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Article ; Online: Special issue on cognitive informatics methods for interactive clinical systems.

Kannampallil, Thomas G / Patel, Vimla L

2017 Volume 71, Page(s) 207–210

MeSH term(s)	Cognition ; Evidence-Based Medicine ; Humans ; Medical Informatics ; Translational Medical Research
Language	English
Publishing date	2017-06-07
Publishing country	United States
Document type	Editorial ; Introductory Journal Article
ZDB-ID	2057141-0
ISSN	1532-0480 ; 1532-0464
ISSN (online)	1532-0480
ISSN	1532-0464
DOI	10.1016/j.jbi.2017.06.003
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Article ; Online: Effect of acute postsurgical pain trajectories on 30-day and 1-year pain.

Awadalla, Saria S / Winslow, Victoria / Avidan, Michael S / Haroutounian, Simon / Kannampallil, Thomas G

PloS one

2022 Volume 17, Issue 6, Page(s) e0269455

Abstract: Untreated pain after surgery leads to poor patient satisfaction, longer hospital length of stay, lower health-related quality of life, and non-compliance with rehabilitation regimens. The aim of this study is to characterize the structure of acute pain ... ...

Abstract	Untreated pain after surgery leads to poor patient satisfaction, longer hospital length of stay, lower health-related quality of life, and non-compliance with rehabilitation regimens. The aim of this study is to characterize the structure of acute pain trajectories during the postsurgical hospitalization period and quantify their association with pain at 30-days and 1-year after surgery. This cohort study included 2106 adult (≥18 years) surgical patients who consented to participate in the SATISFY-SOS registry (February 1, 2015 to September 30, 2017). Patients were excluded if they did not undergo invasive surgeries, were classified as outpatients, failed to complete follow up assessments at 30-days and 1-year following surgery, had greater than 4-days of inpatient stay, and/or recorded fewer than four pain scores during their acute hospitalization period. The primary exposure was the acute postsurgical pain trajectories identified by a machine learning-based latent class approach using patient-reported pain scores. Clinically meaningful pain (≥3 on a 0-10 scale) at 30-days and 1-year after surgery were the primary and secondary outcomes, respectively. Of the study participants (N = 2106), 59% were female, 91% were non-Hispanic White, and the mean (SD) age was 62 (13) years; 41% of patients underwent orthopedic surgery and 88% received general anesthesia. Four acute pain trajectory clusters were identified. Pain trajectories were significantly associated with clinically meaningful pain at 30-days (p = 0.007), but not at 1-year (p = 0.79) after surgery using covariate-adjusted logistic regression models. Compared to Cluster 1, the other clusters had lower statistically significant odds of having pain at 30-days after surgery (Cluster 2: [OR = 0.67, 95%CI (0.51-0.89)]; Cluster 3:[OR = 0.74, 95%CI (0.56-0.99)]; Cluster 4:[OR = 0.46, 95%CI (0.26-0.82)], all p<0.05). Patients in Cluster 1 had the highest cumulative likelihood of pain and pain intensity during the latter half of their acute hospitalization period (48-96 hours), potentially contributing to the higher odds of pain during the 30-day postsurgical period. Early identification and management of high-risk pain trajectories can help in ascertaining appropriate pain management interventions. Such interventions can mitigate the occurrence of long-term disabilities associated with pain.
MeSH term(s)	Acute Pain/etiology ; Adult ; Cohort Studies ; Female ; Humans ; Male ; Middle Aged ; Pain Measurement ; Pain, Postoperative/etiology ; Quality of Life
Language	English
Publishing date	2022-06-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0269455
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Article: Echo: A Large Display Interactive Visualization of ICU Data for Effective Care HandOffs.

Thomas, Manu Mathew / Kannampallil, Thomas / Abraham, Joanna / Marai, G Elisabeta

2017 IEEE Workshop on Visual Analytics in Healthcare (VAHC) : 1 October 2017. Workshop on Visual Analytics in Healthcare (8th : 2017 : Phoenix, Ariz.)

2019 Volume 2017, Page(s) 47–54

Abstract: One of the significant challenges of care transitions in Intensive Care Units (ICUs) is the lack of effective support tools for outgoing clinicians to find, filter, organize, and annotate information that can be effectively handed off to the incoming ... ...

