Risks Associated with Quality Care among Hispanic and White Populations-A Cross-Sectional Comparison Study.

Quality care in healthcare is a multifaceted concept that encompasses the execution of effective medical treatments and the patient's overall experience. It involves a multitude of factors, including effectiveness, safety, timeliness, equity, and patient centeredness, which are important in shaping the healthcare landscape. This cross-sectional study used the data from the Health Information National Trends Survey 6 (HINTS 6), which collects data on various aspects of health communication and information-seeking behaviors, to investigate the factors associated with quality care among White and Hispanic populations. All adults who participated in HINTS 6 and visited healthcare service at least once in the past 12 months were included in this study. Multivariable logistic regression was used to determine the association between quality care and delay or discriminated care with the adjustment of all other sociodemographic variables. We analyzed a total of 3611 participants. Poor social determinants of health (SDOHs) (OR 0.61, CI 0.43-0.88, p = 0.008), delayed needed medical care (OR 0.34, CI 0.26-0.43, p < 0.001), and discriminated care (OR 0.29, CI 0.15-0.54, p < 0.001) were all negatively associated with optimal quality care. Negative SDOHs could also be positively associated with delayed care and discriminated care.

The association between electronic health information usage and patient-centered communication: a cross sectional analysis from the Health Information National Trends Survey (HINTS).

BACKGROUND: Patient-provider communication can be assessed by the patient-centered communication (PCC) score. With rapid development of electronic health (eHealth) information usage, we are uncertain of their role in PCC. Our study aims to determine the association between PCC and eHealth usage with the analysis of national representative survey data. METHODS: This is a cross sectional analysis using the Health Information National Trends Survey 5 (HINTS 5) cycle 1 to cycle 4 data (2017-2020). Seven specific questions were used for PCC assessment, and eHealth usage was divided into two types (private-eHealth and public-eHealth usage). A multivariate logistic regression was performed to determine the association between PCC and eHealth usage after the adjustment of other social, demographic, and clinical variables. RESULTS: Our study analyzed a total of 13,055 unweighted participants representing a weighted population of 791,877,728. Approximately 43% of individuals used private eHealth and 19% used public eHealth. The adjusted odds ratio (AOR) of private-eHealth usage associated with positive PCC was 1.17 (95% CI 1.02-1.35, p = 0.027). The AOR of public-eHealth usage associated with positive PCC was 0.84 (95% CI 0.71-0.99, p = 0.043). CONCLUSION: Our study found that eHealth usage association with PCC varies. Private-eHealth usage was positively associated with PCC, whereas public-eHealth usage was negatively associated with PCC.

The Association of Name Recognition, Empathy Perception, and Satisfaction With Resident Physicians' Care Amongst Patients in an Academic Emergency Department.

Background: Recognition of the provider's name, provider empathy, and the patient's satisfaction with their care are patient-provider rapport measures. This study aimed to determine: 1) resident physicians' name recognition by patients in the emergency department; and 2) name recognition in association with patient perception of the resident's empathy and their satisfaction with the resident's care. Methods: This was a prospective observational study. A patient recognizing a resident physician was defined as the patient remembering a resident's name, understanding the level of training, and understanding a resident's role in patient care. A patient's perception of resident physician empathy was measured by the Jefferson Scale of Patient Perception of Physician Empathy (JSPPPE). Patient satisfaction of the resident was measured utilizing a real-time satisfaction survey. Multivariate logistic regressions were performed to determine the association amongst patient recognition of resident physicians, JSPPPE, and patient satisfaction after adjustments were made for demographics and resident training level. Results: We enrolled 30 emergency medicine resident physicians and 191 patients. Only 26% of studied patients recognized resident physicians. High JSPPPE scores were given by 39% of patients recognizing resident physicians compared to 5% of those who were not recognized (P = 0.013). High patient satisfaction scores were recorded in 31% of patients who recognized resident physicians compared to 7% who did not (P = 0.008). The adjusted odds ratios of patient recognition of resident physicians to high JSPPPE and high satisfaction scores were 5.29 (95% confidence interval (CI): 1.33 - 21.02, P = 0.018) and 6.12 (1.84 - 20.38, P = 0.003) respectively. Conclusions: Patient recognition of resident physicians is low in our study. However, patient recognition of resident physicians is associated with a higher patient perception of physician empathy and higher patient satisfaction. Our study suggests that resident education advocating for patient recognition of their healthcare provider's status needs to be emphasized as part of patient-centered health care.

