©2010 Jones and Bartlett Publishers Healthcare Statistics, Research and Epidemiology

©2010 Jones and Bartlett Publishers Healthcare Statistics

©2010 Jones and Bartlett Publishers Define Statistics The overall science of extracting information from a group of data and using the information to make inference about that larger group of data. The study of variation Descriptive Statistics –Statistical data collected concerning the attributes of a population Inferential Statistics –Statistical data collected from a sample to make inference about the population from which the sample is extracted

©2010 Jones and Bartlett Publishers Importance of Maintaining Healthcare Statistics Strategic planning To compare past with current performance indicators For accreditation compliance Healthcare Agencies

©2010 Jones and Bartlett Publishers HIM role in Healthcare Statistics Decide if health information collected meets statistical needs of health care facility Be aware or sources of data within the facility Be prepared to merge other data with data from the health record Collect quality health data Organize data into databases Statistically analyze collected data Develop, generate and interpret health care statistical reports

©2010 Jones and Bartlett Publishers Definitions Census –Number of patients present at any given time Daily Inpatient Census –Number of patients present at the official census taking time (usually 12 midnight) each day plus the number of patients admitted and discharged the same day Inpatient Service Day –Unit of measure denoting the services received by one inpatient in one 24 hour period Total Inpatient Service Days –Sum of all inpatient service days for each of the days in the period under consideration

©2010 Jones and Bartlett Publishers Definitions Length of Stay –The number of calendar days from admission to discharge Total Length of Stay –The sum of days stay of any group of inpatients discharged during a specific period of time Inpatient Bed Count –The number of available facility inpatient beds both occupied and vacant on a given day Inpatient Bed Count Day –The unit of measure denoting the presence of one inpatient bed either occupied or vacant set up and staffed for use in one 24 hour period

©2010 Jones and Bartlett Publishers Definitions Hospital Inpatient Autopsy –The postmortem examination performed in a hospital facility (performed by a pathologist or other responsible physician) on the body of a patient who died during inpatient hospitalization Hospital Autopsy –The postmortem examination, wherever performed (by a pathologist or responsible physician) of the body of a person who has at some time been a hospital patient Nosocomial Infection –Those acquired during hospitalization Inpatient Discharge Analysis –Health record information is reviewed to determine types of services provided, length of stay, discharge status and other data to assist in calculating hospital performance indicators.

©2010 Jones and Bartlett Publishers Definitions Vital Statistics –Crucial events in life such as births, deaths, adoptions, marriages and divorces –National Center for Health Statistics (NCHS) recommends standard forms which most states adopt to develop birth, death and fetal death certificates Estimate –Any statistic calculated on a sample of observations Sampling error –The principle that the characteristics of a sample are not identical to the characteristics of the population from which the sample is drawn

©2010 Jones and Bartlett Publishers Definitions Population –Any defined aggregate of objects, persons or events (sum total) –The variables used as the basis for classification or measurement being specified Parameter –Statistic calculated on a population value Sample –Any sub-aggregate drawn from the population –A small group that observed that is drawn from the population in order to make inference back to the population from which it was drawn

©2010 Jones and Bartlett Publishers Common Hospital Services Internal Medical Surgery Obstetrics and Gynecology Neonatal Anesthesiology Pediatrics Radiology Diagnostic imaging Neurology Psychiatry Pathology

©2010 Jones and Bartlett Publishers Presentation of Data Data should be presented in such a manner which catches the reader’s attention, encourages interest and makes data easy to interpret and use

©2010 Jones and Bartlett Publishers Tables Columns of figures, each labeled to identify contents Include title, date, and person who prepared table Include narrative explanation of what table depicts

©2010 Jones and Bartlett Publishers Graphs Horizontal axis (independent variable) Vertical axis (dependent variable) Types of Graphs –Bar Used to report count values of categorical data

©2010 Jones and Bartlett Publishers Histogram Graphic representations of frequency distributions

©2010 Jones and Bartlett Publishers Line Used to provide a simple visual method of monitoring trends over time