Abstract	One of the significant challenges of care transitions in Intensive Care Units (ICUs) is the lack of effective support tools for outgoing clinicians to find, filter, organize, and annotate information that can be effectively handed off to the incoming team. We present a large display interactive multivariate visual approach, aimed towards supporting clinicians during the transition of care. We first provide a characterization of the problem domain in terms of data and tasks, based on an observation session at the University of Illinois Hospital, and on interviews with several biomedical researchers and ICU clinicians. Informed by this experience, we design a scalable, interactive visual approach that supports both overview and detail views of ICU patient data, as well as anomaly detection, comparison, and annotation of the data. We demonstrate a large-display implementation of the visualization on an existing anonymized ICU dataset. Feedback from domain experts indicates this approach successfully meets the requirements of effective care transitions.
Language	English
Publishing date	2019-11-04
Publishing country	United States
Document type	Journal Article
DOI	10.1109/VAHC.2017.8387500
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Article ; Online: Risk factors associated with physician trainee concern over missed educational opportunities during the COVID-19 pandemic.

Lou, Sunny S / Goss, Charles W / Evanoff, Bradley A / Duncan, Jennifer G / Kannampallil, Thomas

BMC medical education

2021 Volume 21, Issue 1, Page(s) 216

Abstract: Background: The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in patient volume, impacting physician trainee education due to lost clinical and didactic ... ...

Abstract	Background: The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in patient volume, impacting physician trainee education due to lost clinical and didactic opportunities. We measured the prevalence of trainee concern over missed educational opportunities and investigated the risk factors leading to such concerns. Methods: All residents and fellows at a large academic medical center were invited to participate in a web-based survey in May of 2020. Participants responded to questions regarding demographic characteristics, specialty, primary assigned responsibility during the previous 2 weeks (clinical, education, or research), perceived concern over missed educational opportunities, and burnout. Multivariable logistic regression was used to assess the relationship between missed educational opportunities and the measured variables. Results: 22% (301 of 1375) of the trainees completed the survey. 47% of the participants were concerned about missed educational opportunities. Trainees assigned to education at home had 2.85 [95%CI 1.33-6.45] greater odds of being concerned over missed educational opportunities as compared with trainees performing clinical work. Trainees performing research were not similarly affected [aOR = 0.96, 95%CI (0.47-1.93)]. Trainees in pathology or radiology had 2.51 [95%CI 1.16-5.68] greater odds of concern for missed educational opportunities as compared with medicine. Trainees with greater concern over missed opportunities were more likely to be experiencing burnout (p = 0.038). Conclusions: Trainees in radiology or pathology and those assigned to education at home were more likely to be concerned about their missed educational opportunities. Residency programs should consider providing trainees with research or at home clinical opportunities as an alternative to self-study should future need for reduced clinical hours arise.
MeSH term(s)	COVID-19 ; Education, Medical, Graduate/trends ; Humans ; Internship and Residency ; Pandemics ; Physicians ; Risk Factors ; Surveys and Questionnaires
Language	English
Publishing date	2021-04-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2044473-4
ISSN	1472-6920 ; 1472-6920
ISSN (online)	1472-6920
ISSN	1472-6920
DOI	10.1186/s12909-021-02665-0
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Article ; Online: Effect of acute postsurgical pain trajectories on 30-day and 1-year pain.

Saria S Awadalla / Victoria Winslow / Michael S Avidan / Simon Haroutounian / Thomas G Kannampallil

PLoS ONE, Vol 17, Iss 6, p e

2022 Volume 0269455

Abstract	Untreated pain after surgery leads to poor patient satisfaction, longer hospital length of stay, lower health-related quality of life, and non-compliance with rehabilitation regimens. The aim of this study is to characterize the structure of acute pain trajectories during the postsurgical hospitalization period and quantify their association with pain at 30-days and 1-year after surgery. This cohort study included 2106 adult (≥18 years) surgical patients who consented to participate in the SATISFY-SOS registry (February 1, 2015 to September 30, 2017). Patients were excluded if they did not undergo invasive surgeries, were classified as outpatients, failed to complete follow up assessments at 30-days and 1-year following surgery, had greater than 4-days of inpatient stay, and/or recorded fewer than four pain scores during their acute hospitalization period. The primary exposure was the acute postsurgical pain trajectories identified by a machine learning-based latent class approach using patient-reported pain scores. Clinically meaningful pain (≥3 on a 0-10 scale) at 30-days and 1-year after surgery were the primary and secondary outcomes, respectively. Of the study participants (N = 2106), 59% were female, 91% were non-Hispanic White, and the mean (SD) age was 62 (13) years; 41% of patients underwent orthopedic surgery and 88% received general anesthesia. Four acute pain trajectory clusters were identified. Pain trajectories were significantly associated with clinically meaningful pain at 30-days (p = 0.007), but not at 1-year (p = 0.79) after surgery using covariate-adjusted logistic regression models. Compared to Cluster 1, the other clusters had lower statistically significant odds of having pain at 30-days after surgery (Cluster 2: [OR = 0.67, 95%CI (0.51-0.89)]; Cluster 3:[OR = 0.74, 95%CI (0.56-0.99)]; Cluster 4:[OR = 0.46, 95%CI (0.26-0.82)], all p<0.05). Patients in Cluster 1 had the highest cumulative likelihood of pain and pain intensity during the latter half of their acute hospitalization period ...
Keywords	Medicine ; R ; Science ; Q
Subject code	616
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effect of acute postsurgical pain trajectories on 30-day and 1-year pain

Saria S. Awadalla / Victoria Winslow / Michael S. Avidan / Simon Haroutounian / Thomas G. Kannampallil

PLoS ONE, Vol 17, Iss

2022 Volume 6

Abstract	Untreated pain after surgery leads to poor patient satisfaction, longer hospital length of stay, lower health-related quality of life, and non-compliance with rehabilitation regimens. The aim of this study is to characterize the structure of acute pain trajectories during the postsurgical hospitalization period and quantify their association with pain at 30-days and 1-year after surgery. This cohort study included 2106 adult (≥18 years) surgical patients who consented to participate in the SATISFY-SOS registry (February 1, 2015 to September 30, 2017). Patients were excluded if they did not undergo invasive surgeries, were classified as outpatients, failed to complete follow up assessments at 30-days and 1-year following surgery, had greater than 4-days of inpatient stay, and/or recorded fewer than four pain scores during their acute hospitalization period. The primary exposure was the acute postsurgical pain trajectories identified by a machine learning-based latent class approach using patient-reported pain scores. Clinically meaningful pain (≥3 on a 0–10 scale) at 30-days and 1-year after surgery were the primary and secondary outcomes, respectively. Of the study participants (N = 2106), 59% were female, 91% were non-Hispanic White, and the mean (SD) age was 62 (13) years; 41% of patients underwent orthopedic surgery and 88% received general anesthesia. Four acute pain trajectory clusters were identified. Pain trajectories were significantly associated with clinically meaningful pain at 30-days (p = 0.007), but not at 1-year (p = 0.79) after surgery using covariate-adjusted logistic regression models. Compared to Cluster 1, the other clusters had lower statistically significant odds of having pain at 30-days after surgery (Cluster 2: [OR = 0.67, 95%CI (0.51–0.89)]; Cluster 3:[OR = 0.74, 95%CI (0.56–0.99)]; Cluster 4:[OR = 0.46, 95%CI (0.26–0.82)], all p<0.05). Patients in Cluster 1 had the highest cumulative likelihood of pain and pain intensity during the latter half of their acute hospitalization period ...
Keywords	Medicine ; R ; Science ; Q
Subject code	616
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effects of Persistent Exposure to COVID-19 on Mental Health Outcomes Among Trainees: a Longitudinal Survey Study.

Goss, Charles W / Duncan, Jennifer G / Lou, Sunny S / Holzer, Katherine J / Evanoff, Bradley A / Kannampallil, Thomas

Journal of general internal medicine

2022 Volume 37, Issue 5, Page(s) 1204–1210

Abstract: Background: The rapid spread of the coronavirus disease 2019 (COVID-19) has created considerable strain on the physical and mental health of healthcare workers around the world. The effects have been acute for physician trainees-a unique group ... ...

