Surveillance and Epidemiologic Investigation Flashcards
Identify the median in the following list of numbers:
6, 2, 9, 7, 1, 4
a. 9
b. 7
c. 5
d. 4
c. 5
In a study of whether Operating room A (OR A) is associated with a higher number of surgical site infections (SSIs) than Operating room B (OR B), the infection preventionist (IP) is testing whether: Ho: OR A SSI rate = OR B SSI rate H a: OR A SSI rate ≠ OR B SSI rate
The IP concludes that the SSI rate in OR A is not equal to the SSI rate in OR B, but in reality the two rates are equal. What type of statistical error has she committed?
a. No error has been committed
b. She committed a Type I error
c. She committed a Type II error
d. She committed an error equal to
B She has committed a Type I error
Rationale: If the IP concluded that the SSI rate in OR A is not equal to the SSI rate in OR B, then she rejects the null hypothesis. However, in this case the null hypothesis was true; therefore she has committed a Type I error. This value is equal to α. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
For which of the following procedure(s) is the surveillance period for deep incisional or organ/space SSI 90 days?
1) Cesarean section
2) Craniotomy
3) Coronary artery bypass graft
4) Laminectomy
a. 1, 2
b. 2, 3
c. 3, 4
d. 1, 4
B 2, 3
Rationale: According to the Centers for Disease Control and Prevention (CDC) SSI surveillance definitions, postoperative surveillance for deep incisional or organ/space SSIs should be conducted for 90 days on craniotomy and coronary artery bypass procedures. Superficial incisional SSIs are only followed for a 30-day period for all procedure types. Reference: APIC Text, 4th edition, Chapter 11 – Surveillance
An appropriate indicator to monitor process compliance would be:
a. Class 1 SSI rate
b. Appropriate antibiotic dosage
c. Central line–associated bloodstream infections
(CLABSIs) in the Neonatal Intensive Care Unit
(NICU)
d. Infections caused by multidrug-resistant organisms
B Appropriate antibiotic dosage
Rationale: A surveillance program should monitor a variety of outcomes, processes, and events, and some indicators should focus on personnel. A process measure focuses on a process or the steps in a process that lead to a specific outcome. Process measures are commonly used to evaluate compliance with desired care or support practices or to monitor variation in these practices. Examples of process indicators include medication errors; influenza vaccination rates in personnel, residents, or patients; hepatitis B immunity rates in personnel; and personnel compliance with infection prevention protocols, such as Standard Precautions, Isolation Precautions, tuberculin skin testing, hand hygiene, instrument processing, sterilization quality assurance testing, environmental cleaning, communicable disease reporting, antimicrobial prescribing and administration, and installing and maintaining barriers during construction and renovation projects. An outcome measure is a measure that indicates the result of the performance (or nonperformance) of a function(s) or process(es). Examples of outcome indicators that may be monitored include HAIs (e.g., bloodstream, urinary tract, pneumonia, surgical site, conjunctivitis, upper respiratory tract, or local intravenous site), infection or colonization with a specific organism (e.g., C. difficile, MRSA, vancomycin-resistant enterococci or other antibiotic-resistant organisms, respiratory syncytial virus, or rotavirus); decubitus ulcers; phlebitis related to peripheral intravascular therapy; pyrogenic reaction or vascular access infection in hemodialysis patients; resident or patient falls; influenza or tuberculin skin test conversions in patients, residents, or healthcare providers; and sharps injuries and blood/body fluid exposures in healthcare providers.
What key infection control activity is defined as the systematic, ongoing collection, management, analysis, and interpretation of data followed by the dissemination of these data to public health programs to stimulate public health action?
a. Research
b. Surveillance
c. Benchmarking
d. Accreditation
B Surveillance
Rationale: Surveillance has been defined as the “ongoing collection, collation, and analysis of data and the ongoing dissemination of information to those who need to know so that action can be taken.” Surveillance is an essential component of an effective infection prevention and control program. Surveillance includes the collection of data with the ultimate objective of dissemination of that data to support and improve public health activities. Reference: APIC Text, 4th edition, Chapter 11 – Surveillance
An IP is reading a journal article that states that the data the authors collected are normally distributed. What does this mean?
