The Effect of Waiting Time on Patient Perceptions of Care Quality

Nottingham, Quinton; Johnson, Dana M.; Russell, Roberta S.

doi:10.1080/10686967.2018.1404368

Cited by 41 publications

(34 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Worsening waiting times have been shown to be associated with patient dissatisfaction, 54 delayed access to treatments, 7 poorer clinical outcomes, 55,56 increased costs, 57 inequality, 58,59 and patient anxiety. 60 For patients with chronic health conditions, there may be a cumulative burden from waiting time.…”

Section: The Consequences Of Increasing Wait Timementioning

confidence: 99%

Waiting Time as an Indicator for Health Services Under Strain: A Narrative Review

McIntyre

Chow

2020

INQUIRY

View full text Add to dashboard Cite

As pressure increases on public health systems globally, a potential consequence is that this is transferred to patients in the form of longer waiting times to receive care. In this review, we overview what waiting for health care encompasses, its measurement, and the data available in terms of trends and comparability. We also discuss whether waiting time is equally distributed according to socioeconomic status. Finally, we discuss the policy implications and potential approaches to addressing the burden of waiting time. Waiting time for elective surgery and emergency department care is the best described type of waiting time, and it either increases or remains unchanged across multiple developed countries. There are many challenges in drawing direct comparisons internationally, as definitions for these types of waiting times vary. There are less data on waiting time from other settings, but existing data suggest waiting time presents a significant barrier to health care access for a range of health services. There is also evidence that waiting time is unequally distributed to those of lower socioeconomic status, although this may be improving in some countries. Further work to better clarify definitions, identify driving factors, and understand hidden waiting times and identify opportunities for reducing waiting time or better using waiting time could improve health outcomes of our health services.

show abstract

Section: The Consequences Of Increasing Wait Timementioning

confidence: 99%

Waiting Time as an Indicator for Health Services Under Strain: A Narrative Review

McIntyre

Chow

2020

INQUIRY

View full text Add to dashboard Cite

show abstract

“…Waiting time on the premises (henceforth WTP), and attention received by patients in their interaction with health professionals (henceforth ATT) are both documented in the literature as building satisfaction [24,25]. Apart from that, lay-people experience information asymmetrically when relating to health services.…”

Section: Waiting Time Attention and Information Reliabilitymentioning

confidence: 99%

Combining Direct and Indirect Measurements to Assess Patients’ Satisfaction with the Quality of Public Health Services in Romania: Uncovering Structural Mechanisms and Their Implications

Druică

Mihăilă

Burcea

et al. 2019

IJERPH

View full text Add to dashboard Cite

Introduction: Patients’ satisfaction was extensively researched over the last decades, given its role in building loyalty, compliance to treatment, prevention, and eventually higher levels of wellbeing and improved health status. Patients’ feedback on the perceived quality of health services can be incorporated into practice; therefore, understanding factors and mechanisms responsible for patients’ satisfaction allows providers to tailor targeted interventions. Method: A questionnaire assessing patients’ perception of the quality of health services was administered to a country-representative sample of 1500 Romanian patients. Using a partial least squares—path modeling approach (PLS-PM), with cross-sectional data, we developed a variance-based structural model, emphasizing the mediating role of trust and satisfaction with various categories of health services. Results: We confirmed the mediating role of trust in shaping the relationship between the procedural accuracy of health professionals, along with the perceived intensity of their interaction with patients, and patients’ experienced quality of the health services. We confirmed the mediating role of satisfaction by the categories of services in the relationship between waiting time on the premises, attention received, and the perceived reliability of the information received, as predictors, and the experienced quality of the health services. In addition, indirect assessment of patients’ satisfaction is a good predictor for direct assessment, thereby affirming the idea that the results of the two types of evaluations converge. Discussions: One of the most efficient solutions to increase both patients’ satisfaction and their compliance is to empower the communication dimension between patients and health practitioners. Given the non-linear relationships among variables, we advocate that, unless the nature of the relationships between satisfaction and its predictors is understood, practical interventions could fail. The most relevant variable for intervention is the degree of attention patients perceive they received. We suggest three methods to turn waiting time into attention given to patients.

show abstract

“…Consequently, the navigation plan will be biased with negative effects toward men, based on information related to their higher tolerance to pain. Similarly, the robot could learn that women have more tolerance to wait longer for medical treatments and spend more overall time than men in the emergency rooms (Nottingham et al, 2018 ). In both situations, the behavior of the robot will be biased given that it systematically benefits a specific group of people.…”

Section: Case Studies and Discussionmentioning

confidence: 99%

“…To carry out this task, robots are equipped with sensors that allow them to perceive the environment and a path planning system that enables them to compute a feasible route to achieve the navigation goal. So far, mobile robots have been successfully employed in various applications, such as material transportation, patrolling, rescue operation, cleaning, guidance, warehouse automation, among others (Nolfi and Floreano, 2002;Poudel, 2013;Hasan et al, 2014;Bogue, 2016). This also elucidates that mobile robot applications are moving closer from the industry to everyday tasks in households, offices, and public spaces.…”

Section: Introductionmentioning

confidence: 95%

From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation

2021

View full text Add to dashboard Cite

The exponentially increasing advances in robotics and machine learning are facilitating the transition of robots from being confined to controlled industrial spaces to performing novel everyday tasks in domestic and urban environments. In order to make the presence of robots safe as well as comfortable for humans, and to facilitate their acceptance in public environments, they are often equipped with social abilities for navigation and interaction. Socially compliant robot navigation is increasingly being learned from human observations or demonstrations. We argue that these techniques that typically aim to mimic human behavior do not guarantee fair behavior. As a consequence, social navigation models can replicate, promote, and amplify societal unfairness, such as discrimination and segregation. In this work, we investigate a framework for diminishing bias in social robot navigation models so that robots are equipped with the capability to plan as well as adapt their paths based on both physical and social demands. Our proposed framework consists of two components: learning which incorporates social context into the learning process to account for safety and comfort, and relearning to detect and correct potentially harmful outcomes before the onset. We provide both technological and societal analysis using three diverse case studies in different social scenarios of interaction. Moreover, we present ethical implications of deploying robots in social environments and propose potential solutions. Through this study, we highlight the importance and advocate for fairness in human-robot interactions in order to promote more equitable social relationships, roles, and dynamics and consequently positively influence our society.

show abstract

The Effect of Waiting Time on Patient Perceptions of Care Quality

Cited by 41 publications

References 38 publications

Waiting Time as an Indicator for Health Services Under Strain: A Narrative Review

Waiting Time as an Indicator for Health Services Under Strain: A Narrative Review

Combining Direct and Indirect Measurements to Assess Patients’ Satisfaction with the Quality of Public Health Services in Romania: Uncovering Structural Mechanisms and Their Implications

From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation

Contact Info

Product

Resources

About