Abstract	Background: The rapid spread of the coronavirus disease 2019 (COVID-19) has created considerable strain on the physical and mental health of healthcare workers around the world. The effects have been acute for physician trainees-a unique group functioning simultaneously as learners and care providers with limited autonomy. Objective: To investigate the longitudinal effects of physician trainee exposure to patients being tested for COVID-19 on stress, anxiety, depression, and burnout using three surveys conducted during the early phase of the pandemic. Design: Longitudinal survey study. Participants: All physician trainees (N = 1375) at an academic medical center. Main measure: Assess the relationship between repeated exposure to patients being tested for COVID-19 and stress, anxiety, depression, and burnout. Key results: Three hundred eighty-nine trainees completed the baseline survey (28.3%). Of these, 191 and 136 completed the ensuing surveys. Mean stress, anxiety, and burnout decreased by 21% (95% confidence interval (CI): - 28 to - 12%; P < 0.001), 25% (95% CI: - 36 to - 11%; P < 0.001), and 13% (95% CI: - 18 to - 7%; P < 0.001), respectively, per survey. However, for each survey time point, there was mean increase in stress, anxiety, and burnout per additional exposure: stress [24% (95% CI: + 12 to + 38%; P < 0.001)], anxiety [22% (95% CI: + 2 to + 46%; P = 0.026)], and burnout [18% (95% CI: + 10 to + 28%; P < 0.001)]. For depression, the association between exposure was strongest for the third survey, where mean depression scores increased by 33% per additional exposure (95% CI: + 18 to + 50%; P < 0.001). Conclusions: Training programs should adapt to address the detrimental effects of the "pileup" of distress associated with persistent exposure through adaptive programs that allow flexibility for time off and recovery.
MeSH term(s)	Anxiety/epidemiology ; Burnout, Professional/epidemiology ; COVID-19/epidemiology ; Depression/epidemiology ; Health Personnel/psychology ; Humans ; Longitudinal Studies ; Outcome Assessment, Health Care ; SARS-CoV-2 ; Surveys and Questionnaires
Language	English
Publishing date	2022-01-28
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-021-07350-y
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Article ; Online: Temporal Associations Between EHR-Derived Workload, Burnout, and Errors: a Prospective Cohort Study.

Lou, Sunny S / Lew, Daphne / Harford, Derek R / Lu, Chenyang / Evanoff, Bradley A / Duncan, Jennifer G / Kannampallil, Thomas

Journal of general internal medicine

2022 Volume 37, Issue 9, Page(s) 2165–2172

Abstract: Background: The temporal progression and workload-related causal contributors to physician burnout are not well-understood.: Objective: To characterize burnout's time course and evaluate the effect of time-varying workload on burnout and medical ... ...

Abstract	Background: The temporal progression and workload-related causal contributors to physician burnout are not well-understood. Objective: To characterize burnout's time course and evaluate the effect of time-varying workload on burnout and medical errors. Design: Six-month longitudinal cohort study with measurements of burnout, workload, and wrong-patient orders every 4 weeks. Participants: Seventy-five intern physicians in internal medicine, pediatrics, and anesthesiology at a large academic medical center. Main measures: Burnout was measured using the Professional Fulfillment Index survey. Workload was collected from electronic health record (EHR) audit logs and summarized as follows: total time spent on the EHR, after-hours EHR time, patient load, inbox time, chart review time, note-writing time, and number of orders. Wrong-patient orders were assessed using retract-and-reorder events. Key results: Seventy-five of 104 interns enrolled (72.1%) in the study. A total of 337 surveys and 8,863,318 EHR-based actions were analyzed. Median burnout score across the cohort across all time points was 1.2 (IQR 0.7-1.7). Individual-level burnout was variable (median monthly change 0.3, IQR 0.1-0.6). In multivariable analysis, increased total EHR time (β=0.121 for an increase from 54.5 h per month (25th percentile) to 123.0 h per month (75th percentile), 95%CI=0.016-0.226), increased patient load (β=0.130 for an increase from 4.9 (25th percentile) to 7.1 (75th percentile) patients per day, 95%CI=0.053-0.207), and increased chart review time (β=0.096 for an increase from 0.39 (25th percentile) to 0.59 (75th percentile) hours per patient per day, 95%CI=0.015-0.177) were associated with an increased burnout score. After adjusting for the total number of ordering sessions, burnout was not statistically associated with an increased rate of wrong-patient orders (rate ratio=1.20, 95%CI=0.76-1.89). Conclusions: Burnout and recovery were associated with recent clinical workload for a cohort of physician trainees, highlighting the elastic nature of burnout. Wellness interventions should focus on strategies to mitigate sustained elevations of work responsibilities.
MeSH term(s)	Burnout, Professional/epidemiology ; Burnout, Professional/etiology ; Child ; Electronic Health Records ; Humans ; Longitudinal Studies ; Prospective Studies ; Workload
Language	English
Publishing date	2022-06-16
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-022-07620-3
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Article ; Online: Cognitive informatics in biomedicine and healthcare.

