The Patient's Voice: Development of an Adolescent Hospital Quality of Care Survey (AHQOCS)

2019 ◽  
Vol 49 ◽  
pp. 43-50 ◽  
Author(s):  
Valerie Lapp
2012 ◽  
Vol 35 (6) ◽  
pp. 566-575 ◽  
Author(s):  
Matthew D. McHugh ◽  
Amy Witkoski Stimpfel

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Diana Benea ◽  
Valeria Raparelli ◽  
hassan behlouli ◽  
Louise Pilote ◽  
Rachel Dryer

Introduction: The extent to which race influences in-hospital quality of care among young adults with acute myocardial infarction (AMI) is unknown. We examined racial differences in in-hospital quality of AMI care in young adults and described the patient and/or clinical characteristics associated with potential disparities in care. Methods: Data from the GENESIS-PRAXY (Canada) and the VIRGO (U.S.) prospective cohorts of young adults with AMI were analyzed. Among a total of 4,048 adults with AMI (≤55 years) (median=49 years [IQR 44-52], 22% non-white, 58% women), we calculated an in-hospital quality of care score (QCS) for AMI (quality indicators divided by total, with higher scores indicating better care) based on AHA quality of care standards, reporting data disaggregated by race. We categorized race as white versus non-white, which included Black, Asian and North American Indigenous populations. Results: This cohort was comprised of 906 non-white individuals and 3142 white individuals. Non-white adults exhibited a clustering of adverse cardiac risk factors, psychosocial risk factors and comorbidities versus whites; they had higher rates of hypertension, diabetes, alcohol abuse and prior AMI and lower rates of physical activity. They were more likely to have a low SES and receive low social support, and were less likely to be employed, a primary earner, or married/living with a partner. Non-white individuals were also more likely to experience a NSTEMI and less likely to receive cardiac rehabilitation, smoking cessation counseling as well as dual antiplatelet therapy at discharge. Furthermore, non-white individuals had a lower crude QCS than whites (QCS=69.99 vs 73.29, P-value<0.0001). In the multivariable model adjusted for clinical and psychosocial factors, non-white race (LS Mean Difference=-1.49 95%CI -2.87, -0.11, P-value=0.0344) was independently associated with a lower in-hospital QCS. Conclusion: Non-white individuals with AMI exhibited higher rates of adverse psychosocial and clinical characteristics than white individuals yet non-white race was independently associated with lower in-hospital quality of care. Interventions are needed to improve quality of AMI care in non-white young adults.


2007 ◽  
Vol 85 (2) ◽  
pp. 3-12 ◽  
Author(s):  
Jeffrey A. Alexander ◽  
Bryan J. Weiner ◽  
Stephen M. Shortell ◽  
Laurence C. Baker

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Astrid Van Wilder ◽  
Jonas Brouwers ◽  
Bianca Cox ◽  
Luk Bruyneel ◽  
Dirk De Ridder ◽  
...  

Abstract Background Quality improvement (QI) initiatives such as accreditation, public reporting, inspection and pay-for-performance are increasingly being implemented globally. In Flanders, Belgium, a government policy for acute-care hospitals incorporates aforementioned initiatives. Currently, questions are raised on the sustainability of the present policy. Objective First, to summarise the various initiatives hospitals have adopted under government encouragement between 2008 and 2019. Second, to study the perspectives of healthcare stakeholders on current government policy. Methods In this multi-method study, we collected data on QI initiative implementation from governmental and institutional sources and through an online survey among hospital quality managers. We compiled an overview of QI initiative implementation for all Flemish acute-care hospitals between 2008 (n = 62) and 2019 (n = 53 after hospital mergers). Stakeholder perspectives were assessed via a second survey available to all healthcare employees and a focus group with healthcare policy experts was consulted. Variation between professions was assessed. Results QI initiatives have been increasingly implemented, especially from 2016 onwards, with the majority (87%) of hospitals having obtained a first accreditation label and all hospitals publicly reporting performance indicators, receiving regular inspections and having entered the pay-for-performance initiative. On the topic of external international accreditation, overall attitudes within the survey were predominantly neutral (36.2%), while 34.5% expressed positive and 29.3% negative views towards accreditation. In examining specific professional groups in-depth, we learned 58% of doctors regarded accreditation negatively, while doctors were judged to be the largest contributors to quality according to the majority of respondents. Conclusions Hospitals have demonstrated increased efforts into QI, especially since 2016, while perceptions on currently implemented QI initiatives among healthcare stakeholders are heterogeneous. To assure quality of care remains a top-priority for acute-care hospitals, we recommend a revision of the current multicomponent quality policy where the adoption of all initiatives is streamlined and co-created bottom-up.


Author(s):  
Afiq Izzudin A. Rahim ◽  
Mohd Ismail Ibrahim ◽  
Kamarul Imran Musa ◽  
Sook-Ling Chua ◽  
Najib Majdi Yaacob

Social media is emerging as a new avenue for hospitals and patients to solicit input on the quality of care. However, social media data is unstructured and enormous in volume. Moreover, no empirical research on the use of social media data and perceived hospital quality of care based on patient online reviews has been performed in Malaysia. The purpose of this study was to investigate the determinants of positive sentiment expressed in hospital Facebook reviews in Malaysia, as well as the association between hospital accreditation and sentiments expressed in Facebook reviews. From 2017 to 2019, we retrieved comments from 48 official public hospitals’ Facebook pages. We used machine learning to build a sentiment analyzer and service quality (SERVQUAL) classifier that automatically classifies the sentiment and SERVQUAL dimensions. We utilized logistic regression analysis to determine our goals. We evaluated a total of 1852 reviews and our machine learning sentiment analyzer detected 72.1% of positive reviews and 27.9% of negative reviews. We classified 240 reviews as tangible, 1257 reviews as trustworthy, 125 reviews as responsive, 356 reviews as assurance, and 1174 reviews as empathy using our machine learning SERVQUAL classifier. After adjusting for hospital characteristics, all SERVQUAL dimensions except Tangible were associated with positive sentiment. However, no significant relationship between hospital accreditation and online sentiment was discovered. Facebook reviews powered by machine learning algorithms provide valuable, real-time data that may be missed by traditional hospital quality assessments. Additionally, online patient reviews offer a hitherto untapped indication of quality that may benefit all healthcare stakeholders. Our results confirm prior studies and support the use of Facebook reviews as an adjunct method for assessing the quality of hospital services in Malaysia.


2010 ◽  
Vol 18 (2) ◽  
pp. 175-181 ◽  
Author(s):  
Danielle Fabiana Cucolo ◽  
Márcia Galan Perroca

This descriptive study aimed to calculate and compare the nursing staff at the medical-surgical clinical units of a philanthropic hospital in current and projected situations, and to investigate how much time the nursing team delivers patient care in the current and projected situations. Gaidzinski's method was used to calculate the nursing staff, and the equation proposed by the Hospital Quality Commitment (HQC) to estimate care hours. The findings showed an increase of 33% in the staff, with a 68.4% increase in the number of nurses and 15.6% in the number of technicians / nursing auxiliaries. According to the projected situation, the care hours varied from 5.7 to 7.2. The number of nursing and the mean care time provided to the patients were inadequate according to the clientele's care needs. This could impair the quality of care.


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