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134 Cards in this Set
- Front
- Back
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Role of the HIM department–
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The HIM Department is frequently responsible for compiling, collecting, and organizing data
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Why Study Statistics?
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• Statistical data collection has increased due to the increasing availability of
– computers – statistical software packages • The health care industry is a major collector of data that are compiled daily, weekly, monthly, and yearly |
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One meaning of Statistics -
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• A numerical fact:
– Numerical facts include the number representing data (income, age, etc.) |
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One meaning of Statistics - |
• A field of discipline of study:
– Collecting, organizing, analyzing, presenting, and interpreting numerical data – Educated guesses: decisions made on the basis of scientific methods – Pure guesses: decisions made without the use of scientific methods (may be unreliable) |
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Statistics
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• Reasonable decisions and valid conclusions may be drawn based upon the analysis of statistical data
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Statistics
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• involves both numbers and the techniques and procedures to be followed in collecting, organizing, analyzing, interpreting, and presenting information in a numerical form
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Types of Statistics
• Two main aspects: |
– Theoretical statistics: deals with the development, derivation, and proof of statistical theorems, formulae, rules, and laws – Applied statistics: involves the application of those theorems, formulae, rules, and laws to solve real-world problems |
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What are the 2 areas of Applied Statistics?
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• Descriptive statistics
• Inferential statistics |
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Descriptive Statistics
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– Describes and analyzes a given group without drawing any conclusions or inferences about a larger group
– Describes a population – Deals with data that are enumerated, organized, and possibly graphically represented – Data can be compiled into a table or graph– An example is “the U.S. Census” – All the statistics in this book are descriptive statistics |
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Inferential Statistics
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• Gives information regarding kinds of claims or statements that can be reasonably made about the population based on data from a sample
• Concerned with reaching conclusions • Generalizations about a population are made based on information obtained from a sample • An example is when inferences are made about a population based on opinion polls • This type of statistics is found in more advanced statistical textbooks |
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Data
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• Data is roughly defined as a fact
• A measured or otherwise determined factor proposition, basic facts and observations • Information organized for analytics or used as a basis for a decision • Numerical information • Raw facts and figures that are meaningless in and of themselves |
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Information
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• Meaningful data
• Knowledge resulting from processing data • Data selected, organized, and processed to be useful |
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Data Collection
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• The process by which data are gathered
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Data Processing
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• The preparation of information for processing by computers
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Data Accuracy
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• Data free of identifiable errors
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*Aggregate Data
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• *Data extracted from the individual (health)records and combined to form deidentified information about the (patient) group that can be compared and analyzed
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Research Data
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• Data used for the purpose of testing a hypothesis or answering a proposed question
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Qualitative Variable
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Yield observations that can be categorized according to some characteristic or quality
– Examples: a person’s occupation, marital status, education level, and race |
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Quantitative Variable
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Yield observations that can be measured
– Examples: height, weight, and blood pressure– |
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Quantitative data are subdivided into -
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discrete and continuous data
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*Discrete Data
(Quantitative data) |
• Discrete data• data is expressed as a whole number or integer (a number without a fractional or decimal subdivision)
• Examples: number of children in family and *number of pregnancies, *physician is counting the number of moles on a patient's arm |
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Continuous Data
(Quantitative data) |
• