Multimorbidity In Primary Care Research Articles

Managing patients with multimorbidity: systematic review of interventions in primary care and community settings

Objective To determine the effectiveness of interventions designed to improve outcomes in patients with multimorbidity in primary care and community settings.Design Systematic review.Data sources Medline, Embase, CINAHL, CAB Health, Cochrane...

The impact of perceived social support and sense of coherence on health-related quality of life in multimorbid primary care patients

This study explores the impact of perceived social support and sense of coherence as positive resources for health-related quality of life in multimorbid primary care patients. We analysed cross-sectional survey data on health-related quality of life (EQ-5D), perceived social support (FSozU-K22), sense of coherence (SOC-L9), social demographics and self reported morbidity of 103 multimorbid patients from 10 general practices in Germany. A multiple linear regression model was used to determine the impact of social support and sense of coherence on the health-related quality of life while controlling for age, sex, educational level, marital status and number of chronic conditions. In the final regression model, higher sense of coherence scores were associated with higher health-related quality of life scores (standardized ß 0.34, p < 0.001) whereas a higher number of chronic conditions was associated with lower health-related quality of life scores (standardized ß -0.41, p < 0.001). In the bivariate model, higher perceived social support was associated with higher health-related quality of life scores (standardized ß 0.35, p < 0.001), whereas the model failed to show a significant association after controlling for sense of coherence which is a potential resource for improving health-related quality of life in multimorbid primary care patients. It emerged as a significant element contributing to the prediction of health-related quality of life. This issue may indicate the importance of internal resources for multimorbid patients.

Multimorbidity in primary care: a systematic review of prospective cohort studies

Primary care increasingly deals with patients with multimorbidity, but relevant evidence-based interventions are scarce. Knowledge about multimorbidity over time is required to inform the development of effective interventions. This review identifies prospective cohort studies of multimorbidity in primary care to determine: their nature, scope and key findings; the methodologies used; and gaps in knowledge. Systematic review. Studies were identified by searching electronic databases, reviewing citations, and writing to authors. Searches were limited to adult populations with no restrictions on publication date or language. In total, 996 articles were identified and screened. Of the 996 articles, six detailing five completed prospective cohort studies were selected as appropriate. Three of the studies were undertaken in the US and two in The Netherlands; none was nationally representative. The main focus of the studies was: healthcare utilisation and/or costs (n = 3); patients' physical functioning (n = 1); and risk factors for developing multimorbidity (n = 1). The conditions that were included varied widely. The findings of these studies showed that multimorbidity increased healthcare costs (n = 2), inpatient admission (n = 1), death rates (n = 1), and service use (n = 3), and reduced physical functioning (n = 1). One study identified psychosocial risk factors for multimorbidity. No study used random sampling, sample sizes were relatively small (414-3745 patients at baseline), and study duration was relatively short (1-4 years). No study focused on prevalence, treatment use, patient safety, service models, cultural or socioeconomic factors, and patient experience, and no study collected qualitative data. Few longitudinal studies based in primary care have investigated multimorbidity. Further large, long-term prospective studies are required to inform healthcare commissioning, planning, and delivery.

Healthcare professionals’ adoption and use of a clinical information system (CIS) in primary care: Insights from the Da Vinci study

Given the increasing prevalence of multimorbidity in primary care (PC), interdisciplinary PC teams supported by appropriate clinical information systems (CIS) are needed in order to deal with the complexity of multimorbid patients’ care. Our team has developed such a system, called the Da Vinci system. However, despite the expected benefits, evidence suggests generally low rates of CIS adoption. To optimize adoption in PC settings, a better understanding of the implementation process of such systems is crucial. Purpose To identify user profiles, investigate the drivers of and barriers to adoption and use of the Da Vinci system, a PC tailored CIS, and understand the dynamics of the CIS adoption for each profile. Methods Using a longitudinal approach, we conducted a qualitative study (individual interviews, documentation and observation) based on the Diffusion of Innovation theory. It included 31 participants (primary care physicians, staff or residents, nurses, pharmacists) from two Family Medicine Groups in Quebec (Canada). Results The different user profiles drawn from the dynamics of implementation are linked to different sets of perceived drivers and barriers that evolve over time. Certain factors favour the decision of adopting Da Vinci early on: e.g. user skills and the system's expected ease of use and usefulness. Certain concerns hinder its adoption: e.g. perceived negative impact on the doctor–patient relationship. Over time, 5 factors appear to be related to more advanced exploitation of the system's functionalities: user skills, ease of use, comfort using the system in front of patients, support from colleagues and, more importantly, perceived positive impacts. Conclusions A better understanding of the dynamics of CIS implementation provides insight into how best to encourage clinicians to adopt and make full use of such systems to improve the quality of care for multimorbid patients followed in PC settings.

