. Stevenson said, is that the name heart failure can be very misleading depending on the stage of the disease that patients have. Patients with stage B (presymptomatic) disease and those with mild stage C disease “don’t see themselves as having heart failure,” as having a heart that has failed them. “We need to be able to convince these patients that they have a disease that we need to treat carefully and aggressively.”
Additionally, labeling tens of millions of people as having stage A heart failure, which is presymptomatic and occurs before the heart shows any sign of damage or dysfunction, is also counterproductive, maintained Dr. Stevenson, professor of medicine at Harvard Medical School and director of the Cardiomyopathy and Heart Failure Program at Brigham and Women’s Hospital in Boston.
“So many people are at risk of developing heart failure,” she noted, including patients with hypertension, diabetes, or coronary artery disease. To label them all as already also having heart failure at that stage “tends to make them ignore the disease that we are trying to get them to pay attention to. Telling patients they have the disease that we are trying to prevent doesn’t help.”
Calling the whole range of the disease heart failure also confuses patients and others. “Patients ask me, ‘How can I have heart failure without any symptoms?’ ‘My ejection fraction improved to almost normal; do I still have heart failure?’ and ‘I don’t understand how my heart muscle is strong but my heart is failing,’ ” she said
For Dr. Stevenson, perhaps the biggest problem is the stigma of failure and the way that word ties a huge weight to the disease that prompts patients and caregivers alike to relegate it to a hidden and neglected place.
“It’s failure. Who is proud to have heart failure? Where are the marches for heart failure? Where are the celebrity champions for heart failure? We have celebrities who are happy to admit that they have Parkinson’s disease, ALS [amyotrophic lateral sclerosis], drug addiction, and even erectile dysfunction, but no one wants to say they have heart failure. We can’t get any traction behind heart failure. It doesn’t sound very inspiring,” an issue that even percolates down to dissuading clinicians from pursuing a career in heart failure care. Young people do not aspire to go into failure, she said.
“We need to call it something else.”
[email protected]
On Twitter @mitchelzoler
EXPERT ANALYSIS FROM HEART FAILURE 2017
Short Takes
Community-based palliative care reduces emergency department visits
By Bryan J. Huang, MD, FHM
Retrospective cohort study showed that patients receiving community-based palliative care were less likely to seek ED care. The reduction was greater for older patients and for patients living in areas of higher socioeconomic status.
Time to intubation after cardiac arrest: Earlier may not be better
By Sarah Horman, MD
In a retrospective, observational, cohort study of 86,628 adults with in-hospital cardiac arrest, intubation during the first 15 minutes was associated with decreased survival, compared with no intubation.
Reference: Andersen, LW, Granfeldt, A, Callaway, CW, et al. Association between Tracheal intubation during adult in-hospital cardiac arrest and survival. JAMA. 2017;317(5):494-506.
DNR orders often not transferred to ED from outside care facilities
By Leslie M. Martin, MD
Prospective chart review of patients presenting from extended care facilities to an urban trauma center found hospital staff did a poor job of noting do not resuscitate preferences, and extended care facilities were inconsistent in providing their patients’ DNR forms.
Reference: McQuown CM, Frey JA, Amireh A, Chaudhary A. Transfer of do not resuscitate orders to the emergency department from extended care facilities. Am J Emerg Med. Published on 4 Feb 2017. doi: 10.1016/j.ajem.2017.02.007.
A quasi-experimental, before-after trial examining the impact of an emergency department mechanical ventilator protocol on clinical outcomes and lung-protective ventilation in acute respiratory distress syndrome
By William James Frederick III, MD, PhD
A single center, quasi-experimental, before-after trial shows a lung-protective mechanical ventilation protocol for emergency department and intensive care patients with Acute Respiratory Distress Syndrome reduced mortality and increased ventilator-free days.
Reference: Fuller BM, Ferguson IT, Mohr NM, et al. A Quasi-Experimental, Before-After Trial Examining the Impact of an Emergency Department Mechanical Ventilator Protocol on Clinical Outcomes and Lung-Protective Ventilation in Acute Respiratory Distress Syndrome. Crit Care Med. 2017;45(4);645-52.
Community-based palliative care reduces emergency department visits
By Bryan J. Huang, MD, FHM
Retrospective cohort study showed that patients receiving community-based palliative care were less likely to seek ED care. The reduction was greater for older patients and for patients living in areas of higher socioeconomic status.
Time to intubation after cardiac arrest: Earlier may not be better
By Sarah Horman, MD
In a retrospective, observational, cohort study of 86,628 adults with in-hospital cardiac arrest, intubation during the first 15 minutes was associated with decreased survival, compared with no intubation.
Reference: Andersen, LW, Granfeldt, A, Callaway, CW, et al. Association between Tracheal intubation during adult in-hospital cardiac arrest and survival. JAMA. 2017;317(5):494-506.
DNR orders often not transferred to ED from outside care facilities
By Leslie M. Martin, MD
Prospective chart review of patients presenting from extended care facilities to an urban trauma center found hospital staff did a poor job of noting do not resuscitate preferences, and extended care facilities were inconsistent in providing their patients’ DNR forms.
Reference: McQuown CM, Frey JA, Amireh A, Chaudhary A. Transfer of do not resuscitate orders to the emergency department from extended care facilities. Am J Emerg Med. Published on 4 Feb 2017. doi: 10.1016/j.ajem.2017.02.007.
A quasi-experimental, before-after trial examining the impact of an emergency department mechanical ventilator protocol on clinical outcomes and lung-protective ventilation in acute respiratory distress syndrome
By William James Frederick III, MD, PhD
A single center, quasi-experimental, before-after trial shows a lung-protective mechanical ventilation protocol for emergency department and intensive care patients with Acute Respiratory Distress Syndrome reduced mortality and increased ventilator-free days.
Reference: Fuller BM, Ferguson IT, Mohr NM, et al. A Quasi-Experimental, Before-After Trial Examining the Impact of an Emergency Department Mechanical Ventilator Protocol on Clinical Outcomes and Lung-Protective Ventilation in Acute Respiratory Distress Syndrome. Crit Care Med. 2017;45(4);645-52.
Community-based palliative care reduces emergency department visits
By Bryan J. Huang, MD, FHM
Retrospective cohort study showed that patients receiving community-based palliative care were less likely to seek ED care. The reduction was greater for older patients and for patients living in areas of higher socioeconomic status.
Time to intubation after cardiac arrest: Earlier may not be better
By Sarah Horman, MD
In a retrospective, observational, cohort study of 86,628 adults with in-hospital cardiac arrest, intubation during the first 15 minutes was associated with decreased survival, compared with no intubation.
Reference: Andersen, LW, Granfeldt, A, Callaway, CW, et al. Association between Tracheal intubation during adult in-hospital cardiac arrest and survival. JAMA. 2017;317(5):494-506.
DNR orders often not transferred to ED from outside care facilities
By Leslie M. Martin, MD
Prospective chart review of patients presenting from extended care facilities to an urban trauma center found hospital staff did a poor job of noting do not resuscitate preferences, and extended care facilities were inconsistent in providing their patients’ DNR forms.
Reference: McQuown CM, Frey JA, Amireh A, Chaudhary A. Transfer of do not resuscitate orders to the emergency department from extended care facilities. Am J Emerg Med. Published on 4 Feb 2017. doi: 10.1016/j.ajem.2017.02.007.
A quasi-experimental, before-after trial examining the impact of an emergency department mechanical ventilator protocol on clinical outcomes and lung-protective ventilation in acute respiratory distress syndrome
By William James Frederick III, MD, PhD
A single center, quasi-experimental, before-after trial shows a lung-protective mechanical ventilation protocol for emergency department and intensive care patients with Acute Respiratory Distress Syndrome reduced mortality and increased ventilator-free days.
Reference: Fuller BM, Ferguson IT, Mohr NM, et al. A Quasi-Experimental, Before-After Trial Examining the Impact of an Emergency Department Mechanical Ventilator Protocol on Clinical Outcomes and Lung-Protective Ventilation in Acute Respiratory Distress Syndrome. Crit Care Med. 2017;45(4);645-52.
Will artificial intelligence make us better doctors?
Given the amount of time physicians spend entering data, clicking through screens, navigating pages, and logging in to computers, one would have hoped that substantial near-term payback for such efforts would have materialized.
Many of us believed this would take the form of health information exchange – the ability to easily access clinical information from hospitals or clinics other than our own, creating a more complete picture of the patient before us. To our disappointment, true information exchange has yet to materialize. (We won’t debate here whether politics or technology is culpable.) We are left to look elsewhere for the benefits of the digitization of the medical records and other sources of health care knowledge.
Lately, there has been a lot of talk about the promise of machine learning and artificial intelligence (AI) in health care. Much of the resurgence of interest in AI can be traced to IBM Watson’s appearance as a contestant on Jeopardy in 2011. Watson, a natural language supercomputer with enough power to process the equivalent of a million books per second, had access to 200 million pages of content, including the full text of Wikipedia, for Jeopardy.1 Watson handily outperformed its human opponents – two Jeopardy savants who were also the most successful contestants in game show history – taking the $1 million first prize but struggling in categories with clues containing only a few words.
MD Anderson and Watson: Dashed hopes follow initial promise
As a result of growing recognition of AI’s potential in health care, IBM began collaborations with a number of health care organizations to deploy Watson.
In 2013, MD Anderson Cancer Center and IBM began a pilot to develop an oncology clinical decision support technology tool powered by Watson to aid MD Anderson “in its mission to eradicate cancer.” Recently, it was announced that the project – which cost the cancer center $62 million – has been put on hold, and MD Anderson is looking for other contractors to replace IBM.
While administrative problems are at least partly responsible for the project’s challenges, the undertaking has raised issues with the quality and quantity of data in health care that call into question the ability of AI to work as well in health care as it did on Jeopardy, at least in the short term.
Health care: Not as data rich as you might think
“We are not ‘Big Data’ in health care, yet.” – Dale Sanders, Health Catalyst.2
In its quest for Jeopardy victory, Watson accessed a massive data storehouse subsuming a vast array of knowledge assembled over the course of human history. Conversely, for health care, Watson is limited to a few decades of scientific journals (that may not contribute to diagnosis and treatment as much as one might think), claims data geared to billing without much clinical information like outcomes, and clinical data from progress notes (plagued by inaccuracies, serial “copy and paste,” and nonstandardized language and numeric representations), and variable-format reports from lab, radiology, pathology, and other disciplines.
To articulate how data-poor health care is, Dale Sanders, executive vice president for software at Health Catalyst, notes that a Boeing 787 generates 500GB of data in a six hour flight while one patient may generate just 100MB of data in an entire year.2 He pointed out that, in the near term, AI platforms like Watson simply do not have enough data substrate to impact health care as many hoped it would. Over the longer term, he says, if health care can develop a coherent, standard approach to data content, AI may fulfill its promise. 
What can AI and related technologies achieve in the near-term?
“AI seems to have replaced Uber as the most overused word or phrase in digital health.” – Reporter Stephanie Baum, paraphrasing from an interview with Bob Kocher, Venrock Partners.3
My observations tell me that we have already made some progress and are likely to make more strides in the coming years, thanks to AI, machine learning, and natural language processing. A few areas of potential gain are:
Clinical documentation
Technology that can derive meaning from words or groups of words can help with more accurate clinical documentation. For example, if a patient has a documented UTI but also has in the record an 11 on the Glasgow Coma Scale, a systolic BP of 90, and a respiratory rate of 24, technology can alert the physician to document sepsis.
