الفهرس 
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Abstract
Safety is a critical component of quality. The Institute of Medicine (IOM) has defined patient safety as ‘‘freedom from accidental injury due to medical care’’. Historically, efforts to improve patient safety were directed solely at identifying medical errors regardless of their association with subsequent adverse events/ harm. This underscores the importance of distinguishing between errors and adverse events. Medical errors are failures in the process of care and, while they have the potential to be harmful, numerous reports have shown that they are often not linked to the injury of patients. An ”adverse event/ harm” is unintended injury caused by medical management rather than by the disease process and are responsible for harm to the patient. AEs are outcome focused. Thus, a focus on harm can target the system rather than the individual.
Several retrospective studies conducted in different parts of the world revealed that at least 10% of patients are harmed while receiving hospital care in developed countries. In developing countries, there is greater probability of adverse events due to the poor state of infrastructure and equipment, unreliable supply and quality of drugs, shortcomings in waste management and infection control, poor performance of personnel because of low motivation or insufficient technical skills, and severe under financing of essential operating costs of health services. In Egypt, the WHO World Alliance for Patient Safety reported that “unsafe healthcare” ranks as the fifth most common cause of death. Many studies concluded that AEs significantly prolongs hospital length of stay and thus increases hospital costs for the treatment of the pain and suffering as a result of the AEs.
Patients admitted to the ICU during their hospital stay are more likely to experience an AE than those in other hospital units the severity of their medical condition as well as the complexity of the critical care.
Different methods were developed to identify adverse events among hospitalized patients. They include incident reports, observational studies and unfocused chart reviews. Each of these methodologies has suffered from various shortcomings. First, Underreporting of adverse events associated with incident reports due to lack of time and pressures of the work place. Second, although direct observation can detect more errors than other methods, yet these errors are less likely to result in patient injury, so it has been ineffective in identifying harm to the patients. Third, Unfocused chart reviews suffer from a lack of consistency due to incomplete conflicting data reporting in the medical records and also are resource intensive. Recently, a different strategy; chart review using Trigger Tool was shown to be superior to conventional methods in the identification of AEs. It implies the use of triggers to promote more focused and efficient chart review. A trigger is defined as a flag found on review of the medical record that ‘triggers’ further investigation to determine the presence or absence of an adverse event.
This study aims to improve the safety of the health care delivered in the intensive care unit of Gamal Abdel Nasser Hospital through the detection of adverse events committed in the intensive care unit of Gamal Abdel Nasser Hospital, measure their rate of occurrence, and assess the level of harm associated with them using Intensive Care Unit Adverse Event Trigger Tool.
Sampled records were reviewed using ICU Adverse Event Trigger Tool, starting at the top of the trigger list and then working down. The patient record was reviewed in the following order; discharge summary, laboratory results, physician orders, radiology reports, procedure reports and nursing notes. As recommended by the IHI, a 20-minute limit was set for reviewing each patient’s record regardless of its size. When a positive trigger is found, we went to the specific area of the record to determine whether an adverse event has occurred related to that trigger. If no adverse event is found, we moved on and looked for other triggers. For every detected adverse event, the degree of patient harm was designated using an adaptation of the National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) Index for categorizing errors. Only categories E-I were included in Trigger tool, as it is designed to identify injury to the patient.
We identified 221 adverse events in 322 randomly selected medical records of patients who were admitted to the ICU. Nineteen out of them were detected by more than one trigger. Apart from those nineteen AEs, 202 adverse events were detected by only one trigger i.e., unique AE. This results in a mean rate of 62.7 AEs per 100 admissions. A total length of stay of 1706 days of the 322 patients yields 118.4 AEs detected per 1000 patient days. A total of 148 patients had >=1 AEs (range: 1-4) during their hospitalization; 107 (72.3%) patients had one adverse event and 41(27.7%) patients had more than one AE. This results in a 45.9 % of admissions with an adverse event
In the present study, a total of 726 triggers were detected in 184 patients resulting in a mean rate of 2.3 triggers per patient. Abrupt medication stop trigger was the most frequent trigger (25%) followed by In-unit procedures trigger which was 15% of all triggers. The triggers; abrupt DROP in Hg>4gms, C.difficile positive, Naloxone (Narcan), positive blood culture and Sodium Polystyrene (Kayexalate) were not detected entirely in the study sample.The trigger tool identified 202 unique AEs. So, the mean positive predictive value of the ICU Adverse Event Trigger Tool is 30.4% (95%CI= 26.6, 34.7).
As regards the types of adverse events detected in the ICU of the study hospital, the most common AEs were adverse drug events (ADEs), which accounted for more than half (63.9 %) of all adverse events followed by nosocomial infection, which accounted for more than third (31.6%) of all adverse events. Nosocomial infection includes; pneumonia, which accounted for 20.8% of all adverse events, catheter related infection (6.9 %) and urinary tract infection (3.9 %). Other less common adverse events were ICU psychosis and peripheral thrombosis. Among adverse drug events, the most common were hypotension (45.7%),bleeding (13%) and hypoglycaemia (9.4%) which are related to the use of antihyertensive drugs, heparin and insulin.
When the NCC MERP index was used to classify the degree of harm, majority of adverse events (62.4%) fell in category E (i.e.: patient experienced temporary harm that required intervention), 37.1% of all adverse events were classified in category F (i.e.: patient experienced temporary harm that required initial or prolonged hospitalization), 0.5% adverse event was classified as category G which includes permanent patient harm and no AEs were classified as category H or I.
In the present study, patients with AEs had longer length of stay than patients without.