Increasing health service access by expanding disease coverage and adding patient navigation: challenges for patient satisfaction

Approaches for enhancing patient-reported experience measurement with ethnically diverse communities: a rapid evidence synthesis

BACKGROUND

Patient-reported experience measures (PREMs) are used to drive and evaluate unit and organisational-level healthcare improvement, but also at a population level, these measures can be key indicators of healthcare quality. Current evidence indicates that ethnically diverse communities frequently experience poorer care quality and outcomes, with PREMs data required from this population to direct service improvement efforts. This review synthesises evidence of the methods and approaches used to promote participation in PREMs among ethnically diverse populations.

METHODS

A rapid evidence appraisal (REA) methodology was utilised to identify the disparate literature on this topic. A search strategy was developed and applied to three major electronic databases in July 2022 (Medline; PsycINFO and CINAHL), in addition to websites of health agencies in Organisation for Economic Co-operation and Development countries via grey literature searches. A narrative evidence synthesis was undertaken to address the review question.

RESULTS

The review resulted in 97 included studies, comprised 86 articles from electronic database searches and 11 articles from the grey literature. Data extraction and synthesis identified five strategies used in PREM instruments and processes to enhance participation among ethnically diverse communities. Strategies applied sought to better inform communities about PREMs, to create accessible PREMs instruments, to support PREMs completion and to include culturally relevant topics. Several methods were used, predominantly drawing upon bicultural workers, translation, and community outreach to access and support communities at one or more stages of design or administration of PREMs. Limited evidence was available of the effectiveness of the identified methods and strategies. PREMs topics of trust, cultural responsiveness, care navigation and coordination were identified as pertinent to and frequently explored with this population.

CONCLUSIONS

The findings provide a basis for a maturity model that may guide change to increase participation of ethnically diverse communities in PREMs. In the short-medium term, health systems and services must be able to recognise and respond to cultural and linguistic diversity in the population when applying existing PREMs. In the longer-term, by working in collaboration with ethnically diverse communities, systems and services may co-create adapted or novel PREMs that tackle the factors that currently inhibit uptake and completion among ethnically diverse communities.

An analysis of the trend towards universal health coverage and access to healthcare in Morocco

OBJECTIVE

We aim in this study to investigate the association between access to health care services and various components of universal health coverage in Morocco, controlling for socioeconomic, demographic, and cultural factors.

DATA AND METHODS

The study employed a logistic regression method to model the relationship between access to health care as binary outcome variable and health coverage, using the longitudinal data collected from the Household Panel Survey of the National Observatory of Human Development (ONDH) spanning the period from 2013 to 2019.

RESULTS

The study reveals a significant association between access to health care services and having medical coverage taking into consideration socioeconomic and demographic characteristics as the main determinants of access to health care services.

CONCLUSION

The study investigates the impact of demographic and socioeconomic factors on medical care utilization. The econometric model reveals that individuals with medical coverage, particularly through AMO and RAMED, are more likely to seek health care services, emphasizing the positive influence of universal health coverage. Additionally, demographic and socioeconomic characteristics such as gender, education, employment, and living environment significantly affect health care-seeking behavior. Urban residents, women, and those with higher standards of living are more inclined to access health care services.

Health insurance coverage and access to care in China

OBJECTIVE

The study examined the relationship between health insurance coverage and access to needed healthcare including preventive, primary, and tertiary care among Chinese adult population.

DATA AND METHODS

Data for this study came from the 2018 China Health and Retirement Longitudinal Study (CHARLS), a population-based probability sample survey. Key measures included insurance coverage (high-, moderate-, low- and no-insurance), access to care (physical examination, physician visit, office visit, inpatient care, and satisfaction with care), and personal sociodemographics. Multiple-factor generalized linear mixed model was applied to estimate the odds ratio (OR) and the 95% confidence interval (CI) of HI coverage for the four indicators of access to care, after controlling for individual characteristics and aggregation among different villages.

RESULTS

The majority of Chinese adults had some health insurance with only 3.15% uninsured. However, most had low-coverage insurance (64.82%), followed by moderate-coverage insurance (16.70%), and high-coverage insurance (15.33%). Health insurance was significantly and positively associated with access to needed healthcare (preventive, primary, and tertiary). There was also a significant gradient association between extent of insurance coverage and access to care.

CONCLUSION

Not only health insurance mattered in enhancing access to care but that there was a significant gradient association between extent of insurance coverage and access to care with higher coverage relating to better access.

Exploring drivers of patient satisfaction using a random forest algorithm

Background

Patient satisfaction is a multi-dimensional concept that provides insights into various quality aspects in healthcare. Although earlier studies identified a range of patient and provider-related determinants, their relative importance to patient satisfaction remains unclear.

Methods

We used a tree-based machine-learning algorithm, random forests, to estimate relationships between patient and provider-related determinants and satisfaction level in two of the main patient journey stages, registration and consultation, through survey data from 411 patients at a hospital in Abu Dhabi, UAE. Radar charts were also generated to determine which type of questions—demographics, time, behaviour, and procedure—influence patient satisfaction.

Results

Our results showed that the ‘age’ attribute, a patient-related determinant, is the leading driver of patient satisfaction in both stages. ‘Total time taken for registration’ and ‘attentiveness and knowledge of the doctor/physician while listening to your queries’ are the leading provider-related determinants in each model developed for registration and consultation stages, respectively. The radar charts revealed that ‘demographics’ are the most influential type in the registration stage, whereas ‘behaviour’ is the most influential in the consultation stage.

Conclusions

Generating valuable results, the random forest model provides significant insights on the relative importance of different determinants to overall patient satisfaction. Healthcare practitioners, managers and researchers can benefit from applying the model for prediction and feature importance analysis in their particular healthcare settings and areas of their concern.