The regular general practitioner and sickness absence – a register-based study

Data

The study comprises all those who were vocationally active (wage income > 1 basic amount; calculation unit used by the Social Insurance System, equal to NOK 82 122 or EUR 10 993 in 2012) in the age group 20 – 66 years, resident in Oslo or Bergen in 2005 – 06 and who had the same RGP on 1 January 2006 and 31 December 2006, altogether 143 624 women and 154 415 men. Data on these individuals’ age, gender, employment, level of education and sickness absence paid for by the NLWA in 2006 were retrieved from the FD-Trygd database. From the RGP registry we retrieved information on the individuals’ chosen RGP and data on the RGPs’ gender, age, specialist status, list length and whether the list was open or closed. Statistics Norway merged the two data sets, which were delivered to us in encrypted form. Altogether 568 RGPs were included in the study. Socio-demographic data from FD-Trygd were also aggregated at the list level and used to characterise the composition of the list populations. Use and merge of data sets had been approved by the registry owners and The Norwegian Data Protection Authority.

Statistical analysis

The outcome variable was whether an individual had at least one period of sickness absence paid for by NLWA in the period studied. This applies mainly to periods of absence lasting more than 16 days. In the article we are using the designation «at least one sickness absence > 16 days».

The individuals’ gender, age and level of education are well-known predictors of sickness absence and were included as explanatory variables in all analytical models. Age was subdivided into the categories 18 – 34 years, 35 – 49 years and ≥ 50 years (Table 1). The age categories reflect that the risk of sickness absence increases with age, and this categorisation had also been used in a previous study (20). The highest attained level of education was dichotomised according to whether the individual had completed a university college or university education or not (< 16 years and ≥ 16 years). We assumed that this would result in significant differences in the odds ratios for sickness absence.

Other explanatory variables included the RGPs’ age (ten-year age groups), gender, specialist status, list length (intervals of 250 patients) and whether the RGP’s list was open or closed. The variables have also been used in previous studies (3, 17, 20).

Furthermore, we included the following variables that characterise the socio-demographic composition of the lists: Proportion of men, proportion of vocationally active, proportion with higher education, proportion of disability pensioners and proportion of elderly people aged over 67. The lists were categorised in quartiles in accordance with these variables.

All these explanatory variables had a statistically significant effect in univariate analyses, with the exception of specialist status, which was excluded from the subsequent analyses. The effect of the various explanatory variables was investigated with the aid of multivariate logistic regression with odds ratios (OR) and an appurtenant confidence interval of 95 % (95 % CI). The regression model assumes that the variables that describe the doctors and the composition of the lists have an effect on the odds ratio for sickness absence, and not vice versa. The analyses were undertaken for women and men separately, since previous research has shown major gender differences in rates of sickness absence (18).

We first analysed the effect of the individuals’ age and gender (Table 2). In e-Table 3 we have also included the age and gender of the doctors, list length and whether the RGP’s list was open or closed. In the final analysis (Table 4) we also included variables associated with the composition of the lists. P for trend is included, except for dichotomous variables.

Characteristics of the doctors that are not captured by available variables, such as the standard of the surgery premises and accessibility by telephone, may also have an effect on the rates of sickness absence in the list population. All analyses have therefore been undertaken in a two-level model that corrects for this (clustering).

Main findings

Altogether 22 % of the women and 13 % of the men had at least one sickness certification > 16 days. The RGPs’ age, gender and list length were not correlated with sickness absence paid for by NLWA. The likelihood of sickness absence > 16 days was reduced for both women and men if they were on lists with a high proportion of highly educated people, a high proportion of elderly people and few disability pensioners. Men who belonged to lists with a high proportion of men and lists with a high proportion of vocationally active people also had lower odds ratios for sickness absence > 16 days. In addition, women who belonged to an open list had lower odds ratios for sickness absence than those who were on a closed list.

Comparison to previous studies

Four previous studies (3, 17, 19 – 20) are particularly relevant, and some of their findings have been widely reported by the media (21). Our results regarding the simple variables that describe the doctors (age and gender) differ from these studies. Markussen and collaborators used data on sickness absence reported by doctors, while Brage & Kann studied a sample of sickness certifications that the RGPs had initiated and completed for their own patients in 2003 – 04. These accounted for half of all sickness certifications during the study period. Markussen’s study was prospective, and included a data set of all sickness certifications received by NLWA in the period 2001 – 4, while we have used cross-sectional data from a sample which was smaller, but consisted of more recent data from the period 2005 – 06.

