scholarly journals Exploring the association of hospice care on patient experience and outcomes of care

2016 ◽  
Vol 9 (1) ◽  
pp. e13-e13 ◽  
Author(s):  
Ruth Kleinpell ◽  
Eduard E Vasilevskis ◽  
Louis Fogg ◽  
E Wesley Ely
Keyword(s):  
Patient Satisfaction ◽  
Hospital Mortality ◽  
Patient Experience ◽  
Pain Control ◽  
Structural Equation ◽  
Hospice Care ◽  
American Hospital ◽  
American Hospital Association ◽  
Outcomes Of Care ◽  
Hospital Deaths

ObjectiveTo examine the association of the use of hospice care on patient experience and outcomes of care. Promoting high-value, safe and effective care is an international healthcare imperative. However, the extent to which hospice care may improve the value of care is not well characterised.MethodsA secondary analysis of variations in care was conducted using the Dartmouth Atlas Report, matched to the American Hospital Association Annual Survey Database to abstract organisational characteristics for 236 US hospitals to examine the relationship between hospice usage and a number of variables that represent care value, including hospital care intensity index, hospital deaths, intensive care unit (ICU) deaths, patient satisfaction and a number of patient quality indicators. Structural equation modelling was used to demonstrate the effect of hospice use on patient experience, clinical and efficiency outcomes.ResultsHospice admissions in the last 6 months of life were correlated with a number of variables, including increases in patient satisfaction ratings (r=0.448, p=0.01) and better pain control (r=0.491, p=0.01), and reductions in hospital days (r=−0.517, p=0.01), fewer hospital deaths (r=−0.842, p=0.01) and fewer deaths occurring with an ICU admission during hospitalisation (r=−0.358, p=0.01). The structural equation model identified that use of hospice care was inversely related to hospital mortality (−0.885) and ICU mortality (−0.457).ConclusionsThe results of this investigation demonstrate that greater use of hospice care during the last 6 months of life is associated with improved patient experience, including satisfaction and pain control, as well as clinical outcomes of care, including decreased ICU and hospital mortality.

scholarly journals Modeling the communication-satisfaction relationship in hospital patients

2019 ◽  
Vol 7 ◽  
pp. 205031211984792 ◽  
Author(s):  
Daniel Pelletier ◽  
Isabelle Green-Demers ◽  
Pierre Collerette ◽  
Michael Heberer
Keyword(s):  
Patient Satisfaction ◽  
Patient Experience ◽  
Structural Equation ◽  
Strong Relationship ◽  
Patient Characteristics ◽  
Integrated Approach ◽  
Communication Satisfaction ◽  
The Other ◽  
University Hospital ◽  
Equation Modeling

Objectives: Although it has long been known that communication with medical professionals presents a strong relationship with patient satisfaction, research on this topic has been hindered by conceptual and methodological issues (e.g. single-item measures, inclusion of idiosyncratic patient characteristics, etc.). Using a more comprehensive and integrated approach, this study had two objectives: to document the multidimensional structure of the Picker Patient Experience–15, and to test a patient communication/satisfaction model that organizes its dimensions in a conceptually logical array of relationships. First, the factorial structure of the Picker Patient Experience–15 was hypothesized to comprise five dimensions: communication with patient, with family, addressing fears/concerns, preparation for discharge, and patient satisfaction. Second, the hypothesized model included positive relationships between all four communications dimensions, on the one hand, and patient satisfaction, on the other. Within communication dimensions, communication with patient was hypothesized to be the incipient factor for other dimensions, and thus to be positively associated with the other three forms of communication. Methods: This research is based on a single time point design, which relied on administrative and questionnaire data. The study was conducted at a large University Hospital in Switzerland. The sample included 54,686 patients who received inpatient treatment, excluding those who were cared for in the intensive and intermediate care units. Patients filled out, over a 5-year period, the Picker Patient Experience questionnaire (PPE-15) after discharge (overall response rate of 41%). Results: The proposed five-factor structure of the Picker Patient Experience–15 was successfully supported by the results of a confirmatory factor analysis. Moreover, the hypothesized network of associations between communication and satisfaction latent constructs was substantiated using structural equation modeling. With the exception of the association between preparation for discharge and patient satisfaction, the hypothesized model was fully corroborated. Conclusion: A more in-depth understanding of patient satisfaction can be achieved when it is studied as a multifaceted phenomenon.

scholarly journals Rural Disparities in Hospital Patient Satisfaction: Multilevel Analysis of the Massachusetts AHA, SID, and HCAHPS Data