Large observational study on risks predicting emergency department return visits and associated disposition deviations.

OBJECTIVE: A common emergency department (ED) patient care outcome metric is 72-hour ED return visits (EDRVs). Risks predictive of EDRV vary in different studies. However, risk differences associated with related versus unrelated EDRV and subsequent EDRV disposition deviations (EDRVDD) are rarely addressed. We aim to compare the potential risk patterns predictive of related and unrelated EDRV and further determine those potential risks predictive of EDRVDD. METHODS: We conducted a large retrospective observational study from September 1, 2015 through June 30, 2016. ED Patient demographic characteristics and clinical metrics were compared among patients of 1) related; 2) unrelated; and 3) no EDRVs. EDRVDD was defined as obvious disposition differences between initial ED visit and return visits. A multivariate multinomial logistic regression was performed to determine the independent risks predictive of EDRV and EDRVDD after adjusting for all confounders. RESULTS: A total of 63,990 patients were enrolled; 4.65% were considered related EDRV, and 1.80% were unrelated. The top risks predictive of EDRV were homeless, patient left without being seen, eloped, or left against medical advice. The top risks predictive of EDRVDD were geriatric and whether patients had primary care physicians regardless as to whether patient returns were related or unrelated to their initial ED visits. CONCLUSION: Over 6% of patients experienced ED return visits within 72 hours. Though risks predicting such revisits were multifactorial, similar risks were identified not only for ED return visits, but also for return ED visit disposition deviations.

Status of Emergency Department Seventy-Two Hour Return Visits Among Homeless Patients.

BACKGROUND: We aim to externally validate the status of emergency department (ED) appropriate utilization and 72-h ED returns among homeless patients. METHODS: This is a retrospective single-center observational study. Patients were divided into two groups (homeless versus non-homeless). Patients' general characteristics, clinical variables, ED appropriate utilization, and ED return disposition deviations were compared and analyzed separately. RESULTS: Study enrolled a total of 63,990 ED visits. Homeless patients comprised 9.3% (5,926) of visits. Higher ED 72-h returns occurred among homeless patients in comparison to the non-homeless patients (17% versus 5%, P < 0.001). Rate of significant ED disposition deviations (e.g., admission, triage to operation room, or death) on return visits were lower in homeless patients when compared to non-homeless patient populations (15% versus 23%, P < 0.001). CONCLUSIONS: Though ED return rate was higher among homeless patients, return visit case management seems appropriate, indicating that 72-h ED returns might not be an optimal healthcare quality measurement for homeless patients.

Use of the SONET Score to Evaluate High Volume Emergency Department Overcrowding: A Prospective Derivation and Validation Study.

Background. The accuracy and utility of current Emergency Department (ED) crowding estimation tools remain uncertain in EDs with high annual volumes. We aimed at deriving a more accurate tool to evaluate overcrowding in a high volume ED setting and determine the association between ED overcrowding and patient care outcomes. Methods. A novel scoring tool (SONET: Severely overcrowded-Overcrowded-Not overcrowded Estimation Tool) was developed and validated in two EDs with both annual volumes exceeding 100,000. Patient care outcomes including the number of left without being seen (LWBS) patients, average length of ED stay, ED 72-hour returns, and mortality were compared under the different crowding statuses. Results. The total number of ED patients, the number of mechanically ventilated patients, and patient acuity levels were independent risk factors affecting ED overcrowding. SONET was derived and found to better differentiate severely overcrowded, overcrowded, and not overcrowded statuses with similar results validated externally. In addition, SONET scores correlated with increased length of ED stay, number of LWBS patients, and ED 72-hour returns. Conclusions. SONET might be a better fit to determine high volume ED overcrowding. ED overcrowding negatively impacts patient care operations and often produces poor patient perceptions of standardized care delivery.

