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1.
Int J Qual Health Care ; 34(4)2022 Dec 08.
Artículo en Inglés | MEDLINE | ID: mdl-36399024

RESUMEN

BACKGROUND: Quality assurance programmes measure and compare certain health outcomes to ensure high-quality care in the health-care sector. The outcome of health-related quality of life is typically measured by patient-reported outcome measures (PROMs). However, certain patient groups are less likely to respond to PROMs than others. This non-response bias can potentially distort results in quality assurance programmes. OBJECTIVE: Our study aims to identify relevant predictors of non-response during assessment using the PROM MacNew Heart Disease questionnaire in cardiac rehabilitation. METHODS: This is a cross-sectional study based on data from the Swiss external quality assurance programme. All patients aged 18 years or older who underwent inpatient cardiac rehabilitation in 16 Swiss rehabilitation clinics between 2016 and 2019 were included. Patients' socio-demographic and basic medical data were analysed descriptively by comparing two groups: non-responders and responders. We used a random intercept logistic regression model to estimate the associations of patient characteristics and clinic differences with non-response. RESULTS: Of 24 572 patients, there were 33.3% non-responders and 66.7% responders. The mean age was 70 years, and 31.0% were women. The regression model showed that being female was associated with non-response [odds ratio (OR) 1.22; 95% confidence interval (CI) 1.14-1.30], as well as having no supplementary health insurance (OR 1.49; 95% CI 1.39-1.59). Each additional year of age increased the chance of non-response by an OR of 1.02 (95% CI 1.02-1.02). Not being a first language speaker of German, French or Italian increased the chance of non-response by an OR of 6.94 (95% CI 6.03-7.99). Patients admitted directly from acute care had a higher chance of non-response (OR 1.23; 95% CI 1.10-1.38), as well as patients being discharged back into acute care after rehabilitation (OR 3.89; 95% CI 3.00-5.04). Each point on the cumulative illness rating scale total score increased the chance of non-response by an OR of 1.05 (95% CI 1.04-1.05). Certain diagnoses also influenced the chance of non-response. Even after adjustment for known confounders, response rates differed substantially between the 16 clinics. CONCLUSION: We have found significant non-response bias among certain patient groups, as well as across different treatment facilities. Measures to improve response rates among patients with known barriers to participation, as well as among different treatment facilities, need to be considered, particularly when PROMs are being used for comparison of providers in quality assurance programmes or outcome evaluation.


Asunto(s)
Rehabilitación Cardiaca , Femenino , Humanos , Anciano , Masculino , Estudios Transversales , Calidad de Vida , Evaluación de Resultado en la Atención de Salud , Medición de Resultados Informados por el Paciente
2.
Z Evid Fortbild Qual Gesundhwes ; 165: 27-34, 2021 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-34412978

RESUMEN

The National Association for Quality Development in Hospitals and Clinics (ANQ) has conducted patient satisfaction measurements in the inpatient sector in Switzerland since 2009. Specifically designed for this measurement, an instrument consisting of five questions was evaluated on an 11-point rating scale. Nevertheless, the instrument showed substantial ceiling effects, which did not allow for hospital discrimination. Therefore, ANQ initiated a revision testing different scales in a pilot study. The results showed that a 5-point verbal scale displayed good psychometric properties. Compared to the 7- or 11-point scales, the 5-point verbal scale exhibited reduced ceiling effects, which was more appropriate to compare hospitals. For the national public reporting of hospitals and clinics, risk adjustment by age and self-reported health status was recommended, which was not the case for gender, principal diagnosis, type of admission and insurance status.


Asunto(s)
Hospitales , Satisfacción del Paciente , Alemania , Humanos , Proyectos Piloto , Psicometría , Encuestas y Cuestionarios , Suiza
3.
Int J Health Care Qual Assur ; ahead-of-print(ahead-of-print)2020 Dec 22.
Artículo en Inglés | MEDLINE | ID: mdl-33350289

RESUMEN

PURPOSE: A common way to handle quality problems and increasing costs of modern health care systems is more transparency through public reporting. Thereby, patient satisfaction is seen as one main reported outcome. Previous studies proposed several associated factors. Only a few of them included organizational determinants with potential to inform the health care provider's management. Therefore, the aim of this study was to investigate the influence of organizational contingency factors on patient satisfaction. DESIGN/METHODOLOGY/APPROACH: As a case, Switzerland's inpatient rehabilitation sector was used. Therein, a cross-sectional study of public released secondary data with an exploratory multiple linear regression (MLR) modeling approach was conducted. FINDINGS: Five significant influencing factors on patient satisfaction were found. They declared 42.2% of the variance in satisfaction on provider level. The organizations' supplementary insured patients, staff payment, outpatients, extracantonal patients and permanent resident population revealed significant correlations with patient satisfaction. RESEARCH LIMITATIONS/IMPLICATIONS: Drawing on publicly available cross-sectional data, statistically no causality can be proved. However, integration of routine data and organization theory can be useful for further studies. PRACTICAL IMPLICATIONS: Regarding inpatient satisfaction, improvement levers for providers' managers are as follow: first, service provision should be customized to patients' needs, expectations and context; second, employees' salary should be adequate to prevent dissatisfaction; third, the main business should be prioritized to avoid frittering. ORIGINALITY/VALUE: Former studies regarding public reporting are often atheoretical and rarely used organizational variables as determinants for relevant outcomes. Therefore, uniformed data are useful.

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