Quality measurement and reporting
Similarly, if technology can recognize words and numbers, it may be able to extract and report quality measures (for example, an ejection fraction of 35% in a heart failure patient) from progress notes without having a nurse-abstractor manually enter such data into structured fields for reporting, as is currently the case.
Predicting readmissions, mortality, other events
While machine learning has had mixed results in predicting future clinical events, this is likely to change as data integrity and algorithms improve. Best-of-breed technology will probably use both clinical and machine learning tools for predictive purposes in the future.
In 2015, I had the privilege of meeting Vinod Khosla, cofounder of SUN Microsystems and venture capitalist, who predicts that computers will largely supplant physicians in the future, at least in domains relying on access to data. As he puts it, “the core functions necessary for complex diagnoses, treatments, and monitoring will be driven by machine judgment instead of human judgment.”4
While the benefits of technology, especially in health care, are often oversold, I believe AI and related technologies will some day play a large role alongside physicians in the care of patients. However, for AI to deliver, we must first figure out how to collect and organize health care data so that computers are able to ingest, digest and use it in a purposeful way.
Note: Dr. Whitcomb is founder and advisor to Zato Health, which uses natural language processing and discovery technology in health care.
He is chief medical officer at Remedy Partners in Darien, Conn., and a cofounder and past president of SHM.
References
1. Zimmer, Ben. Is It Time to Welcome Our New Computer Overlords?. The Atlantic. https://www.theatlantic.com/technology/archive/2011/02/is-it-time-to-welcome-our-new-computer-overlords/71388/. Accessed 23 Apr 2017.
2. Sanders, Dale. The MD Anderson / IBM Watson Announcement: What does it mean for machine learning in healthcare? Webinar. https://www.slideshare.net/healthcatalyst1/the-md-anderson-ibm-watson-announcement-what-does-it-mean-for-machine-learning-in-healthcare. Accessed 23 Apr 2017.
3. Baum, Stephanie. Venrock survey predicts a flight to quality for digital health investments. MedCity News. 12 Apr 2017. http://medcitynews.com/2017/04/venrock-survey-predicts-flight-quality-digital-health-investment/. Accessed 22 Apr 2017.
4. Khosla, Vinod. The Reinvention Of Medicine: Dr. Algorithm V0-7 And Beyond. TechCrunch. 22 Sept 2014. https://techcrunch.com/2014/09/22/the-reinvention-of-medicine-dr-algorithm-version-0-7-and-beyond/. Accessed 22 Apr 2017.
Given the amount of time physicians spend entering data, clicking through screens, navigating pages, and logging in to computers, one would have hoped that substantial near-term payback for such efforts would have materialized.
Many of us believed this would take the form of health information exchange – the ability to easily access clinical information from hospitals or clinics other than our own, creating a more complete picture of the patient before us. To our disappointment, true information exchange has yet to materialize. (We won’t debate here whether politics or technology is culpable.) We are left to look elsewhere for the benefits of the digitization of the medical records and other sources of health care knowledge.
Lately, there has been a lot of talk about the promise of machine learning and artificial intelligence (AI) in health care. Much of the resurgence of interest in AI can be traced to IBM Watson’s appearance as a contestant on Jeopardy in 2011. Watson, a natural language supercomputer with enough power to process the equivalent of a million books per second, had access to 200 million pages of content, including the full text of Wikipedia, for Jeopardy.1 Watson handily outperformed its human opponents – two Jeopardy savants who were also the most successful contestants in game show history – taking the $1 million first prize but struggling in categories with clues containing only a few words.
MD Anderson and Watson: Dashed hopes follow initial promise
As a result of growing recognition of AI’s potential in health care, IBM began collaborations with a number of health care organizations to deploy Watson.
In 2013, MD Anderson Cancer Center and IBM began a pilot to develop an oncology clinical decision support technology tool powered by Watson to aid MD Anderson “in its mission to eradicate cancer.” Recently, it was announced that the project – which cost the cancer center $62 million – has been put on hold, and MD Anderson is looking for other contractors to replace IBM.
While administrative problems are at least partly responsible for the project’s challenges, the undertaking has raised issues with the quality and quantity of data in health care that call into question the ability of AI to work as well in health care as it did on Jeopardy, at least in the short term.
Health care: Not as data rich as you might think
“We are not ‘Big Data’ in health care, yet.” – Dale Sanders, Health Catalyst.2
In its quest for Jeopardy victory, Watson accessed a massive data storehouse subsuming a vast array of knowledge assembled over the course of human history. Conversely, for health care, Watson is limited to a few decades of scientific journals (that may not contribute to diagnosis and treatment as much as one might think), claims data geared to billing without much clinical information like outcomes, and clinical data from progress notes (plagued by inaccuracies, serial “copy and paste,” and nonstandardized language and numeric representations), and variable-format reports from lab, radiology, pathology, and other disciplines.
To articulate how data-poor health care is, Dale Sanders, executive vice president for software at Health Catalyst, notes that a Boeing 787 generates 500GB of data in a six hour flight while one patient may generate just 100MB of data in an entire year.2 He pointed out that, in the near term, AI platforms like Watson simply do not have enough data substrate to impact health care as many hoped it would. Over the longer term, he says, if health care can develop a coherent, standard approach to data content, AI may fulfill its promise.
What can AI and related technologies achieve in the near-term?
“AI seems to have replaced Uber as the most overused word or phrase in digital health.” – Reporter Stephanie Baum, paraphrasing from an interview with Bob Kocher, Venrock Partners.3
My observations tell me that we have already made some progress and are likely to make more strides in the coming years, thanks to AI, machine learning, and natural language processing. A few areas of potential gain are:
Clinical documentation
Technology that can derive meaning from words or groups of words can help with more accurate clinical documentation. For example, if a patient has a documented UTI but also has in the record an 11 on the Glasgow Coma Scale, a systolic BP of 90, and a respiratory rate of 24, technology can alert the physician to document sepsis.
Quality measurement and reporting
Similarly, if technology can recognize words and numbers, it may be able to extract and report quality measures (for example, an ejection fraction of 35% in a heart failure patient) from progress notes without having a nurse-abstractor manually enter such data into structured fields for reporting, as is currently the case.
Predicting readmissions, mortality, other events
While machine learning has had mixed results in predicting future clinical events, this is likely to change as data integrity and algorithms improve. Best-of-breed technology will probably use both clinical and machine learning tools for predictive purposes in the future.
In 2015, I had the privilege of meeting Vinod Khosla, cofounder of SUN Microsystems and venture capitalist, who predicts that computers will largely supplant physicians in the future, at least in domains relying on access to data. As he puts it, “the core functions necessary for complex diagnoses, treatments, and monitoring will be driven by machine judgment instead of human judgment.”4
While the benefits of technology, especially in health care, are often oversold, I believe AI and related technologies will some day play a large role alongside physicians in the care of patients. However, for AI to deliver, we must first figure out how to collect and organize health care data so that computers are able to ingest, digest and use it in a purposeful way.
Note: Dr. Whitcomb is founder and advisor to Zato Health, which uses natural language processing and discovery technology in health care.
He is chief medical officer at Remedy Partners in Darien, Conn., and a cofounder and past president of SHM.
References
1. Zimmer, Ben. Is It Time to Welcome Our New Computer Overlords?. The Atlantic. https://www.theatlantic.com/technology/archive/2011/02/is-it-time-to-welcome-our-new-computer-overlords/71388/. Accessed 23 Apr 2017.
2. Sanders, Dale. The MD Anderson / IBM Watson Announcement: What does it mean for machine learning in healthcare? Webinar. https://www.slideshare.net/healthcatalyst1/the-md-anderson-ibm-watson-announcement-what-does-it-mean-for-machine-learning-in-healthcare. Accessed 23 Apr 2017.
3. Baum, Stephanie. Venrock survey predicts a flight to quality for digital health investments. MedCity News. 12 Apr 2017. http://medcitynews.com/2017/04/venrock-survey-predicts-flight-quality-digital-health-investment/. Accessed 22 Apr 2017.
4. Khosla, Vinod. The Reinvention Of Medicine: Dr. Algorithm V0-7 And Beyond. TechCrunch. 22 Sept 2014. https://techcrunch.com/2014/09/22/the-reinvention-of-medicine-dr-algorithm-version-0-7-and-beyond/. Accessed 22 Apr 2017.
Given the amount of time physicians spend entering data, clicking through screens, navigating pages, and logging in to computers, one would have hoped that substantial near-term payback for such efforts would have materialized.
Many of us believed this would take the form of health information exchange – the ability to easily access clinical information from hospitals or clinics other than our own, creating a more complete picture of the patient before us. To our disappointment, true information exchange has yet to materialize. (We won’t debate here whether politics or technology is culpable.) We are left to look elsewhere for the benefits of the digitization of the medical records and other sources of health care knowledge.
Lately, there has been a lot of talk about the promise of machine learning and artificial intelligence (AI) in health care. Much of the resurgence of interest in AI can be traced to IBM Watson’s appearance as a contestant on Jeopardy in 2011. Watson, a natural language supercomputer with enough power to process the equivalent of a million books per second, had access to 200 million pages of content, including the full text of Wikipedia, for Jeopardy.1 Watson handily outperformed its human opponents – two Jeopardy savants who were also the most successful contestants in game show history – taking the $1 million first prize but struggling in categories with clues containing only a few words.
MD Anderson and Watson: Dashed hopes follow initial promise
As a result of growing recognition of AI’s potential in health care, IBM began collaborations with a number of health care organizations to deploy Watson.
In 2013, MD Anderson Cancer Center and IBM began a pilot to develop an oncology clinical decision support technology tool powered by Watson to aid MD Anderson “in its mission to eradicate cancer.” Recently, it was announced that the project – which cost the cancer center $62 million – has been put on hold, and MD Anderson is looking for other contractors to replace IBM.
While administrative problems are at least partly responsible for the project’s challenges, the undertaking has raised issues with the quality and quantity of data in health care that call into question the ability of AI to work as well in health care as it did on Jeopardy, at least in the short term.
Health care: Not as data rich as you might think
“We are not ‘Big Data’ in health care, yet.” – Dale Sanders, Health Catalyst.2
In its quest for Jeopardy victory, Watson accessed a massive data storehouse subsuming a vast array of knowledge assembled over the course of human history. Conversely, for health care, Watson is limited to a few decades of scientific journals (that may not contribute to diagnosis and treatment as much as one might think), claims data geared to billing without much clinical information like outcomes, and clinical data from progress notes (plagued by inaccuracies, serial “copy and paste,” and nonstandardized language and numeric representations), and variable-format reports from lab, radiology, pathology, and other disciplines.
To articulate how data-poor health care is, Dale Sanders, executive vice president for software at Health Catalyst, notes that a Boeing 787 generates 500GB of data in a six hour flight while one patient may generate just 100MB of data in an entire year.2 He pointed out that, in the near term, AI platforms like Watson simply do not have enough data substrate to impact health care as many hoped it would. Over the longer term, he says, if health care can develop a coherent, standard approach to data content, AI may fulfill its promise.
What can AI and related technologies achieve in the near-term?
“AI seems to have replaced Uber as the most overused word or phrase in digital health.” – Reporter Stephanie Baum, paraphrasing from an interview with Bob Kocher, Venrock Partners.3
My observations tell me that we have already made some progress and are likely to make more strides in the coming years, thanks to AI, machine learning, and natural language processing. A few areas of potential gain are:
Clinical documentation
Technology that can derive meaning from words or groups of words can help with more accurate clinical documentation. For example, if a patient has a documented UTI but also has in the record an 11 on the Glasgow Coma Scale, a systolic BP of 90, and a respiratory rate of 24, technology can alert the physician to document sepsis.
