The effectiveness of intensive lifestyle interventions to prevent, or at least delay, the onset of type 2 diabetes mellitus (DM2) has been demonstrated.1 In addition, the long-term persistent preventive effect has been observed. In Spain, however, both the initial application of interventions and their transfer into the public health system remain a dream.2–4

In 2006, the International Diabetes Federation (IDF) requested the adaptation of the preventive measures to the reality of each country, as well as an analysis of effectiveness.5 Finland, Germany and The Netherlands immediately started diabetes prevention programs with government and legislative support.6 Catalonia also started the European public health project Diabetes in Europe-Prevention using Lifestyle, Physical Activity and Nutritional Intervention (DE-PLAN), which has shown the usefulness of the Finnish Diabetes Risk Score (FINDRISC) scale for screening for glucidic disorders and the feasibility and efficacy of intensive lifestyle interventions in primary care in high-risk subjects.7–9 However, having effective measures does not mean that they are also cost-effective.

In Spain, DM2 consumes 15% of the state budget allocated to health. The costs of DM2 usually begin before diagnosis; it is therefore advisable to increase the investment in prevention.10,11 In fact, various studies support the cost-effectiveness of intervening in early stages of the disease, particularly in subjects with impaired glucose tolerance (IGT) and impaired fasting glucose (IFG), diagnoses that constitute the category of prediabetes.1,9–12 The majority of analyses are contextualized from clinical trials, which have little or nothing to do with the reality of primary care. Computer simulation models are then applied to these analyses.6 There are very few analyses (and virtually none in Spain) of the costs of the process and the preventive intervention itself under the actual conditions of clinical practice in the public health system.

The aim of this study was to perform a cost analysis, compared with the effectiveness and quality of life perceived by the participants, of DM2 prevention, conducted entirely within the primary care setting of Spain.

The European project DE-PLAN in Catalonia was designed in 2 phases: a cross-sectional (1 year) screening and a longitudinal (4 years) cohort follow-up.7 This public health study assessed the viability and effectiveness of an intensive, structured lifestyle intervention in primary care, in comparison with other standardized interventions closer to standard health advising. A total of 18 primary care centers from 7 reference centers participated in the study, a total of 150 professionals (doctors and nurses), providing a representative sample of the treated population between the ages of 45 and 75 years at high risk but with no diagnosis of diabetes. The primary indicator of effectiveness at 4 years was the development of DM2, by protocol and by intention to treat. The ethical requirements, the design and details of the screening and intervention, as well as the first results on the incidence of DM2 in the established cohorts have already been published.7–9

In summary, the participants were recruited consecutively based on a randomized list supplied by the primary care medical records database. The participants were contacted and invited to undergo a health check. Patients were excluded if they had severe psychiatric, renal, hepatic or hematologic diseases. The first screening was conducted using the FINDRISC scale, a European questionnaire with 8 validated items (Spanish version available at http://www.sediabetes.org), which evaluates the risk factors for DM2 on a scale from 0 to 26, classifying individuals according to their risk profile for DM2. The second screening required the oral glucose tolerance test (OGTT), according to WHO regulations. All participants scoring over 14 were invited to be part of the protocol; however, participants scoring 14 or less were also offered the opportunity to undergo the protocol if they so desired. The screening diagnoses were based on a single OGTT, excluding from the intervention those participants who had baseline glucose levels ≥126mg/dL or glucose levels ≥200mg/dL 2h after the OGTT, levels that lie within the range of DM2. We recommended confirmation of the DM2 diagnosis by a second test but outside the study. Both measures were repeated in the annual follow-up visits to establish the incidence of DM2, thereafter requiring confirmation within the study. In addition to glycemia, we analyzed the lipid profile and the glycosylated hemoglobin HbA1c in the baseline blood sample.13

The intervention was proposed to all participants who underwent the screening OGTT (normal, IGT and/or IFG) and scored over 14 on the FINDRISC test. Participants whose score was equal to or less than 14 were also offered the intervention if their voluntary OGTT indicated prediabetes (IGT and/or IFG). The protocol planned for 2 interventions (standardized and intensive) and 2 stages (initial and reinforcement); the intensive intervention assumed 2 modalities (individual and group). We insisted on consecutive assignment to the intervention groups according to the feasibility for each center. After having their baseline measurements taken, the participants assigned to the intensive intervention could opt for one modality or the other. Figs. 1 and 2 summarize the study's screening phases, assignment and follow-up.