2019 ◽  
Vol 7 (4) ◽  
pp. 607-614
Author(s):  
Yu (Sunny) Kang ◽  
Huey-Ming Tzeng ◽  
Ting Zhang
Keyword(s):  
Patient Satisfaction ◽  
Hospital Environment ◽  
Full Time ◽  
Hospital Patient ◽  
Care Needs ◽  
Full Time Equivalent ◽  
American Hospital ◽  
American Hospital Association ◽  
Hispanic Patients ◽  
Satisfaction Measures

Introduction: Hospital patient satisfaction has been a salient policy concern. We examined rurality’s impact on patient satisfaction measures. Methodology: We examined patients (age 50 and up) from 65 rural and urban hospitals in Massachusetts, using the merged data from 2007 American Hospital Association Annual Survey, State Inpatient Database and Survey of Patients’ Hospital Experiences, utilizing Hierarchical binary logistic regression analyses to examine the rural disparities in patient satisfaction measures. Results: Relative to the urban location, rurality reduced the likelihood of cleanliness of environment (odds ratio = 0.66, 95% confidence interval: [0.63-0.70]); but increased the likelihood of staff responsiveness and quietness. Compared to Caucasian counterparts, Hispanic patients were less likely to reside in a quiet hospital. Compared to other payments, Medicare or Medicaid coverage each reduced the likelihood of staff responsiveness and cleanliness. Compared to other diagnoses, depressive or psychosis disorders predicted smaller odds in responsiveness and cleanliness. Anxiety diagnosis reduced the likelihood of cleanness and quietness. At the facility level, higher registered nurse full-time equivalent (FTE)s or being a teaching hospital increased the likelihood of all measures. Conclusion: Relative to the urban counterparts, rural patients experienced lower likelihood of staff responsiveness after adjusting for other factors. Compared to Caucasian patients, Hispanic patients were less likely to reside in quiet hospital environment. Research is needed to further explore the basis of these disparities. Mental health diagnoses in depressive and psychosis disorders also called upon further studies in special care needs.

scholarly journals Telepsychiatry adoption across hospitals in the United States: a cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhong Li ◽  
Sayward E. Harrison ◽  
Xiaoming Li ◽  
Peiyin Hung
Keyword(s):  
Continuity Of Care ◽  
Psychiatric Care ◽  
The United States ◽  
Psychiatric Services ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Promising Alternative ◽  
American Hospital ◽  
American Hospital Association ◽  
Inpatient Psychiatric Care

Abstract Background Access to psychiatric care is critical for patients discharged from hospital psychiatric units to ensure continuity of care. When face-to-face follow-up is unavailable or undesirable, telepsychiatry becomes a promising alternative. This study aimed to investigate hospital- and county-level characteristics associated with telepsychiatry adoption. Methods Cross-sectional national data of 3475 acute care hospitals were derived from the 2017 American Hospital Association Annual Survey. Generalized linear regression models were used to identify characteristics associated with telepsychiatry adoption. Results About one-sixth (548 [15.8%]) of hospitals reported having telepsychiatry with a wide variation across states. Rural noncore hospitals were less likely to adopt telepsychiatry (8.3%) than hospitals in rural micropolitan (13.6%) and urban counties (19.4%). Hospitals with both outpatient and inpatient psychiatric care services (marginal difference [95% CI]: 16.0% [12.1% to 19.9%]) and hospitals only with outpatient psychiatric services (6.5% [3.7% to 9.4%]) were more likely to have telepsychiatry than hospitals with neither psychiatric services. Federal hospitals (48.9% [32.5 to 65.3%]), system-affiliated hospitals (3.9% [1.2% to 6.6%]), hospitals with larger bed size (Quartile IV vs. I: 6.2% [0.7% to 11.6%]), and hospitals with greater ratio of Medicaid inpatient days to total inpatient days (Quartile IV vs. I: 4.9% [0.3% to 9.4%]) were more likely to have telepsychiatry than their counterparts. Private non-profit hospitals (− 6.9% [− 11.7% to − 2.0%]) and hospitals in counties designated as whole mental health professional shortage areas (− 6.6% [− 12.7% to − 0.5%]) were less likely to have telepsychiatry. Conclusions Prior to the Covid-19 pandemic, telepsychiatry adoption in US hospitals was low with substantial variations by urban and rural status and by state in 2017. This raises concerns about access to psychiatric services and continuity of care for patients discharged from hospitals.

Viewpoint of the american hospital association

1983 ◽  
Vol 5 (1) ◽  
pp. 10-13 ◽  
Author(s):  
Elizabeth Lee ◽  
Barbara Giloth
Keyword(s):  
American Hospital ◽  
American Hospital Association

Patient Satisfaction and Short-Term Outcome in Elective Cranial Neurosurgery

Neurosurgery ◽  
2015 ◽  
Vol 77 (5) ◽  
pp. 769-776 ◽  
Author(s):  
Elina Reponen ◽  
Hanna Tuominen ◽  
Juha Hernesniemi ◽  
Miikka Korja
Keyword(s):  
Patient Satisfaction ◽  
Quality Of Care ◽  
Health Status ◽  
Patient Experience ◽  
University Hospital ◽  
Term Outcome ◽  
Major Morbidity ◽  
Patient Reported ◽  
Relationship Of

Abstract BACKGROUND: Patient-reported experience is often used as a measure for quality of care, but no reports on patient satisfaction after cranial neurosurgery exist. OBJECTIVE: To study the association of overall patient satisfaction and surgical outcome and to evaluate the applicability of overall patient satisfaction as a proxy for quality of care in elective cranial neurosurgery. METHODS: We conducted an observational study on the relationship of overall patient satisfaction at 30 postoperative days with surgical and functional outcome (modified Rankin Scale [mRS] score) in a prospective, consecutive, and unselected cohort of 418 adult elective craniotomy patients enrolled between December 2011 and December 2012 at Helsinki University Hospital, Helsinki, Finland. RESULTS: Postoperative overall (subjective and objective) morbidity was present in 194 (46.4%) patients; yet almost 94% of all study patients reported high overall satisfaction. Low overall patient satisfaction at 30 days was not associated with postoperative major morbidity in elective cranial neurosurgery. Dependent functional status (mRS score ≥3) at 30 days, minor infections, poor postoperative subjective overall health status, and patient-reported severe symptoms (double vision, poor balance) may contribute to unsatisfactory patient experience. CONCLUSION: Overall patient satisfaction with elective cranial neurosurgery is high. Even 9 of 10 patients with postoperative major morbidity rated high overall patient satisfaction at 30 days. Overall patient satisfaction may merely reflect patient experience and subjective postoperative health status, and therefore it is a poor proxy for quality of care in elective cranial neurosurgery.

scholarly journals Assessment of acute kidney injury risk using a machine-learning guided generalized structural equation model: a cohort study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Wen En Joseph Wong ◽  
Siew Pang Chan ◽  
Juin Keith Yong ◽  
Yen Yu Sherlyn Tham ◽  
Jie Rui Gerald Lim ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
High Risk ◽  
Hospital Mortality ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Injury Risk ◽  
Kidney Injury ◽  
Equation Model ◽  
Surgical Icu ◽  
One Year

Abstract Background Acute kidney injury is common in the surgical intensive care unit (ICU). It is associated with poor patient outcomes and high healthcare resource usage. This study’s primary objective is to help identify which ICU patients are at high risk for acute kidney injury. Its secondary objective is to examine the effect of acute kidney injury on a patient’s prognosis during and after the ICU admission. Methods A retrospective cohort of patients admitted to a Singaporean surgical ICU between 2015 to 2017 was collated. Patients undergoing chronic dialysis were excluded. The outcomes were occurrence of ICU acute kidney injury, hospital mortality and one-year mortality. Predictors were identified using decision tree algorithms. Confirmatory analysis was performed using a generalized structural equation model. Results A total of 201/940 (21.4%) patients suffered acute kidney injury in the ICU. Low ICU haemoglobin levels, low ICU bicarbonate levels, ICU sepsis, low pre-ICU estimated glomerular filtration rate (eGFR) and congestive heart failure was associated with the occurrence of ICU acute kidney injury. Acute kidney injury, together with old age (> 70 years), and low pre-ICU eGFR, was associated with hospital mortality, and one-year mortality. ICU haemoglobin level was discretized into 3 risk categories for acute kidney injury: high risk (haemoglobin ≤9.7 g/dL), moderate risk (haemoglobin between 9.8–12 g/dL), and low risk (haemoglobin > 12 g/dL). Conclusion The occurrence of acute kidney injury is common in the surgical ICU. It is associated with a higher risk for hospital and one-year mortality. These results, in particular the identified haemoglobin thresholds, are relevant for stratifying a patient’s acute kidney injury risk.

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