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1.
Cureus ; 13(1): e12822, 2021 Jan 20.
Article in English | MEDLINE | ID: mdl-33628687

ABSTRACT

A foreign body in the upper aerodigestive tract can be life-threatening. It is especially challenging for surgeons and anesthesiologists working in a limited shared workspace. A case is presented of an 83-year-old woman with end-stage dementia afflicted with oral fixation as defined as overeating or putting objects in the mouth other than food. She appeared asymptomatic although she had altered baseline mentation and was found to have ingested a large foreign object. This case provides an opportunity to discuss the unique challenges of performing anesthesia on patients undergoing the extraction of a large upper aerodigestive tract foreign body, complicated by end-stage dementia.

2.
Surgery ; 170(1): 320-324, 2021 07.
Article in English | MEDLINE | ID: mdl-33334583

ABSTRACT

Physicians use perioperative decision-support tools to mitigate risks and maximize benefits to achieve the most successful outcome for patients. Contemporary risk-assessment practices augment surgeons' judgement and experience with decision-support algorithms driven by big data and machine learning. These algorithms accurately assess risk for a wide range of postoperative complications by parsing large datasets and performing complex calculations that would be cumbersome for busy clinicians. Even with these advancements, large gaps in perioperative risk assessment remain; decision-support algorithms often cannot account for risk-reduction therapies applied during a patient's perioperative course and do not quantify tradeoffs between competing goals of care (eg, balancing postoperative pain control with the risk of respiratory depression or balancing intraoperative volume resuscitation with the risk for complications from pulmonary edema). Multiobjective optimization solutions have been applied to similar problems successfully but have not yet been applied to perioperative decision support. Given the large volume of data available via electronic medical records, including intraoperative data, it is now feasible to successfully apply multiobjective optimization in perioperative care. Clinical application of multiobjective optimization would require semiautomated pipelines for analytics and reporting model outputs and a careful development and validation process. Under these circumstances, multiobjective optimization has the potential to support personalized, patient-centered, shared decision-making with precision and balance.


Subject(s)
Algorithms , Anesthesia , Decision Support Techniques , Perioperative Care , Clinical Decision-Making , Humans , Pain Management , Pain Measurement , Risk Assessment/methods , Surgical Procedures, Operative
3.
Anesth Analg ; 127(4): 1028-1034, 2018 10.
Article in English | MEDLINE | ID: mdl-29782402

ABSTRACT

BACKGROUND: Successful conflict resolution is vital for effective teamwork and is critical for safe patient care in the operating room. Being able to appreciate the differences in training backgrounds, individual knowledge and opinions, and task interdependency necessitates skilled conflict management styles when addressing various clinical and professional scenarios. The goal of this study was to assess conflict styles in anesthesiology residents via self- and counterpart assessment during participation in simulated conflict scenarios. METHODS: Twenty-two first-year anesthesiology residents (first postgraduate year) participated in this study, which aimed to assess and summarize conflict management styles by 3 separate metrics. One metric was self-assessment with the Thomas-Kilmann Conflict Mode Instrument (TKI), summarized as percentile scores (0%-99%) for 5 conflict styles: collaborating, competing, accommodating, avoiding, and compromising. Participants also completed self- and counterpart ratings after interactions in a simulated conflict scenario using the Dutch Test for Conflict Handling (DUTCH), with scores ranging from 5 to 25 points for each of 5 conflict styles: yielding, compromising, forcing, problem solving, and avoiding. Higher TKI and DUTCH scores would indicate a higher preference for a given conflict style. Sign tests were used to compare self- and counterpart ratings on the DUTCH scores, and Spearman correlations were used to assess associations between TKI and DUTCH scores. RESULTS: On the TKI, the anesthesiology residents had the highest median percentile scores (with first quartile [Q1] and third quartile [Q3]) in compromising (67th, Q1-Q3 = 27-87) and accommodating (69th, Q1-Q3 = 30-94) styles, and the lowest scores for competing (32nd, Q1-Q3 = 10-57). After each conflict scenario, residents and their counterparts on the DUTCH reported higher median scores for compromising (self: 16, Q1-Q3 = 14-16; counterpart: 16, Q1-Q3 = 15-16) and problem solving (self: 17, Q1-Q3 = 16-18; counterpart: 16, Q1-Q3 = 16-17), and lower scores for forcing (self: 13, Q1-Q3 = 10-15; counterpart: 13, Q1-Q3 = 13-15) and avoiding (self: 14, Q1-Q3 = 10-16; counterpart: 14.5, Q1-Q3 = 11-16). There were no significant differences (P > .05) between self- and counterpart ratings on the DUTCH. Overall, the correlations between TKI and DUTCH scores were not statistically significant (P > .05). CONCLUSIONS: Findings from our study demonstrate that our cohort of first postgraduate year anesthesiology residents predominantly take a more cooperative and problem-solving approach to handling conflict. By understanding one's dominant conflict management style through this type of analysis and appreciating the value of other styles, one may become better equipped to manage different conflicts as needed depending on the situations.


Subject(s)
Anesthesiologists/psychology , Anesthesiology/education , Conflict, Psychological , Dissent and Disputes , Education, Medical, Continuing/methods , Internship and Residency , Negotiating/psychology , Anesthesiologists/education , Attitude of Health Personnel , Cooperative Behavior , Humans , Interdisciplinary Communication , Patient Care Team
4.
Stud Health Technol Inform ; 132: 556-61, 2008.
Article in English | MEDLINE | ID: mdl-18391367

ABSTRACT

The current report summarizes case studies from an Office of Naval Research (ONR) funded project to compare the effects of Virtual Reality Graded Exposure Therapy (VRGET) with a treatment as usual control condition in active-duty Navy Corpsmen, Navy SeaBees and Navy and Marine Corps Support Personnel. Details of the collaborative program between the Virtual Reality Medical Center (VRMC) and Naval Medical Center San Diego (NMCSD) will be discussed.


Subject(s)
Monitoring, Physiologic , Occupational Exposure , Stress Disorders, Post-Traumatic/therapy , User-Computer Interface , Warfare , Adult , Humans , Male , Middle Aged , Military Personnel/psychology , Stress Disorders, Post-Traumatic/physiopathology , United States
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