Quality measurement and reporting
Similarly, if technology can recognize words and numbers, it may be able to extract and report quality measures (for example, an ejection fraction of 35% in a heart failure patient) from progress notes without having a nurse-abstractor manually enter such data into structured fields for reporting, as is currently the case.
Predicting readmissions, mortality, other events
While machine learning has had mixed results in predicting future clinical events, this is likely to change as data integrity and algorithms improve. Best-of-breed technology will probably use both clinical and machine learning tools for predictive purposes in the future.
In 2015, I had the privilege of meeting Vinod Khosla, cofounder of SUN Microsystems and venture capitalist, who predicts that computers will largely supplant physicians in the future, at least in domains relying on access to data. As he puts it, “the core functions necessary for complex diagnoses, treatments, and monitoring will be driven by machine judgment instead of human judgment.”4
While the benefits of technology, especially in health care, are often oversold, I believe AI and related technologies will some day play a large role alongside physicians in the care of patients. However, for AI to deliver, we must first figure out how to collect and organize health care data so that computers are able to ingest, digest and use it in a purposeful way.
Note: Dr. Whitcomb is founder and advisor to Zato Health, which uses natural language processing and discovery technology in health care.
He is chief medical officer at Remedy Partners in Darien, Conn., and a cofounder and past president of SHM.
References
1. Zimmer, Ben. Is It Time to Welcome Our New Computer Overlords?. The Atlantic. https://www.theatlantic.com/technology/archive/2011/02/is-it-time-to-welcome-our-new-computer-overlords/71388/. Accessed 23 Apr 2017.
2. Sanders, Dale. The MD Anderson / IBM Watson Announcement: What does it mean for machine learning in healthcare? Webinar. https://www.slideshare.net/healthcatalyst1/the-md-anderson-ibm-watson-announcement-what-does-it-mean-for-machine-learning-in-healthcare. Accessed 23 Apr 2017.
3. Baum, Stephanie. Venrock survey predicts a flight to quality for digital health investments. MedCity News. 12 Apr 2017. http://medcitynews.com/2017/04/venrock-survey-predicts-flight-quality-digital-health-investment/. Accessed 22 Apr 2017.
4. Khosla, Vinod. The Reinvention Of Medicine: Dr. Algorithm V0-7 And Beyond. TechCrunch. 22 Sept 2014. https://techcrunch.com/2014/09/22/the-reinvention-of-medicine-dr-algorithm-version-0-7-and-beyond/. Accessed 22 Apr 2017.
Lactulose plus albumin is more effective than lactulose alone for treatment of hepatic encephalopathy
Clinical Question: Is the combination of lactulose plus albumin more effective than lactulose alone for treatment of hepatic encephalopathy?
Background: Hepatic encephalopathy is caused by the effect of toxins that build up in the bloodstream when the liver is not able to perform its normal functions. Lactulose is primarily directed at the reduction of blood ammonia levels. Albumin is thought to minimize oxidative injury and improve circulatory dysfunction present in cirrhosis.
Setting: Tertiary care centers in India.
Synopsis: 120 patients with overt hepatic encephalopathy were randomized to treatment with lactulose plus albumin (1.5 gm/kg/day; n = 60), versus lactulose alone (n = 60). Patients with serum creatinine greater than 1.5 mg/dL on admission, active alcohol intake less than 4 weeks prior to presentation, other metabolic encephalopathies, or hepatocellular carcinoma were excluded. Treatment was continued up to a maximum of 10 days until complete resolution of hepatic encephalopathy as assessed independently by two expert hepatologists.
Of patients receiving lactulose plus albumin, 75% had complete reversal of hepatic encephalopathy within 10 days, compared with 53% of patients receiving lactulose alone (P = .03). Patients in lactulose plus albumin group had shorter hospital length-of-stay (6.4 vs. 8.6 days; P = .01). There was lower mortality at 10 days in the lactulose plus albumin group (18.3% vs. 31.6%; P = .04).
Limitations of the study include the noted exclusion factors, including presence of alcohol intake, limitation to a single country (India), and a relatively high mortality rate in both groups.
Bottom Line: Combination of lactulose plus albumin is more effective than lactulose alone at reversing hepatic encephalopathy and is also associated with decreased length-of-stay and mortality.
Reference: Sharma BC, Singh J, Srivastava S, et al. A randomized controlled trial comparing lactulose plus albumin with lactulose alone for treatment of hepatic encephalopathy. J Gastroenterol Hepatol. Published online Nov 25, 2016. doi: 10.1111/jgh.13666.
Dr. Huang is associate clinical professor in the division of hospital medicine, department of medicine, University of California, San Diego.
Clinical Question: Is the combination of lactulose plus albumin more effective than lactulose alone for treatment of hepatic encephalopathy?
Background: Hepatic encephalopathy is caused by the effect of toxins that build up in the bloodstream when the liver is not able to perform its normal functions. Lactulose is primarily directed at the reduction of blood ammonia levels. Albumin is thought to minimize oxidative injury and improve circulatory dysfunction present in cirrhosis.
Setting: Tertiary care centers in India.
Synopsis: 120 patients with overt hepatic encephalopathy were randomized to treatment with lactulose plus albumin (1.5 gm/kg/day; n = 60), versus lactulose alone (n = 60). Patients with serum creatinine greater than 1.5 mg/dL on admission, active alcohol intake less than 4 weeks prior to presentation, other metabolic encephalopathies, or hepatocellular carcinoma were excluded. Treatment was continued up to a maximum of 10 days until complete resolution of hepatic encephalopathy as assessed independently by two expert hepatologists.
Of patients receiving lactulose plus albumin, 75% had complete reversal of hepatic encephalopathy within 10 days, compared with 53% of patients receiving lactulose alone (P = .03). Patients in lactulose plus albumin group had shorter hospital length-of-stay (6.4 vs. 8.6 days; P = .01). There was lower mortality at 10 days in the lactulose plus albumin group (18.3% vs. 31.6%; P = .04).
Limitations of the study include the noted exclusion factors, including presence of alcohol intake, limitation to a single country (India), and a relatively high mortality rate in both groups.
Bottom Line: Combination of lactulose plus albumin is more effective than lactulose alone at reversing hepatic encephalopathy and is also associated with decreased length-of-stay and mortality.
Reference: Sharma BC, Singh J, Srivastava S, et al. A randomized controlled trial comparing lactulose plus albumin with lactulose alone for treatment of hepatic encephalopathy. J Gastroenterol Hepatol. Published online Nov 25, 2016. doi: 10.1111/jgh.13666.
Dr. Huang is associate clinical professor in the division of hospital medicine, department of medicine, University of California, San Diego.
Clinical Question: Is the combination of lactulose plus albumin more effective than lactulose alone for treatment of hepatic encephalopathy?
Background: Hepatic encephalopathy is caused by the effect of toxins that build up in the bloodstream when the liver is not able to perform its normal functions. Lactulose is primarily directed at the reduction of blood ammonia levels. Albumin is thought to minimize oxidative injury and improve circulatory dysfunction present in cirrhosis.
Setting: Tertiary care centers in India.
Synopsis: 120 patients with overt hepatic encephalopathy were randomized to treatment with lactulose plus albumin (1.5 gm/kg/day; n = 60), versus lactulose alone (n = 60). Patients with serum creatinine greater than 1.5 mg/dL on admission, active alcohol intake less than 4 weeks prior to presentation, other metabolic encephalopathies, or hepatocellular carcinoma were excluded. Treatment was continued up to a maximum of 10 days until complete resolution of hepatic encephalopathy as assessed independently by two expert hepatologists.
Of patients receiving lactulose plus albumin, 75% had complete reversal of hepatic encephalopathy within 10 days, compared with 53% of patients receiving lactulose alone (P = .03). Patients in lactulose plus albumin group had shorter hospital length-of-stay (6.4 vs. 8.6 days; P = .01). There was lower mortality at 10 days in the lactulose plus albumin group (18.3% vs. 31.6%; P = .04).
Limitations of the study include the noted exclusion factors, including presence of alcohol intake, limitation to a single country (India), and a relatively high mortality rate in both groups.
Bottom Line: Combination of lactulose plus albumin is more effective than lactulose alone at reversing hepatic encephalopathy and is also associated with decreased length-of-stay and mortality.
Reference: Sharma BC, Singh J, Srivastava S, et al. A randomized controlled trial comparing lactulose plus albumin with lactulose alone for treatment of hepatic encephalopathy. J Gastroenterol Hepatol. Published online Nov 25, 2016. doi: 10.1111/jgh.13666.
Dr. Huang is associate clinical professor in the division of hospital medicine, department of medicine, University of California, San Diego.
A case for building our leadership skills
Let me ask you a question: When was the last time you used the Krebs cycle in the hospital?
Now another question: When did you last have to persuade your boss to give you additional resources?
My guess is that your need for additional resources comes up more frequently than the Krebs cycle. It’s interesting that we spent so much time in our training focused on biochemical pathways and next to nothing on leadership skills, such as ways to motivate our health care teams or the most effective way to provide feedback – skills that we use on a regular basis. Yet, these skills are just as critical as understanding the science behind our daily work.
In the past, I would present my case in the following way:
1. Highlight the importance of the ask.
2. Leverage data to prove the point.
3. Illustrate large-scale implications of the ask.
4. Make the ask.
I’ll use a project to increase DVT prophylaxis rates to illustrate this point:
1. Highlight the importance of DVT prophylaxis: I would focus on statistics that would surprise the audience, such as “Hospital acquired venous thromboembolism leads to significant morbidity and mortality, including more than 100,000 deaths.”1
2. Leverage data to prove the point: “Worldwide, only 40%-60% of patients who require DVT prophylaxis actually receive it in the hospital.2 Our performance leaves tremendous room for improvement – we’re currently at 68%.”
3. Illustrate large-scale implications of the ask: “If we do this, it enhances our reputation as a group, and it will improve hospital revenues.”
4. Make the ask: “I have an evidence-based protocol that we need to implement to achieve results.”
Through leadership courses over the past couple of years, I’ve changed my approach significantly. By leveraging concepts from behavioral economics, we can significantly improve the effect of our work. Here’s how I would conduct that same meeting:
1. Connect with the audience in a genuine way: Start off with “You are quality-minded providers who have taken on major challenges in the past and successfully delivered results, like the time you reduced the rates of catheter associated urinary tract infections.”
2. Make the ask: “I’m here to talk to you about improving our DVT prophylaxis rates. Here’s the protocol we need to implement.”
3. Leverage data to prove the point: “DVT prophylaxis rates at the hospital across town (or at another unit in the hospital) are at 82%. What do you think our numbers are? We’re actually at 68%!”
4. Illustrate large-scale implications of the ask: “We all know this. Patients under our care will die or be seriously harmed if we don’t improve our practice. The hospital will also lose money, which will ultimately impact us. So, we have two options: a) We can continue what we’ve been doing – work as hard as we can and our practice will not improve. b) Or we can decide today to pilot this new protocol and change our practice and performance.”
Let’s look at the changes above in greater detail:
Connect with the audience in a genuine way: Instead of highlighting the importance of the ask with statistics, use an attention getter to connect with the group. Highlighting the fact that the group is “quality-minded” and has surmounted challenging obstacles in the past reinforces the providers’ sense of identity.3 This helps the group think more openly about the proposal.
Make the ask: Now that you’ve captured their attention, make your ask, clearly and concisely, upfront. Remember, in today’s health care settings, we have short attention spans. You’re minutes away from someone getting paged away from the meeting or people checking their emails or the latest Facebook post. Don’t schedule the protocol review as the last item on the agenda.
