[Índice de Saturación Modificado y Ambulancias (ISMA): Ambulance assignment and remote Emergency Room Bed Reservation]. / Índice de Saturación Modificado y Ambulancias (ISMA): asignación de ambulancias y reservación remota de camas en los Servicios de Urgencias Médicas.

INTRODUCTION: In most places all over the world­including our country­services in emergency rooms are oversaturated. This situation frequently forces the continuously arriving ambulances to be redirected to other medical units, delaying the admission of patients moved and thus adversely affecting their physical condition. OBJECTIVE: To introduce an improvement to the Índicede Saturación Modificado computational system, which monitors the degree of saturation of a network of emergency medical services, to include a network of ambulances, enabling in the system: (i) the effective allocation of ambulances to the site of the accident, or severe clinical event, and (ii) the remote booking of beds in the nearest and least saturated emergency room available. MATERIAL AND METHODS: The evaluation and connectivity of the computational improvement to the Índicede Saturación Modificado system was carried out with a computational test verifying these two aspects, using only differences in postal codes, for time measuring. RESULTS: The verification of its sustainability online showed the new Índice de Saturación Modificado y Ambulancias system (ISMA) has a robust structure capable of being adapted to mobile phones, laptops or tablets, and can efficiently administrate: (i) the quantification of excessive demand in the emergency room services of a hospital network, (ii) the allocation of ambulances attending the site of the event or contingency, and (iii) the allocation of ambulances and patients, in the best distance-time conditions, from the site of the accident or clinical event to the nearest and least saturated emergency room service. CONCLUSIONS: This administrative management tool is efficient and simple to use, and it optimally relates independent service networks.

[Evaluation of policies in the procedures for food handling to prevent nosocomial infections in general hospitals and public institutions of health in Mexico]. / Evaluación de políticas en manejo de alimentos para prevenir infecciones nosocomiales en hospitales generales de instituciones públicas de salud en México.

OBJECTIVE: To evaluate the implementation and proper use of policies and procedures for food handling to prevent nosocomial gastrointestinal infections in major General Hospitals and Public Institutions of Health in Mexico. MATERIAL AND METHODS: We performed a cross-sectional study of food services in 54 second-level general hospitals from these institutions: Mexican Institute of Social Security (IMSS), Institute of Security and Social Services for State Workers (ISSSTE), and the Ministry of Health (SESA). A questionnaire was made to identify risk factors for food contamination. In the statistical analysis, we determined the relative frequency of food handling complying with the norm; a qualitative analysis was performed using an intentional non-probabilistic sampling, targeting department heads, managers, and operational staff. The qualitative variables were verified through non-parametric tests. RESULTS: From 54 hospitals evaluated, 81% had procedure and operation manuals, 35% prepared and stored food according to NOM-251-SSA1-2009, 52% performed ongoing training, 62% had a record of microbiological analysis done to staff and 81% done to foods, and 31% had first in first out (FIFO) temperature control systems. CONCLUSIONS: Second-level health institutions in Mexico have deficiencies in the implementation of norms and procedures to handle, store, and prepare food that can lead to gastrointestinal outbreaks of nosocomial infections in patients, health staff, and visitors. In order to ensure the quality of food preparation for distribution and consumption in hospitals, it is necessary that food services comply with current norms and regulations, updating policies and procedures, and training their staff continuously.

[Modified overcrowd index in emergency room]. / Índice de saturación modificado en el servicio de urgencias médicas.

INTRODUCTION: Overcrowd of emergency rooms affects efficiency and quality of medical care. OBJECTIVES: To describe the mathematical-computational system modified overcrowd index which measures in real time and in four levels of warnings (non crowded, crowded, overcrowded and extreme overcrowded) emergency room saturation in a network of hospitals, from only seven simple variables (number of available beds, physicians and nurses, number of patients in the waiting room, in medical consultation and admitted for further evaluation, as well as number of critically ill patients admitted). MATERIALS AND METHODS: The modified overcrowd index was exhaustively tested with 245,280 virtual transactions from seven hospitals in an uninterrupted schedule basis simulating hourly surveillance for four years. RESULTS: From 224 episodes of overcrowd, 216 (97%) where correctly identified and verified by the network of hospitals warnings, its time series also provided useful information about available personnel and resource distribution within the hospital network. CONCLUSIONS: Modified overcrowd index is an efficient tool detecting emergency room overcrowd outbreaks in a network of hospitals.

Detection of severe respiratory disease epidemic outbreaks by CUSUM-based overcrowd-severe-respiratory-disease-index model.

A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008-2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts.