The distribution of the demand from primary care in the mental health units could be a way of facilitating the coordination and improving the attention to patients. For this reason, in our unit we have made a repartition of the areas among the different psychiatrists.

To analyze if there was a correlation between the geographical origin of the patients or their primary care areas and the referrals, and between them and their attendance.

This is an epidemiological, analytic, prospective study of patients referred to our department. The following variables were collected: (1) referral protocol, (2) reason, (3) demographic data (origin, gender, age), (4) Primary Care area, (5) attendance to appointment, (6) diagnosis impression and (7) destination of referral. The SPSS 19.0 was used to analyze the data.

A total of 1048 patients were sampled. A statistically significant relationship hasn’t been found between place of residence, primary care area or areas of distribution in the Unit and attendance (Chi2). If we analyze the population of each distribution, we can describe similar percentages depending on the size of these.

Although a different distribution and a relationship is thought between some areas and the attendance or the number of referrals, we didn’t find out them in our sample.

The authors have not supplied their declaration of competing interest.

The first visit is crucial, since it is where a treatment plan is selected and the decision to refer or not the patient to a specialized unit is made. Mental care could be improved through the centralization of demand and the identification of patients’ and psychiatrists’ expectations.

Analyzing patients’ and psychiatrists’ demands and expectations in the first visit to use them as a starting point for the planning and coordination of treatment actions.

To design a record system of the Minimum Basic Data Set of the Centralized Department of our Unit.

This is an epidemiological, observational, prospective study of patients referred to our department. Following variables were collected:

– referral origin;

– reason;

– demographic data;

– diagnosis impression;

– destination of referral.

The Statistical Package for Social Science version 19.0 was used to analyze the data.

Table 1.

The data obtained are consistent with those reported in the literature for this population. The high rate of wrong referrals reveals the necessity of improving coordination and establishing specific referral criteria. Some initiatives have been designed and will be prospectively evaluated in the future.

Table 1

The authors have not supplied their declaration of competing interest.

The first time when people attempt suicide first contact is critical. Psychiatrists must decide to hospitalize them or follow-up in mental health units and the bases of a doctor-patient relationship are formed.

An analysis of referrals to psychiatry from the emergency room (ER) was developed. Our objective was to discover if there was a statistical correlation between gender and other variables, especially repeated visits and admissions.

Our sample was composed of patients who visited the ER for suicidal tendencies for 20 months. We carried out an observational retrospective study. The variables collected were: age, gender, cause, repeated visit (visit to the ER in the following two months), previous attempts, previous follow-up, method used, use of toxic substances during the attempt, intentionality, referral from the ER, later follow-up and diagnostic impression at the ER.

A total of 620 patients were sampled. The relationship between gender and repeated visit, previous attempts, dysfunctional personality traits, use of substances and later follow-up was found (Chi2). Although the relationship between admissions and gender were not statistically significant, influence by gender (over all in males) can be observed in logistic regression models. As well as, in patients who visited the ER several times, dysfunctional personality traits seem to be the most common but gender marks significant differences between groups.

The data obtained is consistent with those reported in previous studies. To know who the riskier groups are can allow professionals to plan protocols and unify admission criteria.

The authors have not supplied their declaration of competing interest.