Figure 1.

Flow diagram of the DE-PLAN-CAT project.

Abbreviations: OGTT: oral glucose tolerance test; DM2: type 2 diabetes mellitus; IGT: impaired glucose tolerance; IFG: impaired fasting tolerance.

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Figure 2.

Assignment to the intervention and schedule of the DE-PLAN-CAT project.

Abbreviations: V1 to V10: formal clinical visits of the project.

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The standard intervention group received general individual information (without a structured schedule) on diet, cardiovascular health and the risk of DM2, reinforced by taking advantage of routine visits. The intensive intervention group received a structured schedule of 6h (4 sessions) for 5–15 participants, using specific teaching material. The method was adapted to the available experience, needs and capacity and was based on support, motivation and positive feedback. This program was provided one by one to the participants in the individual modality. The intervention was reinforced with telephone calls, text messages, letters and interviews, scheduled for every 6–8 weeks.

During the formal visits, the participants’ family and personal history, sociodemographic data and laboratory test results were recorded. Quality of life was assessed before the intervention and then annually using the validated 15D questionnaire.14 For the analysis of costs generated by the process and the intervention, the coordinating centers (those that were able to do so) were requested to record data from the first 30 cases assigned consecutively, creating a representative sample of the evaluated population whose economic parameters also form part of the follow-up.

The necessary measures for calculating the costs were recorded in 8 forms whose content has been previously described.15 We assessed the human resources (staff), materials (documentation, teaching, analysis) and time (hours dedicated) used during the screening to convene and inform the participants, complete the questionnaire and perform all laboratory tests. We also assessed the resources used in the initial intensive intervention, including teaching material for staff training (meetings, duration, attendees) and participants (number of sessions and teachers, duration and subject). In addition, we included the resources invested for periodic reinforcement (telephone calls, text messages, letters and visits) and those resulting from visits to the center and laboratory as part of the intervention.

To assess the efficiency of the intervention, a cost-effectiveness analysis (disease incidence) and a cost-usefulness analysis (stated quality of life) were planned. The basic concepts of cost-effectiveness and cost-usefulness studies in the economics of health are briefly presented in Appendix A. To deduce the likelihood or effectiveness ratio, we determined the annual and 4-year cumulative incidence of DM2, comparing both groups (standardized and intensive) and strategies (individual intensive and group) and performing a sensitivity analysis. We calculated the mean cost per participant according to the type and modality of intervention, the incremental cost of the intensive intervention compared with the standardized intervention and the incremental ratio of the cost-effectiveness based on averted new cases of DM2. The usefulness score was based on the 15D questionnaire, which provides a unit transformation (0–1) of the 15 dimensions measured.16 We took into account the final and annual proportion of participants in each assigned intervention group and also the mean annual arithmetic and weighted quality of life gained, always compared with the baseline visit, expressed by the difference in scores.

The quality-adjusted life-years (QALYs) were calculated based on the annual measures of usefulness provided by the 15D questionnaire, representing the QALYs gained or lost and the annual differences between the two groups. These gains or losses of usefulness were the basis for the calculation of the cost-usefulness index (the ratio between the cost of the option and its usefulness) and the incremental cost-usefulness index, which was used to contrast the increased costs with the increased effectiveness and quality of life among the various preventive alternatives compared.