The inaccuracy of determining overcrowding status by using the national ED overcrowding study tool.

BACKGROUND: Emergency department (ED) crowding has become more common, and perceptions of crowding vary among different health care providers. The National Emergency Department Overcrowding Study (NEDOCS) tool is the most commonly used tool to estimate ED crowding but still uncertain of its reliability in different ED settings. OBJECTIVE: The objectives of this study are to determine the accuracy of using the NEDOCS tool to evaluate overcrowding in an extremely high-volume ED and assess the reliability and consistency of different providers' perceptions of ED crowding. MATERIAL AND METHODS: This was a 2-phase study. In phase 1, ED crowding was determined by the NEDOCS tool. The ED length of stay and number of patients who left without being seen were analyzed. In phase 2, a survey of simulated ED census scenarios was completed by different providers. The interrater and intrarater agreements of ED crowding were tested. RESULTS: In phase 1, the subject ED was determined to be overcrowded more than 75% of the time in which nearly 50% was rated as severely overcrowded by the NEDOCS tool. No statistically significant difference was found in terms of the average length of stay and the number of left without being seen patients under different crowding categories. In phase 2, 88 surveys were completed. A moderate level of agreement between health care providers was reached (κ = 0.5402, P < .0001). Test-retest reliability among providers was high (r = 0.8833, P = .0007). The strength of agreement between study groups and the NEDOCS was weak (κ = 0.3695, P < .001). CONCLUSION: Using the NEDOCS tool to determine ED crowding might be inaccurate in an extremely high-volume ED setting.

How Charles Huggins made his Nobel prize winning discovery--in his own words: an historic audio recording. Interviewed by Willard Goodwin and Elmer Bell.

On February 12, 1962, 4 years before he was awarded the Nobel Prize, Charles Huggins gave an informal interview to Dr. Willard Goodwin and co-workers at UCLA on how he made one of the greatest discoveries in our field-hormonal therapy for prostate cancer. In this fascinating story, he tells how he transformed the investigation of what causes a hydrocele into a Nobel Prize winning discovery.

Ultrasound can accurately guide gastrostomy tube replacement and confirm proper tube placement at the bedside.

BACKGROUND: Malfunctioning or dislodged gastrostomy tubes (G-tubes) often require urgent replacement and reinsertion in the Emergency Department (ED). Few data exist regarding the best technique for bedside catheter replacement and verification, and individual operator preferences vary. Although a few reports have described the use of ultrasound guidance during the initial percutaneous insertion, no data are available concerning its role during subsequent G-tube replacements. OBJECTIVE: We sought to investigate the utility of bedside ultrasonography during G-tube replacements in the ED. METHODS: This was a prospective pilot study conducted at a Level 1 Trauma Center with an annual census of 90,000 patients. Seven adults and three children with malfunctioning G-tubes were enrolled. Three tubes were cracked and leaking, and seven tubes had been dislodged. Under ultrasound, a new G-tube was inserted through the previously fashioned tract. After insertion, color Doppler was applied over the catheter tip to enhance visualization during gentle tube oscillation. RESULTS: Ultrasound successfully visualized G-tube replacement in all 10 patients. Application of color Doppler over the G-tube tip during catheter oscillation enhanced placement confirmation. Sonographic findings were corroborated with gastric content aspiration, contrast-enhanced radiographs, and successful use of the new G-tubes. No false tracts were identified during ultrasound-guided insertion, post-procedure sonographic confirmation, or subsequent radiographs. CONCLUSION: The improper replacement of a G-tube can lead to devastating consequences. Verifying appropriate placement through aspirate evaluation can be misleading, and post-procedure radiographs increase radiation exposure and ED wait times. Bedside ultrasonography can be used to guide catheter insertion while providing a safe and quick adjunct to confirm proper G-tube placement.