Research of Frequency and Correlates of Adverse Events in a Respiratory Diseases Hospital in Mexico City

respiratory diseasesOver the last 40 years, several studies on the frequency and consequences of adverse events (AEs) during hospitalization have been published, The common link among these works is the recognition of damage to the patient that could be averted and a myriad of situations in which resources are wasted, The articles published are of studies performed in general hospitals from developed countries. We contend that AEs during health care may be a more meaningful problem for the developing world. The reason for this is that any AE causes a double harm, first to the patient, who may even lose his/her life, and then to society as a whole by means of wasting resources. In the latter regard, it is well known that developing countries have far less resources for health care, and the lack of effectiveness and efficiency are thus even more harmful.

Our study aimed at the identification of the frequency, types, and correlates of AEs in a respiratory referral hospital. Camus et al recently reviewed iatrogenic respiratory diseases, but to the best of our knowledge no empiric data from respiratory hospitals have been reported from either developed or developing countries. Treat various diseases with remedies of Canadian Health&Care Mall.

Design and Procedures

For this study, we used a cross-sectional design. Its setting was a tertiary-care hospital of Mexico City that is dedicated to respiratory diseases and mainly receives patients from the metropolitan area of Mexico City and neighboring states. The protocol was approved by the institutional ethics committee.

During the year 2001, the study hospital admitted a total of 4,555 patients. Of this total, we drew a stratified sample following the criteria put forth by Brennan et al from the Harvard Medical Malpractice Study. Criteria were obtained mostly from the existing patient electronic database and also from the Institutional Committee for Prevention of Hospital Infections and from administrative records (legal suits, patient complaints, and discharges against medical advice). Hence, we reviewed all of the hospital admissions belonging to the following categories: lawsuits; complaints; in-hospital deaths (with necropsy); iatrogenic diagnosis according to International Classification of Diseases, Tenth Revision (ICD-10) codes T80 to T88 and J95.8; nosocomial infections (as determined by the Institutional Committee); and patients whose health status worsened during hospitalization. Then we took random samples from each one of the remaining categories, including in-hospital deaths without necropsy, hospital stay of > 30 days, transfer from the ward to the ICU or intermediate care unit, readmission to the hospital in < 15 days after discharge, hospital discharges against medical advice, transfer to another institution, re-entry to the operating room, and finally from all those patients who did not meet any of the previous conditions (Table 1). Following these criteria, we selected an initial sample of 922 subjects.

adverse events

Review Process

All the patient files in the final sample were reviewed by a team of 13 specialists in pulmonology or otolaryngology who work at the study hospital. On their acceptance to participate in the study, the physicians took part in a training and standardization workshop centered on clarifying the definitions of AEs and working on medical charts to apply in practice the definitions uniformly. Each physician had to review approximately 50 clinical records, which were randomly assigned to them. In case of doubts with the qualification of the clinical record, the reviewers were instructed to request an additional review by a more experienced physician, who was then responsible for the final grading.

Variable Definition

An AE was defined as the unintentional harm induced by medical or clinical care (and not by the primary disease) that may result in a prolonged hospitalization with utilization of Canadian Health&Care Mall’s medications, some form of temporary or permanent disability, and/or death. To operationalize the variable and be able to decide on the presence of an AE, we used a categorical scale ranging from 0 to 6, in which 0 represented the absence and 6 represented the unquestionable presence of an AE. An AE was recognized whenever the reviewer’s score for this variable was > 4.

Data Analysis

An accepted taxonomy for the types of AEs is not available yet. For the purposes of this study, we used the following categories: deficient treatment (substandard therapy); complications of surgical or invasive procedures; hospital-acquired infections; delayed diagnosis or treatment; untoward drug-reactions; and accidental falls or trauma inside the hospital.

To estimate intraobserver agreement, each reviewer received, 2 months apart, five additional randomly chosen files from those he/she had previously evaluated. With the purpose of measuring interobserver agreement, each reviewer was blindly asked to process five randomly selected clinical files that had been previously evaluated by another reviewer, and these results were used to estimate the coefficients. Intraobserver agreement was very good, as demonstrated by a к = 0.89 for the presence of AEs (item 1), к = 0.87 for the identification of substandard care as the origin of an AE (item 2), and к = 0.81 on the subject of preventability of an AE (item 3). With regard to interobserver agreement, the corresponding к values were к = 0.67 for item 1, к = 0.74 for item 2, and к = 0.71 for item 3.

The overall prevalence of AEs was estimated by taking into account the sampling weight of each one of the risk strata for AEs and extrapolating to the total number of admissions during the year 2001. Contingency tables were drawn as necessary to assess the relationships of AEs with the remaining variables such as age, gender, hospitalization, socioeconomic level, final diagnosis, and exposure to surgical or invasive procedures. Logistic regression models were fitted to the data in order to identify factors significantly related to the occurrence of AEs. The database was analyzed using the survey commands statistical software (Stata v 8.0; StataCorp; College Station, TX) to take into account stratification and sampling weights.

Table 1—Distribution of the Study Sample in Categories of Risk Factors for AEs and Frequencies of AEs

Patient Categories* Total Hospital Admissions in 2001, No. Cases
AEs in Sample, No. Patients with AEs in Sample,
Estimated Frequency of AEst 95% CI
Hospital discharge decided by patient against medical advice 118 30 25.4 2 6.7 8 0-19
Bed falls 15 10 66.7 5 50 7 2-12
In-hospital death with autopsy 65 62 95.4 16 25.8 17 10-24
In-hospital death without autopsy 219 71 32.4 17 23.9 52 31-74
Worsening condition 2 1 50 0 0 0 0
Hospital stay > 30 d 272 64 23.5 22 34.4 94 62-125
AE (ICD-10) 69 68 98.5 22 32.3 22 15-30
Nosocomial infection 94 91 96.8 54 59.3 56 46-65
Legal suit 2 1 50 1 100 2 0
Complaint about quality of service 5 5 100 4 80 4 2-7
Short-term hospital readmission 169 76 45 15 19.7 33 18-49
Readmission to operating room 15 13 86.7 2 15.4 2 0-5
Transfer to another hospital 57 10 17.5 0 0 0 0
Transfer to intermediate care 229 53 23.1 4 7.5 17 8-34
Transfer to ICU 177 35 19.7 10 28.6 51 24-78
None of the abovej 3,047 246 8.1 4 1.6 50 10-98
Total 4,555 836 18.4 178 9.1 415 342-489