Leverage data to prove your point: Data are powerful, but only if presented in the right way. Use questions to keep your audience engaged (“What do you think our numbers are?”), particularly around data, where most people decide to switch their attention to their smartphones. Based on your access to data sources, find another unit or institution with a higher performance than yours. State that upfront. It anchors,the group to a higher number, so, when you reveal your current performance, the gap is highlighted. 3,4 In the first case, when the lower national average of 40-60% is presented initially, the group will be happy that their performance is in fact better at 68%.
Illustrate large-scale implications of the ask: There are two concepts at work here: First, loss aversion.3,4 We tend to experience greater psychological burden with losses versus gains. Changing the framing from the fact that the hospital will lose money, versus making money in the first case, changes how we perceive the information. Second, active choice.3 Emphasizing that a decision has to be made today and giving the group a choice around it increases the likelihood of walking out of the meeting with a decision.
With some simple, yet thoughtful, modifications, the message takes on a more effective tone, and, based on my experience, it is significantly more impactful.
So, while I’m a fan of biochemical pathways that enable us to generate energy, I also hope we can integrate leadership lessons into our day-to-day learning and life.
Dr. Afsar is an assistant clinical professor in the departments of medicine and neurosurgery and the associate chief medical officer at UCLA Hospitals.
References
1. The Surgeon General’s Call to Action to Prevent Deep Vein Thrombosis and Pulmonary Embolism. Office of the Surgeon General (US); National Heart, Lung, and Blood Institute (US). Office of the Surgeon General (US). 2008.
2. Cohen AT, Tapson VF, Bergmann JF, et al. Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): A multinational cross-sectional study. Lancet. 2008;371(9610):387-94.
3. Soman D. The Last Mile. 2015.
4. Thaler RH, Sunstein CR. Nudge. 2009.
Let me ask you a question: When was the last time you used the Krebs cycle in the hospital?
Now another question: When did you last have to persuade your boss to give you additional resources?
My guess is that your need for additional resources comes up more frequently than the Krebs cycle. It’s interesting that we spent so much time in our training focused on biochemical pathways and next to nothing on leadership skills, such as ways to motivate our health care teams or the most effective way to provide feedback – skills that we use on a regular basis. Yet, these skills are just as critical as understanding the science behind our daily work.
In the past, I would present my case in the following way:
1. Highlight the importance of the ask.
2. Leverage data to prove the point.
3. Illustrate large-scale implications of the ask.
4. Make the ask.
I’ll use a project to increase DVT prophylaxis rates to illustrate this point:
1. Highlight the importance of DVT prophylaxis: I would focus on statistics that would surprise the audience, such as “Hospital acquired venous thromboembolism leads to significant morbidity and mortality, including more than 100,000 deaths.”1
2. Leverage data to prove the point: “Worldwide, only 40%-60% of patients who require DVT prophylaxis actually receive it in the hospital.2 Our performance leaves tremendous room for improvement – we’re currently at 68%.”
3. Illustrate large-scale implications of the ask: “If we do this, it enhances our reputation as a group, and it will improve hospital revenues.”
4. Make the ask: “I have an evidence-based protocol that we need to implement to achieve results.”
Through leadership courses over the past couple of years, I’ve changed my approach significantly. By leveraging concepts from behavioral economics, we can significantly improve the effect of our work. Here’s how I would conduct that same meeting:
1. Connect with the audience in a genuine way: Start off with “You are quality-minded providers who have taken on major challenges in the past and successfully delivered results, like the time you reduced the rates of catheter associated urinary tract infections.”
2. Make the ask: “I’m here to talk to you about improving our DVT prophylaxis rates. Here’s the protocol we need to implement.”
3. Leverage data to prove the point: “DVT prophylaxis rates at the hospital across town (or at another unit in the hospital) are at 82%. What do you think our numbers are? We’re actually at 68%!”
4. Illustrate large-scale implications of the ask: “We all know this. Patients under our care will die or be seriously harmed if we don’t improve our practice. The hospital will also lose money, which will ultimately impact us. So, we have two options: a) We can continue what we’ve been doing – work as hard as we can and our practice will not improve. b) Or we can decide today to pilot this new protocol and change our practice and performance.”
Let’s look at the changes above in greater detail:
Connect with the audience in a genuine way: Instead of highlighting the importance of the ask with statistics, use an attention getter to connect with the group. Highlighting the fact that the group is “quality-minded” and has surmounted challenging obstacles in the past reinforces the providers’ sense of identity.3 This helps the group think more openly about the proposal.
Make the ask: Now that you’ve captured their attention, make your ask, clearly and concisely, upfront. Remember, in today’s health care settings, we have short attention spans. You’re minutes away from someone getting paged away from the meeting or people checking their emails or the latest Facebook post. Don’t schedule the protocol review as the last item on the agenda.
Leverage data to prove your point: Data are powerful, but only if presented in the right way. Use questions to keep your audience engaged (“What do you think our numbers are?”), particularly around data, where most people decide to switch their attention to their smartphones. Based on your access to data sources, find another unit or institution with a higher performance than yours. State that upfront. It anchors,the group to a higher number, so, when you reveal your current performance, the gap is highlighted. 3,4 In the first case, when the lower national average of 40-60% is presented initially, the group will be happy that their performance is in fact better at 68%.
Illustrate large-scale implications of the ask: There are two concepts at work here: First, loss aversion.3,4 We tend to experience greater psychological burden with losses versus gains. Changing the framing from the fact that the hospital will lose money, versus making money in the first case, changes how we perceive the information. Second, active choice.3 Emphasizing that a decision has to be made today and giving the group a choice around it increases the likelihood of walking out of the meeting with a decision.
With some simple, yet thoughtful, modifications, the message takes on a more effective tone, and, based on my experience, it is significantly more impactful.
So, while I’m a fan of biochemical pathways that enable us to generate energy, I also hope we can integrate leadership lessons into our day-to-day learning and life.
Dr. Afsar is an assistant clinical professor in the departments of medicine and neurosurgery and the associate chief medical officer at UCLA Hospitals.
References
1. The Surgeon General’s Call to Action to Prevent Deep Vein Thrombosis and Pulmonary Embolism. Office of the Surgeon General (US); National Heart, Lung, and Blood Institute (US). Office of the Surgeon General (US). 2008.
2. Cohen AT, Tapson VF, Bergmann JF, et al. Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): A multinational cross-sectional study. Lancet. 2008;371(9610):387-94.
3. Soman D. The Last Mile. 2015.
4. Thaler RH, Sunstein CR. Nudge. 2009.
Let me ask you a question: When was the last time you used the Krebs cycle in the hospital?
Now another question: When did you last have to persuade your boss to give you additional resources?
My guess is that your need for additional resources comes up more frequently than the Krebs cycle. It’s interesting that we spent so much time in our training focused on biochemical pathways and next to nothing on leadership skills, such as ways to motivate our health care teams or the most effective way to provide feedback – skills that we use on a regular basis. Yet, these skills are just as critical as understanding the science behind our daily work.
In the past, I would present my case in the following way:
1. Highlight the importance of the ask.
2. Leverage data to prove the point.
3. Illustrate large-scale implications of the ask.
4. Make the ask.
I’ll use a project to increase DVT prophylaxis rates to illustrate this point:
1. Highlight the importance of DVT prophylaxis: I would focus on statistics that would surprise the audience, such as “Hospital acquired venous thromboembolism leads to significant morbidity and mortality, including more than 100,000 deaths.”1
2. Leverage data to prove the point: “Worldwide, only 40%-60% of patients who require DVT prophylaxis actually receive it in the hospital.2 Our performance leaves tremendous room for improvement – we’re currently at 68%.”
3. Illustrate large-scale implications of the ask: “If we do this, it enhances our reputation as a group, and it will improve hospital revenues.”
4. Make the ask: “I have an evidence-based protocol that we need to implement to achieve results.”
Through leadership courses over the past couple of years, I’ve changed my approach significantly. By leveraging concepts from behavioral economics, we can significantly improve the effect of our work. Here’s how I would conduct that same meeting:
1. Connect with the audience in a genuine way: Start off with “You are quality-minded providers who have taken on major challenges in the past and successfully delivered results, like the time you reduced the rates of catheter associated urinary tract infections.”
2. Make the ask: “I’m here to talk to you about improving our DVT prophylaxis rates. Here’s the protocol we need to implement.”
3. Leverage data to prove the point: “DVT prophylaxis rates at the hospital across town (or at another unit in the hospital) are at 82%. What do you think our numbers are? We’re actually at 68%!”
4. Illustrate large-scale implications of the ask: “We all know this. Patients under our care will die or be seriously harmed if we don’t improve our practice. The hospital will also lose money, which will ultimately impact us. So, we have two options: a) We can continue what we’ve been doing – work as hard as we can and our practice will not improve. b) Or we can decide today to pilot this new protocol and change our practice and performance.”
Let’s look at the changes above in greater detail:
Connect with the audience in a genuine way: Instead of highlighting the importance of the ask with statistics, use an attention getter to connect with the group. Highlighting the fact that the group is “quality-minded” and has surmounted challenging obstacles in the past reinforces the providers’ sense of identity.3 This helps the group think more openly about the proposal.
Make the ask: Now that you’ve captured their attention, make your ask, clearly and concisely, upfront. Remember, in today’s health care settings, we have short attention spans. You’re minutes away from someone getting paged away from the meeting or people checking their emails or the latest Facebook post. Don’t schedule the protocol review as the last item on the agenda.
Leverage data to prove your point: Data are powerful, but only if presented in the right way. Use questions to keep your audience engaged (“What do you think our numbers are?”), particularly around data, where most people decide to switch their attention to their smartphones. Based on your access to data sources, find another unit or institution with a higher performance than yours. State that upfront. It anchors,the group to a higher number, so, when you reveal your current performance, the gap is highlighted. 3,4 In the first case, when the lower national average of 40-60% is presented initially, the group will be happy that their performance is in fact better at 68%.
Illustrate large-scale implications of the ask: There are two concepts at work here: First, loss aversion.3,4 We tend to experience greater psychological burden with losses versus gains. Changing the framing from the fact that the hospital will lose money, versus making money in the first case, changes how we perceive the information. Second, active choice.3 Emphasizing that a decision has to be made today and giving the group a choice around it increases the likelihood of walking out of the meeting with a decision.
With some simple, yet thoughtful, modifications, the message takes on a more effective tone, and, based on my experience, it is significantly more impactful.
So, while I’m a fan of biochemical pathways that enable us to generate energy, I also hope we can integrate leadership lessons into our day-to-day learning and life.
Dr. Afsar is an assistant clinical professor in the departments of medicine and neurosurgery and the associate chief medical officer at UCLA Hospitals.
References
1. The Surgeon General’s Call to Action to Prevent Deep Vein Thrombosis and Pulmonary Embolism. Office of the Surgeon General (US); National Heart, Lung, and Blood Institute (US). Office of the Surgeon General (US). 2008.
2. Cohen AT, Tapson VF, Bergmann JF, et al. Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): A multinational cross-sectional study. Lancet. 2008;371(9610):387-94.
3. Soman D. The Last Mile. 2015.
4. Thaler RH, Sunstein CR. Nudge. 2009.
Family reports provide additional information regarding adverse events
Clinical Question: Do family reports of adverse events improve incident detection, compared with clinician reports and hospital incident reports?
Background: Hospital incident reports, which are voluntary and suffer from underreporting, capture only a fraction of errors and adverse events (defined as errors resulting in harm). Systematic, prospective surveillance by researchers is the gold standard but is time consuming and expensive. The authors hypothesized that family reports would improve error and adverse event detection.