The costs were counted in euros (€), using the current public fees during the 2007 fiscal year, always from the perspective of the public health service provider whose entire practice is free for users at the place of service17 and assuming that the data reveal actual costs during the study period. We did not apply a correction for inflation due to global financial uncertainty, the continuous changes to the tax code (for example, the value-added tax) and because we did not intend to create estimates by using computerized projection models in the future. The statistical methodology employed for the descriptive analysis, for the incidence of DM2 and for its determinants has also been published.9

Although the information collected was more extensive, for this economic assessment we only considered direct costs attributable to the screening and intervention program, as well as those generated by the study's own activities. To contrast the cost-effectiveness and cost-usefulness options, we used the software package DATA Pro® (TreeAge Software Inc., Waltham, MA, USA, 2001), using the estimated probability in each group of developing DM2 at 4 years (base model) and annually (alternative models). We assigned an effect of 1 to participants who did not develop DM2 and 0 to those who developed the disease.

We contacted 2547 users. A total of 2054 (80.6%) responded to the FINDRISC questionnaire. Of these, 1192 (58%) gave their consent to perform the oral glucose tolerance test (OGTT). A high risk of DM2 was detected in 624 participants, either from the questionnaire (n=347) or the OGTT (n=106) or from both (n=171). Ultimately, 552 (88.5%) agreed to the intervention. We assigned 219 (39.7%) to the standardized intervention and 333 (60.3%) to the intensive intervention. Of these, we assigned 230 (41.6%) to the group modality and 103 (18.7%) to the individual modality. Both groups (standardized and intensive) were comparable in age (approximately 62 years), gender (practically two-thirds were women), body mass index (approximately 31kg/m2), FINDRISC score (approximately 16 sutures), baseline glycemia (95.4/93.6mg/dl), after overload (127.8/124.2mg/dl) and in the declared interest in making changes to their lifestyle.

After a median 4.2 years of follow-up, 124 participants were diagnosed with DM2, 61 (18.3% [95% CI 14.3–22.9%]) in the intensive intervention (20% and 14.6% for the group and individual modalities, respectively) and 63 (28.8% [95% CI 22.9–35.3%]) in the standardized intervention (HR, 0.64; 95% CI, 0.47–0.87; p<.004). Fig. 3 shows the annual cumulative incidence that increased with time, although not proportionally given that it was lower in the intensive intervention group, reaching statistically significant differences starting in the third year. The absolute incidence of diabetes was 4.6 cases/100 individuals/year in the intensive intervention (4 and 3.6 for the group and individual modalities, respectively) and 7.2 cases/100 individuals/year in the standardized intervention, representing an overall reduction of the relative risk of diabetes of 36.5% (p<.005, log-rank test). Accordingly, the intensive intervention prevented 3% of new DM2 cases each year (3.6% annually and 4% annually in its group and individual formats, respectively) in comparison with the standardized intervention (7.2% annually). Taking into account the cumulative incidence of diabetes, the number of participants required in the intensive intervention for 4 years in order to reduce the incidence of diabetes by 1% was 9.56.

Figure 3.

Cumulative incidence of diabetes according to the intervention groups.

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In 6 of the 7 coordinating primary care centers it was possible to record the use of resources throughout the intervention, creating a total sample of 133 individuals (24.1% of the complete group) whose data were integrated into the analysis. Of these, 40 (30.1%) participated in the standardized intervention and 93 (69.9%) in the intensive intervention; 65 (48.8%) in the group modality and 28 (21.1%) in the individual modality. There were no statistical differences in the screening variables between this segment and the complete group. Table 1 summarizes the attributable costs, scale and accumulated cost by participant in the full intervention. The majority of the costs were due to medical visits, laboratory tests and, to a lesser degree, the contributions of other professionals (nursing and dieticians), as well as the material used (educational or any other type). The costs were higher during the first year of follow-up, which included the screening procedure and the initial intervention.

The mean cost per participant was €646 in the standardized intervention and €686 in the intensive intervention, with €752 for the group format and €656 for the individual format. Therefore, the incremental cost of the intensive intervention compared with the standardized intervention was €40 (6.2%), with €106 (16.4%) for the group modality and €10 (1.5%) for the individual modality.