a. When the data are plotted on a curve, it is skewed b. The mean is less than the median
c. The skewness value is equal to 1
d. The mean, median, and mode of the data are equal
D The mean, median, and mode of the data are equal
Rationale: If the data are normally distributed, then the mean, median, and mode are all equal and the curve will have a bell shape, with most observations clustering at the center and then tapering off on either side of the center. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
Which of the following is indicative of a superficial SSI?
a. Pain at the incision site 10 days after a breast
reduction procedure; drainage is culture-positive
for methicillin- susceptible Staphylococcus aureus
(MSSA)
b. Stitch abscess that is cultured 14 days after surgery
and is positive for Enterococcus faecalis
c. Purulent drainage from an episiotomy that occurs
within 5 days of delivery
d. Burn wound that cultures positive for Acinetobacter
baumannii 10 days after debridement procedure
A Pain at the incision site 10 days after a breast reduction procedure; drainage is culture positive for methicillin-susceptible Staphylococcus aureus (MSSA)
Rationale: SSI continues to be a major source of morbidity, economic cost, and even death in surgical patients. To meet the criteria for a superficial SSI, the infection must occur within 30 days after the operation and involve only skin or subcutaneous tissue. In addition, one of the following must be met: • Purulent drainage, with or without laboratory confirmation, from the superficial incision • Organisms isolated from an aseptically obtained culture of fluid or tissue from the superficial incision • And patient has at least one of the following: ° Purulent drainage from the superficial incision ° Organisms isolated from an aseptically obtained culture of fluid or tissue from the superficial incision ° Superficial incision that is deliberately opened by a surgeon, attending physician, or other designee And patient has at least one of the following signs or symptoms: pain or tenderness, localized swelling, redness, or heat. A culture negative finding does not meet this criterion. ° Diagnosis of superficial incisional SSI by the surgeon or attending physician or other designee References: Centers for Disease Control and Prevention. Procedure-associated Module – Surgical Site Infection (SSI) Event. CDC website. January 2014. Available at: http://www.cdc.gov/nhsn/pdfs/pscmanual/9pscssicurrent.pdf; APIC Text, 4th edition, Chapter 37 – Surgical Site Infection
An IP is preparing the quarterly report for the Infection Control Committee. What information will be needed to calculate a CLABSI rate for the ICU?
1) The total number of patients in the unit for the time
period
2) The total number of central line catheters for the
time period
3) The number of patients who had bloodstream
infections identified
4) The number of device days for the time period
a. 2, 3
b. 1, 3
c. 1, 2
d. 3, 4
- D 3, 4
Rationale: The numerator would be the number of patients who had bloodstream infections identified and who had a central line during the time period. The denominator would be the number of device days (at the same time every day, count the number of patients with one or more central lines) for the time period. Basic Formula for All Types of Rates • Rate = x/y × k Where: • x = The numerator, which equals the number of times the event (e.g., infections) has occurred during a specified time interval • y = The denominator, which equals a population (e.g., number of patients at risk) from which those experiencing the event were derived during the same time interval • k = A constant used to transform the result of division into a uniform quantity so that it can be compared with other, similar quantities. A whole number (fractions are inconvenient) such as 100, 1,000, 10,000, or 100,000 is usually used (selection of k is usually made so that the smallest rate calculated has at least one digit to the left of the decimal point) or is determined by accepted practice (the magnitude of numerator compared with denominator). Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
What type of rate would the IP want to calculate to give feedback to the surgeons at her facility?
a. Procedure-specific
b. Provider-specific
c. Unit-specific
d. Device-specific
B Provider-specific
Rationale: Providing feedback of appropriate SSI surveillance data to surgeons has been shown to be important to reducing SSI risk. Furthermore, providing active rather than passive feedback of surveillance results to surgeons has the greatest effect in reducing SSI rates. When surgical teams are engaged in examining their SSI rates and in appraising clinical processes, there is greater probability of success in reducing infection rates. Reference: APIC Text, 4th edition, Chapter 17 – Performance Measures
The IP has been benchmarking her data to other facilities performing similar activities for a period of time. The IP should analyze the entire process to ensure that which of the following conditions are met?
