The Evaluation Of Emergency Response Capability In Medical Service Institutions Of A Certain Garrison

Objective1. To learn the condition of emergency response capability for public healthemergencies in grassroots army medical service institutions.2. To set up the comprehensive evaluation model of emergency responsecapability for public health emergencies.3. To explore the impact factors of the emergency response capability for publichealth emergencies in grassroots army medical service institutions.Methods1. Multi-stage random sampling method was used to choose subjects who weconducted the questionnaire survey on in Henan grassroots army medical serviceinstitutions.2. Epidata3.1was adopted to established the database and the consistencycheck was conducted after double entry twice; SPSS13.0and Clementine12.0wasused to do the relevant analysis, taking α=0.05as the size of the statistical test.3. Factor analysis method was used to set up the comprehensive evaluationmodel of emergency response capability for public health emergency; The twoindependent samples rank sum test was used to compare the composite factor scorebetween the two kinds of medical service institutions.4. The artificial neural network method was applied to build the predictionmodel of the classification of composite factor score, and explore the impact factorsof the emergency response capability for public health emergencies in grassrootsarmy medical service institutions.Results1. Most grassroots army medical service institutions attached great importanceto the emergency forces building, most of them set up a small emergency responsegroup or emergency response office. But the formulating percentage of laboratorybiosafety regime and biological/chemical terrorist incident emergency response plan,the setting percentage of remote consultation equipment and syndromic surveillance, and laboratory comprehensive capabilities were very low. In addition, other aspects ofthe emergency system were also inadequate.2. Three common factors were extracted in this research and the cumulativecontribution rate reached80.324%. The comprehensive evaluation model was F=0.385F1+0.340F2+0.275F3, and F1, F2, F3were respectively the factor scores ofemergency equipments(weight value=0.385), emergency training(weight value=0.340) and emergency attention(weight value=0.275); Through the two independentsamples rank sum test, the composite factor score of hospitals was higher than thehealth centers’(Z=-3.818, P<0.001).3. The Feature Selection node in Clementine software selected4indicators intothe BP Artificial Neural Network model, including institution level, the proportion ofintermediate professional title or above, the proportion of bachelor degree or aboveand the average annual outpatient amount. The accuracy of final estimate was84.615%, accuracy of the model analysis was76.19%, the model fitting effect wasgood. The judgment accuracy of training set was76.19%, the judgment accuracy oftest set was83.33%; the accuracy were both greater than70.00%.Conclusions1. Grassroots army medical service institutions have already had a certainemergency response capability for public health emergencies, but there are still manyaspects requiring a lot of improvement.2. The model we set up can be used to preliminarily evaluate the emergencyresponse capability for public health emergencies in grassroots army medical serviceinstitutions. Health center’s emergency response capability needs furtherstrengthening improvement.3. The BP Artificial Neural Network model we set up has certain feasibilityand provides reliable theory basis for grassroots army medical service institutions tofurther improve their emergency response capability for public health emergencies.