Name

HEP 444 Epidemiology

Dr. Adams

9/5/2022

HEP 444 Case Study Sorrow and Statistics

The setting of the story in terms place of the disease outbreak, persons affected, and time from the initial case to the end of death.

In the province of Ontario, four suspicious infant deaths were reported in March 1981. This occurrence was in a sick children’s hospital, specifically cardiology service ward 4A. The following year, the hospital also reported unclear illness in five babies in the neonatal ward, and one of them died of what seemed like a bloodstream infection. The ward was evacuated, and the sick infants were taken to the intensive care unit for further evaluation. These deaths ended with the arrest of Susan Nelles.

Explanation of what epi-curve shows and its importance in the outbreak.

The epidemiological curve shows the infant death per 10,000 patient days from January 1976 to September 1982. Ward 5A was used for cardiology services before April 1981, after which the services were moved to wards 4A and 4B. The significance of the curve is that the large peak shows a steep rise in death rates. The peak lasted nine months, where twenty-six babies died in ward 4A and eight in Ward 4B. The increase in infant deaths was significant and too large to be coincidental. From the peaks in the curve, the rise in death rates was only witnessed in cardiology wards, and outside the peak period, the rise in death rates is significant in the operating room.

Which nurse is the guiltiest according to deaths and why?

According to the statistics in Table 1, nurse A is the most suspect. First, the combined relative risk for both night and day shifts was 64.6, meaning there was a high probability of an infant dying while on duty compared to off-duty. Secondly, the death rate during off-duty was zero making the relative risk for the night shift infinity. Lastly, the time approximated for overdose administration for all the reported cases occurred when nurse A was on duty.

How epidemiology data were treated by the legal system when the health officials tried to show one of their nurses killed the infants

The lawyer representing Trayner’s team identified various data errors, including transposition errors, tabulation errors in the analysis, and a missing date on the transmittal letter report. On the other hand, the attorney representing the coroner’s office and the attorney general pointed out that, other than the critiquing statical data and study design, it was impossible in the provided epidemiology data that any other person other than Trayner could be linked with the suspicious deaths. The lawyer representing the individual nurses and the Registered Nursing Association dismissed the epidemiology data that stated only nurses had access to the ward in question (cardiology) during late night.

Conclusion on legal process and investigation regarding patient and nurses’ safety

Hospitals should ensure excellent mortality data analysis and routine mortality surveillance by keeping detailed records on all deaths for unusual mortality patterns to be identified. Moreover, hospitals should avoid keeping bottles of medicines on shelves but instead dispense them in a standard pharmacy. To strengthen these efforts, hospitals should record the cause of death and the time and the nurses on duty during such occurrence. Lastly, ward-specific death rates should be calculated over a long period to avoid data errors.

Works Cited

Levitt, Alexandra M. Deadly outbreaks: how medical detectives save lives threatened by killer pandemics, exotic viruses, and drug-resistant parasites. Simon and Schuster, 2015.