Our findings are more in line with those of Aakvik and collaborators, who used data from all parts of Norway and concluded that the variables describing the doctors are of little significance (19). Similar findings have been made in the UK as well (22).

The findings are also in line with results from our previous study from 2010, where identical data were used (20). Then as now, we found insignificant correlations between sickness absence and characteristics of the doctors, while the proportion of disability pensioners on the RGPs’ lists was correlated to the number of sickness days. With the exception of gender composition and the proportion of disability pensioners, our variables pertaining to the composition of the lists have never previously been used for studies of sickness absence.

Methodological considerations

This study does not investigate variations in the RGP’s sickness certification rates or how many certifications an RGP issues over a specified period of time. Such studies have been undertaken previously, in Norway as well as internationally (2, 13 – 14). In addition to the fact that the number of sickness certifications reflects the doctor’s patient population, the number also depends on productivity (the number of consultations per day) and accessibility (the proportion of consultations accounted for by acutely ill patients). The role played by the doctor thus cannot be easily determined, and the results from this type of study therefore tend to vary significantly.

We therefore chose to take an epidemiological approach, where focus is placed on the vocationally active population’s risk of being certified as sick. Characteristics of the RGPs are used as one of several explanatory factors, although we do not know what proportion of the sickness certifications has been issued by the patient’s own RGP. This investigative methodology has also been used on previous occasions (17, 19 – 20).

We only studied sickness absence > 16 days, which has the greatest significance for the social economy (16) and for exclusion from the labour market (23). This is a rough measure of sickness absence, and the frequency and duration of the periods of absence were not taken into account. Self-reported absence and absence reported by doctors but paid for by employers were not included (16, 18).

We chose to use the average level of education and the proportion of disability pensioners aged 20 – 67 as indicators of socio-economic status. Other variables could also have been used for this purpose.

The study is cross-sectional in nature, and causal relationships cannot be deduced with any certainty. However, we are using a data set containing complete data for the sickness absence which is paid for by the NLWA in Norway’s two largest municipalities for an entire year.

Studies of Norwegian sickness absence have identified large geographical differences (24). By choosing two major cities, the effect of the varying coverage of doctors in rural and small municipalities is reduced, and the results more directly reflect the effects of characteristics of the doctors and their lists. Results from the metropolitan populations in Oslo and Bergen may also be more relevant with regard to international comparisons.

The fact that the study included only persons who were resident in the same municipality and had the same RGP over the entire period will make the results more precise, but will to some extent reduce their amenability to generalisation.

We undertook the analyses for women and men separately, since the genders have different patterns of sickness absence. In addition, we observed that women and men have considerable differences in their choice of an RGP. A total of 42 % of the women had a woman RGP, compared to 21 % for men, and there are more women who are entered on closed lists (61 %, compared to 50 % for men).

Implications and the need for further studies

In the RGP scheme, list composition is in principle unrelated to geography. There is nevertheless reason to assume that lists with a low socio-economic status belong to doctors who have their practices in less prosperous districts. Such a list composition may also indicate that over time, the RGP has followed liberal practices with regard to certification of sickness and social benefits, which may have attracted patients with a large need for such benefits.

The study shows that the socio-economic composition of the list has an impact on the odds ratio for sickness certification > 16 days also among those who have a higher socio-economic status, measured in terms of their level of education. Conversely, this means that people with little education belonging to RGP lists where the average social status is high are certified sick more rarely than equivalent patients on other lists. This could be perceived as differential treatment in relation to social insurance rights.

The finding that vocationally active people found on lists with many elderly patients (> 66 years) had a lower risk of being certified sick > 16 days was unexpected and merits further investigation. The segment of the population that changes to another RGP, with or without relocating, may constitute a risk group for sickness absence, and should therefore be studied in more detail. The use of other socio-economic variables, such as income and profession, and possibly including previous periods of unemployment, might have provided a more complete picture.