Setting: Four U.S. pediatric hospitals.
Synopsis: The authors developed a Family Safety Interview, administered weekly and on discharge, and compared reporting of errors and adverse events to clinician reports, hospital incident reports, and systematic review of records by researchers. Of 989 hospitalized pediatric patients, 746 parents/caregivers completed interviews between December 2014 and July 2015. From all sources, the authors found a total of 179 errors and 113 adverse events. Families reported a total of 39 of these 179 errors (including 19 unique errors not reported elsewhere) and 33 of 113 adverse events (8 unique).
Overall, error rates with family-reported errors were 15.5% higher (95% confidence interval, 9.0%-22.3%) than without. Adverse event rates with family reporting were 9.8% higher (95% CI, 3.1%-16.9%) than without. Family-reported error rates were 5 times higher (95% CI, 1.9-13.0) than hospital incident report rates.
The study showed that family-reported error and adverse event rates were significantly higher than voluntary, clinician-only hospital incident report rates. The study was limited to pediatric hospitals on general pediatric and subspecialty services, though findings potentially may be applicable more broadly (for example, adult and surgical services).
Bottom Line: Using a structured interview, families report significantly higher rates of errors and adverse events, compared with other sources.
Reference: Khan A, Coffey M, Litterer KP, et al. Families as partners in hospital error and adverse event surveillance. JAMA Pediatrics. Published online Feb 27, 2017. doi: 10.1001/jamapediatrics.2016.4812.
Clinical Question: Do family reports of adverse events improve incident detection, compared with clinician reports and hospital incident reports?
Background: Hospital incident reports, which are voluntary and suffer from underreporting, capture only a fraction of errors and adverse events (defined as errors resulting in harm). Systematic, prospective surveillance by researchers is the gold standard but is time consuming and expensive. The authors hypothesized that family reports would improve error and adverse event detection.
Setting: Four U.S. pediatric hospitals.
Synopsis: The authors developed a Family Safety Interview, administered weekly and on discharge, and compared reporting of errors and adverse events to clinician reports, hospital incident reports, and systematic review of records by researchers. Of 989 hospitalized pediatric patients, 746 parents/caregivers completed interviews between December 2014 and July 2015. From all sources, the authors found a total of 179 errors and 113 adverse events. Families reported a total of 39 of these 179 errors (including 19 unique errors not reported elsewhere) and 33 of 113 adverse events (8 unique).
Overall, error rates with family-reported errors were 15.5% higher (95% confidence interval, 9.0%-22.3%) than without. Adverse event rates with family reporting were 9.8% higher (95% CI, 3.1%-16.9%) than without. Family-reported error rates were 5 times higher (95% CI, 1.9-13.0) than hospital incident report rates.
The study showed that family-reported error and adverse event rates were significantly higher than voluntary, clinician-only hospital incident report rates. The study was limited to pediatric hospitals on general pediatric and subspecialty services, though findings potentially may be applicable more broadly (for example, adult and surgical services).
Bottom Line: Using a structured interview, families report significantly higher rates of errors and adverse events, compared with other sources.
Reference: Khan A, Coffey M, Litterer KP, et al. Families as partners in hospital error and adverse event surveillance. JAMA Pediatrics. Published online Feb 27, 2017. doi: 10.1001/jamapediatrics.2016.4812.
Clinical Question: Do family reports of adverse events improve incident detection, compared with clinician reports and hospital incident reports?
Background: Hospital incident reports, which are voluntary and suffer from underreporting, capture only a fraction of errors and adverse events (defined as errors resulting in harm). Systematic, prospective surveillance by researchers is the gold standard but is time consuming and expensive. The authors hypothesized that family reports would improve error and adverse event detection.
Setting: Four U.S. pediatric hospitals.
Synopsis: The authors developed a Family Safety Interview, administered weekly and on discharge, and compared reporting of errors and adverse events to clinician reports, hospital incident reports, and systematic review of records by researchers. Of 989 hospitalized pediatric patients, 746 parents/caregivers completed interviews between December 2014 and July 2015. From all sources, the authors found a total of 179 errors and 113 adverse events. Families reported a total of 39 of these 179 errors (including 19 unique errors not reported elsewhere) and 33 of 113 adverse events (8 unique).
Overall, error rates with family-reported errors were 15.5% higher (95% confidence interval, 9.0%-22.3%) than without. Adverse event rates with family reporting were 9.8% higher (95% CI, 3.1%-16.9%) than without. Family-reported error rates were 5 times higher (95% CI, 1.9-13.0) than hospital incident report rates.
The study showed that family-reported error and adverse event rates were significantly higher than voluntary, clinician-only hospital incident report rates. The study was limited to pediatric hospitals on general pediatric and subspecialty services, though findings potentially may be applicable more broadly (for example, adult and surgical services).
Bottom Line: Using a structured interview, families report significantly higher rates of errors and adverse events, compared with other sources.
Reference: Khan A, Coffey M, Litterer KP, et al. Families as partners in hospital error and adverse event surveillance. JAMA Pediatrics. Published online Feb 27, 2017. doi: 10.1001/jamapediatrics.2016.4812.
Here’s what’s trending at SHM
HM17 On Demand now available
Couldn’t make it to Las Vegas for SHM’s annual meeting, Hospital Medicine 2017? HM17 On Demand gives you access to over 80 online audio and slide recordings from the hottest tracks, including clinical updates, rapid fire, pediatrics, comanagement, quality, and high-value care.
Additionally, you can earn up to 70 American Medical Association Physician Recognition Award Category 1 Credit(s) and up to 30 American Board of Internal Medicine Maintenance of Certification credits. HM17 attendees can also benefit by earning additional credits on the sessions you missed out on.
To easily access content through SHM’s Learning Portal, visit shmlearningportal.org/hm17-demand to learn more.
Chapter Excellence Awards
SHM is proud to recognize outstanding chapters for the fourth annual Chapter Excellence Awards. Each year, chapters strive to demonstrate growth, sustenance, and innovation within their chapter activities.
View more at www.hospitalmedicine.org/chapterexcellence. Please join SHM in congratulating the following chapters on their success!
Silver Chapters
Boston Association of Academic Hospital Medicine (BAAHM)
Charlotte Metro Area
Houston
Kentucky
Los Angeles
Minnesota
North Jersey
Pacific Northwest
Philadelphia Tri-State
Rocky Mountain
San Francisco Bay
South Central PA
Gold Chapters
New Mexico
Wiregrass
Platinum Chapters
IowaMaryland
Michigan
NYC/Westchester
St. Louis
Outstanding Chapter of the Year
Michigan
Rising Star Chapter
Wiregrass
Student Hospitalist Scholar grant winners
SHM’s Student Hospitalist Scholar Grant provides funds with which medical students can conduct mentored scholarly projects related to quality improvement and patient safety in the field of hospital medicine. The program offers a summer and a longitudinal option.
Congratulations to the 2017-2018 Student Hospitalist Scholar Grant recipients:Summer Program
Anton Garazha
Rosalind Franklin University of Medicine and Science
“Effectiveness of Communication During ICU to Ward Transfer and Association with Medical ICU Readmission”
Cole Hirschfeld
Weill Cornell Medical College
“The Role of Diagnostic Bone Biopsies in the Management of Osteomyelitis”
Farah Hussain
University of Cincinnati College of Medicine
“Better Understanding Clinical Deterioration in a Children’s Hospital”
Longitudinal Program
Monisha Bhatia
Vanderbilt University School of Medicine
“Using Electronic Medical Record Phenotypic Data to Predict Discharge Destination”
Victor Ekuta
University of California, San Diego School of Medicine
“Reducing CAUTI with Noninvasive UC Alternatives and Measure-vention”
Yun Li
Geisel School of Medicine at Dartmouth
“Developing and implementing clinical pathway(s) for hospitalized injection drug users due to injection-related infection sequelae”
Learn more about the Student Hospitalist Scholar Grant at hospitalmedicine.org/scholargrant.
SPARK ONE: A tool to teach residents
SPARK ONE is a comprehensive, online self-assessment tool created specifically for hospital medicine professionals. The activity contains 450+ vignette-style multiple-choice questions covering 100% of the American Board of Internal Medicine’s Focused Practice in Hospital Medicine (FPHM) exam blueprint. This online tool can be utilized as a training mechanism for resident education on hospital medicine.
As a benefit of SHM membership, residents will receive a free subscription. SPARK ONE provides in-depth review of the following content areas:
- Cardiology
- Pulmonary Disease and Critical Care Medicine
- Gastroenterology and Hepatology
- Nephrology and Urology
- Endocrinology
- Hematology and Oncology
- Neurology
- Allergy, Immunology, Dermatology, Rheumatology and Transitions in Care
- Palliative Care, Medical Ethics and Decision-making
- Perioperative Medicine and Consultative Co-management
- Patient Safety
- Quality, Cost and Clinical Reasoning
“SPARK ONE provides a unique platform for academic institutions, engaging learners in directed learning sessions, reinforcing teaching points as we encounter specific conditions.” – Rachel E. Thompson, MD, MPH, SFHM
Visit hospitalmedicine.org/sparkone to learn more.
Sharpen your coding with the updated CODE-H
SHM’s Coding Optimally by Documenting Effectively for Hospitalists (CODE-H) has launched an updated program with all new content. It will now include eight recorded webinar sessions presented by expert faculty, downloadable resources, and an interactive discussion forum through the Hospital Medicine Exchange (HMX), enabling participants to ask questions and learn the most relevant best practices.
Following each webinar, learners will have the opportunity to complete an evaluation to redeem continuing medical education credits.
Webinars in the series include:
- E/M Basics Part I
- E/M Basics Part II
- Utilizing Other Providers in Your Practice
- EMR and Mitigating Risk
- Putting Time into Critical Care Documentation
- Time Based Services
- Navigating the Rules for Hospitalist Visits
- Challenges of Concurrent Care
To purchase CODE-H, visit hospitalmedicine.org/CODEH. If you have questions about the new program, please contact [email protected].
Set yourself apart as a Fellow in Hospital Medicine
The Fellow in Hospital Medicine (FHM) designation signals your commitment to the hospital medicine specialty and dedication to quality improvement and patient safety. This designation is available for hospital medicine practitioners, including practice administrators, nurse practitioners, and physician assistants. If you meet the prerequisites and complete the requirements, which are rooted in the Core Competencies in Hospital Medicine, you can apply for this prestigious designation and join more than 1,100 FHMs who are dedicated to the field of hospital medicine. Learn more and apply at hospitalmedicine.org/fellow.
New guide & modules on multimodal pain strategies for postoperative pain management
Pain management can pose multiple challenges in the acute care setting for hospitalists and front-line prescribers. While their first priority is to optimally manage pain in their patients, they also face the challenges of treating diverse patient populations, managing patient expectations, and considering how pain control and perceptions affect Hospital Consumer Assessment of Healthcare Providers and Systems scores. Furthermore, because of the ongoing opioid epidemic, prescribers must ensure that pain is managed responsibly and ethically.
To address these issues, SHM developed a guide to address how to work in an interdisciplinary team, identify impediments to implementation, and provide examples of appropriate pain management. In accompaniment with this Multimodal Pain Strategies Guide for Postoperative Pain Management, there are three modules presented by the authors which supplement the electronic guide.
To download the guide or view the modules, visit hospitalmedicine.org/pain.
