Table of Contents Author Guidelines Submit a Manuscript
Journal of Diabetes Research
Volume 2015, Article ID 368570, 14 pages
http://dx.doi.org/10.1155/2015/368570
Research Article

Towards Patient-Oriented Diabetes Care: Results from Two KORA Surveys in Southern Germany

1Institute of Health Economics and Health Care Management, Helmholtz Zentrum Munich, 85764 Neuherberg, Germany
2Institute of Epidemiology II, Helmholtz Zentrum Munich, 85764 Neuherberg, Germany
3German Center for Diabetes Research (DZD e.V.), 85764 Neuherberg, Germany

Received 9 December 2014; Revised 22 February 2015; Accepted 25 February 2015

Academic Editor: Francis M. Finucane

Copyright © 2015 Michaela Schunk et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective. This study aims to examine the relationship of diabetes care processes and patient outcomes with an expanded set of indicators regarding patient-oriented care delivery, such as treatment satisfaction, the quality of patient-physician relationship, and a wider range of patient outcomes such as self-management, health behaviour, disease-related burden, and health-related quality of life (HRQL). Methods. The study population consisted of 486 participants with type 2 diabetes in two population-based follow-up surveys, conducted in 2003 to 2005 and 2006 to 2008 in Southern Germany. Data were self-reported and questionnaire-based, including the SF-12 for HRQL. Multiple regression models were used to identify associations between care processes and outcomes with adjustment for confounders. Results. Frequent medical examinations increased the likelihood of self-monitoring activities, such as foot care. A positive patient experienced relationship with their physician is associated with higher adherence to medical recommendations, such as medication intake, and the score of the SF-12 mental component. Participants with diabetes-related complications reported higher levels of medical examinations and multiprofessional care. Conclusions. Indicators of patient-oriented care should become an indispensable part of diabetes clinical practice guidelines with the aim of striving for more effective support of patients.

1. Introduction

Type 2 diabetes mellitus (T2DM) is a major global chronic disease with immense and increasing healthcare costs and a high disease burden. Complications are the main driver of diabetes care costs [1, 2]. Diabetes and diabetes-related complications considerably decrease health-related quality of life (HRQL) [3]. There is an indispensable need to study how diabetes care can further be improved to limit the disease burden and costs.

Health care systems attempt to deal with chronic diseases by standardizing treatment and clinical practice. Important policy strategies include the development of national clinical practice guidelines and indicators for the quality of care [47]. A review of observational studies examining the relationship between guideline-defined diabetes processes and health outcomes notes that effects are often surprisingly small and inconsistent [8].

Health care planners are optimistic about the capacity of patients to take responsibility for their health and the management of their chronic illness [9, 10]. The promotion of patients’ involvement in the management of their chronic disease has become a popular concept and is delineated in the chronic care model and the patient empowerment approach [11, 12]. A patient-centered approach to diabetes care, endorsed as a central aim by the American Diabetes Association and the European Association for the Study of Diabetes [13], includes patient education but goes beyond this to embrace multiprofessional care, care management activities, and a proactive, respectful communication with patients. Glasgow et al. and others argue for a broader inclusion of patient-centered measures in studies of quality of diabetes care [1416].

Studies have shown that diabetes care provided along these lines enhances metabolic control and clinical outcomes, in particular, when patients engage actively in their self-management [1720]. Accordingly, we would argue that care delivery based on a partnership model between health professionals and patients should improve patient commitment to their health behaviour, self-management, and adherence, which can be conceptualised as patient outcomes.

Striving towards the use of patient-oriented quality of care indicators, the main limitation is a lack of empirical data [21]. Few clinical trials include patient-oriented indicators as primary outcomes [22]. In fact, clinical trials may not be very suitable for determining the impact of these indicators when implemented in actual practice. Population-based observational studies can offer both a view close to health care provision in practice and data on a wide range of structure, process, and outcome indicators of diabetes care.

Drawing on data from two population-based survey studies that were conducted in a region in Southern Germany from 2003 to 2008 we performed a post hoc analysis to test whether patients well supported by health professionals (as indicated by higher levels of care processes such as medical examinations, diabetes education, and multiprofessional care as well as high treatment satisfaction and good quality of the relationship between patients and physicians) attain higher levels of health behaviour and self-management and better adherence as well as less disease-related burden and higher HRQL.

2. Methods

2.1. Research Design

The study population consisted of 486 participants with T2DM who took part in either of two follow-up survey studies conducted in 2003–05 (F3) and 2006–08 (F4). F3 was a follow-up cohort study () to a 1994-1995 population-based MONICA survey (S3) with a response rate of 76%. F4 was a follow-up cohort study () of the KORA S4 survey conducted in 1999–2001 with a response rate of 80%. The KORA research platform (Cooperative Research in the Region of Augsburg) is a population-based data pool established in 1996 to continue and expand the MONICA project in Augsburg, a region with a mixed urban and rural population of about 600,000 inhabitants in the southern part of Germany, about 70 km west of Munich. Four cross-sectional health surveys (S1 to S4) have been performed in the city of Augsburg and its two surrounding counties at five-year intervals from 1984/85 onwards, each drawn as an independent random sample. The four cross-sectional surveys serve as cohorts for long term follow-up studies like F3 and F4. Both studies utilize the sampling in the original surveys, although data may not be fully representative due to death and loss to follow-up. Study designs, sampling methods, and data collection have been described in detail elsewhere [23].

Both surveys included a personal interview, several self-administered questionnaires (including the SF-12 questionnaire on HRQL), medical examinations, physical measurements, computer assisted documentation of medication during the last 7 days (IDOM), and laboratory tests. Data were collected at the study centre in Augsburg. The analysed data is based mainly on items from a questionnaire filled in by participants with diabetes but includes information collected in the interview (social-demographic data; type and duration of diabetes; cardiovascular comorbidity, BMI, physical activity, smoking, and alcohol) and SF-12 questionnaire data. IDOM data were used for the classification of diabetes treatment. Data quality was thoroughly checked in both studies. For the present analysis, only questions with identical wording and answer choice order were included to ascertain the validity of the joint analysis of both studies. Both studies were approved by the Ethics Committee of the Bavarian Medical Association and by the Bavarian Commissioner for Data Protection and Privacy. All study participants provided written consent.

2.2. Participants

Only study participants with type 2 diabetes in F3 and F4 were included in our analysis. Diabetes status and type of diabetes were assessed by a question in the interview (self-report of a physician-confirmed diagnosis of diabetes). Negative self-reports were checked with documentation of respective antidiabetes medication (ATC Codes: A10A and A10B) and corrected, if necessary. In case of doubt, the primary physician was contacted to confirm the diagnosis. Of the participants of F3, were classified as participants with type 2 diabetes, respectively, of the participants of F4. We excluded (F3) respective (F4) participants with self-reported type 1 diabetes to improve sample homogeneity. The sample for analysis consists of 486 participants in total, combining the data of those two surveys to increase sample size for the analysis. Participants over 75 years of age filled in a shortened version of the SF-12 in the F3 survey, leading to a higher number of missing values for HRQL.

2.3. Measurements
2.3.1. Process Parameters

Diabetes care processes are defined in this study as elements of diabetes care that result from direct interactions between health professionals and patients. Processes of diabetes care were assessed with the following variables: (1) medical examinations and advice, (2) diabetes education, (3) treatment satisfaction, (4) patient-perceived quality of patient/physician relationship, and (5) multiprofessional care. Five types of medical examinations (eye exam, foot exam, HbA1c lab, blood pressure, and protein/urine testing) and two types of advice given by the physician on diet and physical exercise were assessed by the percentage of participants who reported this activity as having been performed during the last 12 months (yes/no). Diabetes education was assessed by the number of courses participants reported to have attended. Treatment satisfaction was assessed with a single item: “In total, how satisfied are you with the diabetes treatment (including treatment with insulin, tablets and/or diet) you have been receiving in the past weeks?” Responses from 1 (very dissatisfied) to 7 (very satisfied) were analyzed across the entire range. The quality of the patient/physician relationship was assessed by items relating to four different quality aspects: comprehensibility of information, opportunity to ask questions, shared decision-making, and psychological support. Responses for these variables were dichotomized as “excellent, good” versus “other” to ascertain good discriminatory power. Multiprofessional care was assessed by two items asking whether dieticians and/or podiatrists were involved in the diabetes care (yes/no) during the past 12 months.

To prepare process parameters for the multivariate analysis, we added up answers to respective questions in each group (medical examinations (7 items), quality of patient/physician relationship (4 items), and multiprofessional care (2 items)), which were identical in wording and answer format (see Table 5). Diabetes education (number of classes attended) and treatment satisfaction (range 1–7) were already available as single values.

Missing values were set to “0” except for missings with regard to treatment satisfaction, where the sample mean value of 5 was imputed. We excluded participants with >3 missings in the variables relating to process parameters to minimize the need for such imputations in this dataset with its many missing values (see Table 5) but to retain a workable sample size for the multivariate analyses.

2.3.2. Outcome Parameters

In this study we perceive self-management, adherence, and health behaviour as intermediate patient outcomes, that is, activities that may result from care processes providing effective support of patients. Complications and health-related quality of life are considered as medium and long term outcome indicators. Taken together, patient outcomes were assessed with the following variables: (1) patient self-management, (2) adherence, (3) health behaviour, (4) diabetes complications, and (5) health-related quality of life.

Patient self-management was assessed with items regarding self-monitoring activities. Participants were asked whether and how frequently they had self-monitored feet, weight, blood glucose, and blood pressure within the past 6 months. Each item was dichotomized into “1” for frequencies of once a month or more and “0” for less. These activities are included in a validated scale of diabetes self-care activities (Summary of Diabetes Self Care Activities, SDSCA [24]), although this scale uses a different design to assess frequency.

Adherence was assessed with self-reported information on whether participants were following medical advice regarding medication, physical activity, diet, and foot care (i) without difficulties, (ii) with some difficulties, or (iii) with major difficulties. Each item was dichotomized into “1” for a report of no difficulties and “0” for some or major difficulties. For descriptive analysis, we also compared how many participants stated that they had not received recommendations. The respective answer category reads “does not apply to me” (Table 5).

