Refusal of emergency medical care: An analysis of patients who left without being seen, eloped, and left against medical advice

Marco, Catherine A.; Bryant, Morgan Litchfield; Landrum, B. Mark; Drerup, Brenden; Weeman, Mitchell

doi:10.1016/j.ajem.2019.158490

Cited by 13 publications

(19 citation statements)

References 28 publications

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“…Pham et al 7 analyzed data from NHAMCS and reported higher levels of LWBS at the extremes of age, which was corroborated by our analyses. Contrary to our findings, many studies show the pediatric population as being more predisposed to LWBS 14,20,21 . Ding et al 20 found that patients lacking insurance, self‐paying, or having Medicaid had higher rates of LWBS, and we placed these 3 categories into a single group for our analysis.…”

Section: Discussioncontrasting

confidence: 96%

“…Contrary to our findings, many studies show the pediatric population as being more predisposed to LWBS. 14,20,21 Ding et al 20 found that patients lacking insurance, self-paying, or having Medicaid had higher rates of LWBS, and we placed these 3 categories into a single group for our analysis. Other studies conducted in the United States have also reported a lack of insurance for children 6 and adults 5 to be important factors.…”

Section: Discussionmentioning

confidence: 99%

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Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Sheraton¹,

Gooch²,

Kashyap

2020

JACEP Open

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Section: Discussioncontrasting

confidence: 96%

Section: Discussionmentioning

confidence: 99%

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Sheraton¹,

Gooch²,

Kashyap

2020

JACEP Open

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“… USA Patient-centered approach; documentation Original research Authors (year of publication) Title Country of publication Type of research Domains/themes Strengths Weaknesses Brenner et al (2016) [ 28 ] Against Medical Advice: A Survey of ED Clinicians' Rationale for Use USA Retrospective cohort study Patient-centered approach; documentation Collects factual information about an existing phenomenon Allows to appreciate current practices Important recall bias: small number of physicians included in the study Edwards et al (2013) [ 41 ] Discharge against medical advice: how often do we intervene? USA Retrospective cohort study Patient-centered approach; harm reduction; documentation Single institution: possibility to miss some information that may not be recorded in charts Lekas et al (2016) [ 20 ] The role of patient-provider interactions: Using an accounts framework to explain hospital discharges against medical advice USA Retrospective cohort study Patient-centered approach; alternative discharge; harm reduction; documentation Small sample of 33 HIV infected patients Limits the scope of this study’s applicability Machin et al (2018) [ 15 ] An Alternative View of Self-Discharge Against Medical Advice: An Opportunity to Demonstrate Empathy, Empowerment, and Care UK Semi-structured in depth interviews Patient-centered approach; alternative discharge; informed refusal; harm reduction; documentation Allows a thorough understanding of the phenomenon Small sample size Limited demographic details, and Self-selecting participants Marco et al (2021) [ 24 ...…”

Section: Resultsmentioning

confidence: 99%

“…A strategic way for physicians to approach patients leaving AMA is to position them at the center of care by actively listening to their concerns, thus increasing the quality of communication [15,20,21]. Physicians must aim without prejudice or bias to identify why patients wish to leave AMA [1,12,[22][23][24]. Correctly identifying the reason for departure is essential to set a base for the patient-physician discussion.…”

Section: Patient-centered Approachmentioning

confidence: 99%

A step-by-step approach to patients leaving against medical advice (AMA) in the emergency department

2022

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Objectives Patients leaving against medical advice (AMA) can be distressing for emergency physicians trying to navigate the medical, social, psychological, and legal ramifications of the situation in a fast-paced and chaotic environment. To guide physicians in fulfilling their obligation of care, we aimed to synthesize the best approaches to patients leaving AMA. Methods We conducted a scoping review across various fields of work, research context and methodology to synthesize the most relevant strategies for emergency physicians attending patients leaving AMA. We searched Medline, CINAHL, PSYCHO Legal Source, PsycINFO, PsycEXTRA, Psychological and Behavioural Sciences collection, SocIndex and Scopus. Search strategies included controlled vocabulary (i.e., MESH) and keywords relevant to the subject chosen by a team of four people, including two specialized librarians. Results The literature review included 34 relevant papers about approaches to patients leaving AMA: 8 case presentations, 4 ethical case analyses, 10 legal letters, 4 reviews and 8 original studies. The main identified strategies were prioritizing a patient-centered approach, proposing alternative discharge and reducing harm while properly documenting the encounter. Conclusion A systematic approach to patients leaving AMA could help improve patient care, support physicians and decrease stigmatization of this population. We advocate that emergency physicians should receive training on how to approach patients leaving AMA to limit the impact on this vulnerable population.

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“…The association between patient experience and the perception of quality of care has been demonstrated by Schneider et al [ 10 ]. Reasonable wait times are expected by patients [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Barriers to and Facilitators of Automated Patient Self-scheduling for Health Care Organizations: Scoping Review

Woodcock¹

2022

J Med Internet Res

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Background Appointment management in the outpatient setting is important for health care organizations, as waits and delays lead to poor outcomes. Automated patient self-scheduling of outpatient appointments has demonstrable advantages in the form of patients’ arrival rates, labor savings, patient satisfaction, and more. Despite evidence of the potential benefits of self-scheduling, the organizational uptake of self-scheduling in health care has been limited. Objective The objective of this scoping review is to identify and to catalog existing evidence of the barriers to and facilitators of self-scheduling for health care organizations. Methods A scoping review was conducted by searching 4 databases (PubMed, CINAHL, Business Source Ultimate, and Scopus) and systematically reviewing peer-reviewed studies. The Consolidated Framework for Implementation Research was used to catalog the studies. Results In total, 30 full-text articles were included in this review. The results demonstrated that self-scheduling initiatives have increased over time, indicating the broadening appeal of self-scheduling. The body of literature regarding intervention characteristics is appreciable. Outer setting factors, including national policy, competition, and the response to patients’ needs and technology access, have played an increasing role in influencing implementation over time. Self-scheduling, compared with using the telephone to schedule an appointment, was most often cited as a relative advantage. Scholarly pursuit lacked recommendations related to the framework’s inner setting, characteristics of individuals, and processes as determinants of implementation. Future discoveries regarding these Consolidated Framework for Implementation Research domains may help detect, categorize, and appreciate organizational-level barriers to and facilitators of self-scheduling to advance knowledge regarding this solution. Conclusions This scoping review cataloged evidence of the existence, advantages, and intervention characteristics of patient self-scheduling. Automated self-scheduling may offer a solution to health care organizations striving to positively affect access. Gaps in knowledge regarding the uptake of self-scheduling by health care organizations were identified to inform future research.

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Refusal of emergency medical care: An analysis of patients who left without being seen, eloped, and left against medical advice

Cited by 13 publications

References 28 publications

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

A step-by-step approach to patients leaving against medical advice (AMA) in the emergency department

Barriers to and Facilitators of Automated Patient Self-scheduling for Health Care Organizations: Scoping Review

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