Proven excellence through a unique education style: Academic Hospitalist Academy
Don’t miss the eighth annual Academic Hospitalist Academy (AHA), Sept. 25-28, 2017, at the Lakeway Resort and Spa in Austin, Texas. AHA attendees experience an energizing, interactive learning environment featuring didactics, small-group exercise and skill-building breakout sessions. Each full day of learning is facilitated by leading clinician-educators, hospitalist researchers, and clinical administrators in a 1 to 10 faculty to student ratio.
The Principal Goals of the Academy are to:
- Develop junior academic hospitalists as the premier teachers and educational leaders at their institutions
- Help academic hospitalists develop scholarly work and increase scholarly output
- Enhance awareness of the value of quality improvement and patient safety work
- Support academic promotion of all attendees
Don’t miss out on this unique, hands-on experience. Register before July 18, 2017, to receive the early-bird rates. Visit academichospitalist.org to learn more.
Choosing Wisely Case Study compendium now available
The Choosing Wisely Case Study Competition, hosted by SHM, sought submissions from hospitalists on innovative improvement initiatives implemented in their respective institutions. These initiatives reflect and promote movement toward reducing unnecessary medical tests and procedures and changing a culture that dictates, “More care is better care.”
Submissions were judged by the Choosing Wisely Subcommittee, a panel of SHM members, under adult and pediatric categories. One grand prize winner and three honorable mentions were selected from these categories. The compendium includes these case studies along with additional exemplary submissions.
View the Choosing Wisely Case Study Compendium at hospitalmedicine.org/choosingwisely.
Strengthen your interactions with the 5 Rs of Cultural Humility
Look inside this issue for your 5 Rs of Cultural Humility pocket card. It can be easily referenced on rounds and shared with colleagues. We hope to achieve heightened awareness of effective interactions. In addition to the definitions of each of the Rs, the card features questions to ask yourself before, during, and after every interaction to aid in attaining cultural humility.
For more information, visit hospitalmedicine.org/5Rs.
Brett Radler is communications specialist at the Society of Hospital Medicine.
HM17 On Demand now available
Couldn’t make it to Las Vegas for SHM’s annual meeting, Hospital Medicine 2017? HM17 On Demand gives you access to over 80 online audio and slide recordings from the hottest tracks, including clinical updates, rapid fire, pediatrics, comanagement, quality, and high-value care.
Additionally, you can earn up to 70 American Medical Association Physician Recognition Award Category 1 Credit(s) and up to 30 American Board of Internal Medicine Maintenance of Certification credits. HM17 attendees can also benefit by earning additional credits on the sessions you missed out on.
To easily access content through SHM’s Learning Portal, visit shmlearningportal.org/hm17-demand to learn more.
Chapter Excellence Awards
SHM is proud to recognize outstanding chapters for the fourth annual Chapter Excellence Awards. Each year, chapters strive to demonstrate growth, sustenance, and innovation within their chapter activities.
View more at www.hospitalmedicine.org/chapterexcellence. Please join SHM in congratulating the following chapters on their success!
Silver Chapters
Boston Association of Academic Hospital Medicine (BAAHM)
Charlotte Metro Area
Houston
Kentucky
Los Angeles
Minnesota
North Jersey
Pacific Northwest
Philadelphia Tri-State
Rocky Mountain
San Francisco Bay
South Central PA
Gold Chapters
New Mexico
Wiregrass
Platinum Chapters
IowaMaryland
Michigan
NYC/Westchester
St. Louis
Outstanding Chapter of the Year
Michigan
Rising Star Chapter
Wiregrass
Student Hospitalist Scholar grant winners
SHM’s Student Hospitalist Scholar Grant provides funds with which medical students can conduct mentored scholarly projects related to quality improvement and patient safety in the field of hospital medicine. The program offers a summer and a longitudinal option.
Congratulations to the 2017-2018 Student Hospitalist Scholar Grant recipients:Summer Program
Anton Garazha
Rosalind Franklin University of Medicine and Science
“Effectiveness of Communication During ICU to Ward Transfer and Association with Medical ICU Readmission”
Cole Hirschfeld
Weill Cornell Medical College
“The Role of Diagnostic Bone Biopsies in the Management of Osteomyelitis”
Farah Hussain
University of Cincinnati College of Medicine
“Better Understanding Clinical Deterioration in a Children’s Hospital”
Longitudinal Program
Monisha Bhatia
Vanderbilt University School of Medicine
“Using Electronic Medical Record Phenotypic Data to Predict Discharge Destination”
Victor Ekuta
University of California, San Diego School of Medicine
“Reducing CAUTI with Noninvasive UC Alternatives and Measure-vention”
Yun Li
Geisel School of Medicine at Dartmouth
“Developing and implementing clinical pathway(s) for hospitalized injection drug users due to injection-related infection sequelae”
Learn more about the Student Hospitalist Scholar Grant at hospitalmedicine.org/scholargrant.
SPARK ONE: A tool to teach residents
SPARK ONE is a comprehensive, online self-assessment tool created specifically for hospital medicine professionals. The activity contains 450+ vignette-style multiple-choice questions covering 100% of the American Board of Internal Medicine’s Focused Practice in Hospital Medicine (FPHM) exam blueprint. This online tool can be utilized as a training mechanism for resident education on hospital medicine.
As a benefit of SHM membership, residents will receive a free subscription. SPARK ONE provides in-depth review of the following content areas:
- Cardiology
- Pulmonary Disease and Critical Care Medicine
- Gastroenterology and Hepatology
- Nephrology and Urology
- Endocrinology
- Hematology and Oncology
- Neurology
- Allergy, Immunology, Dermatology, Rheumatology and Transitions in Care
- Palliative Care, Medical Ethics and Decision-making
- Perioperative Medicine and Consultative Co-management
- Patient Safety
- Quality, Cost and Clinical Reasoning
“SPARK ONE provides a unique platform for academic institutions, engaging learners in directed learning sessions, reinforcing teaching points as we encounter specific conditions.” – Rachel E. Thompson, MD, MPH, SFHM
Visit hospitalmedicine.org/sparkone to learn more.
Sharpen your coding with the updated CODE-H
SHM’s Coding Optimally by Documenting Effectively for Hospitalists (CODE-H) has launched an updated program with all new content. It will now include eight recorded webinar sessions presented by expert faculty, downloadable resources, and an interactive discussion forum through the Hospital Medicine Exchange (HMX), enabling participants to ask questions and learn the most relevant best practices.
Following each webinar, learners will have the opportunity to complete an evaluation to redeem continuing medical education credits.
Webinars in the series include:
- E/M Basics Part I
- E/M Basics Part II
- Utilizing Other Providers in Your Practice
- EMR and Mitigating Risk
- Putting Time into Critical Care Documentation
- Time Based Services
- Navigating the Rules for Hospitalist Visits
- Challenges of Concurrent Care
To purchase CODE-H, visit hospitalmedicine.org/CODEH. If you have questions about the new program, please contact [email protected].
Set yourself apart as a Fellow in Hospital Medicine
The Fellow in Hospital Medicine (FHM) designation signals your commitment to the hospital medicine specialty and dedication to quality improvement and patient safety. This designation is available for hospital medicine practitioners, including practice administrators, nurse practitioners, and physician assistants. If you meet the prerequisites and complete the requirements, which are rooted in the Core Competencies in Hospital Medicine, you can apply for this prestigious designation and join more than 1,100 FHMs who are dedicated to the field of hospital medicine. Learn more and apply at hospitalmedicine.org/fellow.
New guide & modules on multimodal pain strategies for postoperative pain management
Pain management can pose multiple challenges in the acute care setting for hospitalists and front-line prescribers. While their first priority is to optimally manage pain in their patients, they also face the challenges of treating diverse patient populations, managing patient expectations, and considering how pain control and perceptions affect Hospital Consumer Assessment of Healthcare Providers and Systems scores. Furthermore, because of the ongoing opioid epidemic, prescribers must ensure that pain is managed responsibly and ethically.
To address these issues, SHM developed a guide to address how to work in an interdisciplinary team, identify impediments to implementation, and provide examples of appropriate pain management. In accompaniment with this Multimodal Pain Strategies Guide for Postoperative Pain Management, there are three modules presented by the authors which supplement the electronic guide.
To download the guide or view the modules, visit hospitalmedicine.org/pain.
Proven excellence through a unique education style: Academic Hospitalist Academy
Don’t miss the eighth annual Academic Hospitalist Academy (AHA), Sept. 25-28, 2017, at the Lakeway Resort and Spa in Austin, Texas. AHA attendees experience an energizing, interactive learning environment featuring didactics, small-group exercise and skill-building breakout sessions. Each full day of learning is facilitated by leading clinician-educators, hospitalist researchers, and clinical administrators in a 1 to 10 faculty to student ratio.
The Principal Goals of the Academy are to:
- Develop junior academic hospitalists as the premier teachers and educational leaders at their institutions
- Help academic hospitalists develop scholarly work and increase scholarly output
- Enhance awareness of the value of quality improvement and patient safety work
- Support academic promotion of all attendees
Don’t miss out on this unique, hands-on experience. Register before July 18, 2017, to receive the early-bird rates. Visit academichospitalist.org to learn more.
Choosing Wisely Case Study compendium now available
The Choosing Wisely Case Study Competition, hosted by SHM, sought submissions from hospitalists on innovative improvement initiatives implemented in their respective institutions. These initiatives reflect and promote movement toward reducing unnecessary medical tests and procedures and changing a culture that dictates, “More care is better care.”
Submissions were judged by the Choosing Wisely Subcommittee, a panel of SHM members, under adult and pediatric categories. One grand prize winner and three honorable mentions were selected from these categories. The compendium includes these case studies along with additional exemplary submissions.
View the Choosing Wisely Case Study Compendium at hospitalmedicine.org/choosingwisely.
Strengthen your interactions with the 5 Rs of Cultural Humility
Look inside this issue for your 5 Rs of Cultural Humility pocket card. It can be easily referenced on rounds and shared with colleagues. We hope to achieve heightened awareness of effective interactions. In addition to the definitions of each of the Rs, the card features questions to ask yourself before, during, and after every interaction to aid in attaining cultural humility.
For more information, visit hospitalmedicine.org/5Rs.
Brett Radler is communications specialist at the Society of Hospital Medicine.
HM17 On Demand now available
Couldn’t make it to Las Vegas for SHM’s annual meeting, Hospital Medicine 2017? HM17 On Demand gives you access to over 80 online audio and slide recordings from the hottest tracks, including clinical updates, rapid fire, pediatrics, comanagement, quality, and high-value care.
Additionally, you can earn up to 70 American Medical Association Physician Recognition Award Category 1 Credit(s) and up to 30 American Board of Internal Medicine Maintenance of Certification credits. HM17 attendees can also benefit by earning additional credits on the sessions you missed out on.
To easily access content through SHM’s Learning Portal, visit shmlearningportal.org/hm17-demand to learn more.
Chapter Excellence Awards
SHM is proud to recognize outstanding chapters for the fourth annual Chapter Excellence Awards. Each year, chapters strive to demonstrate growth, sustenance, and innovation within their chapter activities.
View more at www.hospitalmedicine.org/chapterexcellence. Please join SHM in congratulating the following chapters on their success!
Silver Chapters
Boston Association of Academic Hospital Medicine (BAAHM)
Charlotte Metro Area
Houston
Kentucky
Los Angeles
Minnesota
North Jersey
Pacific Northwest
Philadelphia Tri-State
Rocky Mountain
San Francisco Bay
South Central PA
Gold Chapters
New Mexico
Wiregrass
Platinum Chapters
IowaMaryland
Michigan
NYC/Westchester
St. Louis
Outstanding Chapter of the Year
Michigan
Rising Star Chapter
Wiregrass
Student Hospitalist Scholar grant winners
SHM’s Student Hospitalist Scholar Grant provides funds with which medical students can conduct mentored scholarly projects related to quality improvement and patient safety in the field of hospital medicine. The program offers a summer and a longitudinal option.