©2010 Jones and Bartlett Publishers Pie Chart Displays frequencies in each category

©2010 Jones and Bartlett Publishers Pareto Chart Type of bar graph which displays categories of data in descending order of frequency or significance

©2010 Jones and Bartlett Publishers Scatter diagram Used to plot the points for two variables that may be related to each other

©2010 Jones and Bartlett Publishers Frequency polygon Similar to a histogram Graph of a frequency distribution in line form rather than a bar graph

©2010 Jones and Bartlett Publishers Ratios, Proportions, and Rates General formula for calculating Ratios, Proportions and Rates: Ratio, proportion, rate = x/y x 10n

©2010 Jones and Bartlett Publishers Ratios, Proportions, and Rates (cont.) Ratios –The quantities being compared may be expressed so that x and y are completely independent of each other, or x may be included in y Proportions –A type of ratio in which x is a portion of the whole (x + y) –The numerator is always included in the denominator Rates –Used to measure events over a period of time

©2010 Jones and Bartlett Publishers Measures of Central Tendency Mean –Average calculated by adding the values of all observations and dividing the total by the number of observations Median –Middle most value when values are ranked in numeric order Mode –Value that occurs most frequently –When no value repeats more than once, there is no mode –When several values repeat with the same frequency, each is the mode

©2010 Jones and Bartlett Publishers Measures of Variability Measures of Dispersion, the amount of variability of the measurement around the mean or median. The degree to which numerical data tend to be spread about an average value

©2010 Jones and Bartlett Publishers Measures of Variability Range –The difference between the highest and lowest values Variance –Demonstrate how values are spread or dispersed around the mean –Computed by squaring each deviation from the mean, summing them and then dividing their sum by the degrees of freedom (n-1) Standard Deviation –Demonstrate how values are spread or dispersed around the mean –The most common measure of variation –The square root of the variance –Small standard deviation demonstrates data are close to mean and a large standard deviation means data are more spread out from the mean –Example: December discharges for Houston Hospital had a mean of 6 days and a standard deviation of 2. Therefore, if a patient stayed in the hospital one standard deviation above the mean, he had a length of stay of 8 days (6 + 2 = 8). If a patient had a length of stay of 2 days, then he was in the hospital 2 standard deviations below the mean (6 – 2 – 2 = 4)

©2010 Jones and Bartlett Publishers Normal Distribution Measures of central tendency and variation are interpreted as they relate to the normal distribution Theoretical family of distributions that may have any mean or any standard deviation A bell-shaped curve (also referred to as “Normal Curve”) that is symmetrical about the mean –50% of observations fall above the mean and 50% fall below the mean –Each side of the mean extends to a tail When the research hypothesis is directed to only one end of the curve, it is considered a one-tailed test When the research hypothesis is directed to both ends of the curve, it is considered a two- tailed test

©2010 Jones and Bartlett Publishers Normal Curve Mean Median Mode = 0

©2010 Jones and Bartlett Publishers Hospital Performance Indicators Number of Admissions and Discharges Average Daily Census Average Length of Stay Occupancy rate Mortality rates Autopsy rate Infection rates Consultation rate Other indicators of hospital performance is requested or required

©2010 Jones and Bartlett Publishers Average Daily Census (formula) Total inpatient service days for a period (excluding newborn) Total number of days in period

©2010 Jones and Bartlett Publishers Average Daily Census (calculated) 4, = = 146

©2010 Jones and Bartlett Publishers Average Length of Stay (formula) Total length of stay or discharge days (excluding newborns) Total discharges

©2010 Jones and Bartlett Publishers Average LOS (calculated) = = 1.6

©2010 Jones and Bartlett Publishers Occupancy rate (formula) Total inpatient service days for a period x Total inpatient bed count days in period under consideration (beds x days)

©2010 Jones and Bartlett Publishers Occupancy rate (calculated) x 100 = 301 x % June, 200x

©2010 Jones and Bartlett Publishers Death rate (formula) Total # deaths (including newborns) for a period x Total # discharges (including deaths) Also referred to as Gross Death Rate

©2010 Jones and Bartlett Publishers Death rate (calculated) (7 + 3) x = 1.29% # admissions 685 # discharges 688 # deaths 7 # newborn discharges 90 #newborn deaths 3

©2010 Jones and Bartlett Publishers Post-Operative Death rate (formula) Number of post-op deaths for a period x Number of patients operated upon

©2010 Jones and Bartlett Publishers Post-op Death rate (calculated) 2 x , ,523 =.02% # patients operated upon 10,111 # newborn pts operated upon 1,523 # adult/children deaths 41 # newborn deaths 2 # deaths within 10 days post-op 2

©2010 Jones and Bartlett Publishers Fetal Death rate (formula) Number of intermediate and late fetal deaths for a period x Total number of live births + intermediate and late fetal deaths for the period

©2010 Jones and Bartlett Publishers Fetal Death rate (calculated) (2 + 4) x = 4.58% During January, 200x, Houston hospital had 125 live births, 2 intermediate fetal death, and 4 late fetal deaths. What was the fetal death rate for January?

©2010 Jones and Bartlett Publishers Maternal Death rate (formula) Number of direct maternal deaths for a period x Number of OB discharges (including deaths) for the period

©2010 Jones and Bartlett Publishers Maternal Death rate (calculated) 3 x =.21% During March, 200x, there were 3 maternal deaths following c-sections. In addition, 5 patients had abortions. The OB unit admitted 1405 patients and discharged 1411 patients. What was the maternal death rate for the hospital?

©2010 Jones and Bartlett Publishers Gross Autopsy rate (formula) Total inpatient autopsies for a period x Total inpatient deaths for the period

©2010 Jones and Bartlett Publishers Gross Autopsy rate (calculated) 10 x = 32.26% During December, 200x, there were 1001 discharges, 31 deaths (including newborns), and 10 autopsies. What was the gross autopsy rate?

©2010 Jones and Bartlett Publishers Net Autopsy rate Total inpatient autopsies x Total inpatient deaths – unautopsied coroners’ or medical examiners’ cases

©2010 Jones and Bartlett Publishers Net Autopsy rate (calculated) 5 x = 71.43% During April 200x, there were 559 discharges, 10 inpatient deaths and 5 autopsies. Three (3) deaths were unavailable for autopsy because they were released to the coroner. What was the Net Autopsy Rate for the month?

©2010 Jones and Bartlett Publishers Adjusted Hospital Autopsy rate (formula) Total hospital autopsies x Total number of deaths of hospital patients whose bodies are available for hospital autopsy

©2010 Jones and Bartlett Publishers Adjusted Hospital Autopsy rate (calculated) 5 x = 16.13% During September 200x, 36 inpatient deaths occurred. Two (2) outpatients died and their bodies were brought to the hospital. Among these, 4 deaths were reported to the coroner, 3 were transferred to another city therefore no autopsy was performed, and 5 hospital autopsies were performed. What was the Adjusted Hospital Autopsy Rate?

©2010 Jones and Bartlett Publishers Post-operative Infection rate Number of infections in clean surgical cases for a period x Number of surgical operation for the period

©2010 Jones and Bartlett Publishers Post-Op Infection rate (calculated) 3 X =.37% During August 200x, 802 surgical operations were performed. The infection control committee reported 3 post-operative infections in clean surgical cases. What was the Post-Operative Infection Rate?

©2010 Jones and Bartlett Publishers Calculating Any Percentage What you actually have x 100 What you could have had

©2010 Jones and Bartlett Publishers Calculate Retrieval Rate x = 96.2% Clerk retrieved 153 of the 159 charts requested by the pulmonary clinic. What was the retrieval rate?

