The application of Iberoamerican study of adverse events (IBEAS) methodology in Brazilian hospitals

The application of Iberoamerican study of adverse events (IBEAS) methodology in Brazilian hospitals Abstract Objective To assess the prevalence of adverse events (AE) and to investigate its association with factors related to the patient and to hospital admission. Design Cross-sectional study. Setting Four general hospitals located in the southeastern region of Brazil. Participants All patients admitted to the participating hospitals at the time of the study were surveyed. Intervention The methodology was based on the Iberoamerican study of adverse events, a two-stage medical record review. Main Outcome Measure Medical records were screened for AE only in the day (24-h) immediately before the review process, independently of the admission date. Results A total of 695 admissions were examined. Prevalence was 12.8%. Almost 43% of AE were preventable. More than 60% of patients with an event prolonged hospital stay. In final regression model, urgent admission (OR: 2.68; Confidence Interval (CI) 95%: 1.53–4.69), submission to a procedure (odds ratio (OR): 2.41; CI 95%: 1.33–4.39), presence of central venous catheter (OR: 2.25; CI 95%: 1.14–4.41) and immunosuppressive therapy (OR: 3.41; CI 95%: 1.57–7.40) were statistically associated with AE. Conclusions Our results indicate that around 1.3 AE happen in each 10 hospital admissions in Brazil. As patient safety continues to be a Public Health concern worldwide and mainly in developing countries, this would indicate the potential use of prevalence measures for monitoring patient safety in Brazilian context. patient safety, adverse events, epidemiology and detection, healthcare quality improvement, hospital medicine Introduction Patient safety has gained prominence in the international debate about quality of healthcare since the 1999 Institute of Medicine report ‘To Err Is Human’ [1]. Despite the debate [2], a recent study states that medical errors are the third leading cause of death in the USA [3]. At the same time, sizeable efforts and initiatives have been developed to reverse this situation [4]. The concept of adverse event (AE) is essential to the analysis in the Patient Safety domain. Since the Harvard Medical Practice Study in 1990 [5], several studies have been conducted to evaluate the frequency of AE in the USA, Australia, New Zealand, UK, Canada, Denmark, France, Brazil, Spain, Tunisia, the Netherlands, Portugal, Italy, countries around the Mediterranean Sea and recently, Ireland [6–20]. Most of them were based on the retrospective review of medical records methodology and reported AE incidence rates ranging from 2.9% to 16.6% of all hospital admissions and preventable AE proportion rates ranging from 27% to 83%. Considering the importance of Patient Safety and the impact of AE in terms of morbidity and mortality, studies that evaluate magnitude and methods of detection remain relevant, especially in developing countries. Brazil is the largest country in Latin America, with a total population of 206 million inhabitants [21]. Brazilian Health System is public and universal but around 25% of its population has private health insurance. In 2009, a retrospective cohort study based on patient charts review was conducted, evaluating AE incidence and proportion of preventable AE [13]. Although prevalence studies can be useful strategies for monitoring the occurrence of AE, few studies reporting prevalence measures of AE have been done worldwide. The methodology used in such studies is similar to that used in the retrospective ones but unlike incidence’s study, in the former patients were screened for AE only in the 24-h immediately prior to the review process [22]. A French study compared three methods for estimating rates of AE, including the cross-sectional design [12], showing dependency between the study design and measure/magnitude of the safety problems. The Iberoamerican study of adverse events (IBEAS) is the largest published study of prevalence of AE, conducted in five Latin American countries (Argentina, Colombia, Costa Rica, Mexico and Peru). This was mainly a sectional study, but also a concurring follow-up study was performed to estimate AE incidence from a sample of patients from the prevalence study [22]. In Brazil, following the incidence study [13], the research team engaged in a prevalence study to determine the prevalence of AE, as well as to investigate its association with factors related to the patient and to hospital admission. Methods This is a cross-sectional study based on the review of medical records in four general hospitals located in the Southeastern Region of Brazil. These are three public hospitals and one private general hospital. The methodology applied in this study was based on the IBEAS, a prevalence study developed in five Spanish spoken countries, which estimated the point prevalence of patients showing an AE. According to this methodology, a prevalent AE is the AE that is present on the day of observation [22]. The nomenclature used in this study was based on the Harvard Medical Practice Study, according to which an AE is ‘an injury that was caused by medical management (rather than the underlying disease) and that prolonged the hospitalization, produced a disability at the time of discharge or both’ [6]. Regarding inclusion and exclusion criteria, all hospital admissions were included, regardless of their diagnosis or the hospitalization area or medical specialty. Even if the patient was not present at the moment of the study screening, but his/her medical record was present, the data collection was normally performed. All patients admitted to the participating hospitals at the time of the study were surveyed. Medical records were screened for AE only in the day (24-h) immediately before the review process, independently of the admission date. Data collection took place between 2010 and 2011. Medical record review was conducted according to two stages: during stage 1, the screening for AEs was performed by nurses with clinical experience using the Screening Form; during stage 2, AE identification was performed by doctors (clinicians or medical residents) using the Modular Form (MRF-2). In stage 1, 19 criteria were used for screening AEs. The presence of at least one criterion caused the case to be selected for completing module A of the MRF-2 form. In this module, physicians had to describe patient comorbidities, hospital admission information, probability of an AE occurrence and AE characteristics (such as AE preventability and type: if related to general care, medication, hospital-acquired infection, related to diagnosis or to a procedure and others). AE related to a procedure included surgery, anesthesia, chemotherapy, radiotherapy, fracture treatment and other invasive procedures. Therefore, in stage 2, a structured implicit review was used to identify the AE based on completion of the MRF-2 form. The two electronic forms were adapted and translated to Portuguese by the research team with the participation of a linguistic specialist. No validity testing was applied in the translation process. Four evaluators were selected in each hospital (two nurses and two physicians). They were previously trained for two consecutive days and at the end agreement among nurses were found to be 100%. Before considering an AE, the physician needed to fill out the causality assessment module of MRF-2 form which consists on a six-point scale on chance of an AE occurrence. A score >3 means that the analyzed event was an AE. Also, the physician reviewer had to complete the MRF-2 form by assessing the AE preventability scale (six-point scale on chance of a preventable AE). A score >3 in this scale means that the AE was preventable. A total of 695 admissions were examined in this study. Figure 1 below shows the number of screened admissions, number of AE detected and also the number of preventable AE, based on the two-steps methodology applied. Figure 1 View largeDownload slide Medical records review and screened cases. Figure 1 View largeDownload slide Medical records review and screened cases. Exposure variables considered in this study were social and demographic characteristics, type of admission, patient intrinsic and extrinsic factors, presence and types of comorbidities and submission to a procedure during the admission. The outcome was AE occurrence. Regarding intrinsic and extrinsic factors, these were risk factors potentially associated with an AE occurrence, collected during stage 1 (Screening Form). Intrinsic factors were considered exposure variables related to the patient or case severity, such as, coma, renal insufficiency, diabetes, cancer, immunodeficiency/AIDS, chronic pulmonary disease, leukopenia, chronic hepatopathy, obesity, hypoalbuminemia/malnutrition, pressure ulcer, congenital malformations, cardiac insufficiency, coronary artery disease, arterial hypertension, hypercholesterolemia and alcoholism. Extrinsic factors were exposure variables related to hospital care, such as, closed urinary catheter system, peripheral venous catheter, arterial catheter, peripherally inserted central catheter, central venous catheter, parenteral nutrition, enteral nutrition, nasogastric/nasoenteral tube, tracheostomy, mechanical ventilation, tracheal intubation, immunosuppressive therapy, infusion pump, hemodialysis and peritoneal dialysis. Chi-squared tests were conducted to test the association between variables. A final logistic regression model was built to analyze the association between exposure and outcome. The software IBEAS-Brazil System was developed for the study purpose to allow electronic data collection and to avoid double entries in the process of screening and assessment of AEs. Data were analyzed using Stata/IC software version 11 (Stata Corporation, College Station, USA). The study was approved by the Ethics Committee of Oswaldo Cruz Foundation (No. 549/10). Results Most patients were male (52.7%), with a median age of 63 years (Interquartile range—IQR: 45–77). Almost 90% of patients had comorbidities (88.6%). Among them, arterial hypertension was the most prevalent (56.8%), followed by diabetes (27.9%), other endocrine disorders (26.3), coronary disease (25.5%) and cardiac insufficiency (25.2). Urgent admissions were the most frequent type of admissions (57.4%) and 66% of patient underwent a procedure during the admission (Table 1). Table 1 Characteristics of the study population regarding social and demographic factors, comorbidities and hospital admission factors (695 inpatients) Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  aFor example: thyroid and adrenal disorders. Table 1 Characteristics of the study population regarding social and demographic factors, comorbidities and hospital admission factors (695 inpatients) Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  aFor example: thyroid and adrenal disorders. Regarding risk factors, collected during stage 1, the most frequent intrinsic factors among patients were arterial hypertension (47.6%), mellitus diabetes (21.7%) and cancer (20.3%). The most frequent extrinsic factor found was peripheral venous catheter (74.4%), infusion pump (34.1%) and closed urinary catheter system (24.6%). In binary analysis of intrinsic factors, renal insufficiency and arterial hypertension were statistically associated with an AE (P < 0.05). Among extrinsic factors, closed urinary catheter system, central venous catheter, enteral nutrition, nasogastric/nasoenteral tube, tracheostomy, mechanical ventilation, tracheal intubation, immunosuppressive therapy, infusion pump and hemodialysis were statistically associated with AE occurrence (P < 0.05) (Table 2). Table 2 Frequency of intrinsic factors (factors associated with the patient) and extrinsic factors (factors related to hospital care) and their association with AE occurrence   n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634    n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634  Bold: P-values less than 0.05 considered statistically significant. Table 2 Frequency of intrinsic factors (factors associated with the patient) and extrinsic factors (factors related to hospital care) and their association with AE occurrence   n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634    n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634  Bold: P-values less than 0.05 considered statistically significant. About 89 patients had an AE prevalence of 12.8%. Thirty-eight of them (42.7%) were evaluated as preventable. Additional hospitalization days due to AE were almost 40 days and 11.6 additional days in ICU hospitalizations. The severity of the event was mild in 13.3% of cases, which means that the AE did not increase the hospital stay; moderate in 60.2% of cases, that is, prolonged hospital stay for at least 1 day; and severe in 26.5% of cases, which means that the AE caused death, disability at hospital discharge or required surgery. The most frequent types of AE were general care and related to procedure (27.6% each), followed by infection (19.4%), medication (18.4%) and diagnosis (2.0%), the less frequent in this study (Table 3). Table 3 Adverse events characteristics: prevalence, preventability, severity, types and impact   n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0    n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  SD, standard deviation; ICU, intensive care unit. Table 3 Adverse events characteristics: prevalence, preventability, severity, types and impact   n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0    n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  SD, standard deviation; ICU, intensive care unit. In binary analysis, no association was found between AE occurrence and social and demographic variables (gender, age and education). Type of admission (urgent) was statistically associated with AE (P < 0.001). The variables admission sector and presence of comorbidity were not associated with AE occurrence in this study. On the other hand, submission to a diagnostic or a treatment procedure during the admission was statistically associated with AE (P = 0.001). In the final model of logistic regression (Table 4), including the exposure variables which showed statistical significance with AE prevalence in binary analysis, only type of admission, submission to a diagnostic or a treatment procedure, central venous catheter and immunosuppressive therapy remained associated with AE. Urgent admission and submission to a procedure during admission increased more than two times the chance of having an AE (OR: 2.68; CI 95%: 1.53–4.69, and OR: 2.41; CI 95%: 1.33–4.39, respectively). In this phase, no patient factors presented statistical significance. However, presence of central venous catheter nearly doubled the chance of having an AE (OR: 2.25; CI 95%: 1.14–4.41), possibly due to patient severity condition. Submission to immunosuppressive therapy increased more than three times the chance of having an AE (OR: 3.41; CI 95%: 1.57–7.40). This extrinsic factor was strongly related to medication AE (P = 0.001). Among the 12 cases that referred immunosuppressive therapy as an extrinsic factor, eight of them (66.7%) had one medication AE. Table 4 Final logistic regression model of the association between AE occurrence and hospital admission factors Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Bold: P-values less than 0.05 considered statistically significant. CI: Confidence interval. Table 4 Final logistic regression model of the association between AE occurrence and hospital admission factors Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Bold: P-values less than 0.05 considered statistically significant. CI: Confidence interval. Discussion In the present study, we found a prevalence of 12.8% of AE in four Brazilian hospitals, higher to the prevalence found in IBEAS study (10.5%). This is probably due to the similar nature of hospitals selection and the same methodology applied. As in IBEAS study, in this study the selection of hospitals was voluntary and based on feasibility, which tends to include services more engaged in patient safety actions or concerns [22]. However, we found a lower proportion of preventable AE (42.7%) compared with IBEAS study (60%) and to our previous incidence study (66.7%) [13], which may be explained by the specificity of our sample: patients with higher education levels, coming from better quality hospitals. Although Michel et al. [12], when comparing three methods for AE detection, found similar AE rates between the prospective and retrospective methods (15.4% and 14.5%, respectively), and the lowest rate when using the cross-sectional method (9.8%), our study found a higher AE rate compared with the previous incidence study (7.6%) [13]. This finding is also probably related to the nature of our sample and its size, comparatively to incidence study: better quality hospitals, with better healthcare, greater patient safety concerns and better hospital documentation. In this study, urgent admission, submission to a surgical or invasive procedure, presence of central venous catheter and submission to immunosuppressive therapy were factors with the greatest contribution to AE occurrence. Gender, age and presence of comorbidity, and the intrinsic factors did not show effect on the chance of having an AE. We suspect that may be comorbidities registration in patient records is affected by underestimation [23], or may be, due to the characteristics of the prevalence design, with 24-h evaluation, the information related to patient factors was underrepresented, comparatively to admission factors. In a previous study, conducted by the research group using an incidence design, comorbidity was associated both with AE and death [24]. In this study, admission factors seem to be representative of patient severity. Therefore, although variables measuring patient comorbidity factors have not shown statistical significance, the association of AE with type of admission (urgent) and also with presence of central venous catheter seems to indicate case severity. Central venous catheter could also indicate AE due to central line infection. Patients submitted to immunosuppressive therapy had three times more chance of having an AE and most of them are medication AE, which indicates an important area of AE prevention. According to our results, 60.2% of patients had moderate AE and had a prolonged hospital stay for at least 1 day. This finding is alarming considering that prolongation of hospitalization time increases the chance hospital-acquired infections, as well as increases the cost for the healthcare system. Generally, emergency admissions are more severe compared with elective and scheduled admissions. In IBEAS original study, urgent admissions also increased the risk of having an AE (OR: 1.34; CI 95%: 1.12–1.61). Thereby, these results showed that more attention should be given in urgent admissions, especially in the emergency department, with health team continual training to detect and avoid such problems. The performance of diagnostic and therapeutical procedures during admission should follow checklists and guidelines to avoid AE occurrence, as well as patients submitted to tracheal intubation deserve more attention by the caregiver. These results suggest that quality of care initiatives should focus on those high-risk patients in order to reduce the risk of AE and also reduce mortality, such as the ongoing initiatives for reducing the risk of postoperative respiratory complications, including death, in major abdominal surgeries [25]. The limitations of this study are related to the characteristics of our sample size. First, interpretation of results should take into consideration that this is not a random sample representative from all the Brazilian hospitals and that the hospitals were chosen by convenience. The frequency of AE may vary as the hospitals characteristics vary. Some statistical analyses were impaired due to our limited sample size. We performed analysis according to AE preventability and severity, but did not show statistical significance. Also, the quality of collected data (for example, case severity) must have been affected by the poor quality of medical records. Besides, it is important to note that, as this is a cross-sectional design, no causality has been established between exposure and outcome, but on the other hand, the intention is to create a hypothesis that should be tested in longitudinal studies. Regarding research instruments, we observed that, in some cases, pressure ulcer was both classified as an AE and an intrinsic factor for the same patient. We considered these cases inconsistencies and we proceeded to reclassify them as adverse events. Future research using the same instrument should consider to intensify evaluators training in the identification of the presence of pressure ulcer before admission comparatively to its development during the hospitalization to avoid misclassification. Despite the limitations, this is the first prevalence study of AE conducted in Brazilian hospitals and it adapted and translated to Portuguese a methodology used in a previous published Latin American study [22]. Although the methodological differences, drew attention the rates obtained by the incidence and prevalence studies have been close. Our results indicate that around 1.3 AE happen in each 10 hospital admissions in Brazil. This is alarming considering the specificity of our sample size. As patient safety continues to be a Public Health concern worldwide and mainly in developing countries, this would indicate the potential use of prevalence measures for monitoring patient safety in Brazilian context. Considering the convenience regarding costs and methodology, prevalence designs, rather than incidence ones, can be a useful tool for monitoring AE rates in hospitals. Supplementary material Supplementary material is available at International Journal for Quality in Health Care online. Acknowledgements The authors wish to thank Daniel Andrade for his help in data collection, Priscilla Mouta for her assistance in questionnaires translation to Portuguese, and Lucimar Santos, for her assistance in data analysis. This research project was done in cooperation with WHO’s Patient Safety program. Funding This work was supported by the National Council for Scientific and Technological Development, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), grant number 471685/2007-0. References 1 Kohn LT, Corrigan JM, Donaldson MS. (Institute of Medicine). To Err Is Human: Building a Safer Health System . Washington, DC: National Academy Press, 2000. 2 Shojania KG, Dixon-Woods M. Estimating deaths due to medical error: the ongoing controversy and why it matters. BMJ Qual Saf  2017; 26: 423– 8. doi:10.1136/bmjqs-2016-006144. Google Scholar CrossRef Search ADS PubMed  3 Makary MA, Daniel M. Medical error—the third leading cause of death in the US. BMJ  2016; 353: i2139. Google Scholar CrossRef Search ADS PubMed  4 Shekelle PG, Pronovost PJ, Wachter RM et al.  . The top patient safety strategies that can be encouraged for adoption now. Ann Intern Med  2013; 158: 365– 8. Google Scholar CrossRef Search ADS PubMed  5 Brennan TA, Leape LL, Laird NM et al.  . Incidence of adverse events and negligence in hospitalized patients. Results of the Harvard Medical Practice Study I. N Engl J Med  1991; 324: 370– 6. Google Scholar CrossRef Search ADS PubMed  6 Thomas EJ, Studdert DM, Burstin HR et al.  . Incidence and types of adverse events and negligent care in Utah and Colorado. Med Care  2000; 38: 261– 71. Google Scholar CrossRef Search ADS PubMed  7 Wilson RM, Runciman WB, Gibberd RW et al.  . The quality in Australian health care study. Med J Aust  1995; 163: 458– 71. Google Scholar PubMed  8 Davis P, Lay-Yee R, Briant R et al.  . Adverse events in New Zealand public hospitals I: occurrence and impact. NZ Med J  2002; 115: U271. 9 Vincent C, Neale G, Woloshynowych M. Adverse events in British hospitals: preliminary retrospective record review. BMJ  2001; 322: 517– 9. Google Scholar CrossRef Search ADS PubMed  10 Baker GR, Norton PG, Flintoft V et al.  . The Canadian adverse events study: the incidence of adverse events among hospital patients in Canada. CMAJ  2004; 170: 1678– 86. Google Scholar CrossRef Search ADS PubMed  11 Schioler T, Lipczak H, Pedersen BL et al.  . Danish Adverse Event Study, incidence of adverse events in hospitals. A retrospective study of medical records. Ugeskr Laeger  2002; 164: 4377– 9. Google Scholar PubMed  12 Michel P, Quenon JL, de Sarasqueta AM et al.  . Comparison of three methods for estimating rates of adverse events and rates of preventable adverse events in acute care hospitals. BMJ  2004; 328: 199– 202. 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Segurança do doente: eventos adversos em hospitais portugueses: estudo piloto de incidência, impacte e evitabilidade . Lisboa: Editora Escola Nacional de Saúde Pública, 2011. ISBN 978-989-97342-0-3. 18 Sommella L, de Waure C, Ferriero AM et al.  . The incidence of adverse events in an Italian acute care hospital: findings of a two-stage method in a retrospective cohort study. BMC Health Serv Res  2014; 14: 358. Google Scholar CrossRef Search ADS PubMed  19 Wilson RM, Michel P, Olsen S et al.  . Patient safety in developing countries: retrospective estimation of scale and nature of harm to patients in hospital. BMJ  2012; 344: e832. Google Scholar CrossRef Search ADS PubMed  20 Rafter N, Hickey A, Conroy RM et al.  . The Irish National Adverse Events Study (INAES): the frequency and nature of adverse events in Irish hospitals—a retrospective record review study. BMJ Qual Saf  2017; 26: 111– 19. Google Scholar CrossRef Search ADS PubMed  21 Brazilian Institute of Geography and Statistics. http://www.ibge.gov.br/apps/populacao/projecao/ (June 2016, date last accessed). 22 Aranaz-Andrés JM, Aibar-Remón C, Limón-Ramírez R et al.  . Prevalence of adverse events in the hospitals of five Latin American countries: results of the Iberoamerican study of adverse events (IBEAS). BMJ Qual Saf  2011; 20: 1043– 51. Google Scholar CrossRef Search ADS PubMed  23 Pavão AL, Andrade D, Mendes W et al.  . Incidence of in-hospital adverse events in the State of Rio de Janeiro, Brazil: evaluation of patient medical record. Rev Bras Epidemiol  2011; 14: 651– 61. Google Scholar CrossRef Search ADS PubMed  24 Martins M, Travassos C, Mendes W et al.  . Hospital deaths and adverse events in Brazil. BMC Health Serv Res  2011; 11: 223. Google Scholar CrossRef Search ADS PubMed  25 Pearse RM, Abbott TE, Haslop R et al.  . The Prevention of Respiratory Insufficiency after Surgical Management (PRISM) Trial. Report of the protocol for a pragmatic randomised controlled trial of CPAP to prevent respiratory complications and improve survival following major abdominal surgery. Minerva Anestesiol  2017; 83: 175– 82. doi:10.23736/S0375-9393.16.11502-0. Google Scholar PubMed  © The Author(s) 2018. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal for Quality in Health Care Oxford University Press

The application of Iberoamerican study of adverse events (IBEAS) methodology in Brazilian hospitals

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Abstract

Abstract Objective To assess the prevalence of adverse events (AE) and to investigate its association with factors related to the patient and to hospital admission. Design Cross-sectional study. Setting Four general hospitals located in the southeastern region of Brazil. Participants All patients admitted to the participating hospitals at the time of the study were surveyed. Intervention The methodology was based on the Iberoamerican study of adverse events, a two-stage medical record review. Main Outcome Measure Medical records were screened for AE only in the day (24-h) immediately before the review process, independently of the admission date. Results A total of 695 admissions were examined. Prevalence was 12.8%. Almost 43% of AE were preventable. More than 60% of patients with an event prolonged hospital stay. In final regression model, urgent admission (OR: 2.68; Confidence Interval (CI) 95%: 1.53–4.69), submission to a procedure (odds ratio (OR): 2.41; CI 95%: 1.33–4.39), presence of central venous catheter (OR: 2.25; CI 95%: 1.14–4.41) and immunosuppressive therapy (OR: 3.41; CI 95%: 1.57–7.40) were statistically associated with AE. Conclusions Our results indicate that around 1.3 AE happen in each 10 hospital admissions in Brazil. As patient safety continues to be a Public Health concern worldwide and mainly in developing countries, this would indicate the potential use of prevalence measures for monitoring patient safety in Brazilian context. patient safety, adverse events, epidemiology and detection, healthcare quality improvement, hospital medicine Introduction Patient safety has gained prominence in the international debate about quality of healthcare since the 1999 Institute of Medicine report ‘To Err Is Human’ [1]. Despite the debate [2], a recent study states that medical errors are the third leading cause of death in the USA [3]. At the same time, sizeable efforts and initiatives have been developed to reverse this situation [4]. The concept of adverse event (AE) is essential to the analysis in the Patient Safety domain. Since the Harvard Medical Practice Study in 1990 [5], several studies have been conducted to evaluate the frequency of AE in the USA, Australia, New Zealand, UK, Canada, Denmark, France, Brazil, Spain, Tunisia, the Netherlands, Portugal, Italy, countries around the Mediterranean Sea and recently, Ireland [6–20]. Most of them were based on the retrospective review of medical records methodology and reported AE incidence rates ranging from 2.9% to 16.6% of all hospital admissions and preventable AE proportion rates ranging from 27% to 83%. Considering the importance of Patient Safety and the impact of AE in terms of morbidity and mortality, studies that evaluate magnitude and methods of detection remain relevant, especially in developing countries. Brazil is the largest country in Latin America, with a total population of 206 million inhabitants [21]. Brazilian Health System is public and universal but around 25% of its population has private health insurance. In 2009, a retrospective cohort study based on patient charts review was conducted, evaluating AE incidence and proportion of preventable AE [13]. Although prevalence studies can be useful strategies for monitoring the occurrence of AE, few studies reporting prevalence measures of AE have been done worldwide. The methodology used in such studies is similar to that used in the retrospective ones but unlike incidence’s study, in the former patients were screened for AE only in the 24-h immediately prior to the review process [22]. A French study compared three methods for estimating rates of AE, including the cross-sectional design [12], showing dependency between the study design and measure/magnitude of the safety problems. The Iberoamerican study of adverse events (IBEAS) is the largest published study of prevalence of AE, conducted in five Latin American countries (Argentina, Colombia, Costa Rica, Mexico and Peru). This was mainly a sectional study, but also a concurring follow-up study was performed to estimate AE incidence from a sample of patients from the prevalence study [22]. In Brazil, following the incidence study [13], the research team engaged in a prevalence study to determine the prevalence of AE, as well as to investigate its association with factors related to the patient and to hospital admission. Methods This is a cross-sectional study based on the review of medical records in four general hospitals located in the Southeastern Region of Brazil. These are three public hospitals and one private general hospital. The methodology applied in this study was based on the IBEAS, a prevalence study developed in five Spanish spoken countries, which estimated the point prevalence of patients showing an AE. According to this methodology, a prevalent AE is the AE that is present on the day of observation [22]. The nomenclature used in this study was based on the Harvard Medical Practice Study, according to which an AE is ‘an injury that was caused by medical management (rather than the underlying disease) and that prolonged the hospitalization, produced a disability at the time of discharge or both’ [6]. Regarding inclusion and exclusion criteria, all hospital admissions were included, regardless of their diagnosis or the hospitalization area or medical specialty. Even if the patient was not present at the moment of the study screening, but his/her medical record was present, the data collection was normally performed. All patients admitted to the participating hospitals at the time of the study were surveyed. Medical records were screened for AE only in the day (24-h) immediately before the review process, independently of the admission date. Data collection took place between 2010 and 2011. Medical record review was conducted according to two stages: during stage 1, the screening for AEs was performed by nurses with clinical experience using the Screening Form; during stage 2, AE identification was performed by doctors (clinicians or medical residents) using the Modular Form (MRF-2). In stage 1, 19 criteria were used for screening AEs. The presence of at least one criterion caused the case to be selected for completing module A of the MRF-2 form. In this module, physicians had to describe patient comorbidities, hospital admission information, probability of an AE occurrence and AE characteristics (such as AE preventability and type: if related to general care, medication, hospital-acquired infection, related to diagnosis or to a procedure and others). AE related to a procedure included surgery, anesthesia, chemotherapy, radiotherapy, fracture treatment and other invasive procedures. Therefore, in stage 2, a structured implicit review was used to identify the AE based on completion of the MRF-2 form. The two electronic forms were adapted and translated to Portuguese by the research team with the participation of a linguistic specialist. No validity testing was applied in the translation process. Four evaluators were selected in each hospital (two nurses and two physicians). They were previously trained for two consecutive days and at the end agreement among nurses were found to be 100%. Before considering an AE, the physician needed to fill out the causality assessment module of MRF-2 form which consists on a six-point scale on chance of an AE occurrence. A score >3 means that the analyzed event was an AE. Also, the physician reviewer had to complete the MRF-2 form by assessing the AE preventability scale (six-point scale on chance of a preventable AE). A score >3 in this scale means that the AE was preventable. A total of 695 admissions were examined in this study. Figure 1 below shows the number of screened admissions, number of AE detected and also the number of preventable AE, based on the two-steps methodology applied. Figure 1 View largeDownload slide Medical records review and screened cases. Figure 1 View largeDownload slide Medical records review and screened cases. Exposure variables considered in this study were social and demographic characteristics, type of admission, patient intrinsic and extrinsic factors, presence and types of comorbidities and submission to a procedure during the admission. The outcome was AE occurrence. Regarding intrinsic and extrinsic factors, these were risk factors potentially associated with an AE occurrence, collected during stage 1 (Screening Form). Intrinsic factors were considered exposure variables related to the patient or case severity, such as, coma, renal insufficiency, diabetes, cancer, immunodeficiency/AIDS, chronic pulmonary disease, leukopenia, chronic hepatopathy, obesity, hypoalbuminemia/malnutrition, pressure ulcer, congenital malformations, cardiac insufficiency, coronary artery disease, arterial hypertension, hypercholesterolemia and alcoholism. Extrinsic factors were exposure variables related to hospital care, such as, closed urinary catheter system, peripheral venous catheter, arterial catheter, peripherally inserted central catheter, central venous catheter, parenteral nutrition, enteral nutrition, nasogastric/nasoenteral tube, tracheostomy, mechanical ventilation, tracheal intubation, immunosuppressive therapy, infusion pump, hemodialysis and peritoneal dialysis. Chi-squared tests were conducted to test the association between variables. A final logistic regression model was built to analyze the association between exposure and outcome. The software IBEAS-Brazil System was developed for the study purpose to allow electronic data collection and to avoid double entries in the process of screening and assessment of AEs. Data were analyzed using Stata/IC software version 11 (Stata Corporation, College Station, USA). The study was approved by the Ethics Committee of Oswaldo Cruz Foundation (No. 549/10). Results Most patients were male (52.7%), with a median age of 63 years (Interquartile range—IQR: 45–77). Almost 90% of patients had comorbidities (88.6%). Among them, arterial hypertension was the most prevalent (56.8%), followed by diabetes (27.9%), other endocrine disorders (26.3), coronary disease (25.5%) and cardiac insufficiency (25.2). Urgent admissions were the most frequent type of admissions (57.4%) and 66% of patient underwent a procedure during the admission (Table 1). Table 1 Characteristics of the study population regarding social and demographic factors, comorbidities and hospital admission factors (695 inpatients) Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  aFor example: thyroid and adrenal disorders. Table 1 Characteristics of the study population regarding social and demographic factors, comorbidities and hospital admission factors (695 inpatients) Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  Variables  n  %  Social and demographic       Men  366  52.7   70 years of age or older  271  39.0   White  299  95.2   College degree  117  33.7  Comorbidities       Hypertension  214  56.8   Diabetes  105  27.9   Endocrine disordersa  99  26.3   Coronary disease  96  25.5   Cardiac insufficiency  95  25.2   Anemia  79  21.0   Cancer  73  19.4   Allergies  63  16.7   Chronic kidney disease  53  14.1  Hospital admission       Type of admission (urgent)  397  57.4   Procedure during admission  454  65.7   Total  695  100,0  aFor example: thyroid and adrenal disorders. Regarding risk factors, collected during stage 1, the most frequent intrinsic factors among patients were arterial hypertension (47.6%), mellitus diabetes (21.7%) and cancer (20.3%). The most frequent extrinsic factor found was peripheral venous catheter (74.4%), infusion pump (34.1%) and closed urinary catheter system (24.6%). In binary analysis of intrinsic factors, renal insufficiency and arterial hypertension were statistically associated with an AE (P < 0.05). Among extrinsic factors, closed urinary catheter system, central venous catheter, enteral nutrition, nasogastric/nasoenteral tube, tracheostomy, mechanical ventilation, tracheal