A telemonitoring program, via mobile phone messages, appears to be useful for improving the risk profile in ACS survivors and can be an effective tool for secondary prevention, especially for overweight patients.

BackgroundChronic obstructive pulmonary disease (COPD) is frequent and often coexists with other diseases. The aim of this study was to quantify the prevalence of COPD and related chronic comorbidity among patients aged over 40 years visiting family practices in an area of Madrid.MethodsAn observational, descriptive, cross-sectional study was conducted in a health area of the Madrid Autonomous Region (Comunidad Autónoma de Madrid). The practice population totalled 198,670 persons attended by 129 Family Physicians (FPs), and the study population was made up of persons over the age of 40 years drawn from this practice population. Patients were deemed to have COPD if this diagnosis appeared on their clinical histories. Prevalence of COPD; prevalence of a further 25 chronic diseases in patients with COPD; and standardised prevalence ratios, were calculated.ResultsPrevalence of COPD in family medicine was 3.2% (95% CI 3.0–3.3) overall, 5.3% among men and 1.4% among women; 90% of patients presented with comorbidity, with a mean of 4 ± 2.04 chronic diseases per patient, with the most prevalent related diseases being arterial hypertension (52%), disorders of lipid metabolism (34%), obesity (25%), diabetes (20%) and arrhythmia (15%). After controlling for age and sex, the observed prevalence of the following ten chronic diseases was higher than expected: heart failure; chronic liver disease; asthma; generalised artherosclerosis; osteoporosis; ischaemic heart disease; thyroid disease; anxiety/depression; arrhythmia; and obesity.ConclusionsPatients with COPD, who are frequent in family practice, have a complex profile and pose a clinical and organisational challenge to FPs.

IntroductionHealthcare management is oriented toward single diseases, yet multimorbidity is nevertheless the rule and there is a tendency for certain diseases to occur in clusters. This study sought to identify comorbidity patterns in patients with chronic diseases, by reference to number of comorbidities, age and sex, in a population receiving medical care from 129 general practitioners in Spain, in 2007.MethodsA cross-sectional study was conducted in a health-area setting of the Madrid Autonomous Region (Comunidad Autónoma), covering a population of 198,670 individuals aged over 14 years. Multiple correspondences were analyzed to identify the clustering patterns of the conditions targeted.ResultsForty-two percent (95% confidence interval [CI]: 41.8–42.2) of the registered population had at least one chronic condition. In all, 24.5% (95% CI: 24.3–24.6) of the population presented with multimorbidity.In the correspondence analysis, 98.3% of the total information was accounted for by three dimensions. The following four, age- and sex-related comorbidity patterns were identified: pattern B, showing a high comorbidity rate; pattern C, showing a low comorbidity rate; and two patterns, A and D, showing intermediate comorbidity rates.ConclusionsFour comorbidity patterns could be identified which grouped diseases as follows: one showing diseases with a high comorbidity burden; one showing diseases with a low comorbidity burden; and two showing diseases with an intermediate comorbidity burden.

The evaluation in real-life settings of services for the follow-up and control of hypertensive patients is a complex intervention, which still needs analysis of the roles, tasks, and resources involved in the basic items: patient, healthcare professional, and the interaction between the two. To evaluate the impact of patient-general practitioner (GP) short-messages-based interaction, isolated from other items, on the degree of hypertension control in the follow-up of medium-to-low-risk patients in primary care, a randomized controlled trial has been performed: 38 GPs enrolled 285 hypertensive patients who recorded the results of self-blood-pressure (BP) monitoring, heart rate, and body weight, and completed an optional questionnaire in an identical manner over a six-month period. The telemedicine group (TmG) sent the data to a telemedicine-based system that enabled patient-GP interaction; the control group (CG) recorded the data on paper and could only deliver it to their GP personally in the routine visits. In the TmG, the results were better, but not significantly so, for: 1) degree of hypertension control, in terms of the percentage of uncontrolled hypertensives at the final visit (TmG versus CG: 31.7% versus 35.6%; p = 0.47); 2) reduction in hypertension during follow-up, comparing measurements (performed by a professional) at the initial and final visits of systolic BP (15.5 versus 11.9; p = 0.13) and diastolic BP (9.6 versus 4.4; p = 0.40); and 3) adherence to the protocol within compliance levels of interest in a real-life follow-up service: >>50% (84.8% versus 73.3%) and >>25% (92.4.8% versus 75.4%) ( p = 0.053). Other factors such as average values of self-measured systolic BP, diastolic BP and heart rate, acceptability of the protocol, and median number of consultations and hospital admissions were similar in both groups. Outcomes show that, taken alone, the patient-GP short-messages-based interaction has very little impact on the degree of hypertension control in patients with this profile. In complex interventions, to discriminate the impact of each of its components in isolation will enable us to design an efficient follow-up service, little demanding in terms of healthcare professional dedication, and optimized in other basic aspects.

A platform built around three information entities (patient, health-care_agent, and central_station) was designed to enable patients with chronic heart disease (in stable condition; emergency situations were excluded deliberately) to complete specifically defined protocols for out-of-hospital follow-up and monitoring. The patients belonged to one of four specific risk groups: arterial hypertension, malignant arrhythmias, heart failure, and postinfarction rehabilitation. They were provided with portable recording equipment and a cellular phone that supported data transmission [electrocardiogram (ECG)] and wireless application protocol (WAP) (remaining parameters and ad hoc questionnaires). The central station was an automatized platform, with no human operator. The information received was organized chronologically in patient folders. The health-care_agents had continuous and secure access to the patient folders, through tools based on the world wide web and WAP, and to short messages sent by their patients. A pilot project was conducted with 89 patients (mean length of participation: 50.1 days). A total of 2168 ECGs (mean duration transmission = 2 min/30 s; network errors < 0.1%) and 4011 short messages (none lost, in 95% of cases 30 s < delay < 1 min) were transmitted; 6083 WAP sessions (mean duration = 3 min 11 s; network failures < 0.1%) were The functionality of the platform was also evaluated, analyzing the subjective component of usability, showing the evolution of patient acceptance over time.