OBJECTIVE: This paper addresses the issue of monitoring the features of the psychiatric inpatient population of a Prepaid Medical System in Buenos Aires City, paying special attention to its length of stay, diagnosis and readmission rate. METHOD: Between april 1 2000 and march 31 2002 all the psychiatric admissions have been registered and readmission rates and diagnosis prevalence were studied in a naturalistic setting. RESULTS: There were 244 admissions (0.8 per thousand enrollees per year) and 17% was readmitted during this period (1 out of every 4 readmissions in the month following discharge). Their length of stay was an average of 11,8 days. 66% was admitted due to a suicidal attempt or suicidal thoughts. 42% had a discharge diagnosis of Mood disorder, 34% Personality disorder and 12% Schizophrenia or other psychosis. CONCLUSIONS: Inpatients belonging to this Prepaid Medical System seem to be different from other inpatient populations making the comparison among them hard to analyze. Future research should bring more data in order to perform further matching and benchmarking. This kind of information should be no secret and every System should be requested to show its results to allow users' and buyers auditory as well as State's control.
OBJECTIVE: This paper addresses the issue of monitoring the features of the psychiatric inpatient population of a Prepaid Medical System in Buenos Aires City, paying special attention to its length of stay, diagnosis and readmission rate. METHOD: Between april 1 2000 and march 31 2002 all the psychiatric admissions have been registered and readmission rates and diagnosis prevalence were studied in a naturalistic setting. RESULTS: There were 244 admissions (0.8 per thousand enrollees per year) and 17% was readmitted during this period (1 out of every 4 readmissions in the month following discharge). Their length of stay was an average of 11,8 days. 66% was admitted due to a suicidal attempt or suicidal thoughts. 42% had a discharge diagnosis of Mood disorder, 34% Personality disorder and 12% Schizophrenia or other psychosis. CONCLUSIONS: Inpatients belonging to this Prepaid Medical System seem to be different from other inpatient populations making the comparison among them hard to analyze. Future research should bring more data in order to perform further matching and benchmarking. This kind of information should be no secret and every System should be requested to show its results to allow users' and buyers auditory as well as State's control.