The prevalence of multimorbidity in primary care and its effect on health care utilization and cost

Multimorbidity is common among the heterogeneous primary care population, but little data exist on its association with health care utilization or cost. The aim of this observational study was to examine the prevalence and associated health care utilization and cost of patients with multimorbidity. All patients >50 years of age were eligible for the study which took place in three primary care practices in the West of Ireland. Chronic medical conditions and associated health care utilization in primary and secondary care were identified through patient record review. In a sample of 3309 patients in the community, the prevalence of multimorbidity was 66.2% (95% CI: 64.5-67.8) in those >50 years of age. Health care utilization and cost was significantly increased among patients with multimorbidity (P < 0.001). After multivariate adjustment for age, gender and free medical care eligibility, the addition of each chronic condition led to an associated increase in primary care consultations (P = 0.001) (11.9 versus 3.7 for >4 conditions versus 0 conditions); hospital out-patient visits (P = 0.001) (3.6 versus 0.6 for >4 conditions versus 0 conditions); hospital admissions (P = 0.01) [adjusted odds ratio (OR) of 4.51 for >4 conditions versus 0 conditions] and total health care costs (P < 0.001) (€4,096.86 versus €760.20 for >4 conditions versus 0 conditions) over the previous 12 months. Multimorbidity is very common in primary care and in a system with strong gatekeeping is associated with high health care utilization and cost across the health care system. Interventions to address quality and cost associated with multimorbidity must focus on primary as well as secondary care.

Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study

In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity. To describe the epidemiology of multimorbidity and relationships between multimorbidity and primary care consultation rates and continuity of care. Retrospective cohort study. Random sample of 99 997 people aged 18 years or over registered with 182 general practices in England contributing data to the General Practice Research Database. Multimorbidity was defined using two approaches: people with multiple chronic conditions included in the Quality and Outcomes Framework, and people identified using the Johns Hopkins University Adjusted Clinical Groups (ACG®) Case-Mix System. The determinants of multimorbidity (age, sex, area deprivation) and relationships with consultation rate and continuity of care were examined using regression models. Sixteen per cent of patients had more than one chronic condition included in the Quality and Outcomes Framework, but these people accounted for 32% of all consultations. Using the wider ACG list of conditions, 58% of people had multimorbidity and they accounted for 78% of consultations. Multimorbidity was strongly related to age and deprivation. People with multimorbidity had higher consultation rates and less continuity of care compared with people without multimorbidity. Multimorbidity is common in the population and most consultations in primary care involve people with multimorbidity. These people are less likely to receive continuity of care, although they may be more likely to gain from it.

GPs' and pharmacists' experiences of managing multimorbidity: a ‘Pandora's box’

Multimorbidity is defined as the occurrence of two or more chronic diseases in one individual. Patients with multimorbidity generally have poorer health and functioning and higher rates of attendance in primary care and specialty settings. To explore the views and attitudes of GPs and pharmacists managing patients with multimorbidity in primary care. Qualitative study using focus groups. Primary care in Ireland. Three focus groups were held in total, involving 13 GPs and seven pharmacists. Focus groups were recorded, transcribed, and analysed using the 'framework' approach. The predominant themes to emerge from the focus groups were: 1) the concept of multimorbidity and the link to polypharmacy and ageing; 2) health systems issues relating to lack to time, inter-professional communication difficulties, and fragmentation of care; 3) individual issues from clinicians relating to professional roles, clinical uncertainty, and avoidance; 4) patient issues; and 5) potential management solutions. This study provides information on the significant impact of multimorbidity from a professional perspective. It highlights potential elements of an intervention that could be designed and tested to achieve improvements in the management of multimorbidity, outcomes for individuals affected, and the experiences of those providing healthcare.

The electronic Cumulative Illness Rating Scale: a reliable and valid tool to assess multi-morbidity in primary care

The presence of multiple concomitant diseases is an increasing health problem, and prompted by the limitations of the disease count, several indices measuring multi-morbidity or co-morbidity have been described to account for the overall burden of morbidity. The Cumulative Illness Rating Scale (CIRS) is one of those indices. We developed an electronic version of the CIRS (eCIRS) to take advantage of computerized data processing. The aim of this study was to evaluate the reliability and validity of the eCIRS scored in a primary care setting. Two nurses interviewed 48 adult patients recruited during consecutive consultation periods in a primary care setting and scored the eCIRS in a random order during two sessions of data collection (T1 and T2) 1 month apart. We measured intra- and inter-rater reliability [intra-class correlation coefficient (ICC)]. We also assessed concomitant validity [(Pearson's correlation (r)] using standard CIRS scored by the attending family doctors. Intra-rater (ICC: 0.90 and 0.95) and inter-rater reliability (ICC: 0.86 and 0.91) were both excellent. No significant differences between the nurses' scores at T1 and T2 (P = 0.40 for nurse 1, P = 0.73 for nurse 2) were found. The eCIRSs scored by the nurses were highly correlated with the CIRSs scored by the doctors (r = 0.80 and 0.88). Reliable and valid, the eCIRS completed during patient interviews with trained nurses can be used to quantify multi-morbidity in primary care, either for research or clinical use.

The German MultiCare-study: Patterns of multimorbidity in primary health care – protocol of a prospective cohort study

BackgroundMultimorbidity is a highly frequent condition in older people, but well designed longitudinal studies on the impact of multimorbidity on patients and the health care system have been remarkably scarce in numbers until today. Little is known about the long term impact of multimorbidity on the patients' life expectancy, functional status and quality of life as well as health care utilization over time. As a consequence, there is little help for GPs in adjusting care for these patients, even though studies suggest that adhering to present clinical practice guidelines in the care of patients with multimorbidity may have adverse effects.Methods/DesignThe study is designed as a multicentre prospective, observational cohort study of 3.050 patients aged 65 to 85 at baseline with at least three different diagnoses out of a list of 29 illnesses and syndromes. The patients will be recruited in approx. 120 to 150 GP surgeries in 8 study centres distributed across Germany. Information about the patients' morbidity will be collected mainly in GP interviews and from chart reviews. Functional status, resources/risk factors, health care utilization and additional morbidity data will be assessed in patient interviews, in which a multitude of well established standardized questionnaires and tests will be performed.DiscussionThe main aim of the cohort study is to monitor the course of the illness process and to analyse for which reasons medical conditions are stable, deteriorating or only temporarily present. First, clusters of combinations of diseases/disorders (multimorbidity patterns) with a comparable impact (e.g. on quality of life and/or functional status) will be identified. Then the development of these clusters over time will be analysed, especially with regard to prognostic variables and the somatic, psychological and social consequences as well as the utilization of health care resources. The results will allow the development of an instrument for prediction of the deterioration of the illness process and point at possibilities of prevention. The practical consequences of the study results for primary care will be analysed in expert focus groups in order to develop strategies for the inclusion of the aspects of multimorbidity in primary care guidelines.

