Patient Care Teams in treatment of diabetes and chronic heart failure in primary care: An observational networks study

Scientific Institute for Quality of Healthcare, Radboud University Nijmegen Medical Centre, P,O, Box 9101, 6500 HB, Nijmegen, the Netherlands. .
Implementation Science (Impact Factor: 4.12). 07/2011; 6(1):66. DOI: 10.1186/1748-5908-6-66
Source: PubMed


Patient care teams have an important role in providing medical care to patients with chronic disease, but insight into how to improve their performance is limited. Two potentially relevant determinants are the presence of a central care provider with a coordinating role and an active role of the patient in the network of care providers. In this study, we aimed to develop and test measures of these factors related to the network of care providers of an individual patient.
We performed an observational study in patients with type 2 diabetes or chronic heart failure, who were recruited from three primary care practices in The Netherlands. The study focused on medical treatment, advice on physical activity, and disease monitoring. We used patient questionnaires and chart review to measure connections between the patient and care providers, and a written survey among care providers to measure their connections. Data on clinical performance were extracted from the medical records. We used network analysis to compute degree centrality coefficients for the patient and to identify the most central health professional in each network. A range of other network characteristics were computed including network centralization, density, size, diversity of disciplines, and overlap among activity-specific networks. Differences across the two chronic conditions and associations with disease monitoring were explored.
Approximately 50% of the invited patients participated. Participation rates of health professionals were close to 100%. We identified 63 networks of 25 patients: 22 for medical treatment, 16 for physical exercise advice, and 25 for disease monitoring. General practitioners (GPs) were the most central care providers for the three clinical activities in both chronic conditions. The GP's degree centrality coefficient varied substantially, and higher scores seemed to be associated with receiving more comprehensive disease monitoring. The degree centrality coefficient of patients also varied substantially but did not seem to be associated with disease monitoring.
Our method can be used to measure connections between care providers of an individual patient, and to examine the association between specific network parameters and healthcare received. Further research is needed to refine the measurement method and to test the association of specific network parameters with quality and outcomes of healthcare.

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    • "Previous research, which used SNA in health care, showed that social networks of patients and healthcare professionals could be measured in a valid way and showed substantial variation [6-8]. Pilot studies in primary care in the Netherlands have confirmed the feasibility and viability of specific measures for documenting social networks of information sharing [9-11]. Despite these and other studies in health care, insights into network-related mechanisms underlying healthcare delivery and self-management (health-related behaviors) are still limited. "
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    ABSTRACT: Background In recent years, preventive and clinical interventions for cardiovascular risk management have been implemented widely in primary care in the Netherlands. Although this has enhanced quality and outcomes of cardiovascular risk management, further improvement remains possible. In the planned observational study, we aim to examine the role of social networks of healthcare providers and patients in quality and outcomes of cardiovascular risk management. Methods/Design In a longitudinal observational study, data on social networks of approximately 300 primary care providers from 30 general practices and 900 cardiovascular patients will be collected twice, with a six month interval, using a mix of measures. Social networks are documented with specifically designed questionnaires for patients, relatives, and healthcare professionals. For each included patient, we will extract from medical records to gather data on clinical processes and cardiovascular risk predictors. Data on self-management and psychosocial outcomes of patients will be collected using questionnaires for patients. The analysis focuses on identifying network characteristics, which are associated with (changes in) cardiovascular risk management or self-management. Discussion This research will provide insight into the role of social networks of patients and providers in cardiovascular risk management in primary practice. Trial registration Nederlands Trial Register NTR4069.
    BMC Health Services Research 06/2014; 14(1):265. DOI:10.1186/1472-6963-14-265 · 1.71 Impact Factor
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    • "The present study had a low response compared to recent studies conducted in Dutch general practice [29,30]. This low response may indicate selection bias, making it uncertain whether the sample reflected the general practice population. "
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    ABSTRACT: Background Patient reported outcome measures (PROMs) have been introduced in studies to assess healthcare performance. The development of PROMs for primary care poses specific challenges, including a preference for generic measures that can be used across diseases, including early phases or mild conditions. This pilot study aimed to explore the potential usefulness of seven generic measures for assessing health outcomes in primary care patients. Methods A total of 300 patients in three general practices were invited to participate in the study, shortly after their visit to the general practitioner. Patients received a written questionnaire, containing seven validated instruments, focused on patient empowerment (PAM-13 or EC-17), quality of life (EQ-5D or SF-12), mental health (GHQ-12), enablement (PEI) and perceived treatment effect (GPE). Furthermore, questions on non-specific symptoms and number of GP contacts were included. After 4 weeks patients received a second, identical, questionnaire. Response and missing items, total scores and dispersion, responsiveness, and associations between instruments and other measures were examined. Results A total of 124 patients completed the questionnaire at baseline, of whom 98 completed it both at baseline and 4 weeks later (response rate: 32.7%). The instruments had a full completion rate of 80% or higher. Differences between baseline and follow up were significant for the EQ-5D (p = 0.026), SF-12 PCS (p = 0.026) and the GPE (p = 0.006). A strong correlation (r ≥ 0.6) was found between the SF-12 MCS and GHQ-12, at both baseline measurement and after four weeks. Other observed associations between instruments were moderately strong. No strong correlations were found between instruments and non-specific symptoms or number of GP contacts. Conclusions The present study is among the first to explore the use of generic patient-reported outcome measures in primary care. It provides several leads for developing a generic PROM questionnaire in primary care as well as for potential limitations of such instruments.
    BMC Family Practice 05/2014; 15(1):88. DOI:10.1186/1471-2296-15-88 · 1.67 Impact Factor
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    • "Although, network approaches’ application in medical care research is fairly new, in many scientific disciplines such as neurosciences, molecular life sciences, and public health, it has been used. Recent research including studies of patient care teams in treatment of diabetes and chronic heart failure in primary care [32], opinion networks of long-term care specialists [41], and connectedness of health care professionals in the treatment of Parkinson [33]. A social network approach may be particularly relevant if actors (people) have flawed knowledge on their performance options and the disease-related outcomes. "
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    ABSTRACT: Identification of Educational Influentials (EIs) in clinical settings helps considerably to knowledge transfer among health and medical practice providers. The aim of this study was identifying EIs in diabetic foot ulcers (DFU) by medical students (clerks, interns and residents) and providing their relational pattern in this subject. Subjects were medical students at clerk, intern and resident levels in a local educational hospital. A standard questionnaire with four domains (knowledge, communication, participation and professional ethics) was used for identifying EIs. Students introduced those people with these characteristics who referred them for DFU. Respective communication networks were drawn as intra-group (such as resident-resident) and inter-group (such as intern-resident) networks and quantitative criteria of density, in-degree and out-degree centrality and reciprocity were measured. The network density of clerks-residents (0.024) and interns-residents (0.038) were higher than clerks-attends (0.015) and interns-attends (0.05); indicating that there were more consulting interactions in former networks than the latter. Degree centrality in residents-related networks (clerks-residents = 2.3; interns-residents = 2.6) were higher than attends-related ones (clerks-attends = 1.1; interns-attends = 1.7), while they were not statistically significant. However, In-degree centralization, which indicating a degree of variance of the whole network of ingoing relationships, in attends-related networks was greater than resident-related networks. Resident were consulted with almost as same as attends on DFU. It showed that residents were playing a remarkable role in knowledge transfer and they can be considered as EIs in this clinical setting. It seemed that the availability was the main reason for this key role.
    Journal of Diabetes and Metabolic Disorders 09/2013; 12(1):44. DOI:10.1186/2251-6581-12-44
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