For health behaviour, we used self-reported information on physical activity, smoking, and alcohol consumption and coded them in accordance with guidelines [2527]. Physical activity is dichotomized as “1” (≥2 hr/week regularly in winter and summer) versus “0” (<2 hr/week regularly in winter, summer, or both). Smoking is dichotomized into “1” (never-smokers and ex-smokers) and “0” (regular and occasional smokers). Alcohol intake is transformed by using cut-off values of weekly consumption in gram (“0” = men > 20 g, women > 10 g; “1” = equal or less) [28].

Diabetes-related burden was assessed with regard to common diabetes complications and the occurrence of hyper- and hypoglycaemia. Diabetic complications refer to the clinical diagnosis (“ever” versus “never”) of retinopathy, poor blood circulation in legs, peripheral neuropathy, and microalbuminuria. The answer “do not know” is treated as missing value. Two items ask to recall the occurrence of hypoglycemic and/or hyperglycemic episodes during the past 6 months (yes versus no). HRQL is assessed with the SF-12, a validated questionnaire and short form of the SF-36 [29]. Values are expressed as two scores, the physical health score and mental health score (PCS and MCS). Both scores range from 0 to 100, with higher values indicating better HRQL. Scores are calculated using published standard algorithms [30].

All of the above variables are described in Table 5 with regard to their wording, the number of missing values, and the coding used for all analyses. Covariates included in the regression analysis are time of survey, patient age, sex, educational level (basic education versus higher), diabetes duration, diabetes treatment type, and comorbidities (history of stroke/myocardial infarction: yes/no). Treatment type refers to (1) no antidiabetic medication, (2) oral hypoglycemic agents (OHA), and (3) insulin treatment. Age and duration of diabetes are entered as continuous variables. For sample description we added information on the BMI (body mass in kilograms divided by the square of height in units of meters (kg/m2)), health insurance status (% statutory), and enrolment in a diabetes type 2 disease management program (T2DM-DMP).

2.4. Statistical Analysis

Descriptive statistics (percentages, means (SD)) were generated for sample characteristics and process and outcome parameters. Sample characteristics are reported in total and by treatment type. Differences between the populations of the two survey periods with time of survey entered as dichotomous variables (F3, F4) were tested by Student’s t-test for continuous variables and -test for categorical variables. Multiple logistic regression models were used to examine the association between care processes with patient outcomes, controlling for age, sex, education, treatment type, cardiovascular comorbidities (previous myocardial infarction or stroke), and time of survey participation as covariates.

Odds ratios (OR) were calculated for binary variables. For continuous variables, such as quality of life scores, adjusted mean differences were based on a linear regression model. P values less than 0.05 are considered as statistically significant but used in an explanatory sense to retrieve further hypotheses. Statistical analysis was performed using SAS version 9.2 [31].

3. Results

3.1. Sample Description

The sociodemographic characteristics of the total sample and of groups divided by treatment type, (1) no antidiabetic medication, (2) oral hypoglycemic agents (OHA), and (3) insulin treatment, are shown in Table 1. About half of the sample was treated with oral hypoglycemic agents (OHA) (, 53%), with the remainder equally divided between those on insulin only and insulin combination treatment (, 23%) and those without antidiabetic medication (, 24%). The average age is 67.3 years and the proportion of female participants 44%. Average diabetes duration varies across the groups with different treatment types from 5.6 years in the group without antidiabetic medication to 16.2 years in the group with insulin treatment. Cardiovascular comorbidity and BMI were highest in the group with insulin treatment. Overall T2DM disease management-enrolment was 20%; it was lowest in the group with no medication. There were no differences between the survey periods regarding baseline variables entered in the regression analyses (Table 4).

Table 1: Baseline characteristics of study population by treatment group.
3.2. Description of Process and Outcome Parameter

Table 2 shows the frequencies of care processes and patient outcomes across the sample. Blood pressure testing was the most frequent (95%) and feet exams the least frequent (50%) of medical examinations and advice. HbA1c testing at least once in the past 12 months was reported by 63%. Of the seven types of medical examinations and advice, participants received a mean of 4.2 (2.2 SD). Half of the participants had attended at least one patient education class (51%). Across all participants, the average participation completed one diabetes education class (SD 1.8). The mean value for treatment satisfaction was 5.3 (1.6 SD) on a rating scale from 1 (very dissatisfied) to 7 (very satisfied).

Table 2: Descriptive statistics.

Quality of patient/physician relationship was rated high across all items. Only psychological support was acknowledged less often as being “good” or “excellent” (78%), compared with the comprehensibility of information (87%), the opportunity to ask questions (90%), and shared decision-making (85%). Of the four items, participants rated an average of 2.9 (SD 1.5) items as “good” or “excellent.” Participants reported low use of multiprofessional care: only 24% had used a podiatrist during the last 12 months, 17% a dietician.

Patient self-management, that is, monthly or more self-monitoring of blood-pressure, weight, feet, and blood-glucose, was reported by 65–80% of participants with the highest percentage for monitoring weight (81%). Differences between high adherence with respect to medication and feet care (>80%) and much lower adherence with regard to physical activity and diet (ca. 40%) were identified. Up to a quarter of participants stated that they did not receive respective medical recommendations. Only 14% of participants reported to engage in regular physical activity of more than 2 hours per week. However, more than 88% reported not smoking and 73% moderate/no alcohol consumption.

Disease-related burden was increased for 9% of participants with diabetic retinopathy, 12% with microalbuminuria, 21% with poor circulation in legs, and 29% with peripheral neuropathy. More than half of the participants stated to have experienced episodes of hyper- and hypoglycemia in the last 6 months. Mean HRQL was 41.5 in the physical component score (PCS-12) and 49.8 in the mental component score (MCS-12).

3.3. Evaluation of Relationship between Process and Outcome Parameters

Results of the regression analyses are presented in Table 3. We excluded participants (14% of the total sample) because of >3 missing values in variables pertaining to care processes (F3: ; F4: ). Most of them were participants who did not fill in the diabetes-specific questionnaire (F3: of ; F4: of ).

Table 3: Association between care processes and patient outcomes.
Table 4: Baseline characteristics of F3 and F4 study population.
Table 5: Survey items.

Associations with patient self-management, health behaviour, disease-related burden, and health-related quality of life were strongest for medical examinations and advice, diabetes education, and quality of relationship with physician and less strong for treatment satisfaction and multiprofessional care. A higher number of medical examinations and advice were associated with self-monitoring of blood pressure (OR 1.18; CI: 1.03, 1.35), feet (OR 1.24; CI: 1.09, 1.42), and blood glucose (OR 1.23; CI: 1.07, 1.42). However, participants with more medical examinations and advice also reported less frequently that they had no difficulties with adherence to diet (OR 0.82; CI 0.70; 0.95). Participation in diabetes education was positively associated with self-monitoring feet (OR 1.30; CI 1.06, 1.60) and blood glucose (OR 1.50; CI 1.18, 1.90). Patient-perceived positive quality of relationship with the physician was most strongly associated with adherence to medication (OR 1.92; CI: 1.39, 2.64) and the mental component score of HRQL (mean score difference 2.04 CI: 0.95, 3.13). It was less strongly, but still significantly, associated with adherence to recommendations regarding diet (OR 1.33; CI: 1.04, 1.71) and feet care (OR 1.33; CI: 1.02; 1.73) as well as self-monitoring of weight (OR 1.26, CI: 1.00; 1.58). Multiprofessional care was positively associated with self-monitoring of blood glucose (OR 1.63, CI: 1.02, 2.62).

Contrary to our hypothesis, a number of associations indicated that participants reporting a higher level of care processes were more likely to report diabetes-related complications, episodes of hyperglycemia, and lower scores in the mental component of HRQL. Participants who receive multiprofessional care are less likely to be free of poor blood circulation in legs (OR 0.54; CI: 0.35, 0.83), peripheral neuropathy (OR 0.68; CI: 0.47, 0.99), and hyperglycemia (OR 0.61; CI: 0.40; 0.91). The risk of no retinopathy decreases with more diabetes education (OR 0.75; CI: 0.63; 0.90), and the physical component HRQL score is lower (mean score difference: −1.01; CI: −1.76; −0.26). The risk of no microalbuminuria decreases with a higher mean score in medical examination and advice (OR 0.79; CI: 0.63; 0.99). Finally, the only association found for treatment satisfaction indicates that participants with more treatment satisfaction are less likely to not have been diagnosed with retinopathy (OR 0.71; CI: 0.51; 0.98).

To investigate the robustness of our results, sensitivity analyses were performed. Models were calculated when (1) adjusting for diabetes duration instead of treatment type, (2) diabetes treatment in four (insulin only; insulin and OHA; OHA; no medication) versus three groups (insulin only or insulin and OHA; OHA; no medication), and (3) controlling for T2DM-DMP enrolment. In each case, the results proved to be very comparable (results not shown).

4. Discussion and Conclusion

4.1. Discussion

Measuring quality of care requires process and outcome measures that go beyond specific clinical interventions to integrate components that are guided by the patients themselves [1416, 32]. We have tried to capture quality of care broadly by relating care processes to patient outcomes, expanding the set of indicators to include patients’ activities and experiences. Controlling for treatment type, we aimed at results applicable across all patient groups. Our findings confirm a close relationship between care processes and patient outcomes. Following our hypotheses, frequent medical examinations increase the likelihood of self-monitoring activities. Patient-experienced positive relationship with physician is associated with higher adherence to medical recommendations, for example, medication and the SF-12 mental component score. Contrary to our expectation, higher levels of medical examinations and multiprofessional care did not preclude disease-related burden but were associated with it. This may indicate that patients’ support by health professionals is being initiated too late and is only intensified once complications are present. This study, however, used a cross-sectional design, which introduces problems with confounding. We have adjusted for cardiovascular comorbidity and treatment type, but these adjustments may not be enough to control for the intensified health care needs of sicker patients (i.e., those with more complications). Further research with prospective studies is needed to reevaluate these findings.

On a descriptive level, our results provide evidence that the frequency of care processes still falls short in Germany. With the exception of blood pressure, all medical examinations required to be performed yearly are reported only from 50%–75% of participants. For example, annual eye exams are recommended for all patients with T2DM, but in our data only about two thirds of the patients reported receiving one in the past 12 months. Only 50–60% of participants reported receiving advice on diet or on physical exercise or ever participating in patient diabetes education. Similar findings have been reported by other studies using insurance claim data [33]. Guidelines recommend that all patients should receive these types of examinations and advice as well as patient education [7].

