INTRODUCTION: Patient safety has gained interest last decades. Patient safety focuses on avoiding adverse events (AE), especially preventable AE, which are related to a healthcare-related error. Studies of patient safety emphasize the need to record and learn from the AE that occur at healthcare services. Data collection is one of the most widely used strategies. Nowadays, there is no worldwide established and standardized record for this purpose.
MATERIAL AND METHODS: The study is carried out in the general and digestive surgery of a hospital with 466 acute beds. There has been a daily registration of AE, preventable AE and the detection of healthcare-related errors. The healthcare-related errors have been isolated through this record. Data collection is close to the ideal since it is prospective, voluntary, unpunished, anonymous and independent. The main limitation of the collected data used is the coding of AE, avoidable AE and healthcare-related errors. Since there is no universal source, the results obtained from working with these data are not comparable or generalizable.
RESULTS AND DISCUSSION: We analysed 1006 healthcare-related errors according to the Joint Commission on Accreditation of Healthcare Organizations taxonomic classification, which evaluates the error impact, the type of error, who and where it is carried out and the cause of the error. This classification allows to know that most of our healthcare-related errors isolated have a slight or temporary physical impact, without being able to determine the psychological impact; the majority are patient management type; most are committed by medical personnel and / or nursing, at the level of the hospitalization plant and the operating room; Most are of human cause, secondary to an unconscious error. Even so, it is a difficult tool to use and the result of its application is considered to be very little useful.
A tool has been created to detect the most relevant healthcare-related errors, which are defined as errors that fulfill three characteristics at the same time: being the most frequent, the most serious and the most difficult to detect. This tool is called modified NPR, originally from the Health Care Failure Mode Effects and Analysis. Thanks to this tool, the risk number of 1004 errors has been calculated. The risk number has been calculated through the multiplication of 3 scores determined from 3 different items: GxAxD (G: gravity according to the classification of Dindo-Clavien; A: incidence according to the EA incidence of the service for more of 10 years; D: probability of detection according to a predetermined subjective scale). From this risk number, errors have been stratified and the most relevant errors have been detected. The subjective character of item D (risk number calculation) has been checked and a good inter-observer concordance (kappa index of 0.66) was determined.
Once known the most frequent healthcare-related errors, the error related to the usual medication of the patient has been selected as a target error. Some easy and simple measures have been designed, have been applied and a reduction in the incidence of these targeted errors has been objected. Achieving, therefore, reducing the incidence of preventable AE and an improvement in our patient safety.
CONCLUSION: An avoidable AE incidence reduction has been achieved through the use of a new tool that detects the most relevant healthcare-related errors.
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