Expensive Dactolisib Issues And How These Could Possibly Shock Clients

Perceived barriers to healthcare access for those who reported having a health problem but who did not use healthcare services. The barriers were geographic (far from the household), organisational (slow administrative process, limited health services schedule, long waiting time), opinions about providers�� behaviours (previous experience of being treated badly, lack of confidence), personal (the older adult lacked somebody to accompany him to visit the medical doctor, lack of time), and financial (not enough money for transportation or for paying for the visit and medicines). Study population Figure?1 depicts selection of the study population. ENSANUT 2012 was applied to 194?923 individuals in 50?528 households (87% response rate), from whom ?19?777 were aged 60?years and above, which according to the expansion factors represented more than 10 million older adults. The analysis excluded 61 (0.3%) older adults with private HI, 215 (1.1%) affiliated with two different HIs, and 654 (3.3%) with more than 20% of missing data on OOPHE and other household expenditures. In the latter case, it was not possible to calculate the total expenditures and financial burden variables. The descriptive analysis of the study groups selleck products included 18?847 older adults. The inferential analysis was performed according to the characteristics of each dependent variable. The analysis of access was performed at the individual level. It included 3111 older adults who reported a perceived need for healthcare in the past 15?days. The analysis at the household level was performed with 13?180 households, as we also excluded 510 households that had older adults from different HI groups. Figure?1 Selection of the study population. ENSANUT, Mexican Survey of Health and Nutrition; HI, health insurance; OOPHE, out of pocket health-related expenditures; SPHI, Seguro Popular health insurance; SSHI, Social Security health insurance. Statistical analysis Comparisons of study variables among the three HI groups were performed using the ��2 test for categorical variables. Data were weighted using the survey sampling weights. Propensity score matching (PSM) served to estimate the effect of HI on the dependent variables. The PSM technique allows the effect of a programme or treatment to be evaluated through the use of observational data from non-randomised studies in which selection bias is highly possible. PSM reduces this bias by modelling the conditional probability of participating in the programme or treatment group (T) (in our case being affiliated with a HI) on the basis of background characteristics (X) unaffected by the programme: P(X)=Pr(T=1|X). The individuals of both groups should then be matched on the basis of the propensity score.