Quality Of Life Health Outcomes Research Articles

Quality of Life Health Outcomes Among People Who Lived in a Nursing Home Prior to and During the COVID-19 Pandemic.

The purpose of the current study was to compare quality of life health outcomes during the year prior to and first year of the coronavirus disease 2019 (COVID-19) pandemic among people who lived in a nursing home. This study used quarterly cross-sectional data from Minimum Data Sets between March 2019 and March 2021 among 96 people who resided in a nursing home. Health outcomes were cognitive function, transfer ability, depression, rejecting care, falls, urinary tract infections, physical conflict, and verbal conflict. Data were analyzed using Stuart-Maxwell test to compare differences in health outcomes in the year prior to and first year of the COVID-19 pandemic. There were statistically significant differences between the two time periods for the worsening of health outcomes related to transfer ability, rejecting care, physical conflict, and verbal conflict. Understanding the influence of the COVID-19 pandemic on health outcomes among people who live in nursing homes is critical for improving individual health and health system preparedness. [Journal of Gerontological Nursing, 49(12), 41-48.].

Racial and ethnic disparities in clinical outcomes six months after receiving a PTSD diagnosis in Veterans Health Administration.

Because the mental health burden of PTSD among many racial and ethnic minority veterans is greater than among non-Latinx Whites (NLW) and there are disparities in VHA mental health treatment, we evaluated variations in clinical outcomes across veteran racial and ethnic groups in a large national cohort diagnosed with PTSD in VHA. This was a planned secondary analysis of patient-reported outcomes from a large prospective cohort study of veterans with PTSD. Veterans were surveyed immediately following a PTSD diagnosis and again 6 months later. Changes in PTSD symptoms and mental health quality of life were modeled using initial measures of these factors and demographic characteristics. Primary analyses modeled outcomes constructed from a sample restricted to veterans who initiated some mental health care in the6- month follow-up period (n = 2,992). Additionally, outcomes were modeled using the full cohort of treatment initiators and noninitiators (n = 5,070). Sensitivity and post hoc analyses were used to examine robustness of our findings and to facilitate interpretability. Disparities in PTSD and mental health quality of life outcomes were observed for some racial and ethnic minority groups of veterans. Although improvements in PTSD symptoms and mental health quality of life have been highly associated in other studies, in this sample these outcomes were interrelated in complex ways across groups. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ranolazine Improves Right Ventricular Function in Patients With Precapillary Pulmonary Hypertension: Results From a Double-Blind, Randomized, Placebo-Controlled Trial

IntroductionA major outcome determinant in patients with precapillary pulmonary hypertension (PH) is right ventricular (RV) function. We studied the effect of ranolazine on RV function over 6 months using cardiovascular magnetic resonance (CMR) imaging in patients with precapillary PH (groups I, III, and IV). Methods and ResultsWe enrolled patients with PH and RV dysfunction (CMR imaging ejection fraction [EF] of <45%) in a longitudinal, randomized, double-blinded, placebo controlled, multicenter study of ranolazine treatment. All enrolled patients were on stable PH-specific therapy. Enrolled patients were assessed using CMR imaging, New York Heart Association functional class, N-terminal pro brain natriuretic peptide, 6-minute walk test, and quality of life health outcomes at baseline and repeated at the end of treatment. The primary outcome was change in RVEF after 6 months of treatment. Analysis of covariance was used to analyze the longitudinal changes taking into account baseline values, age, and sex, based on per protocol population. Twenty-two patients were enrolled, and 9 patients completed follow-up CMR imaging after ranolazine treatment and 6 completed placebo treatment. There was significant increase in RVEF at end of treatment compared with baseline in the ranolazine group adjusted for baseline values, age, and sex. There were no statistically significant changes in secondary outcomes such as changes in New York Heart Association functional class, 6-minute walk distance, N-terminal pro brain natriuretic peptide, or quality of life measures. Ranolazine treated patients experienced a higher number of adverse events, but only one was discontinued owing to side effects. ConclusionsRanolazine may improve RV function in patients with precapillary PH. Larger studies are needed to confirm the beneficial effects of ranolazine.

