The SMILE study: a study of medical information and lifestyles in Eindhoven, the rationale and contents of a large prospective dynamic cohort study

Good health is highly valued. For centuries with varying success scientists have tried to find causes of illness and ways to prevent ill health. A lot of progress in improving and maintaining health has been made, especially in the area of infectious diseases. Chronic diseases, however, do not respond to the simple formula "identify the cause and eliminate it" [1], because their development is determined by multiple factors, resulting in limited possibilities for rapid interventions. Even when important risk factors are known, for example smoking in chronic obstructive pulmonary disease, and obesity in diabetes mellitus type II, it appears difficult to intervene in an effective way. Due to the limited success of preventive interventions, changes of the population distribution (a sharp increase of the proportion of elderly people), and societal changes (like changes in social security services, changes in working conditions) the prevalence of chronic diseases is rising, and is expected to rise further in the near future. Given the nature of the current health problems, integral approaches are required, such as advocated by the New Public Health approaches and Ecological Health approaches, where classical medicine collaborates with public health or other disciplines[2, 3].

This has resulted in a growing need among physicians, researchers, and policy makers to gain insight into the mutual influences of different health related, institutional and environmental concepts and their collective developmental processes over time. Only substantial insight into these factors and their relations can help to improve public health by effective interventions in the areas of public health, occupational health, disability management, and care in the home. Such insight can be obtained by combining both physician-registered medical data and patient self-reported data. Often, researchers have of either medical data or questionnaire data at their disposal, which both have their limitations.

Health problems and health behavior are often intertwined, and it is therefore relevant to gather both medical data as registered in general practice and health related data as reported by the patients. Although this notion seems trivial, very few studies do so. The collection of this combined data, albeit more complex and expensive, will have several advantages. First a better understanding of health problems can be developed. Secondly, it is possible to evaluate 'natural' occurring phenomena. E.g. the results of a recent study on health problems of victims of a fireworks disaster in the Netherlands could have been more explicit if self-reported data on patients' perception were also available [4].

Moreover, an integral approach collecting medical, health behavioral, psychosocial and care consumption data, has substantial advantages.

The goal of the SMILE study is to develop a hybrid database containing both medical data and questionnaire data, attempting to resolve the problems described above. Although results of outcomes of elements of this study are already described [5‐7], this paper describes the methodology and design of this new dynamic cohort in primary care, using both medical and questionnaire data, and aiming at gaining a comprehensive, interdisciplinary and modern insight into the mutual influences of different health related, institutional and environmental factors. The name of this new cohort is The Study of Medical Information and Lifestyles in Eindhoven, in short SMILE.

SMILE, is a large prospective cohort study, focusing on different aspects of disease, health and lifestyle of people living in Eindhoven, the Netherlands. Eindhoven is a city in the Southern part of the Netherlands of approximately 200,000 inhabitants.

In November 2002, 2,178 adolescents (aged 12–18 years) and 28,879 adults (aged 18 and older) enrolled in one of the participating health care centers were invited to participate in SMILE. SMILE is a dynamic cohort study, meaning that new participants will enter the population sample when they either reach 12 years of age or when they are enrolled as a new patient in one of the participating centers, and they give their informed consent. Respondents may leave the population either through leaving the participating practice or due to death or drop-out. Furthermore, after two succeeding moments of non-respons patients don't receive any more questionnaires. The dynamic character of SMILE is expected to result in a sufficiently large patient population over time and it prevents vanishing of the study population.

The fundamental goal of SMILE is to study health and disease and their determinants and their consequences in a comprehensive approach for an extended period of time (15 years). Apart from serving data for examining and analyzing relationships between several health-related concepts, SMILE can also serve as a sampling frame to select specific patient groups such as elderly with osteoarthritis,, adolescents with low self-esteem, or adults with a sedentary life style.

To realize this goal, the structure and contents of the SMILE study has two unique characteristics:

This manuscript describes a new scientific initiative, the SMILE study: a longitudinal dynamic cohort using both routinely collected medical information from the EMRs in general practice and periodically collected patient information using questionnaires.