©2010 Jones and Bartlett Publishers Research

©2010 Jones and Bartlett Publishers Research Scientific inquiry or question to make improvements; to increase the body of knowledge. May be applied of basic. Applied Research –Improvement of actual practice Basic –Theory building

©2010 Jones and Bartlett Publishers Research Terms Independent variable –The variable to be manipulated –Also called the experimental or treatment variable Dependent variable –The variable that is measured to determine the effects of the experimental treatment –Also referred to as the control

©2010 Jones and Bartlett Publishers Research Terms (cont.) Reliability –Accuracy of the data in the sense of its ability to be reproduced or its ability to yield the same results on repeated trials Validity –Degree to which an instrument measures what it should measure –Assesses relevance, completeness, accuracy and correctness

©2010 Jones and Bartlett Publishers Types of Samples Random sample –Every member of the population has an equal probability of being included –Example: 15 names place in a hat to draw out 10 names Cluster sample –Random selection of a number of subjects in naturally occurring groups or clusters –A unit chosen is not an individual but a group of individuals who are naturally together –Example: Mailing zip code

©2010 Jones and Bartlett Publishers Types of Samples (cont.) Stratified sample –Sampling of a population which consists of a number of subgroups or strata that may differ in characteristics being studied –Example: Ethnic groups Systematic sample –Drawing a sample by taking every nth from a list of the population –Example: List of 100 names, select every 10th person's name on list

©2010 Jones and Bartlett Publishers Scientific Method Define the problem (Statement of the Problem) –Determine population under study Review the literature Formulate a hypothesis –Define the null and alternative hypotheses –State the independent and dependent variables

©2010 Jones and Bartlett Publishers Scientific Method (cont.) Select a research method or design –Experimental –Observational study –Surveys and Questionnaires –Interviews –Historical-prospective –Participant observation –Cross-sectional or Prevalence Study –Cohort study –Case Control

©2010 Jones and Bartlett Publishers Scientific Method (cont.) Collect the data from sample abstracted from population Analyze the results –Test of significance (t-test, chi-square, ANOVA, etc) –Compare computed result of p-value to alpha level or compare test statistic to critical value –Accept or reject null hypothesis Draw conclusions

©2010 Jones and Bartlett Publishers Test of Significance Purpose is to determine whether observed differences between groups or relationships between variables in the sample being studied are likely to be due to sampling error or are likely to reflect true differences or relationships in the population of interest The method utilized to test the null and alternative hypotheses and to determine whether or not to accept or reject the null hypothesis

©2010 Jones and Bartlett Publishers Test of Significance (cont.) Hypothesis –Identifies the goal of the research and poses a tentative assumption to be tested –Indicates the nature of the difference or relationship that is being tested Null Hypothesis (symbolized as Ho) –States there is no difference or relationship in the population under study Alternative Hypothesis –States there is a difference or relationship in the population under study

©2010 Jones and Bartlett Publishers Commonly Methods to test Null Hypothesis T-test –Determines if there is a significant difference between two groups with respect to the independent and dependent variables –Independent variable –The variable to be manipulated –Also called the experimental or treatment variable –Dependent variable –The variable that is measured to determine the effects of the experimental treatment –Also referred to as the control

©2010 Jones and Bartlett Publishers Commonly Methods to test Null Hypothesis (cont.) Chi-square –Determines if there is a significant difference between observed and expected frequencies –Used for nominal data Pearson Correlation Coefficient –Expressed as “r” –Ranges from 0 to ± 1 –Used to assess the direction and degree of relationship between two variables –As r approaches 0 there tends to be less correlation between the variables; as r approaches 1, there tends to be more correlation –Coefficient of determination –r-squared (symbolized by r2) –Tells how much of the variation in y is accounted for by the x variable –If r =.80 then r2 =.64 and 64% of variation in y is accounted for the x variable

©2010 Jones and Bartlett Publishers Commonly Methods to test Null Hypothesis (cont.) Regression Analysis –Determines the extent one or more explanatory variables can predict an outcome variable –Coefficient of determination (r2) –Ranges from 0 to 1 –Represents the squared correlation between the explanatory variable(s) and the outcome variable –The value of r2 indicates the proportion of variability in the outcome that is explained by the predictor variable(s) –The closer r2 is to one, the stronger the prediction –P value associated with r2 indicates the probability that the observed value of r2 could occur through sampling error alone