intubation, immunosuppressive therapy, infusion pump and hemodialysis were statistically associated with AE occurrence (P < 0.05) (Table 2). Table 2 Frequency of intrinsic factors (factors associated with the patient) and extrinsic factors (factors related to hospital care) and their association with AE occurrence   n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634    n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634  Bold: P-values less than 0.05 considered statistically significant. Table 2 Frequency of intrinsic factors (factors associated with the patient) and extrinsic factors (factors related to hospital care) and their association with AE occurrence   n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634    n  %  P-value  Intrinsic risk factors   Coma  26  3.8  0.324   Renal insufficiency  63  9.1  <0.001   Mellitus diabetes  150  21.7  0.930   Cancer  140  20.3  0.262   Immunodeficiency/AIDS  13  1.9  0.573   Chronic pulmonary disease  55  8.0  0.421   Leukopenia  11  1.6  0.705   Chronic hepatopathy  32  4.6  0.120   Drug abuse  2  0.3  0.586   Obesity  27  3.9  0.139   Hypoalbuminemia/malnutrition  16  2.3  0.423   Pressure ulcer  36  5.2  0.086   Congenital malformations  21  3.0  0.259   Cardiac insufficiency  52  7.5  0.111   Coronary artery disease  124  18.0  0.370   Arterial hypertension  329  47.6  0.029   Hypercholesterolemia  70  10.1  0.995   Prematurity  4  0.6  0.441   Alcoholism  16  2.3  0.963  Extrinsic risk factors         Open urinary catheter system  12  1.7  0.179   Closed urinary catheter system  170  24.6  <0.001   Peripheral venous catheter  513  74.4  0.129   Arterial cateter  88  12.8  0.214   Peripherally inserted central catheter  4  0.58  0.469   Central venous catheter  157  22.8  <0.001   Umbilical venous catheter  3  0.43  0.504   Umbilical arterial catheter  1  0.14  0.700   Parenteral nutrition  9  1.3  0.066   Enteral nutrition  97  14.1  <0.001   Nasogastric/nasoenteral tube  98  14.2  <0.001   Tracheostomy  42  6.1  0.008   Mechanical ventilation  97  14.1  <0.001   Tracheal intubation  86  12.5  <0.001   Immunosuppressive therapy  44  6.4  0.001   Infusion pump  235  34.1  0.010   Hemodialysis  30  4.4  <0.001   Peritoneal dialysis  5  0.7  0.634  Bold: P-values less than 0.05 considered statistically significant. About 89 patients had an AE prevalence of 12.8%. Thirty-eight of them (42.7%) were evaluated as preventable. Additional hospitalization days due to AE were almost 40 days and 11.6 additional days in ICU hospitalizations. The severity of the event was mild in 13.3% of cases, which means that the AE did not increase the hospital stay; moderate in 60.2% of cases, that is, prolonged hospital stay for at least 1 day; and severe in 26.5% of cases, which means that the AE caused death, disability at hospital discharge or required surgery. The most frequent types of AE were general care and related to procedure (27.6% each), followed by infection (19.4%), medication (18.4%) and diagnosis (2.0%), the less frequent in this study (Table 3). Table 3 Adverse events characteristics: prevalence, preventability, severity, types and impact   n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0    n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  SD, standard deviation; ICU, intensive care unit. Table 3 Adverse events characteristics: prevalence, preventability, severity, types and impact   n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0    n  %  Adverse events   AE Prevalence  89  12.8   Preventable AE  38  42.7  AE severity       Mild  13  13.3   Moderate  59  60.2   Severe  26  26.5  Types of AE       General care  27  27.6   Procedure  27  27.6   Hospital-acquired infection  19  19.4   Medication  18  18.4   Diagnosis  2  2.0  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  AE impact  Mean  SD  Additional hospitalization days due to AE  39.9  34.9  Additional ICU days due to AE  11.6  18.9  SD, standard deviation; ICU, intensive care unit. In binary analysis, no association was found between AE occurrence and social and demographic variables (gender, age and education). Type of admission (urgent) was statistically associated with AE (P < 0.001). The variables admission sector and presence of comorbidity were not associated with AE occurrence in this study. On the other hand, submission to a diagnostic or a treatment procedure during the admission was statistically associated with AE (P = 0.001). In the final model of logistic regression (Table 4), including the exposure variables which showed statistical significance with AE prevalence in binary analysis, only type of admission, submission to a diagnostic or a treatment procedure, central venous catheter and immunosuppressive therapy remained associated with AE. Urgent admission and submission to a procedure during admission increased more than two times the chance of having an AE (OR: 2.68; CI 95%: 1.53–4.69, and OR: 2.41; CI 95%: 1.33–4.39, respectively). In this phase, no patient factors presented statistical significance. However, presence of central venous catheter nearly doubled the chance of having an AE (OR: 2.25; CI 95%: 1.14–4.41), possibly due to patient severity condition. Submission to immunosuppressive therapy increased more than three times the chance of having an AE (OR: 3.41; CI 95%: 1.57–7.40). This extrinsic factor was strongly related to medication AE (P = 0.001). Among the 12 cases that referred immunosuppressive therapy as an extrinsic factor, eight of them (66.7%) had one medication AE. Table 4 Final logistic regression model of the association between AE occurrence and hospital admission factors Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Bold: P-values less than 0.05 considered statistically significant. CI: Confidence interval. Table 4 Final logistic regression model of the association between AE occurrence and hospital admission factors Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Variables  Odds ratio  CI 95%  P-value  Urgent admission  2.68  1.53–4.69  0.001  Submission to a procedure during the admission  2.41  1.33–4.39  0.004  Renal insufficiency  1.61  0.71–3.62  0.251  Arterial hypertension  1.53  0.94–2.48  0.087  Closed urinary catheter system  1.08  0.57–2.05  0.812  Central venous catheter  2.25  1.14–4.41  0.019  Enteral nutrition  1.32  0.45–3.83  0.612  Nasogastric/nasoenteral tube  1.12  0.39–3.25  0.835  Tracheostomy  0.75  0.25–2.27  0.614  Mechanical ventilation  1.08  0.29–4.04  0.912  Tracheal intubation  1.12  0.35–3.64  0.848  Immunosuppressive therapy  3.41  