Congratulations to the 2017-2018 Student Hospitalist Scholar Grant recipients:Summer Program
Anton Garazha
Rosalind Franklin University of Medicine and Science
“Effectiveness of Communication During ICU to Ward Transfer and Association with Medical ICU Readmission”
Cole Hirschfeld
Weill Cornell Medical College
“The Role of Diagnostic Bone Biopsies in the Management of Osteomyelitis”
Farah Hussain
University of Cincinnati College of Medicine
“Better Understanding Clinical Deterioration in a Children’s Hospital”
Longitudinal Program
Monisha Bhatia
Vanderbilt University School of Medicine
“Using Electronic Medical Record Phenotypic Data to Predict Discharge Destination”
Victor Ekuta
University of California, San Diego School of Medicine
“Reducing CAUTI with Noninvasive UC Alternatives and Measure-vention”
Yun Li
Geisel School of Medicine at Dartmouth
“Developing and implementing clinical pathway(s) for hospitalized injection drug users due to injection-related infection sequelae”
Learn more about the Student Hospitalist Scholar Grant at hospitalmedicine.org/scholargrant.
SPARK ONE: A tool to teach residents
SPARK ONE is a comprehensive, online self-assessment tool created specifically for hospital medicine professionals. The activity contains 450+ vignette-style multiple-choice questions covering 100% of the American Board of Internal Medicine’s Focused Practice in Hospital Medicine (FPHM) exam blueprint. This online tool can be utilized as a training mechanism for resident education on hospital medicine.
As a benefit of SHM membership, residents will receive a free subscription. SPARK ONE provides in-depth review of the following content areas:
- Cardiology
- Pulmonary Disease and Critical Care Medicine
- Gastroenterology and Hepatology
- Nephrology and Urology
- Endocrinology
- Hematology and Oncology
- Neurology
- Allergy, Immunology, Dermatology, Rheumatology and Transitions in Care
- Palliative Care, Medical Ethics and Decision-making
- Perioperative Medicine and Consultative Co-management
- Patient Safety
- Quality, Cost and Clinical Reasoning
“SPARK ONE provides a unique platform for academic institutions, engaging learners in directed learning sessions, reinforcing teaching points as we encounter specific conditions.” – Rachel E. Thompson, MD, MPH, SFHM
Visit hospitalmedicine.org/sparkone to learn more.
Sharpen your coding with the updated CODE-H
SHM’s Coding Optimally by Documenting Effectively for Hospitalists (CODE-H) has launched an updated program with all new content. It will now include eight recorded webinar sessions presented by expert faculty, downloadable resources, and an interactive discussion forum through the Hospital Medicine Exchange (HMX), enabling participants to ask questions and learn the most relevant best practices.
Following each webinar, learners will have the opportunity to complete an evaluation to redeem continuing medical education credits.
Webinars in the series include:
- E/M Basics Part I
- E/M Basics Part II
- Utilizing Other Providers in Your Practice
- EMR and Mitigating Risk
- Putting Time into Critical Care Documentation
- Time Based Services
- Navigating the Rules for Hospitalist Visits
- Challenges of Concurrent Care
To purchase CODE-H, visit hospitalmedicine.org/CODEH. If you have questions about the new program, please contact [email protected].
Set yourself apart as a Fellow in Hospital Medicine
The Fellow in Hospital Medicine (FHM) designation signals your commitment to the hospital medicine specialty and dedication to quality improvement and patient safety. This designation is available for hospital medicine practitioners, including practice administrators, nurse practitioners, and physician assistants. If you meet the prerequisites and complete the requirements, which are rooted in the Core Competencies in Hospital Medicine, you can apply for this prestigious designation and join more than 1,100 FHMs who are dedicated to the field of hospital medicine. Learn more and apply at hospitalmedicine.org/fellow.
New guide & modules on multimodal pain strategies for postoperative pain management
Pain management can pose multiple challenges in the acute care setting for hospitalists and front-line prescribers. While their first priority is to optimally manage pain in their patients, they also face the challenges of treating diverse patient populations, managing patient expectations, and considering how pain control and perceptions affect Hospital Consumer Assessment of Healthcare Providers and Systems scores. Furthermore, because of the ongoing opioid epidemic, prescribers must ensure that pain is managed responsibly and ethically.
To address these issues, SHM developed a guide to address how to work in an interdisciplinary team, identify impediments to implementation, and provide examples of appropriate pain management. In accompaniment with this Multimodal Pain Strategies Guide for Postoperative Pain Management, there are three modules presented by the authors which supplement the electronic guide.
To download the guide or view the modules, visit hospitalmedicine.org/pain.
Proven excellence through a unique education style: Academic Hospitalist Academy
Don’t miss the eighth annual Academic Hospitalist Academy (AHA), Sept. 25-28, 2017, at the Lakeway Resort and Spa in Austin, Texas. AHA attendees experience an energizing, interactive learning environment featuring didactics, small-group exercise and skill-building breakout sessions. Each full day of learning is facilitated by leading clinician-educators, hospitalist researchers, and clinical administrators in a 1 to 10 faculty to student ratio.
The Principal Goals of the Academy are to:
- Develop junior academic hospitalists as the premier teachers and educational leaders at their institutions
- Help academic hospitalists develop scholarly work and increase scholarly output
- Enhance awareness of the value of quality improvement and patient safety work
- Support academic promotion of all attendees
Don’t miss out on this unique, hands-on experience. Register before July 18, 2017, to receive the early-bird rates. Visit academichospitalist.org to learn more.
Choosing Wisely Case Study compendium now available
The Choosing Wisely Case Study Competition, hosted by SHM, sought submissions from hospitalists on innovative improvement initiatives implemented in their respective institutions. These initiatives reflect and promote movement toward reducing unnecessary medical tests and procedures and changing a culture that dictates, “More care is better care.”
Submissions were judged by the Choosing Wisely Subcommittee, a panel of SHM members, under adult and pediatric categories. One grand prize winner and three honorable mentions were selected from these categories. The compendium includes these case studies along with additional exemplary submissions.
View the Choosing Wisely Case Study Compendium at hospitalmedicine.org/choosingwisely.
Strengthen your interactions with the 5 Rs of Cultural Humility
Look inside this issue for your 5 Rs of Cultural Humility pocket card. It can be easily referenced on rounds and shared with colleagues. We hope to achieve heightened awareness of effective interactions. In addition to the definitions of each of the Rs, the card features questions to ask yourself before, during, and after every interaction to aid in attaining cultural humility.
For more information, visit hospitalmedicine.org/5Rs.
Brett Radler is communications specialist at the Society of Hospital Medicine.
HM17 session summary: Nurse Practitioner/Physician Assistant special interest forum
Presenters
Tracy Cardin, ACNP, SFHM ; Emilie Thornhill, PA-C
Session summary
The Nurse Practitioner and Physician Assistant (NP/PA) special interest forum at HM17 drew more than 60 providers, including NPs, PAs, and physicians.
Emilie Thornhill, a certified PA and chair of the NP/PA Committee, and Tracy Cardin, SHM board member, updated the attendees regarding the work of the NP/PA committee over the last year. The committee has created a comprehensive “NP/PA Toolkit,” which was developed over the last 2 years in response to common inquiries about deployment and integration of NPs and PAs into Hospital Medicine practice groups.
The committee has also developed several goals for the coming year, including an “Optimization and Implementation Project,” intended to positively impact the shallow supply of highly-skilled and experienced HM NPs and PAs through development of partnerships, new content, and use of existing resources to provide a platform for effective workforce training and on-boarding.
The second half of the session was utilized to hear SHM member feedback and to solicit ideas for meaningful work that the committee could accomplish in order to better serve the SHM community. Members used the time to share and describe practice pattern variations and common shared challenges. Project suggestions included:
- Benchmarking Surveys related to NP/PA burnout, including aspects of protected time, engagement, and workload; scheduling and deployment models; and NP/PA designation as faculty or staff.
- Increased utilization and engagement with HMX as a platform for sharing ideas and success stories to increase HM NP/PA visibility.
- Creation of a “Bizarre Bylaws Blog” to disseminate best practices and improve hospital bylaws through innovative storytelling of antiquated bylaws.
- Improved NP and PA participation and engagement with local chapters.
Key takeaways for HM
- An NP/PA Toolkit resource to be posted on the SHM website.
- The NP/PA committee will transition to a Special Interest Group over the next year.
- Hospital Medicine Exchange (HMX) engagement and participation are encouraged.
- An “Implementation and Optimization Project” to help improve workforce development is pending for the coming year.
Nicolas Houghton is an NP hospitalist in Cleveland and an editorial board member of The Hospitalist.
Presenters
Tracy Cardin, ACNP, SFHM ; Emilie Thornhill, PA-C
Session summary
The Nurse Practitioner and Physician Assistant (NP/PA) special interest forum at HM17 drew more than 60 providers, including NPs, PAs, and physicians.
Emilie Thornhill, a certified PA and chair of the NP/PA Committee, and Tracy Cardin, SHM board member, updated the attendees regarding the work of the NP/PA committee over the last year. The committee has created a comprehensive “NP/PA Toolkit,” which was developed over the last 2 years in response to common inquiries about deployment and integration of NPs and PAs into Hospital Medicine practice groups.
The committee has also developed several goals for the coming year, including an “Optimization and Implementation Project,” intended to positively impact the shallow supply of highly-skilled and experienced HM NPs and PAs through development of partnerships, new content, and use of existing resources to provide a platform for effective workforce training and on-boarding.
The second half of the session was utilized to hear SHM member feedback and to solicit ideas for meaningful work that the committee could accomplish in order to better serve the SHM community. Members used the time to share and describe practice pattern variations and common shared challenges. Project suggestions included:
- Benchmarking Surveys related to NP/PA burnout, including aspects of protected time, engagement, and workload; scheduling and deployment models; and NP/PA designation as faculty or staff.
- Increased utilization and engagement with HMX as a platform for sharing ideas and success stories to increase HM NP/PA visibility.
- Creation of a “Bizarre Bylaws Blog” to disseminate best practices and improve hospital bylaws through innovative storytelling of antiquated bylaws.
- Improved NP and PA participation and engagement with local chapters.
Key takeaways for HM
- An NP/PA Toolkit resource to be posted on the SHM website.
- The NP/PA committee will transition to a Special Interest Group over the next year.
- Hospital Medicine Exchange (HMX) engagement and participation are encouraged.
- An “Implementation and Optimization Project” to help improve workforce development is pending for the coming year.
Nicolas Houghton is an NP hospitalist in Cleveland and an editorial board member of The Hospitalist.
Presenters
Tracy Cardin, ACNP, SFHM ; Emilie Thornhill, PA-C
Session summary
The Nurse Practitioner and Physician Assistant (NP/PA) special interest forum at HM17 drew more than 60 providers, including NPs, PAs, and physicians.
Emilie Thornhill, a certified PA and chair of the NP/PA Committee, and Tracy Cardin, SHM board member, updated the attendees regarding the work of the NP/PA committee over the last year. The committee has created a comprehensive “NP/PA Toolkit,” which was developed over the last 2 years in response to common inquiries about deployment and integration of NPs and PAs into Hospital Medicine practice groups.
The committee has also developed several goals for the coming year, including an “Optimization and Implementation Project,” intended to positively impact the shallow supply of highly-skilled and experienced HM NPs and PAs through development of partnerships, new content, and use of existing resources to provide a platform for effective workforce training and on-boarding.
The second half of the session was utilized to hear SHM member feedback and to solicit ideas for meaningful work that the committee could accomplish in order to better serve the SHM community. Members used the time to share and describe practice pattern variations and common shared challenges. Project suggestions included:
- Benchmarking Surveys related to NP/PA burnout, including aspects of protected time, engagement, and workload; scheduling and deployment models; and NP/PA designation as faculty or staff.
- Increased utilization and engagement with HMX as a platform for sharing ideas and success stories to increase HM NP/PA visibility.
- Creation of a “Bizarre Bylaws Blog” to disseminate best practices and improve hospital bylaws through innovative storytelling of antiquated bylaws.
- Improved NP and PA participation and engagement with local chapters.
Key takeaways for HM
- An NP/PA Toolkit resource to be posted on the SHM website.
- The NP/PA committee will transition to a Special Interest Group over the next year.
- Hospital Medicine Exchange (HMX) engagement and participation are encouraged.
- An “Implementation and Optimization Project” to help improve workforce development is pending for the coming year.
Nicolas Houghton is an NP hospitalist in Cleveland and an editorial board member of The Hospitalist.
VIDEO: Software predicts septic shock in hospitalized patients
WASHINGTON – Researchers have devised a program that can predict severe sepsis or septic shock about 12-30 hours in advance of its onset in hospitalized patients, a feat they hope will allow them to apply early interventions to stave off impending sepsis.
“We’d love to see a change in sepsis mortality. Will earlier recognition and implementation of the sepsis bundle – fluids, antibiotics, etc. – improve outcomes?” wondered Heather M. Giannini, MD, in a video interview at an international conference of the American Thoracic Society.
The computer program works by monitoring all the data that enter a patient’s electronic health record during hospitalization. Researchers developed it and designed it specifically for inpatients who are not in the intensive care unit or emergency department.
Results from initial testing during October-December 2015 in 10,448 patients hospitalized at one of three participating Philadelphia hospitals showed the program predicted subsequent severe sepsis or septic shock with a sensitivity of 26% and a specificity of 98%, reported Dr. Giannini, a researcher in the Center for Evidence-Based Practice at the University of Pennsylvania in Philadelphia. Analysis also showed a positive likelihood ratio of 13 for severe sepsis or septic shock actually occurring following an alert generated by the computer program, a level indicating a “very strong” ability to predict sepsis, she said.
Dr. Giannini and her associates developed the prediction program using a technique called “computational machine learning,” an alternative to standard logistic regression modeling that is better suited to analyzing large data sets and can better integrate outlier data points. They took EHR data for all non-ICU, non-ED inpatients at three Philadelphia hospitals during a 3-year period during 2011-2014 and had the program focus particularly on EHR data gleaned from the nearly 1,000 patients who developed severe sepsis or septic shock during the 12 hours preceding the start of these sepsis events. The analysis identified patients as having developed severe sepsis or shock if they had a blood draw positive for infection at the same time as having a blood lactate level above 2.2 mmol/L or a systolic blood pressure below 90 mm Hg.
To create the algorithm the machine-learning device compared the EHR entries for patients who developed severe sepsis or septic shock with EHR data from patients who did not, a process that involved hundred of thousands of data points, Dr. Giannini said. This identified 587 individual types of relevant EHR data entries and ranked them from most important to least important. Important, novel determinants of impending severe sepsis identified this way included anion gap, blood urea nitrogen, and platelet count. The development process also confirmed an important role for many classic markers of septic shock, such as respiration rate, heart rate, and temperature.
The researchers designed the algorithm to have a moderate level of sensitivity to avoid “alert fatigue” from generating too many alarms for impending severe sepsis. Their goal was for clinicians to receive no more than about 10 alerts per day for each hospital.
“We are satisfied with the sensitivity. We felt it was better to have too few alerts rather than overwhelm clinicians. About 10 alerts a day is reasonable,” Dr. Giannini explained. During initial 2015 testing, the system generated a daily average of 11 alerts.
The video associated with this article is no longer available on this site. Please view all of our videos on the MDedge YouTube channel
[email protected]
On Twitter @mitchelzoler
Development of this algorithm is tremendously important and exciting. It is an example of how researchers can use big data to predict patient outcomes and use that information to help deliver better patient care.
The algorithm’s performance so far is laudable and extremely promising, and has great potential to help deliver better care to patients when they need it, but it requires further validation. The potential importance of earlier identification of septic shock is huge.
Michelle N. Gong, MD, is professor of medicine and chief of research in the division of critical care at Albert Einstein College of Medicine and Montefiore Medical Center in New York. She had no disclosures. She made these comments in an interview.
Development of this algorithm is tremendously important and exciting. It is an example of how researchers can use big data to predict patient outcomes and use that information to help deliver better patient care.
The algorithm’s performance so far is laudable and extremely promising, and has great potential to help deliver better care to patients when they need it, but it requires further validation. The potential importance of earlier identification of septic shock is huge.
Michelle N. Gong, MD, is professor of medicine and chief of research in the division of critical care at Albert Einstein College of Medicine and Montefiore Medical Center in New York. She had no disclosures. She made these comments in an interview.
Development of this algorithm is tremendously important and exciting. It is an example of how researchers can use big data to predict patient outcomes and use that information to help deliver better patient care.
The algorithm’s performance so far is laudable and extremely promising, and has great potential to help deliver better care to patients when they need it, but it requires further validation. The potential importance of earlier identification of septic shock is huge.
Michelle N. Gong, MD, is professor of medicine and chief of research in the division of critical care at Albert Einstein College of Medicine and Montefiore Medical Center in New York. She had no disclosures. She made these comments in an interview.
WASHINGTON – Researchers have devised a program that can predict severe sepsis or septic shock about 12-30 hours in advance of its onset in hospitalized patients, a feat they hope will allow them to apply early interventions to stave off impending sepsis.
“We’d love to see a change in sepsis mortality. Will earlier recognition and implementation of the sepsis bundle – fluids, antibiotics, etc. – improve outcomes?” wondered Heather M. Giannini, MD, in a video interview at an international conference of the American Thoracic Society.
The computer program works by monitoring all the data that enter a patient’s electronic health record during hospitalization. Researchers developed it and designed it specifically for inpatients who are not in the intensive care unit or emergency department.
Results from initial testing during October-December 2015 in 10,448 patients hospitalized at one of three participating Philadelphia hospitals showed the program predicted subsequent severe sepsis or septic shock with a sensitivity of 26% and a specificity of 98%, reported Dr. Giannini, a researcher in the Center for Evidence-Based Practice at the University of Pennsylvania in Philadelphia. Analysis also showed a positive likelihood ratio of 13 for severe sepsis or septic shock actually occurring following an alert generated by the computer program, a level indicating a “very strong” ability to predict sepsis, she said.
Dr. Giannini and her associates developed the prediction program using a technique called “computational machine learning,” an alternative to standard logistic regression modeling that is better suited to analyzing large data sets and can better integrate outlier data points. They took EHR data for all non-ICU, non-ED inpatients at three Philadelphia hospitals during a 3-year period during 2011-2014 and had the program focus particularly on EHR data gleaned from the nearly 1,000 patients who developed severe sepsis or septic shock during the 12 hours preceding the start of these sepsis events. The analysis identified patients as having developed severe sepsis or shock if they had a blood draw positive for infection at the same time as having a blood lactate level above 2.2 mmol/L or a systolic blood pressure below 90 mm Hg.
To create the algorithm the machine-learning device compared the EHR entries for patients who developed severe sepsis or septic shock with EHR data from patients who did not, a process that involved hundred of thousands of data points, Dr. Giannini said. This identified 587 individual types of relevant EHR data entries and ranked them from most important to least important. Important, novel determinants of impending severe sepsis identified this way included anion gap, blood urea nitrogen, and platelet count. The development process also confirmed an important role for many classic markers of septic shock, such as respiration rate, heart rate, and temperature.
The researchers designed the algorithm to have a moderate level of sensitivity to avoid “alert fatigue” from generating too many alarms for impending severe sepsis. Their goal was for clinicians to receive no more than about 10 alerts per day for each hospital.
“We are satisfied with the sensitivity. We felt it was better to have too few alerts rather than overwhelm clinicians. About 10 alerts a day is reasonable,” Dr. Giannini explained. During initial 2015 testing, the system generated a daily average of 11 alerts.
The video associated with this article is no longer available on this site. Please view all of our videos on the MDedge YouTube channel
[email protected]
On Twitter @mitchelzoler
WASHINGTON – Researchers have devised a program that can predict severe sepsis or septic shock about 12-30 hours in advance of its onset in hospitalized patients, a feat they hope will allow them to apply early interventions to stave off impending sepsis.
“We’d love to see a change in sepsis mortality. Will earlier recognition and implementation of the sepsis bundle – fluids, antibiotics, etc. – improve outcomes?” wondered Heather M. Giannini, MD, in a video interview at an international conference of the American Thoracic Society.
The computer program works by monitoring all the data that enter a patient’s electronic health record during hospitalization. Researchers developed it and designed it specifically for inpatients who are not in the intensive care unit or emergency department.
Results from initial testing during October-December 2015 in 10,448 patients hospitalized at one of three participating Philadelphia hospitals showed the program predicted subsequent severe sepsis or septic shock with a sensitivity of 26% and a specificity of 98%, reported Dr. Giannini, a researcher in the Center for Evidence-Based Practice at the University of Pennsylvania in Philadelphia. Analysis also showed a positive likelihood ratio of 13 for severe sepsis or septic shock actually occurring following an alert generated by the computer program, a level indicating a “very strong” ability to predict sepsis, she said.
Dr. Giannini and her associates developed the prediction program using a technique called “computational machine learning,” an alternative to standard logistic regression modeling that is better suited to analyzing large data sets and can better integrate outlier data points. They took EHR data for all non-ICU, non-ED inpatients at three Philadelphia hospitals during a 3-year period during 2011-2014 and had the program focus particularly on EHR data gleaned from the nearly 1,000 patients who developed severe sepsis or septic shock during the 12 hours preceding the start of these sepsis events. The analysis identified patients as having developed severe sepsis or shock if they had a blood draw positive for infection at the same time as having a blood lactate level above 2.2 mmol/L or a systolic blood pressure below 90 mm Hg.
To create the algorithm the machine-learning device compared the EHR entries for patients who developed severe sepsis or septic shock with EHR data from patients who did not, a process that involved hundred of thousands of data points, Dr. Giannini said. This identified 587 individual types of relevant EHR data entries and ranked them from most important to least important. Important, novel determinants of impending severe sepsis identified this way included anion gap, blood urea nitrogen, and platelet count. The development process also confirmed an important role for many classic markers of septic shock, such as respiration rate, heart rate, and temperature.
The researchers designed the algorithm to have a moderate level of sensitivity to avoid “alert fatigue” from generating too many alarms for impending severe sepsis. Their goal was for clinicians to receive no more than about 10 alerts per day for each hospital.
“We are satisfied with the sensitivity. We felt it was better to have too few alerts rather than overwhelm clinicians. About 10 alerts a day is reasonable,” Dr. Giannini explained. During initial 2015 testing, the system generated a daily average of 11 alerts.
The video associated with this article is no longer available on this site. Please view all of our videos on the MDedge YouTube channel
[email protected]
On Twitter @mitchelzoler
AT ATS 2017
Key clinical point:
Major finding: The program predicted severe sepsis with a sensitivity of 26% and specificity of 98%.
Data source: A total of 10,448 inpatients at three Philadelphia hospitals during October-December 2015.
Disclosures: Dr. Giannini had no disclosures.