1) Standardized definitions are used consistently
2) Overall rates are used to accurately track trends
over time
3) Adequate training of personnel to collect, store,
manage, and analyze data
4) Data are calculated using the same methodology as
a nationally validated system
a. 1, 2, 3
b. 2, 3, 4
c. 1, 3, 4
d. 1, 2, 4
C 1, 3, 4
Rationale: To accurately trend surveillance data over time within a facility or compare rates between facilities, surveillance criteria (i.e., case definitions) must be consistently used to determine the presence of an HAI, occurrence of an event, or compliance with a process. Rates, rather than raw numbers, must be used to accurately track trends over time. Personnel who are responsible for collecting and managing surveillance data must have adequate training in reviewing medical records, interpreting clinical notes, applying standardized criteria for identifying cases, using appropriate statistical and risk adjustment methods, and using computer tools and technology (especially electronic records, spreadsheets, and databases) to collect, store, manage, and analyze data. Whenever possible, data should be expressed as rates or ratios that are calculated using the same methodology as a nationally validated surveillance system. This allows an organization to compare its rates with another organization or a recognized benchmark. Reference: APIC Text, 4th edition, Chapter 11 – Surveillance
The chi-square test can be used:
1) To evaluate the effect of a variable on outcomes
2) To analyze continuous data
3) To calculate an odds ratio or relative risk
4) If each cell of the table is greater than 5
a. 1, 2, 3
b. 1, 2, 4
c. 2, 3, 4
d. 1, 3, 4
D 1, 3, 4
Rationale: Chi-square tests (χ2) can be used to test the association between two classifications of a set of counts or frequencies (discrete data). This data are commonly displayed as a contingency table or 2 x 2 table where rows represent one variable and columns represent the other. The null hypothesis is that there is no association between the two variables. Row and column totals (marginal totals) are used to predict what count would be expected for each cell if the null hypothesis were true. A test statistic is calculated from the observed and expected frequencies. The larger the test statistic (for given degrees of freedom) the more likely there is to be a statistically significant association between the two variables. Chi-square tests are used for medium to large samples (see Figure 4-1). The Fisher’s exact test is used in place of the χ2 when the sample size number is less than 20 or any one cell in the table is less than 5.
Figure 4-1. Formula for chi-square
χ2 =
(0-E)2 E
Where: O = observed frequency E = expected frequency Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
The measure of central tendency most affected by outliers is:
a. Mean
b. Median
c. Mode
d. Range
A Mean
Rationale: Measures of central tendency describe how observations cluster around a middle value and locate only the center of a distribution measure. The methods include mean, median, and mode. The most commonly used parameter is the arithmetic mean (average). The mean of a data set is inaccurate if there are extreme values (outliers) in a data set. Most statistical tests use the mean because it is more amenable to mathematical manipulation than the median or the mode. However, because the mean includes the value of each observation, it is the measurement most affected by outliers (unusually high or low values), especially when the number of observations is small. As the sample size gets very large, outliers are less important. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
The p value in statistical test results indicates:
a. Causation
b. The probability of having committed a Type I error
c. The probability of having committed a Type II error
d. The probability of data being accurate and valid
B The probability of having committed a Type I error
Rationale: A Type I error occurs when one rejects the null hypothesis (H0) when it is true. This is also called a false-positive result (as we incorrectly conclude that the research hypothesis is true when in fact it is not). The p value or calculated probability is the estimated probability of rejecting the null hypothesis of a study question when that hypothesis is true. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
On a normally distributed data set, what percentage of values lies within three standard deviations from the mean?
a. 68.2
b. 95.5
c. 92.4
d. 99.7
D 99.7
Rationale: Standard deviation is a measure of dispersion of the raw scores that reflects the variability in values around the mean. It employs the squared deviations from the mean (variance), which therefore gives added emphasis to larger deviations. The standard deviation indicates how small the variability is (i.e., the spread) among observations. If the variability is small, all the values are close to the mean. If it is large, the values are not close to the mean. The significance of the standard deviation is that with normal (bell-shaped) distributions, the following empirical rules for the normal curve apply: • The interval from one standard deviation below the mean to one standard deviation above the mean contains approximately 68 percent of the measurements. • The interval from two standard deviations below the mean to two standard deviations above the mean contains approximately 95 percent of the measurements. • The interval from three standard deviations below the mean to three standard deviations above the mean contains approximately 99.7 percent (or approximately all) of the measurements. (see Figure 4-2)
Source: Potts A. Use of Statistics in Infection Prevention. In: Grota P, ed. APIC Text of Infection Control and Epidemiology, 4th edition. Washington, DC: Association for Professionals in Infection Control and Epidemiology, 2014. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
Which statistical test is used when the data are small in numbers?