The mean attendance at the meetings for the intensive intervention group was 10.75 participants per session. Considering this fact, the cost of the group and individual intensive intervention was €8.88 and €105 per participant, respectively. The difference between the two groups was directly related to a lower cost for staff involved in the group modality and, obviously, with additional costs distributed among the participants. Extrapolating to the entire intensive intervention group, the incremental cost-effectiveness ratio was €376.17 per case of averted DM2, corresponding €108.09 per averted case to the group modality and €745.66 to the individual modality.

The conversion of scores obtained from the 15D questionnaire in measures of usefulness showed initial figures that were statistically similar in both intervention groups, standardized (0.887±0.98) and intensive (0.885±0.96). This similarity was maintained over the course of the follow-up until the final visit (4 years) when a significant difference emerged, with the stated quality of life greater in the intensive intervention group (0.92±0.71) than in the standardized intervention group (0.91±0.79; p=.013). Similarly, the assessment of the participants who did not develop DM2 tended to be better than that of those who developed DM2, the more the follow-up progressed, although it did not reach statistical significance. The cumulative gain in usefulness at 4 years was 3.64 and 3.63 QALYs, respectively, signifying a difference of 0.012 QALYs gained in favor of the intensive intervention group. The incremental cost-usefulness index indicated a total of €3243 per QALY gained, a figure that corresponds to the investment to be made by the public health service provider to improve the quality of life of this at-risk population and avoid the progression to diabetes. Table 2 summarizes a number of the details of the calculation of all of these indicators.

The sensitivity analysis showed that the costs were very sensitive to various levels of probability although always remaining acceptable. We can hypothesize that as the proportion of participants in the individual modality increased, the intensive intervention decreased in efficiency. Finally, we estimated that while the likelihood of developing DM2 was below 28.9% for the group modality and below 34.4% for the individual modality, it would be more efficient to provide the intensive intervention than not to provide it, thus leaving the outcome of the cohort in the hands of the natural history of the process, obviously in the primary health care context.

To date, the economic analyses on the impact of diabetes have been directed towards the cost of treatment and its complications. Less common are the studies on the cost of interventions for preventing or delaying the onset of DM2, and the economic analysis of such interventions during clinical practice is exceptional. In Spain, these studies have not been conducted either, perhaps because the medical professionals are not familiar with the concepts of economics, perhaps due to the complexity of implementing and demonstrating the effectiveness of an intervention in an actual scenario. However, clinical trials have demonstrated not only the efficacy but also the cost-effectiveness of interventions based on lifestyle changes to prevent DM2 in at-risk patients.1,6,18,19

It is commonly accepted that adopting preventive measures requires a rapid investment in resources, which can only be recovered in the medium to long-term if the incidence of the disease is truly reduced and the quality of life improved. These two aspects are the basis for cost-effectiveness and cost-usefulness studies, whose results require monetary (currency) and usefulness (quality-adjusted life-years gained) indicators for them to be compared.15 Traditionally, lacking an analysis under actual conditions, researchers have resorted to emulating these conditions using computer simulation models that, although speculative, offer relevant results based on the calculation of probabilities.4,20 The present study is a public health study, distanced from computer simulations. We analyzed the actual direct costs of a DM2 prevention program in high-risk participants, taking into account the professional perspective, the participant's perception and the actual cost for the public health system, without making projections for the future. The naturalistic design has advantages and disadvantages, but the results are closer to reality during the evaluated period than any virtual computer scenario.

The recommendations of the IDF for the global management of diabetes established various intensities for the preventive activities. While minimal interventions are recommended for countries’ scarce resources, those countries with greater purchasing power are advised to undertake more expensive interventions, with each country prioritizing the maximum acceptable expenditure. By consensus, the maximum limit per QALY is USD $50,000 (€38,460) for the intervention to be considered cost-effective.5 In this respect and even without having assessed the indirect costs incurred by the DE-PLAN intervention, we can consider it a cost-effective strategy overall.