Comparison of Ferguson\u2019s \u03b4 and the Gini coefficient used for measuring the inequality of data related to health quality of life outcomes

BackgroundFerguson’s δ and Gini coefficient (GC) are defined as contrasting statistical measures of inequality among members within populations. However, the association and cutting points for these two statistics are still unclear; a visual display is required to inspect their similarities and differences.MethodsA simulation study was conducted to illustrate the pertinent properties of these statistics, along with Cronbach’s α and dimension coefficient (DC) to assess inequality. We manipulated datasets containing four item lengths with two number combinations (0 and 33%) in item length if two domains exist. Each item difficulty with five-point polytomous responses was uniformly distributed across a ± 2 logit range. A simulated response questionnaire was designed along with known different structures of true person scores under Rasch model conditions. This was done for 20 normally distributed sample sizes. A total of 320 scenarios were administered. Four coefficients (Ferguson’s δ, GC, test reliability Cronbach’s α, and DC) were simultaneously calculated for each simulation dataset. Box plots were drawn to examine which of these presented the correct property of inequality on data. Two examples were illustrated to present the index on Google Maps for securing the discriminatory power of individuals.ResultsWe found that 1-Ferguson’s δ coefficient has a high correlation (0.95) with GC. The cutting points of Ferguson’s δ, GC, test reliability Cronbach’s α, and the DC are 0.15, 0.50, 0.70, and 0.67, respectively. Two applications are shown on Google Maps with GCs of 0.14 and 0.42, respectively. Histogram legends and Lorenz curves are used to display the results.ConclusionThe GC is recommended to readers as an index for measuring the extent of inequality (or lower discrimination power) in a given dataset. It can also show the study results of person measures to determine the inequality in the health-related quality of life outcomes.

Do self-report and medical record comorbidity data predict longitudinal functional capacity and quality of life health outcomes similarly?

BackgroundThe search for a reliable, valid and cost-effective comorbidity risk adjustment method for outcomes research continues to be a challenge. The most widely used tool, the Charlson Comorbidity Index (CCI) is limited due to frequent missing data in medical records and administrative data. Patient self-report data has the potential to be more complete but has not been widely used. The purpose of this study was to evaluate the performance of the Self-Administered Comorbidity Questionnaire (SCQ) to predict functional capacity, quality of life (QOL) health outcomes compared to CCI medical records data.MethodAn SCQ-score was generated from patient interview, and the CCI score was generated by medical record review for 525 patients hospitalized for Acute Coronary Syndrome (ACS) at baseline, three months and eight months post-discharge. Linear regression models assessed the extent to which there were differences in the ability of comorbidity measures to predict functional capacity (Activity Status Index [ASI] scores) and quality of life (EuroQOL 5D [EQ5D] scores).ResultsThe CCI (R2 = 0.245; p = 0.132) did not predict quality of life scores while the SCQ self-report method (R2 = 0.265; p < 0.0005) predicted the EQ5D scores. However, the CCI was almost as good as the SCQ for predicting the ASI scores at three and six months and performed slightly better in predicting ASI at eight-month follow up (R2 = 0.370; p < 0.0005 vs. R2 = 0.358; p < 0.0005) respectively. Only age, gender, family income and Center for Epidemiologic Studies-Depression (CESD) scores showed significant association with both measures in predicting QOL and functional capacity.ConclusionsAlthough our model R-squares were fairly low, these results show that the self-report SCQ index is a good alternative method to predict QOL health outcomes when compared to a CCI medical record score. Both measures predicted physical functioning similarly. This suggests that patient self-reported comorbidity data can be used for predicting physical functional capacity and QOL and can serve as a reliable risk adjustment measure. Self-report comorbidity data may provide a cost-effective alternative method for risk adjustment in clinical research, health policy and organizational improvement analyses.Trial registrationClinical Trials.gov NCT00416026

Subjective assessments of comorbidity correlate with quality of life health outcomes: Initial validation of a comorbidity assessment instrument

BackgroundInterventions to improve care for persons with chronic medical conditions often use quality of life (QOL) outcomes. These outcomes may be affected by coexisting (comorbid) chronic conditions as well as the index condition of interest. A subjective measure of comorbidity that incorporates an assessment of disease severity may be particularly useful for assessing comorbidity for these investigations.MethodsA survey including a list of 25 common chronic conditions was administered to a population of HMO members age 65 or older. Disease burden (comorbidity) was defined as the number of self-identified comorbid conditions weighted by the degree (from 1 to 5) to which each interfered with their daily activities. We calculated sensitivities and specificities relative to chart review for each condition. We correlated self-reported disease burden, relative to two other well-known comorbidity measures (the Charlson Comorbidity Index and the RxRisk score) and chart review, with our primary and secondary QOL outcomes of interest: general health status, physical functioning, depression screen and self-efficacy.Results156 respondents reported an average of 5.9 chronic conditions. Median sensitivity and specificity relative to chart review were 75% and 92% respectively. QOL outcomes correlated most strongly with disease burden, followed by number of conditions by chart review, the Charlson Comorbidity Index and the RxRisk score.ConclusionSelf-report appears to provide a reasonable estimate of comorbidity. For certain QOL assessments, self-reported disease burden may provide a more accurate estimate of comorbidity than existing measures that use different methodologies, and that were originally validated against other outcomes. Investigators adjusting for comorbidity in studies using QOL outcomes may wish to consider using subjective comorbidity measures that incorporate disease severity.