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1.  Multimorbidity patterns in a primary care population aged 55 years and over 
Family Practice  2015;32(5):505-513.
To support the management of multimorbid patients in primary care, evidence is needed on prevalent multimorbidity patterns.
To identify the common and distinctive multimorbidity patterns.
Clinical data of 120480 patients (≥55 years) were extracted from 158 general practices in 2002–11. Prevalence rates of multimorbidity were analyzed (overall, and for 24 chronic diseases), adjusted for practice, number of diseases and patients’ registration period; differentiated between patients 55–69 and ≥70 years. To investigate multimorbidity patterns, prevalence ratios (prevalence rate index-disease group divided by that in the non-index-disease group) were calculated for patients with heart failure, diabetes mellitus, migraine or dementia.
Multiple membership multilevel models showed that the overall adjusted multimorbidity rate was 86% in patients with ≥1 chronic condition, varying from 70% (migraine) to 98% (heart failure), 38% had ≥4 chronic diseases. In patients 55–69 years, 83% had multimorbidity. Numerous significant prevalence ratios were found for disease patterns in heart failure patients, ranging from 1.2 to 7.7, highest ratio for chronic obstructive pulmonary disease-cardiac dysrhythmia. For diabetes mellitus, dementia or migraine patients highest ratios were for heart failure-visual disorder (2.1), heart failure-depression (3.9) and depression-back/neck disorder (2.1), respectively (all P-values <0.001).
Multimorbidity management in general practice can be reinforced by knowledge on the clinical implications of the presence of the comprehensive disease patterns among the elderly patients, and those between 55 and 69 years. Guideline developers should be aware of the complexity of multimorbidity. As a consequence of this complexity, it is even more important to focus on what matters to a patient with multimorbidity in general practice.
PMCID: PMC4576758  PMID: 26040310
Chronic disease; general practice; multimorbidity; prevalence; primary health care.
2.  Labour intensity of guidelines may have a greater effect on adherence than GPs' workload 
BMC Family Practice  2009;10:74.
Physicians' heavy workload is often thought to jeopardise the quality of care and to be a barrier to improving quality. The relationship between these has, however, rarely been investigated. In this study quality of care is defined as care 'in accordance with professional guidelines'. In this study we investigated whether GPs with a higher workload adhere less to guidelines than those with a lower workload and whether guideline recommendations that require a greater time investment are less adhered to than those that can save time.
Data were used from the Second Dutch National survey of General Practice (DNSGP-2). This nationwide study was carried out between April 2000 and January 2002.
A multilevel logistic-regression analysis was conducted of 170,677 decisions made by GPs, referring to 41 Guideline Adherence Indicators (GAIs), which were derived from 32 different guidelines. Data were used from 130 GPs, working in 83 practices with 98,577 patients. GP-characteristics as well as guideline characteristics were used as independent variables. Measures include workload (number of contacts), hours spent on continuing medical education, satisfaction with available time, practice characteristics and patient characteristics. Outcome measure is an indicator score, which is 1 when a decision is in accordance with professional guidelines or 0 when the decision deviates from guidelines.
On average, 66% of the decisions GPs made were in accordance with guidelines. No relationship was found between the objective workload of GPs and their adherence to guidelines. Subjective workload (measured on a five point scale) was negatively related to guideline adherence (OR = 0.95). After controlling for all other variables, the variation between GPs in adherence to guideline recommendations showed a range of less than 10%.
84% of the variation in guideline adherence was located at the GAI-level. Which means that the differences in adherence levels between guidelines are much larger than differences between GPs. Guideline recommendations that require an extra time investment during the same consultation are significantly less adhered to: (OR = 0.46), while those that can save time have much higher adherence levels: OR = 1.55). Recommendations that reduce the likelihood of a follow-up consultation for the same problem are also more often adhered to compared to those that have no influence on this (OR = 3.13).
No significant relationship was found between the objective workload of GPs and adherence to guidelines. However, guideline recommendations that require an extra time investment are significantly less well adhered to while those that can save time are significantly more often adhered to.
PMCID: PMC2791751  PMID: 19943953
3.  Do decision support systems influence variation in prescription? 
Translating scientific evidence into daily practice is problematic. All kinds of intervention strategies, using educational and/or directive strategies, aimed at modifying behavior, have evolved, but have been found only partially successful. In this article the focus is on (computerized) decision support systems (DSSs). DSSs intervene in physicians' daily routine, as opposed to interventions that aim at influencing knowledge in order to change behavior. We examined whether general practitioners (GPs) are prescribing in accordance with the advice given by the DSS and whether there is less variation in prescription when the DSS is used.
Data were used from the Second Dutch National Survey of General Practice (DNSGP2), collected in 2001. A total of 82 diagnoses, 749811 contacts, 133 physicians, and 85 practices was included in the analyses. GPs using the DSS daily were compared to GPs who do not use the DSS. Multilevel analyses were used to analyse the data. Two outcome measures were chosen: whether prescription was in accordance with the advice of the DSS or not, and a measure of concentration, the Herfindahl-Hirschman Index (HHI).
GPs who use the DSS daily prescribe more according to the advice given in the DSS than GPs who do not use the DSS. Contradictory to our expectation there was no significant difference between the HHIs for both groups: variation in prescription was comparable.
We studied the use of a DSS for drug prescribing in general practice in the Netherlands. The DSS is based on guidelines developed by the Dutch College of General Practitioners and implemented in the Electronic Medical Systems of the GPs. GPs using the DSS more often prescribe in accordance with the advice given in the DSS compared to GPs not using the DSS. This finding, however, did not mean that variation is lower; variation is the same for GPs using and for GPs not using a DSS. Implications of the study are that DSSs can be used to implement guidelines, but that it should not be expected that variation is limited.
PMCID: PMC2662826  PMID: 19183464

Results 1-3 (3)