Patient self-monitoring levels as reported in this study must also be regarded as relatively low level, considering that 20–30% of patients do not carry out these activities at least on a monthly basis. However, in the light of diabetes treatment guidelines which only very generally recommend that physicians should review health behaviour with each patient on a regular basis (i.e., at least annually) this may be explainable [7, 34]. Although self-monitoring of weight was reported relatively more often compared to the other types of self-monitoring, adherence to medical recommendations concerning physical activities and diet was difficult for the majority of participants. Whilst adherence to most types of medical recommendations, except recommendations concerning physical activity, is higher when patients perceive the quality of patient-physician relationship to be good, patients’ self-monitoring is associated with more frequent medical examinations, advice, and diabetes education. In the guidelines, self-monitoring of blood glucose should be encouraged by physicians as deemed suitable for the individual treatment. Reimbursement of glucose test strips has been cut for OHA-treated patients with diabetes in 2011 by the federal regulatory bodies [35]. They were however available at the time of the study.

Care processes were not associated with any of the three types of health behaviour which we assessed, that is, physical activity, smoking, and alcohol consumption. Only about 15% of participants report regular physical exercise. Participants do better managing smoking and alcohol consumption, but approximately 30% report a higher than recommended intake of alcohol and approximately 10% are smoking. These figures are consistent with data from a nationwide German health survey, carried out between 2008 and 2011 [36]. Patient education must address these issues more thoroughly and substantially increase its reach. Only half of the participants in our study state that they have attended diabetes education classes at least once. Loveman et al. (2008) conclude that patient education must have a clear program at the outset and be reinforced at additional points of contact and should be delivered by a team of educators [37]. There need to be more efforts to monitor age, sex, and socioeconomic differences in health behaviour to target interventions and evaluate these kinds of complex interventions.

In our study, we found that a higher patient-perceived quality of patient-physician relationship is associated with a higher score for the mental component of health-related quality of life (MCS-12), roughly equalling the difference in MCS-12 scores between women with and without diabetes [38]. This indicates the potential benefits of intensified patient-oriented care processes for patient outcomes.

The strength of this study is its population-based approach, providing data regardless of contact to medical care providers or membership in a particular sickness insurance fund. Baseline characteristics of our sample, such as the distribution across the treatment groups (no medication, OHA, and insulin), are similar to what has been found for patients with T2DM in other study samples in Germany [39]. We have used multiple logistic regression models and adjusted for important covariables such as education, cardiovascular comorbidity, and duration of diabetes. Models proved to be very robust when sensitivity analyses were performed, that is, when adjusting for diabetes duration instead of treatment type.

The questionnaire used in this study did not contain validated scales for the assessment of care processes or self-management, such as the Patient Assessment of Chronic Illness Care (PACIC) [40], Diabetes Management Self-Efficacy Scale (DMSES) [41], Diabetes Treatment Satisfaction Questionnaire (DTSQ) [42], or SDSCA scale, most of which are not available in German or have only recently been translated [24, 43]. We combined the items on medical examinations, quality of patient-physician relationship, and multiprofessional care to reduce complexity of the analysis. This must be regarded as exploratory and calls for further validation or the use of validated scales in future studies. With regard to measuring HRQL, the use of disease-specific quality of life questionnaires for type 2 diabetes in addition to generic questionnaires such as the SF-12 is important to capture the full spectrum of experiences with diabetes, including the psychological burden of the disease [44].

Some items had a large number of missing values. Thus the analysis was run on a smaller sample, removing participants with >3 missing values in process or outcome variables. The assessment of comorbidities and diabetic complications based on patient-reports may be particularly susceptible to information and recall bias. However, studies that use insurance data or review physicians’ charts have found comparable rates of comorbidities and diabetic complications in Germany [45, 46]. Recall of medical examinations can also be biased. A comparison with data from the largest statutory health insurance fund in Germany shows good agreement with regard to HbA1c testing (in our data 64%, health insurance data 69%) but a higher frequency of self-reported eye exams (in our data 69%, health insurance data 35%) [33]. Other types of medical examinations studied here are not accounted for in administrative data in way that would be comparable to our data.

Our data only captured some aspects of quality of care while others may be added by other studies. Also, classifying the elements as done in this study is one way to conceptualise possible associations and there may be others which are equally valuable. For example, treatment satisfaction can be regarded as patient outcome, when factors not under control of the health care system or the health professionals are considered equally important. Following this, self-monitoring, adherence, and health behaviours can be treated as care processes when focusing on the interaction between health professional and patient to initiate, adopt, and maintain actions. In this study however, we perceive self-management, adherence, and health behaviour as intermediate outcomes, that is, activities that may develop when care processes work well beforehand.

Overall, our analysis should be regarded as explorative and qualitative in its approach. Generalizations from this rather small regional study with mainly self-reported data should be done carefully and only in the light of additional data. This study relied mainly on self-reported questionnaire data with its limitations in validity and reliability. However, the data offer rich insights on patients’ perceptions of quality of diabetes care, which are rare and valuable for expanding our understanding of patient-oriented processes and outcomes in diabetes care.

4.2. Conclusion

Efforts to improve diabetes care need to go beyond guidelines to standardizing treatment and clinical practice and integrate indicators pertaining to higher levels of patient-oriented care processes and outcomes. Our study underlines the importance of monitoring and evaluating diabetes care by drawing on patient-reported indicators for both processes and outcomes as an indispensable part of clinical practice.

Our results stress the importance of finding more effective strategies to support patients to change health behaviour, in particular with regard to physical activity. Attention should be paid to fostering the patient-perceived quality of patient-physician relationship. Diabetes education must broaden its reach and scope, for example, in the field of health behaviour. Rather than programs delivered just once per patient, it must be remodelled into providing long-term support to maintain patient engagement [47, 48]. Further research is warranted to consider how diabetes self-management is associated with patients’ prioritization of health outcomes and quality of life, caregiver support as well as costs.

Authors’ Declaration

I confirm all patient/personal identifiers have been removed or disguised so the patient/person(s) described are not identifiable and cannot be identified through the details of the story.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

The KORA research platform (KORA, Cooperative Research in the Region of Augsburg) was initiated and financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research and by the State of Bavaria. The patient survey regarding diabetes was part of the project “Health Economic Aspects of Diabetes Mellitus Type 2 in Longitudinal and Cross-Sectional Studies” funded by the Federal Association of Statutory Regional Health Funds (AOK Bundesverband). The Helmholtz Zentrum München, German Research Center for Environmental Health, is a partner institution of the German Center for Diabetes Research (DZD e.V.) funded by the German Federal Ministry of Education and Research (BMBF).