©2010 Jones and Bartlett Publishers Commonly Methods to test Null Hypothesis (cont.) ANOVA –Analysis of Variance –Determines if there is a significant difference between two or more groups

©2010 Jones and Bartlett Publishers Test Statistic or t-stat The absolute value of the t-stat is compared to the critical value. If the t-stat is greater than the critical value, then the researcher will reject the null hypothesis. –Measures the size of the difference or relationship observed in the sample. –The probability that the observed value of the test statistic could occur in the event that the null hypothesis is true is determined. This is called the p-value, which ranges from 0 to 1. P-value answers the question: how likely is it that the observed difference or relationship is due to chance or due to sampling error? As the p-value approaches 0, the smaller the probability that the observed difference or relationship is due to chance or sampling error.

©2010 Jones and Bartlett Publishers Level of Significance Also referred to as alpha level and symbolized by the Greek letter ά P-value is compared to level of significance to determine whether to accept or reject the null hypothesis. If the p-value is less than the alpha level, then the researcher will reject the null hypothesis.

©2010 Jones and Bartlett Publishers Common Levels of Significance.05 means the decision will be to reject the null hypothesis if the probability is smaller than 5 in 100 that the observed difference or relationship could be due to sampling error. Setting it at.01 means the decision to reject will be made if the probability is smaller than 1 in 100.

©2010 Jones and Bartlett Publishers Test of Significance Errors Type I error –Rejecting the null hypothesis when it is true Type II error –Accepting the null hypothesis when it is false

©2010 Jones and Bartlett Publishers Epidemiology

©2010 Jones and Bartlett Publishers Epidemiology The study of disease and the determinants of disease in populations The study of clinical and health care trend or patterns and the ability to recognize trends or patterns with large amounts of data The study of the distribution and determinants of diseases and injuries in human populations

©2010 Jones and Bartlett Publishers Common Epidemiological Terms Health –State of complete physical, mental and social well being and not merely the absence of disease Levels of prevention –Primary – prevention by reducing exposure –Secondary – early detection and treatment –Tertiary – alleviation of disability resulting from disease Rehabilitation –Attempt to restore an affected individual to a useful, satisfying and self-sufficient role in society

©2010 Jones and Bartlett Publishers Common Epidemiological Terms Risk Factor –Associated with an increased likelihood that the disease will develop at a later time Cohort –A group under study for a period of time Epidemic –The occurrence in a community or region of a group of illnesses of similar nature, clearly in excess of normal expectancy Endemic –Occurrence that is the habitual presence of a disease or infectious agent within a geographical area or the usual prevalence of a given disease within such area

©2010 Jones and Bartlett Publishers Common Epidemiological Terms Prevalence Rate (PR) –The number of existing cases of a disease in a specified time period divided by the population at that time –Describes the magnitude of an epidemic Incident rate (IR) –The number of newly reported cases of a disease in a specified time period divided by the population at that time –Used to compare the frequency of disease in populations Relative risk (RR) –Used to determine which groups have a greater risk of developing the disease under study

©2010 Jones and Bartlett Publishers Epidemiological Research Descriptive Cross Sectional Prevalence Study –Concurrently describes or examines the distribution of disease or characteristics and health outcomes at one specific point or period in time –Used when little is known about the disease or characteristic under study –Used to generate hypotheses, not to test them Case-Control or Retrospective –Analytical study design in which a disease or health condition is examined to determine possible causes –Researcher collects data on disease and controls by looking back in time

©2010 Jones and Bartlett Publishers Epidemiological Research (cont.) Prospective –Determines whether the characteristics or suspected risk factors preceded the disease or health condition Cohort –Prospective study –Subjects are separated into two groups based upon their exposures or health characteristics and then followed forward to determine whether they develop the disease

©2010 Jones and Bartlett Publishers Epidemiological Research (cont.) Historical Prospective –Past records are used to collect information regarding the exposure characteristics or risk factors under study Experimental Studies for Clinical and Community Trials –Modifies the health characteristics that are found to cause the disease by using health care interventions that control progression of the disease or prevent the disease from occurring