Dataset Information

Assessment of patient experience profiles and satisfaction with expectations of treatment effects by using latent class analysis based on a national patient experience survey in Taiwan.

ABSTRACT:

Objectives

Health system responsiveness is a complicated issue that guides researchers wishing to design an efficient methodology for enhancing understanding of perspectives regarding healthcare systems. This study examined the relationship between patient experience profiles and satisfaction with expectations of treatment effects.

Design

This was a cross-sectional study. We used eight items obtained from latent class analysis to develop patient experience profiles.

Setting

Primary care users in Taiwan.

Participants

This study conducted an annual National Health Insurance survey in Taiwan and sampled from those who had experience with the medical service in primary care clinics in 2015.

Primary outcome measure

Respondents were asked to indicate the extent of their satisfaction with their expectation of treatment effects (or symptom improvement).

Results

The proportions of participants in groups 1-4 were 34%, 24%, 29% and 12%, respectively. Patients in good health were more satisfied with their expectations of treatment effects (OR 1.639, p=0.007). Furthermore, group 4 (-eAll) were less satisfied with their expectations of treatment effects than those in the other three groups (ORs: group 1 (+eAll): 9.81, group 2 (-CwR): 4.14 and group 3 (-CnR): 4.20).

Conclusions

The results revealed that experiences of poor accessibility and physician-patient relationships affected the patients' expectations. Therefore, greater accessibility and more positive physician-patient relationships could lead to higher patient satisfaction with their expectations of treatment effects. Furthermore, the findings could assist authorities in targeting specific patients, with the objective of improving their healthcare service experience. They could also serve as a mechanism for improving the quality of healthcare services and increase accountability in healthcare practices.

SUBMITTER: Chiou SJ

PROVIDER: S-EPMC6429738 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

Assessment of patient experience profiles and satisfaction with expectations of treatment effects by using latent class analysis based on a national patient experience survey in Taiwan.

Chiou Shang-Jyh SJ Lee Pei-Chen PC Chang Yu-Hsuan YH Huang Pei-Shan PS Lee Li-Hui LH Lin Kuan-Chia KC

BMJ open 20190308 3

<h4>Objectives</h4>Health system responsiveness is a complicated issue that guides researchers wishing to design an efficient methodology for enhancing understanding of perspectives regarding healthcare systems. This study examined the relationship between patient experience profiles and satisfaction with expectations of treatment effects.<h4>Design</h4>This was a cross-sectional study. We used eight items obtained from latent class analysis to develop patient experience profiles.<h4>Setting</h4 ...[more]

PMID: 30852529

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Project description:ImportanceMedically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date.ObjectiveTo define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters.Design, setting, and participantsThis cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles.Main outcomes and measuresComplex patient profiles, 1-year health care utilization, and mortality outcomes by profile.ResultsThe analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management.Conclusions and relevanceThe findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.

Project description:BackgroundPatient experience surveys are important tools for improving the quality of cancer services, but the representativeness of responders is a concern. Increasingly, patient surveys that traditionally used postal questionnaires are incorporating an online response option. However, the characteristics and experience ratings of online responders are poorly understood.ObjectiveWe sought to examine predictors of postal or online response mode, and associations with patient experience in the (English) Cancer Patient Experience Survey.MethodsWe analyzed data from 71,186 patients with cancer recently treated in National Health Service hospitals who responded to the Cancer Patient Experience Survey 2015. Using logistic regression, we explored patient characteristics associated with greater probability of online response and whether, after adjustment for patient characteristics, the online response was associated with a more or less critical evaluation of cancer care compared to the postal response.ResultsOf the 63,134 patients included in the analysis, 4635 (7.34%) responded online. In an adjusted analysis, male (women vs men: odds ratio [OR] 0.50, 95% confidence interval [CI] 0.46-0.54), younger (<55 vs 65-74 years: OR 3.49, 95% CI 3.21-3.80), least deprived (most vs least deprived quintile: OR 0.57, 95% CI 0.51-0.64), and nonwhite (nonwhite vs white ethnic group: OR 1.37, 95% CI 1.24-1.51) patients were more likely to respond online. Compared to postal responders, after adjustment for patient characteristics, online responders had a higher likelihood of reporting an overall satisfied experience of care (OR 1.24, 95% CI 1.16-1.32). For 34 of 49 other items, online responders more frequently reported a less than positive experience of care (8 reached statistical significance), and the associations were positive for the remaining 15 of 49 items (2 reached statistical significance).ConclusionsIn the context of a national survey of patients with cancer, online and postal responders tend to differ in their characteristics and rating of satisfaction. Associations between online response and reported experience were generally small and mostly nonsignificant, but with a tendency toward less than positive ratings, although not consistently. Whether the observed associations between response mode and reported experience were causal needs to be examined using experimental survey designs.

Dataset Information

Assessment of patient experience profiles and satisfaction with expectations of treatment effects by using latent class analysis based on a national patient experience survey in Taiwan.

Objectives

Design

Setting

Participants

Primary outcome measure

Results

Conclusions

Publications

Assessment of patient experience profiles and satisfaction with expectations of treatment effects by using latent class analysis based on a national patient experience survey in Taiwan.

Similar Datasets

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