References

  1. P. Zhang, X. Zhang, J. Brown et al., “Global healthcare expenditure on diabetes for 2010 and 2030,” Diabetes Research and Clinical Practice, vol. 87, no. 3, pp. 293–301, 2030. View at Publisher · View at Google Scholar
  2. A. Norlund, J. Apelqvist, P.-O. Bitzén, P. Nyberg, and B. Scherstén, “Cost of illness of adult diabetes mellitus underestimated if comorbidity is not considered,” Journal of Internal Medicine, vol. 250, no. 1, pp. 57–65, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Sundaram, J. Kavookjian, J. H. Patrick, L.-A. Miller, S. Suresh Madhavan, and V. Scott, “Quality of life, health status and clinical outcomes in Type 2 diabetes patients,” Quality of Life Research, vol. 16, no. 2, pp. 165–177, 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. C. E. De Beaufort, A. Reunanen, V. Raleigh et al., “European Union diabetes indicators: fact or fiction?” European Journal of Public Health, vol. 13, no. 3, supplement, pp. 51–54, 2003. View at Publisher · View at Google Scholar · View at Scopus
  5. M. P. McGovern, D. J. Williams, P. C. Hannaford et al., “Introduction of a new incentive and target-based contract for family physicians in the UK: good for older patients with diabetes but less good for women?” Diabetic Medicine, vol. 25, no. 9, pp. 1083–1089, 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. NICE, NICE: Guidelines for Diabetes, NICE, 2010, http://guidance.nice.org.uk/Topic/EndocrineNutritionalMetabolic/Diabetes.
  7. ÄZQ, Nationale Versorgungsleitlinien: Typ-2-Diabetes-Gesamtübersicht-Aktuelles, 2011, http://www.versorgungsleitlinien.de/aktuelles/t2dakt.
  8. G. Sidorenkov, F. M. Haaijer-Ruskamp, D. De Zeeuw, H. Bilo, and P. Denig, “Relation between quality-of-care indicators for diabetes and patient outcomes: a systematic literature review,” Medical Care Research and Review, vol. 68, no. 3, pp. 263–289, 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. H. Holman and K. Lorig, “Patient self-management: a key to effectiveness and efficiency in care of chronic disease,” Public Health Reports, vol. 119, no. 3, pp. 239–243, 2004. View at Publisher · View at Google Scholar · View at Scopus
  10. I. M. Ravn, K. Frederiksen, and K. Beedholm, “The chronic responsibility: a critical discourse analysis of Danish chronic care policies,” Qualitative Health Research, 2015. View at Publisher · View at Google Scholar
  11. T. Bodenheimer, K. Lorig, H. Holman, and K. Grumbach, “Patient self-management of chronic disease in primary care,” Journal of the American Medical Association, vol. 288, no. 19, pp. 2469–2475, 2002. View at Publisher · View at Google Scholar · View at Scopus
  12. R. M. Anderson and M. M. Funnell, “Patient empowerment: reflections on the challenge of fostering the adoption of a new paradigm,” Patient Education and Counseling, vol. 57, no. 2, pp. 153–157, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. S. E. Inzucchi, R. M. Bergenstal, J. B. Buse et al., “Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD),” Diabetes Care, vol. 35, no. 6, pp. 1364–1379, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. R. E. Glasgow, M. Peeples, and S. E. Skovlund, “Where is the patient in diabetes performance measures? The case for including patient-centered and self-management measures,” Diabetes Care, vol. 31, no. 5, pp. 1046–1050, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. J. Caro-Bautista, F. J. Martín-Santos, and J. M. Morales-Asencio, “Systematic review of the psychometric properties and theoretical grounding of instruments evaluating self-care in people with type 2 Diabetes Mellitus,” Journal of Advanced Nursing, vol. 70, no. 6, pp. 1209–1227, 2014. View at Publisher · View at Google Scholar · View at Scopus
  16. M.-J. Santana and D. Feeny, “Framework to assess the effects of using patient-reported outcome measures in chronic care management,” Quality of Life Research, vol. 23, no. 5, pp. 1505–1513, 2013. View at Publisher · View at Google Scholar · View at Scopus
  17. P. A. Nutting, W. P. Dickinson, L. M. Dickinson et al., “Use of chronic care model elements is associated with higher-quality care for diabetes,” Annals of Family Medicine, vol. 5, no. 1, pp. 14–20, 2007. View at Publisher · View at Google Scholar · View at Scopus
  18. D. S. Cobden, L. W. Niessen, C. E. Barr, F. F. H. Rutten, and W. K. Redekop, “Relationships among self-management, patient perceptions of care, and health economic outcomes for decision-making and clinical practice in type 2 diabetes,” Value in Health, vol. 13, no. 1, pp. 138–147, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. S. L. Norris, M. M. Engelgau, and K. M. V. Narayan, “Effectiveness of self-management training in type 2 diabetes: a systematic review of randomized controlled trials,” Diabetes Care, vol. 24, no. 3, pp. 561–587, 2001. View at Publisher · View at Google Scholar · View at Scopus
  20. M. Laxy, A. Mielck, M. Hunger et al., “The association between patient-reported self-management behavior, intermediate clinical outcomes, and mortality in patients with type 2 diabetes: results from the kora—a study,” Diabetes Care, vol. 37, no. 6, pp. 1604–1612, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. M. Berger and I. Mühlhauser, “Diabetes care and patient-oriented outcomes,” Journal of the American Medical Association, vol. 281, no. 18, pp. 1676–1678, 1999. View at Publisher · View at Google Scholar · View at Scopus
  22. G. Y. Gandhi, M. H. Murad, A. Fujiyoshi et al., “Patient-important outcomes in registered diabetes trials,” The Journal of the American Medical Association, vol. 299, no. 21, pp. 2543–2549, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. R. Holle, M. Happich, H. Löwel, and H. E. Wichmann, “KORA—a research platform for population based health research,” Gesundheitswesen, vol. 67, no. 1, pp. S19–S25, 2005. View at Publisher · View at Google Scholar · View at Scopus
  24. D. J. Toobert, S. E. Hampson, and R. E. Glasgow, “The summary of diabetes self-care activities measure: results from 7 studies and a revised scale,” Diabetes Care, vol. 23, no. 7, pp. 943–950, 2000. View at Publisher · View at Google Scholar · View at Scopus