a. Fisher’s exact
b. t test
c. Chi-square
d. z test
A Fisher’s exact
Rationale: Fisher’s exact test is a statistical significance test used in the analysis of contingency tables. Although in practice it is employed when sample sizes are small, it is valid for all sample sizes. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
Statistical process control (SPC) charts are used for all of the following purposes except:
a. Monitor the process of care
b. Facilitate the determination of variation
c. Eliminate natural variation
d. Monitor outcomes
C Eliminate natural variation
Rationale: SPC is a method of quality control that uses statistical methods and is an essential component of quality assurance and performance improvement. The principles of statistical process control are used to monitor both processes and outcomes in a systematic and statistically valid manner. Control charts can assist in determining special-cause or common-cause variations, which may be helpful for early detection of abnormal events. Reference: APIC Text, 4th edition, Chapter 14 – Process Control Charts
Seventy-five patients were admitted to the Medical-Surgical ICU. Forty were on the surgical service and 35 were on the medical service. Fifteen patients developed a healthcare-associated infection with methicillin-resistant Staphylococcus aureus (MRSA). Nine of the patients with MRSA infection were on the surgical service. There were 230 patient days in the ICU for the surgical patients in January, and 325 patient days for medical patients. What was the incidence density of MRSA attack infection for patients on the surgical service?
a. 29 infections per 1,000 patient days
b. 26 infections per 1,000 patient days
c. 19 infections per 100 patient days
d. 39 infections per 1,000 patient days
D 39 infections per 1,000 patient days
Rationale: The incidence rate is the number of new cases per population at risk in a given time period. When the denominator is the sum of the persontime of the at-risk population, it is also known as the incidence density rate or person-time incidence rate. The incidence-density rate for this scenario is 9 (new cases of MRSA) ÷ 230 (total number of patient days) x 1,000 = 39.13 (round to 39) infections per 1,000 patient days. Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
Plague is endemic in parts of the Southwest United States. The word “endemic” means:
a. Natives are immune to plague
b. An expected number of cases occurs each year in a given geographical area
c. Plague has become resistant to all forms of treatment for this population
d. The disease is seen in a seasonal pattern each year for this area
B An expected number of cases occurs each year in a given geographical area
Rationale: The term “endemic” refers to the usual incidence of a given disease within a geographical area during a specified time period. Reference: APIC Text, 4th edition, Chapter 10 – General Principles of Epidemiology
A pandemic differs from an epidemic in that:
a. Only one disease is involved
b. It is usually vectorborne
c. There is a higher mortality rate
d. Several countries or continents are involved
D Several countries or continents are involved
Rationale: The term “pandemic” refers to an epidemic of disease spread over a wide geographical area across countries or continents. Reference: APIC Text, 4th edition, Chapter 10 – General Principles of Epidemiology
Specificity of a test for infection or disease is calculated as:
a. The number of true negatives divided by the
number of positives found, times 100
b. The number of true negatives divided by the total
number of persons with disease, times 100
c. The number of true positives divided by the total
number of persons with disease, times 100
d. The number of true negatives divided by the total
number of persons without disease, times 100
D The number of true negatives divided by the total number of persons without disease, times 100
Rationale: Sensitivity (also called the true positive rate) measures the proportion of actual positives that are correctly identified as such (e.g., the percentage of sick people who are correctly identified as having the condition). Specificity (sometimes called the true negative rate) measures the proportion of negatives that are correctly identified as such (e.g., the percentage of healthy people who are correctly identified as not having the condition). Specificity = True negatives ÷ True negatives + False positives Reference: APIC Text, 4th edition, Chapter 13 – Use of Statistics in Infection Prevention
