Icd Gps 153 Pdf Free

Socioeconomic status (enabling variables). Wealth was assessed according to the number of reported household assets (motor vehicles; television; fridge and/or freezer; water and electricity utilities; telephone; plumbed toilet; plumbed bathroom). Participants were asked to disclose whether they received income from an occupational or government pension, and whether they had purchased any medical insurance cover.

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Out-of-pocket payments were required for most private doctor consultations in all sites other than Puerto Rico (Table 3). In Cuba, government primary care and hospital outpatient services were free at the point of delivery, while in China almost all consultations required out-of-pocket payments. Relatively high proportions reporting out-of-pocket payments were seen for primary care in the Dominican Republic, Peru, rural Mexico, urban India and Nigeria, and for hospital outpatients in the Dominican Republic, Mexico, rural India and Nigeria.

The mutually adjusted effects of participants' sociodemographic, socioeconomic and health characteristics on use of any community healthcare service are reported for each site in Table 4 model 1. Female sex and higher levels of education were overall associated with a higher prevalence of use of community health services in the past three months. However, controlling for the same covariates, men were consistently more likely to be admitted to hospital (meta-analysed PR 1.33, 95% CI 1.10-1.62, Cochrane's Q 14.1, 11 degrees of freedom, p = 0.23). There was no evidence, overall, to support an association between age, marital status, co-residence with children, and use of any community healthcare service. There was a strong association between being currently married and a higher prevalence of service use in urban India alone. The number of physical impairments, and ICD-10 depression were strongly positively associated with service use, but with considerable heterogeneity between sites. The inverse association between dementia and health service use was more consistent. Health insurance cover was positively associated with service use in most sites, but with much heterogeneity; the association was strongest in Puerto Rico, urban Peru and in China, and weakest in urban India, where only 1.3% of participants were covered. Household assets were positively associated with service use in the Dominican Republic, Puerto Rico, urban China and urban India, but the trend of the association was in the opposite direction in Cuba, rural China and rural India. In a post hoc analysis, when disclosing receipt of a government or occupational pension was substituted for household assets in the model, the effect was significant and more consistent across sites (PR 1.09, 95% CI 1.04-1.14; Cochrane's Q = 23.6 (12 df), p = 0.02). In the final stage, we added restricted mobility (extreme difficulty or incapability of walking one kilometre) to the model (Table 4 model 2). While the pooled estimate suggested no effect, again there was considerable heterogeneity, with an inverse association with service use in Cuba, and positive associations in Peru, urban Mexico and rural China.

We carried out catchment area surveys of representative samples of older people in six Latin American countries (Cuba, Dominican Republic, Puerto Rico, Venezuela, Mexico and Peru), India, China and Nigeria. In all we completed 17,944 interviews with a high response rate in most sites. Our eight urban and five rural catchment area sites encompassed wide variation in age distributions, prevailing economic circumstances, levels of education, and pension and health insurance coverage. Our data adds considerably to current understanding of patterns of service utilisation among older people in LMIC, with respect to the range of services assessed (using a standard protocol in all sites), the detailed assessment of health status, and the comprehensive assessment of predisposing and enabling variables, including the impact of health insurance coverage. There are potential limitations, particularly with respect to the self-reported data on health service use. Utilization of healthcare (in practice) is not the same as access to healthcare (in principle), which may be the more relevant construct with respect to issues of equity [7]. Information systems in most LMIC are inadequate for routinely recorded data to be used. Studies have shown that self-reported health service use may be biased by a slight tendency towards underreporting, and that measures are most accurate for recent episodes of medical care [27]. We used data on recent use (the three months preceding the interview). Misclassification is likely to have been random with respect to correlates of healthcare utilisation, biasing any associations towards the null. This may not have been the case for dementia since those with the condition might have been less likely to recall service use, and the family informant that was relied upon under such circumstances may not have always been aware. Finally, while the common research protocols and demonstrable cross-cultural validity of our methods allow direct comparisons to be made between samples from the different countries surveyed, our findings should be generalized with caution and only to populations similar to those that we focused upon. Certain of the local health systems could not be considered to be typical of rural and urban settings in the country concerned, particularly in India, where Voluntary Health Services in urban Chennai and the Christian Medical College in rural Vellore operate as charitable non-governmental service providers running comprehensive primary care, inpatient and outpatient hospital services free of charge to those who cannot afford to subscribe or pay.

Inequity was particularly evident in the positive association between educational level and use of healthcare services, and the strong effect of health insurance cover on use of community healthcare services at least in those sites where out-of-pocket expenses were common, and where private health insurance was an important component of healthcare financing. In this context, the heterogeneous association between household assets and use of healthcare services was puzzling. For countries such as Cuba, where healthcare is free at the point of delivery, it makes sense that educational level rather than socioeconomic position is associated with increased healthcare utilisation particularly of prevention and promotion services, and through better adherence to chronic disease management protocols. In some other settings, it may be that household assets, an index of accumulated wealth, may be less salient than regular personal income to meet out-of-pocket expenses. We found no consistent evidence for ageism in the demand for or delivery of healthcare services, although older people were significantly less likely to use healthcare services in Cuba and rural India, after adjusting for health status and other variables, with a strong trend in that direction in rural China. There was also little evidence for the exclusion of those with disabilities, at least as regards those with restricted mobility. Of course, one of the likely mechanisms for the under usage of healthcare services by people with dementia may be the impact of cognitive disability on help seeking, compounded by the lack of outreach services to meet the special needs of this group [32]. The finding that women are more likely than men to access community healthcare services is now also conclusively demonstrated for older people in LMIC. We have previously reported that the apparent excess disability among women in our surveys may be accounted for by selective underreporting by men [32]. Studies from LMIC suggest that men have a higher mortality in late-life [33, 34], and in our survey, as in others, are much more likely to be admitted acutely to hospital. Attention should therefore be directed towards encouraging timely help seeking, detection, treatment and control of chronic diseases and their risk factors among men.

The questionnaires were designed by the researchers (pharmacist (ICKW), pharmacoepidemiologist (MLM) and adult psychiatrist (PA)) to address the outcome measures below. Questionnaires were in a check box format, although respondents (GPs) had the opportunity to give additional information, using free text. For most questions, respondents could provide more than one answer. The questionnaires for the three cohorts were similar in terms of content and format e.g. patient demographics, however the context for some of the topic areas were specific to the patient cohort e.g. for patients who stopped ADHD treatment before adulthood (Group 1), questions regarding psychological therapy for ADHD refer to the period since stopping medication, whereas for patients in Group 2, those who continued treatment from childhood into adulthood, questions refer to patients receiving psychological therapy in addition to pharmacological therapy. GPs were provided with information on the symptoms of ADHD (as per NICE guidelines 2008) and information on psychotropic medications (as per British National Formulary). Copies of the questionnaires are available from the authors on request. 2ff7e9595c