The costs of preventing DM2 vary significantly. The economic assessment of the Finnish Diabetes Prevention Study (DPS) using a simulation model showed an overrun of €2363 per QALY.17 The initial computer projection to 30 years of the United States Diabetes Prevention Program (DPP) showed that lifestyle intervention created additional social costs estimated at USD $62,600 (€48,154) per QALY gained, but the use of metformin (with USD $24,500 [€18,846]) was more cost-effective.21 It seems contradictory that if this projection in time were shortened, the results would favor the lifestyle intervention.22 When the actual data from the DPP was mined after 10 years of follow-up, the use of metformin was shown to be less expensive, but the lifestyle intervention was more cost-effective, gaining 6.81 QALYs at a cost of USD $10,037 (€7720) per QALY.4 Therefore, it is not surprising to find mixed results depending on the methodology, population sample, geographic setting and national health system evaluated.23–26

On one hand, the economic results of the DE-PLAN project are closer to those of the Finnish DPS, perhaps because its intervention was a precursor to the one developed in Catalonia. On the other hand, if we look at the similarity of the method, these data are more like those of the US DPP, comparing the USD $10,037 (€7720) with the USD $4216 per QALY gained (€3243) in our demarcation. In fact, a strong point of the DE-PLAN was the prior demonstration of the feasibility and effectiveness of the intervention in the same population, avoiding estimates based on other sources.9 The consistency of the data is supported by the greater incidence of DM2 in the standardized intervention group than in the intensive group, an incidence that is also very similar to that found in previous local studies without the implementation of a prevention program.7 Additionally, the data from the PREDIMED study, conducted in the same territory, point in the same direction.27

The most important limitation of the global study lies in the assignment of participants to the interventions, because it did not use a randomized list but rather requests sequential access, to the extent of the actual possibilities of each center, respecting the participant's preference for one or the other intensive intervention, individual or group. One of the main limitations of the economic analysis is the noninclusion of indirect costs and working only with the direct costs generated by the intervention, given the complexity of the clinical environment. It is apparent that the indirect costs of DM2 dominate the long-term expenditue28 but, presumably, its relative weight in this study is low given that the participants who developed DM2 mostly received the standardized intervention and had a disease with a very short evolution. On the other hand, they accessed more information on their risk than they would have received in routine practice and probably benefited from the information. This situation also influences the indirect costs but in the opposite direction. Perhaps it would be more relevant to specify what spending threshold is willing to be paid to minimize the overrun associated with early detection compared with the treatment of the disease and its complications.29,30

In recent decades and due to the increased incidence of DM2, public health providers have endured a significant increase in expenditure attributable to the disease. In times of economic crisis, it has been decided that the available resources are insufficient for treating the consequences of the disease; investing in prevention is therefore fully justified. The analysis of the DE-PLAN project in Catalonia showed that intensive lifestyle intervention is not only feasible in primary care but also substantially reduces the incidence of DM2 in at-risk participants and has a reasonably acceptable cost for the national health system. As a result, the efficiency of the intervention (in economic terms) supports the decision to transfer and distribute the intervention to everyday clinical practice in the Spanish primary health care system.

The project received grants from the Commission of the European Communities, Directorate C – Public Health (ref.: 2004310); Institute of Health Carlos III (PI05-033 and PS09-001112); Department of Health (Government of Catalonia): award for Innovation in the processes of care and organization in primary care (2010), Innovation Plan in Primary Care and Community Health (2010), BP-2010 award (Comprehensive Plan for the Promotion of Health through Physical Activity and Healthy Eating). The project also won the first prize of the XI edition of the Research Grants of the Catalan Society of Family and Community Medicine (November, 2010).

The authors declare that they have no conflicts of interest.

• 1.

  Concept and design of the manuscript: B. Costa, R. Sagarra, J.J. Cabré and O. Solá-Morales.

• 2.

  Data collection: B. Costa and J.J. Cabré.

• 3.

  Data analysis and interpretation: O. Solá-Morales, R. Sagarra and F. Barrio.

• 4.

  Drafting, review and approval of submitted manuscript: R. Sagarra, B. Costa, J.J. Cabré, O. Solá-Morales and F. Barrio.