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Critical appraisal of cross-sectional surveys
Published in O. Ajetunmobi, Making Sense of Critical Appraisal, 2021
Population mortality measures include the ‘crude mortality rates’, the ‘specific mortality rates’, the ‘standardized mortality rates’ and the ‘standardized mortality ratio’. The meanings of the various mortality measures and how they are derived are described below.
Adapting Smartphone-Based Applications for Performance Improvement Metrics’ Tracking in Healthcare Facilities as a Managerial Tool
Published in Abdel-Badeeh M. Salem, Innovative Smart Healthcare and Bio-Medical Systems, 2020
Adriana Burlea-Schiopoiu, Koudoua Ferhati
From the data shown in Table 7.8, the waiting time is going from a minimum of 29 minutes in the fifth week to a maximum of 51 minutes in the third week, with an observable decreasing from the first 4 weeks to the last 4 weeks. Mortality rate A standardized mortality ratio is calculated as the observed number of deaths divided by the expected number of deaths [22]. In this metric, we assess the number of death cases every week in the given healthcare facility.
STATISTICAL EVALUATION OF THE RISK OF CANCER MORTALITY AMONG INDUSTRIAL POPULATIONS
Published in Richard G. Cornell, Statistical Methods for Cancer Studies, 2020
Michael J. Symons, John D. Taulbee
The cornerstone for a historic prospective cohort mortality study lies in determining the amount of risk of death for the workforce over an observation period. This evaluation requires the combined information on the number of cohort members and period of observation for each member. The term “historic prospective” derives from the identification of all those workers defined to be members of the cohort as of the same past date and followed to a more recent past date. For this period of observation the expected deaths for all causes or a specific cause are calculated. The ratio of the observed deaths to the expected, possibly multiplied by 100 and reported as a percentage, is termed the standardized mortality ratio. The standardization refers to the specific death rates used from a comparison population. For example, the use of white male age-specific death rates for leukemias in the United States, as applied to a white male cohort, would provide an age standardized mortality ratio.
The Ethical Defensibility of Harm Reduction and Eating Disorders
Published in The American Journal of Bioethics, 2021
Andria Bianchi, Katherine Stanley, Kalam Sutandar
Persons with AN do not have a normal body weight in accordance with their age and height. The threshold for AN is typically a body mass index (BMI) of 18.5 kg/m2 or less (National Initiative for Eating Disorders 2016–2018b), where a healthy BMI is considered to be between 18.5 and 24.9 kg/m2 (World Health Organization). Persons with AN may engage in restrictive behaviors by limiting their caloric intake and/or by binging/purging the food that they consume. Persons with AN will typically have an extreme and constant fear of gaining weight or becoming “fat” even though they are severely underweight and restricting their energy intake (National Eating Disorders Association 2018a). Approximately 0.9% of females and 0.3% of males suffer from AN (Hudson et al. 2007). Persons diagnosed with anorexia nervosa (AN) have the highest death rate of any mental health disorder; the mortality rate for AN is 5.6% per decade of illness (i.e. the risk of death increases the longer one has been ill) (Sullivan 1995). The standardized mortality ratio is 5.86 (Arcelus et al. 2011). AN also has the highest suicide rate of any psychiatric illness, and according to the Academy of Eating Disorders, “[t]he risk of death [for people with AN] is three times higher than in depression, schizophrenia or alcoholism and 12 times higher than in the general population.”
Identifying and mitigating Sudden Unexpected Death in Epilepsy (SUDEP) risk factors
Published in Expert Review of Neurotherapeutics, 2018
Lance Watkins, Rohit Shankar, Josemir W. Sander
The reported incidence rates of SUDEP range widely from 0.09 to 9.3 per 1000 person-years [7]. The identification of SUDEP cases in community samples and epilepsy cohorts has largely been retrospective in nature, involving review of data from hospital and autopsy records. A large population-based study of people with epilepsy in the USA reported an estimated incidence of 0.35 cases per 1000 person-years. This gives a Standardized Mortality ratio of nearly 24 times that of the general population [8]. Similar results have been replicated in a nationwide Danish population study [9]. Other studies have reported significantly higher rates of SUDEP in the epilepsy population. The reason for such variance in incidence rates is likely related to case selection and methodological differences in study design. A more recent systematic review of the literature estimates a crude annual incidence rate of 1.16 (0.95–1.36) per 1000 person-years [10].
Suicide Risk by Unit Component among Veterans Who Served in Iraq or Afghanistan
Published in Archives of Suicide Research, 2018
Tim Bullman, Aaron Schneiderman, Robert Bossarte
Suicide risk was assessed first by comparing the observed number of suicides among OEF/OIF/OND veterans, when stratified by service in either Active versus Reserve/National Guard component, to the expected number of suicides based on the U.S. general population, with adjustment for race, sex, age at entry to follow-up and year of death. This comparison is expressed as a standardized mortality ratio (SMR) (Schubauer-Berigan et al., 2005). Suicide risk by Active versus Reserve/National Guard status was further assessed using a Cox Proportional Hazards Model generated by SAS® PHREG procedure. The Cox Model, which incorporates time at risk, was used to calculate Hazards Ratios (HR)s that assessed the effect of covariates on risk of suicide among all 1.4 million cohort veterans (SAS Institute, 2011). Covariates included in the model were: age at entry to follow-up; race (white); gender (male); marital status (single); rank (Enlisted); served as a ground troop, i.e., served in either Army or Marines; and service in an Active component unit during OEF/OIF/OND deployment.