1.57–7.40  0.002  Infusion pump  0.68  0.35–1.29  0.238  Hemodialysis  1.57  0.55–4.48  0.398  Bold: P-values less than 0.05 considered statistically significant. CI: Confidence interval. Discussion In the present study, we found a prevalence of 12.8% of AE in four Brazilian hospitals, higher to the prevalence found in IBEAS study (10.5%). This is probably due to the similar nature of hospitals selection and the same methodology applied. As in IBEAS study, in this study the selection of hospitals was voluntary and based on feasibility, which tends to include services more engaged in patient safety actions or concerns [22]. However, we found a lower proportion of preventable AE (42.7%) compared with IBEAS study (60%) and to our previous incidence study (66.7%) [13], which may be explained by the specificity of our sample: patients with higher education levels, coming from better quality hospitals. Although Michel et al. [12], when comparing three methods for AE detection, found similar AE rates between the prospective and retrospective methods (15.4% and 14.5%, respectively), and the lowest rate when using the cross-sectional method (9.8%), our study found a higher AE rate compared with the previous incidence study (7.6%) [13]. This finding is also probably related to the nature of our sample and its size, comparatively to incidence study: better quality hospitals, with better healthcare, greater patient safety concerns and better hospital documentation. In this study, urgent admission, submission to a surgical or invasive procedure, presence of central venous catheter and submission to immunosuppressive therapy were factors with the greatest contribution to AE occurrence. Gender, age and presence of comorbidity, and the intrinsic factors did not show effect on the chance of having an AE. We suspect that may be comorbidities registration in patient records is affected by underestimation [23], or may be, due to the characteristics of the prevalence design, with 24-h evaluation, the information related to patient factors was underrepresented, comparatively to admission factors. In a previous study, conducted by the research group using an incidence design, comorbidity was associated both with AE and death [24]. In this study, admission factors seem to be representative of patient severity. Therefore, although variables measuring patient comorbidity factors have not shown statistical significance, the association of AE with type of admission (urgent) and also with presence of central venous catheter seems to indicate case severity. Central venous catheter could also indicate AE due to central line infection. Patients submitted to immunosuppressive therapy had three times more chance of having an AE and most of them are medication AE, which indicates an important area of AE prevention. According to our results, 60.2% of patients had moderate AE and had a prolonged hospital stay for at least 1 day. This finding is alarming considering that prolongation of hospitalization time increases the chance hospital-acquired infections, as well as increases the cost for the healthcare system. Generally, emergency admissions are more severe compared with elective and scheduled admissions. In IBEAS original study, urgent admissions also increased the risk of having an AE (OR: 1.34; CI 95%: 1.12–1.61). Thereby, these results showed that more attention should be given in urgent admissions, especially in the emergency department, with health team continual training to detect and avoid such problems. The performance of diagnostic and therapeutical procedures during admission should follow checklists and guidelines to avoid AE occurrence, as well as patients submitted to tracheal intubation deserve more attention by the caregiver. These results suggest that quality of care initiatives should focus on those high-risk patients in order to reduce the risk of AE and also reduce mortality, such as the ongoing initiatives for reducing the risk of postoperative respiratory complications, including death, in major abdominal surgeries [25]. The limitations of this study are related to the characteristics of our sample size. First, interpretation of results should take into consideration that this is not a random sample representative from all the Brazilian hospitals and that the hospitals were chosen by convenience. The frequency of AE may vary as the hospitals characteristics vary. Some statistical analyses were impaired due to our limited sample size. We performed analysis according to AE preventability and severity, but did not show statistical significance. Also, the quality of collected data (for example, case severity) must have been affected by the poor quality of medical records. Besides, it is important to note that, as this is a cross-sectional design, no causality has been established between exposure and outcome, but on the other hand, the intention is to create a hypothesis that should be tested in longitudinal studies. Regarding research instruments, we observed that, in some cases, pressure ulcer was both classified as an AE and an intrinsic factor for the same patient. We considered these cases inconsistencies and we proceeded to reclassify them as adverse events. Future research using the same instrument should consider to intensify evaluators training in the identification of the presence of pressure ulcer before admission comparatively to its development during the hospitalization to avoid misclassification. Despite the limitations, this is the first prevalence study of AE conducted in Brazilian hospitals and it adapted and translated to Portuguese a methodology used in a previous published Latin American study [22]. Although the methodological differences, drew attention the rates obtained by the incidence and prevalence studies have been close. Our results indicate that around 1.3 AE happen in each 10 hospital admissions in Brazil. This is alarming considering the specificity of our sample size. As patient safety continues to be a Public Health concern worldwide and mainly in developing countries, this would indicate the potential use of prevalence measures for monitoring patient safety in Brazilian context. Considering the convenience regarding costs and methodology, prevalence designs, rather than incidence ones, can be a useful tool for monitoring AE rates in hospitals. 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International Journal for Quality in Health CareOxford University Press

Published: Mar 31, 2018

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