Patel, Vimla L / Kannampallil, Thomas G

Journal of biomedical informatics

2015 Volume 53, Page(s) 3–14

Abstract: Cognitive Informatics (CI) is a burgeoning interdisciplinary domain comprising of the cognitive and information sciences that focuses on human information processing, mechanisms and processes within the context of computing and computer applications. ... ...

Abstract	Cognitive Informatics (CI) is a burgeoning interdisciplinary domain comprising of the cognitive and information sciences that focuses on human information processing, mechanisms and processes within the context of computing and computer applications. Based on a review of articles published in the Journal of Biomedical Informatics (JBI) between January 2001 and March 2014, we identified 57 articles that focused on topics related to cognitive informatics. We found that while the acceptance of CI into the mainstream informatics research literature is relatively recent, its impact has been significant - from characterizing the limits of clinician problem-solving and reasoning behavior, to describing coordination and communication patterns of distributed clinical teams, to developing sustainable and cognitively-plausible interventions for supporting clinician activities. Additionally, we found that most research contributions fell under the topics of decision-making, usability and distributed team activities with a focus on studying behavioral and cognitive aspects of clinical personnel, as they performed their activities or interacted with health information systems. We summarize our findings within the context of the current areas of CI research, future research directions and current and future challenges for CI researchers.
MeSH term(s)	Brain-Computer Interfaces ; Cognition ; Computational Biology/methods ; Computational Biology/trends ; Decision Making ; Delivery of Health Care ; Humans ; Intensive Care Units ; Interdisciplinary Communication ; Medical Informatics ; Operating Rooms ; Problem Solving ; Reproducibility of Results ; Research Design ; Workflow
Language	English
Publishing date	2015-02
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2057141-0
ISSN	1532-0480 ; 1532-0464
ISSN (online)	1532-0480
ISSN	1532-0464
DOI	10.1016/j.jbi.2014.12.007
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Article ; Online: When past is not a prologue: Adapting informatics practice during a pandemic.

Kannampallil, Thomas G / Foraker, Randi E / Lai, Albert M / Woeltje, Keith F / Payne, Philip R O

Journal of the American Medical Informatics Association : JAMIA

2020 Volume 27, Issue 7, Page(s) 1142–1146

Abstract: Data and information technology are key to every aspect of our response to the current coronavirus disease 2019 (COVID-19) pandemic-including the diagnosis of patients and delivery of care, the development of predictive models of disease spread, and the ... ...

Abstract	Data and information technology are key to every aspect of our response to the current coronavirus disease 2019 (COVID-19) pandemic-including the diagnosis of patients and delivery of care, the development of predictive models of disease spread, and the management of personnel and equipment. The increasing engagement of informaticians at the forefront of these efforts has been a fundamental shift, from an academic to an operational role. However, the past history of informatics as a scientific domain and an area of applied practice provides little guidance or prologue for the incredible challenges that we are now tasked with performing. Building on our recent experiences, we present 4 critical lessons learned that have helped shape our scalable, data-driven response to COVID-19. We describe each of these lessons within the context of specific solutions and strategies we applied in addressing the challenges that we faced.
MeSH term(s)	Betacoronavirus ; COVID-19 ; Coronavirus Infections/epidemiology ; Datasets as Topic ; Electronic Health Records ; Humans ; Medical Informatics ; Pandemics ; Pneumonia, Viral/epidemiology ; SARS-CoV-2
Keywords	covid19
Language	English
Publishing date	2020-04-24
Publishing country	England
Document type	Journal Article
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocaa073
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