To measure health related processes in time, a long-term prospective cohort study is the most convenient study design. A powerful feature of cohort studies is the opportunity to collect both repeated exposure data and repeated outcome data, which provides many analytical opportunities to deduce the effects of random measurement error and to evaluate various hypothesized temporal relations between exposure and outcome [10]. The dynamic nature of many risk factors and their relation in time to disease occurrence can only be captured in the cohort design; this temporal interplay is inherently absent from cross-sectional data [11]. The ability to evaluate multiple endpoints simultaneously within the same population is particularly valuable when there are competing risks and benefits [10].

The SMILE study comprises a dynamic population, contrary to most of the other health related large cohort studies, like the Framingham Heart Study [12, 13], or the Maastricht Aging Study; MAAS [14]. Furthermore, other cohorts are often more focused on a specific condition (e.g. cancer [15]) or on a subsample of the population (e.g. elderly people [16]). We believe our approach to be more effective, because of the many analytic opportunities that are created with relatively small additional efforts.

Possible disadvantage of this approach are: difficulties in deciding which (limited set of) concepts to measure. This was, however, solved by intense communication within SMILE.

Because the establishment of a large cohort typically represents a major investment in resources, it is efficient to examine all major health outcomes [10]. Since SMILE has the capacity to measure a wide variety of both exposures and outcomes, we have the opportunity to address a large number of important public health issues. Making maximum use of such a resource requires the involvement of numerous investigators, both because of the volume of the potential issues and because expert knowledge in various substantive areas is required. This is rapidly changing the nature of epidemiologic research, from numerous small fiefdoms to cooperative groups of interacting investigators. Such working relations, although created by necessity, can greatly enhance the level of scientific endeavor and productivity [10]. Despite all the advantages of interdisciplinary studies, some participating researchers and GPs have shown cold feet. It's not easy being interdisciplinary [17]. The SMILE team spends considerable time and energy to keep together and to stimulate the stakeholders of the different disciplines to assure continuous development of the research model and the accompanying studies. However, now that the conceptual framework as well as the practical implementation of data collection is becoming more clear and definite, and an increasing amount of data is available, participation of interested disciplines is clearly improving, showing from a number of accepted and published manuscripts and abstracts.

More extensive use of the data will be stimulated by continuous efforts to maintain and to further improve data quality. In this regards continuous participation of both GPs and patients is of the utmost importance in a longitudinal study. For this type of research the setting of general practice linked to academic departments is especially suitable, covering both an unselected patient population and a broad scope of morbidity. This is especially true in the Netherlands, where all people are enrolled as a patient in a general practice.

Several efforts are made to stimulate participation, like raffling of record tokens among adolescents. Once a year a newsletter is sent to all participants, containing results, interviews etc. to stimulate participants' engagement in the SMILE study. Also, at each measurement a press release is sent out, which is usually elaborated by the local press and posters are distributed in the practices reminding patients to fill in their questionnaire.

GP involvement is stimulated in other ways. First of all registration is as close as possible to daily routine, so that keeping up the EMRs does not take much additional time.

Benchmarking is another tool which can result in better quality of registration (completeness as well as correctness), and which at the same time helps GPs to improve the quality of their care. Finally, the Eindhoven Corporation of Primary Health Care Centers is receiving a reimbursement to compensate for additional efforts in the context of the SMILE study.

There has been a sharp increase in the scientific use of electronic medical records (EMRs), collected on a routinely basis [18]. These routinely collected data can be used for audit, quality improvement, health service planning, and scientific research. Primary care research networks are increasingly seen as an important tool for the future of primary care. Research from such networks will allow policy makers and practitioners to address primary care and public health issues from the perspective of data rather than mere belief. Stange [19] even stated that research in practice-based networks is critical to the future of primary care and is badly needed to guide both practice and health-policy decisions. The SMILE study can further contribute to these developments.