Multimorbidity in primary care: developing the research agenda

Multimorbidity in primary care: developing the research agenda

Multimorbidity in primary care: Prevalence and trend over the last 20 years

Objective: To determine the prevalence of multimorbidity in primary care, by age, sex, and socio-economic class, and to analyse the trend in multimorbidity over the last 20 years. Methods: We performed an observational study using data from the Continuous Morbidity Registration (CMR) Nijmegen. This registration includes approximately 13 500 enlisted patients. To study the distribution of multimorbidity by age, sex, and socio-economic class, we analysed all patients enlisted in the CMR in 2005. To analyse the trend of multimorbidity over time, we studied the prevalence of multimorbidity from 1985 to 2005. Results: We found that increasing age, female sex, and low socio-economic class are associated with an increasing number of patients with multimorbidity. The prevalence of chronic diseases doubled between 1985 and 2005. The proportion of patients with four or more chronic diseases increased in this period by approximately 300%.Conclusion: The increasing amount of multimorbidity in primary care as well as the increasing number of chronic diseases per patient leads to more complex medical care. The general practitioner needs guidelines focusing on multimorbidity to support this care. The registration of chronic diseases by the general practitioner will become more complex and time-consuming.

Psychological Distress and Multimorbidity in Primary Care

Psychological distress may decrease adherence to medical treatments and lead to poorer health outcomes of chronic diseases. The aim of this study was to evaluate the relationship between psychological distress and multimorbidity among patients seen in family practice after controlling for potential confounding variables and taking into account the severity of diseases. We evaluated 238 patients to construct quintiles of increasing multimorbidity based on the Cumulative Illness Rating Scale (CIRS), which is a comprehensive multimorbidity index that takes into account disease severity. Patients completed a psychiatric symptom questionnaire as a measurement of their psychological distress. In the first model of logistic regression analyses, we used the counted number of chronic diseases as the independent variable. In subsequent models, we used the quintiles of CIRS. After adjusting for confounding factors, multimorbidity measured by a simple count of chronic diseases was not related to psychological distress (OR, 1.12; 95% CI, 0.97-1.29; P = .188), whereas multimorbidity measured by the CIRS remained significantly associated (OR, 1.67; 95% CI, 1.19-2.37; P = .002). The estimate risk of psychological distress by quintile of CIRS was as follows: Q1/2 = 1.0; Q3 = OR, 1.72; 95% CI, 0.53-5.86; Q4 = OR, 2.99; 95% CI, 1.01-9.74; Q5 = OR, 4.67; 95% CI, 1.61-15.16. Psychological distress increased with multimorbidity when we accounted for disease severity. Clinicians should be aware of the possible presence of psychological distress, which can further complicate the comprehensive management of these complex patients.

Clinical factors contributing to the differential diagnosis of primary insomnia and insomnia related to mental disorders.

Primary insomnia and insomnia related to mental disorders are the two most common DSM-IV insomnia diagnoses, but distinguishing between them is difficult in clinical practice. This analysis was performed to identify clinical factors used by sleep specialists to distinguish primary insomnia from insomnia related to mental disorders. Clinicians evaluated 216 patients referred for insomnia at five clinical sites, rated a list of clinical factors judged to contribute to each patient's presentation, and assigned diagnoses. Analysis of variance was performed, with contributing factors as the dependent variable and diagnostic group and clinic location as independent variables. Sleep specialists rated a psychiatric disorder as a stronger factor for insomnia related to mental disorders and rated negative conditioning and sleep hygiene as stronger factors for primary insomnia. However, a psychiatric disorder was rated as a contributing factor for 77% of patients who received a first diagnosis of primary insomnia. While neither sleep hygiene nor negative conditioning is a diagnostic criterion in DSM-IV, these results support the face validity of these clinical factors distinguishing between primary insomnia and insomnia related to mental disorders. The use of a psychiatric disorder as an inclusion criterion for insomnia related to mental disorders and an exclusion criterion for primary insomnia reinforces a categorical distinction between the two diagnoses, but the contribution of psychiatric symptoms in primary insomnia appears to be a clinically relevant one. These findings suggest the need for studies on the validity of negative conditioning and sleep hygiene in the etiology of primary insomnia, as well as on the significance of psychiatric disorders, especially depression, in primary insomnia.