1 INTRODUCTION

Patients’ evaluation of care is a key element of the quality of health care. To study this, many patient-reported outcome measures (PROMs) have been created.¹ Most PROMs are disease-specific and concern planned care.² In primary care, the range of problems that patients present during consultations is unrestricted, a specific diagnosis is often not reached,^{3, 4} and a large part of care is unplanned. Therefore, a generic approach to PROMs is required. One such approach is patient enablement.

Patient enablement is a concept that was developed to measure quality of care, especially in primary care. It is defined as the patient's ability to understand and cope with illness and life after a consultation with a doctor.⁵ It could be measured using the Patient Enablement Instrument (PEI), a six-item questionnaire addressed to a patient after a consultation.⁵ It is suggested that the PEI is a good PROM^5-7 and it has been applied in several countries.^7-15 Also, a single-item measure has been shown to adequately identify patients with low enablement with high negative predictive value.¹⁶

In previous studies, several factors are found to be associated with patient enablement. These could be divided into patient, consultation and system factors.¹⁷ Patient factors include patient characteristics, expectations and skills. Consultation factors include actions and perceptions of the consultation and general practitioner (GP) characteristics. System factors include organizational characteristics, such as characteristics of GP/practices or the structure of the health-care system. A conceptual model of the process leading to patient enablement is presented in Figure 1.

When comparing separate studies, patient enablement seems to differ across countries. However, only one study directly compares patient enablement between countries¹⁵ and only a few report on comparisons of patient enablement between practices or doctors.^18-22 Furthermore, to our knowledge there are no publications that consider the possible effect of cultural aspects on enablement. In other words, a comparative analysis to explain the differences in patient enablement between health-care systems and countries is lacking.

The aim of this study is to explain variations in patient enablement between patients, GPs and countries. Based on the current literature, we have formulated hypotheses concerning the process of patient enablement. We test these hypotheses with a large international data set from 31 countries, using multi-level modelling. We use a single-item measure as an indicator of patient enablement. To our knowledge, this is the first study of patient enablement that takes the differences between health-care system features or cultural aspects into consideration.

2 HYPOTHESES

In the following sections, we present the current knowledge on factors associated with enablement and hypothesize the mechanisms behind these associations. Consequently, we formulate our study hypotheses.

3 METHODS

3.2 Statistical analyses

Due to the collection method, the structure of the QUALICOPC data is hierarchically clustered, meaning that patients are nested within their GPs and the GPs are nested within countries, forming three levels: patient, GP and country levels. With this kind of data, multi-level modelling should be used.⁵² Multi-level modelling allows the analysis of individual-level outcomes in relation to variables at the same or higher levels and to split up the total variation in an outcome variable into parts that are attributable to the different levels.⁵³

Multi-level, multivariable logistic regression models were constructed in order to explain variations in patient enablement between patients, practices/GPs and countries, and to find significant factors associated with lower enablement. The modelling strategy is presented in Figure 2. First, ‘a null model’ (Model 0) was performed to explore variances between countries and practices. To calculate the share of variance at practice and country levels, individual-level variance was approximated by pi²/3. Second, patient-level variables (patient characteristics and patient perceptions of the consultation) were included (Model 1). Next, practice-level variables (GP and practice characteristics) were added to Model 1 (Model 2). Finally, country-level variables (health-care system characteristics, primary care dimensions and cultural dimensions) were added one by one. Three country-level variables that could best explain the variation were then retained in the final model (Model 3). The explanatory power of the models was evaluated by calculating the explained variance of each model compared to the variance in the null model.

Also, median odds ratios (MORs) were calculated for each model. The MOR is the median odds ratio between two randomly chosen individuals with the same covariates but from different clusters.⁵⁴ When using this approach, differences in probability/risk are entirely quantified by the cluster-specific effects.^{54, 55} The MOR is comparable with individual-level ORs and thus helps to quantify the extent of clustering.⁵⁵

As the number of higher-level variables should not exceed 10% of the number of higher-level units,⁵³ only three country-level variables could be included simultaneously in the final model. Missing values were excluded from the analyses. For two variables (trust in doctors in Australia and Poland and mean consultation time in Australia), there were no observations. Thus, value imputation (replacing the missing value by an average value of the subset of other countries) was used in order to minimize the loss of data.

4 RESULTS

Data collected from a total of 7210 GPs from 31 countries were used in this analysis. From the practices of these GPs, 61 458 patients were recruited to participate. The distributions of patient and GP characteristics are presented in Tables 1 and 2. Among the participants, 58 930 patients answered the dependent variable ‘After this visit, I feel I am able to cope better with my symptom/illness than before the appointment’. Some 13 367 (21.7%) answered ‘no’ or ‘don't know’, interpreted as lower enablement. Table 3 presents the distribution of the dependent variable in each country. The distributions varied largely between countries: for example, the proportion of lower enablement varied from 9.2% in New Zealand to 39.6% in Sweden.

5 DISCUSSION

In this study, we found that patient enablement, measured by a single question, varies largely between 31 countries. By using multivariable, multi-level models, this variation between countries could be explained to a rather large extent. The logistic regression results of this study show that, for example, patient's older age, female gender and positive perceptions of patient satisfaction and patient involvement are associated with decreased risk of lower enablement. In contrast, for example, patient's worse self-perceived health, reason for consultation and lower trust in doctors are associated with increased risk of lower enablement.

In general, patient characteristics and patients’ perception of the consultation do not explain the variation between countries. However, they do explain variance between practices to some extent. Furthermore, although adding GP-level variables to the models improved it, the overall explained practice variance remained rather low—over 80% of variance remained unexplained. It is possible that the variables available in the QUALICOPC framework may not have included all the potentially important factors related to practices and GPs. In particular, the personal characteristics of a GP could have a strong influence on enablement; it is assumed that there are ‘high enablers’ and ‘low enablers’ among GPs.²⁰

None of the PHAMEU structural elements of the health-care system explained enablement variation between countries, contrary to our hypothesis. None of them was statistically associated with enablement. Thus, it seems that the mechanisms behind patient enablement are not system-associated but more culture-associated.