  25. K. Esefeld, P. Zimmer, M. Stumvoll, and M. Halle, “Diabetes, sport und bewegung,” Diabetologie, vol. 9, pp. S196–S201, 2014, http://www.deutsche-diabetes-gesellschaft.de/fileadmin/Redakteur/Leitlinien/Praxisleitlinien/2014/DuS_S2-14_DDG_S196-S201_Diabetes-Sport-Bewegung.pdf. View at Google Scholar
  26. J. Mann, I. De Leeuw, K. Hermansen et al., “Evidence-based nutritional approaches to the treatment and prevention of diabetes mellitus,” Nutrition, Metabolism and Cardiovascular Diseases, vol. 14, no. 6, pp. 373–394, 2004. View at Google Scholar
  27. BMG, “Zwanzigste Verordnung zur Änderung der Risikostruktur-Ausgleichsverordnung (20. RSA-ÄndV),” in Bundesgesetzblatt, vol. 35, pp. 1542–1550, 2009. View at Google Scholar
  28. D. Mozaffarian, A. Kamineni, M. Carnethon, L. Djoussé, K. J. Mukamal, and D. Siscovick, “Lifestyle risk factors and new-onset diabetes mellitus in older adults: the cardiovascular health study,” Archives of Internal Medicine, vol. 169, no. 8, pp. 798–807, 2009. View at Publisher · View at Google Scholar · View at Scopus
  29. J. Alonso, M. Ferrer, B. Gandek et al., “Health-related quality of life associated with chronic conditions in eight countries: results from the International Quality of Life Assessment (IQOLA) Project,” Quality of Life Research, vol. 13, no. 2, pp. 283–298, 2004. View at Publisher · View at Google Scholar · View at Scopus
  30. M. Bullinger and I. Kirchberger, Der SF-36 Fragebogen zum Gesundheitszustand, Hogrefe, Göttingen, Germany, 1998.
  31. SAS_Institute, SAS 9.2, SAS Institute, Cary, NC, USA, 2008.
  32. A. Ash, “Measuring quality,” Medical Care, vol. 46, no. 2, pp. 105–108, 2008. View at Publisher · View at Google Scholar · View at Scopus
  33. I. Schubert and I. Köster, “Diabetes mellitus: Versorgungsmonitoring auf Basis von Routinedaten,” in Versorgungsreport 2011, C. Günster, J. Klose, and N. Schmacke, Eds., pp. 129–145, Schattauer, Stuttgart, Germany, 2011. View at Google Scholar
  34. BMG, “Zwölfte Verordnung zur Änderung der Risikostruktur-Ausgleichsverordnung (12.RSA-ÄndV),” Bundesgesetzblatt, vol. 50, pp. 2457–2472, 2005. View at Google Scholar
  35. GBA, “Bekanntmachung eines Beschlusses des Gemeinsamen Bundesausschusses über die Änderung der Arzneimittel-Richtlinie (AM-RL): Anlage III-Übersicht der Verordnungseinschränkungen und -ausschlüsse Harn- und Blutzuckerteststreifen bei Diabetes mellitus Typ 2,” in 1084 A, GBgSV, Ed., Bundesministerium für Gesundheit, Berlin, Germany, 2011. View at Google Scholar
  36. RKI, German Health Interview and Examination Survey for Adults (DEGS), Robert Koch Institute, Berlin, Germany, 2013, http://www.degs-studie.de/english/results/basic-reporting.html.
  37. E. Loveman, G. K. Frampton, and A. J. Clegg, “The clinical effectiveness of diabetes education models for Type 2 diabetes: a systematic review,” Health Technology Assessment, vol. 12, no. 9, pp. 1–116, 2008. View at Google Scholar · View at Scopus
  38. M. Schunk, P. Reitmeir, S. Schipf et al., “Health-related quality of life in subjects with and without Type 2 diabetes: pooled analysis of five population-based surveys in Germany,” Diabetic Medicine, vol. 29, no. 5, pp. 646–653, 2012. View at Publisher · View at Google Scholar · View at Scopus
  39. E. Huppertz, L. Pieper, J. Klotsche et al., “Diabetes mellitus in german primary care: quality of glycaemic control and subpopulations not well controlled—results of the DETECT study,” Experimental and Clinical Endocrinology and Diabetes, vol. 117, no. 1, pp. 6–14, 2009. View at Publisher · View at Google Scholar · View at Scopus
  40. R. E. Glasgow, E. H. Wagner, J. Schaefer, L. D. Mahoney, R. J. Reid, and S. M. Greene, “Development and validation of the Patient Assessment of Chronic Illness Care (PACIC),” Medical Care, vol. 43, no. 5, pp. 436–444, 2005. View at Publisher · View at Google Scholar · View at Scopus
  41. J. J. van der Bijl, A. van Poelgeest-Eeltink, and L. Shortridge-Baggett, “The psychometric properties of the diabetes management self-efficacy scale for patients with type 2 diabetes mellitus,” Journal of Advanced Nursing, vol. 30, no. 2, pp. 352–359, 1999. View at Publisher · View at Google Scholar · View at Scopus
  42. C. Bradley, “The diabetes treatment satisfaction questionnaire: DTSQ,” in Handbook of Psychology and Diabetes: A Guide to Psychological Measurement in Diabetes Research and Practice, C. Bradley, Ed., pp. 111–132, Harwood Academic Publishers, Chur, Switzerland, 1994. View at Google Scholar
  43. K. Goetz, T. Freund, J. Gensichen, A. Miksch, J. Szecsenyi, and J. Steinhaeuser, “Adaptation and psychometric properties of the PACIC short form,” The American Journal of Managed Care, vol. 18, no. 2, pp. e55–e60, 2012. View at Google Scholar · View at Scopus
  44. J. Speight, M. D. Reaney, and K. D. Barnard, “Not all roads lead to Rome—a review of quality of life measurement in adults with diabetes,” Diabetic Medicine, vol. 26, no. 4, pp. 315–327, 2009. View at Publisher · View at Google Scholar · View at Scopus
  45. H. Hauner, I. Köster, and I. Schubert, “Trends in der Prävalenz und ambulanten Versorgung von Menschen mit Diabetes mellitus,” Deutsches Ärzteblatt, vol. 104, no. 41, pp. 2799–2805, 2007. View at Google Scholar
  46. P. Ott, I. Benke, J. Stelzer, C. Köhler, and M. Hanefeld, “‘Diabetes in Germany’ (DIG) study—a prospective 4-year-follow-up study on the quality of risk factor control in patients with type 2 diabetes in daily practice,” Deutsche Medizinische Wochenschrift, vol. 134, no. 7, pp. 291–297, 2009. View at Publisher · View at Google Scholar · View at Scopus
  47. K. Khunti, L. J. Gray, T. Skinner et al., “Effectiveness of a diabetes education and self management programme (DESMOND) for people with newly diagnosed type 2 diabetes mellitus: three year follow-up of a cluster randomised controlled trial in primary care,” British Medical Journal, vol. 344, no. 7860, Article ID e2333, 2012. View at Publisher · View at Google Scholar · View at Scopus
  48. L. Minet, S. Møller, W. Vach, L. Wagner, and J. E. Henriksen, “Mediating the effect of self-care management intervention in type 2 diabetes: A meta-analysis of 47 randomised controlled trials,” Patient Education and Counseling, vol. 80, no. 1, pp. 29–41, 2010. View at Publisher · View at Google Scholar · View at Scopus