Analía Baum

Factors associated with nonattendance at clinical medicine scheduled outpatient appointments in a university general hospital

Introduction Nonattendance at scheduled outpatient appointments for primary care is a major health care problem worldwide. Our aim was to estimate the prevalence of nonattendance at scheduled appointments for outpatients seeking primary care, to identify associated factors and build a model that predicts nonattendance at scheduled appointments. Methods A cohort study of adult patients, who had a scheduled outpatient appointment for primary care, was conducted between January 2010 and July 2011, at the Italian Hospital of Buenos Aires. We evaluated the history and characteristics of these patients, and their scheduling and attendance at appointments. Patients were divided into two groups: those who attended their scheduled appointments, and those who did not. We estimated the odds ratios (OR) and corresponding 95% confidence intervals (95% CI), and generated a predictive model for nonattendance, with logistic regression, using factors associated with lack of attendance, and those considered clinically relevant. Alternative models were compared using Akaike’s Information Criterion. A generation cohort and a validation cohort were assigned randomly. Results Of 113,716 appointments included in the study, 25,687 were missed (22.7%; 95% CI: 22.34%–22.83%). We found a statistically significant association between nonattendance and age (OR: 0.99; 95% CI: 0.99–0.99), number of issues in the personal health record (OR: 0.98; 95% CI: 0.98–0.99), time between the request for and date of appointment (OR: 1; 95% CI: 1–1), history of nonattendance (OR: 1.07; 95% CI: 1.07–1.07), appointment scheduled later than 4 pm (OR: 1.30; 95% CI: 1.24–1.35), and specific days of the week (OR: 1.00; 95% CI: 1.06–1.1). The predictive model for nonattendance included characteristics of the patient requesting the appointment, the appointment request, and the actual appointment date. The area under the receiver operating characteristic curve of the predictive model in the generation cohort was 0.892 (95% CI: 0.890–0.894). Conclusion Evidence related to patient characteristics, and the identification of appointments with a higher likelihood of nonattendance, should promote guided strategies to reduce the rate of nonattendance, as well as to future research on this topic. The use of predictive models could further guide management strategies to reduce the rate of nonattendance.

10x10 comes full circle: Spanish version back to United States in Puerto Rico.

The adaptation of the 10x10 certificate program in health information systems for a Puerto Rican audience is described. The 10x10 program was initially developed in the USA by the Oregon Health Sciences University (OHSU), then adapted to Latin America by Hospital Italiano de Buenos Aires. Puerto Rico is in the intersection of the United States and Latin America, in terms of government, health care system, culture and language. Therefore, it seemed reasonable to re-adapt the program back to the USA, in Spanish, taking into account these facts and the experience of the team in delivering blended learning adapted to local needs. Forty professionals from Puerto Rico are currently taking the first version of the course, supported by the Regional Extension Center for Puerto Rico and the US Virgin Islands, and endorsed by the American Medical Informatics Association (AMIA).

Curso en línea de Informática Biomédica para Puerto Rico: resultados de una experiencia de colaboración panamericana

Resumen Introduccion La explosion de tecnologias de informacion ha impactado en la sociedad en general y tambien en el area de la salud. Si bien la Informatica Biomedica y en Salud ha crecido rapidamente como disciplina dando respuesta a vertiginosos cambios, se necesitan compromisos mundiales y nacionales para que los sistemas sanitarios actuales adopten y utilicen sistemas de informacion integrados. Entre los elementos esenciales se incluyen recursos humanos especializados que puedan conformar equipos de trabajo multidisciplinarios para acompanar el cambio. Objetivo Describir los resultados de la adaptacion para Puerto Rico del programa educativo 10x10 de la American Medical Informatics Association (AMIA), un curso universitario de 155 horas de estudio sobre sistemas de informacion en organizaciones de salud. Metodo Se aplico un modelo en 5 fases utilizado en Puerto Rico para otras actividades educativas que implica la integracion de actividades sincronicas y asincronicas, presenciales y a distancia, el conocimiento de la realidad local y sus necesidades, la integracion de lideres e instituciones locales, la adecuacion del diseno y la certificacion con validez local. Esta edicion se realizo entre agosto y diciembre de 2012. Resultados Completaron el proceso de inscripcion y participaron en el curso 40 profesionales de distintas disciplinas, aprobando el mismo 28 de ellos (70%). El 71% de quienes respondieron la encuesta de evaluacion del curso nunca habian realizado una actividad de educacion a distancia. Conclusiones La adaptacion del curso 10x10 en espanol para ciudadanos estadounidenses de Puerto Rico fue posible y resulto util para los participantes involucrados.