The cultural dimension, long-term orientation, was the only country-level variable that had a statistically significant association with patient enablement. According to the results of this study, people in more long term–oriented cultures have a decreased risk of lower enablement. This cultural dimension deals with change; in long term–oriented cultures, ‘the basic notion of the world is that it is in flux, and preparing for the future is needed’.⁵¹ In short term–oriented cultures, ‘the world is essentially as is was created, so the past provides a moral compass’.⁵¹ To our knowledge, there is no other evidence of a role of this dimension in the health-care context. Perhaps people in more long term–oriented cultures adopt a more flexible attitude to changes in health as well.

The fact that the structure of the primary care system is not related to enablement, but a dimension of national culture is, has implications for the international comparison of PROMs. Before using PROMs as indicators for health system performance, the relationships with specific characteristics of health systems on the one hand and cultural characteristics on the other should be further explored. Previous research has shown that cultural values are related to different aspects of primary care.⁵⁶

Patient characteristics show rather strong associations with patient enablement. In particular, a patient's age and gender have a clear association with patient enablement, even after adjusting for several other variables. This is against the a priori expectations which were based on contradictory results in the previous literature. However, in a large systematic review, older age is related to higher patient satisfaction,⁵⁷ and the mechanism behind achieving enablement might be similar. It may be that young patients are more critical of care than the elderly, leading to lower enablement. In addition, elderly patients may have built a relationship with their GPs, after seeing them more often, and thus more easily experience enablement. Furthermore, women tend to have a more active attitude towards treatment and health,⁵⁸ and this could also promote reported enablement following consultation.

The patients’ perception of a consultation seems to play a role in the enablement process. As expected, positive perceptions of the doctor-patient relationship (eg involvement and continuity of care) decreased the risk of poorer enablement. Previous evaluations of doctors’ patient-centeredness,^{27, 33} partnership with the patient ²⁶ or patient satisfaction^{20, 22, 28, 29} have suggested positive associations with enablement. Furthermore, it is encouraging to find that the propensity to seek care from GPs significantly decreased the risk of poorer enablement—possibly a reflection of patients’ trust in primary health care. Against expectations, the patient's perception of communication was not associated with enablement in our study.

Two of our five GP-level hypotheses were confirmed. As expected, GP’s age and gender were not associated with patient enablement. Instead, practice location played a role: more rural location was associated with a higher risk of lower enablement. This could be due to different patients and problems in rural compared to urban areas. Also, poorer continuity may have an effect: for instance, a Norwegian study showed that continuity was better in larger and usually more central municipalities.³⁶ Better resources and access to care in more urban areas might be one reason for this result. In addition, the doctors (n = 1331) who meet more patients during a regular workday (over 45 compared to less than 15 patients) tend to enable their patients more than their colleagues with fewer daily patient contacts. This is contrary to the evidence ^{5, 20, 25, 30, 33, 34, 37} that a longer consultation time promotes enablement—the mechanism behind this result must be something other than just the minutes spent. Perhaps in systems where the GPs have as many as 45 consultations per day, patient has different expectations towards consultations. Also, the reasons for an encounter may be simpler in these systems.

6 STRENGTHS AND LIMITATIONS

A strength of this study is the large sample of GPs and their patients from many countries. Use of multi-level modelling with this kind of data is necessary—the robust statistical analyses are the major strength of the study.

The QUALICOPC framework was designed to study and compare primary health-care properties and patient perceptions between countries, not patient enablement in itself. Therefore, the measurement was a single-item question and not the ‘gold standard’ Patient Enablement Instrument with six questions. Nonetheless, this question seems to be adequate for identifying patients with low enablement scores.¹⁶ Furthermore, not all potential factors could be included in the analyses. For example, more detailed data of GP personal characteristics or actual time consumed in the consultation were not available. In addition, despite the large amount of data, loss of observations due to missing values—a common challenge with a logistic regression analysis—and merging several data sets collected in separate studies caused some loss of data. Additionally, there could be a circularity phenomenon for all perceptual patient variables, for example patient satisfaction and trust in doctors. Lastly, since this is a study about associations, conclusions in terms of causality cannot be drawn.

7 CONCLUSIONS

In the international context, cultural dimensions and GP and practice characteristics explain patient enablement variation between countries to a rather large extent. Patient and—to some extent—practice characteristics seem to explain a minor part of practice variation. In contrast, structural elements of health care show no significant associations. In addition, several independent variables seem to be associated with patient enablement. GPs and researchers should be aware of the potential importance of cultural aspects, particularly when comparing health survey results between countries and adopting measurements across countries.

8 CLINICAL IMPLICATIONS

Enablement is a goal worth pursuing for all patients, in order to ensure an experience of coping and understanding. Doctors should aim to strengthen patient enablement, not only as a measure of quality but also as an important issue in itself. Recognizing factors that associate with lower enablement—for example patients’ lower self-perceived health—may help doctors to focus on the patients who may need more attention or actions in order to achieve enablement. Practising skills related to patient-centred consultation and patient involvement, as well as improving continuity and access to care, may contribute to better patient enablement across countries.

ETHICAL APPROVAL AND CONSENT TO PARTICIPATE

Ethical approval was acquired in accordance with the legal requirements in each country. Both GP and patient surveys were carried out anonymously. Although a standardized data collection procedure across all countries was strongly recommended and strived for, in the actual data collection strategy cultural and ethical requirements for each country were taken into account.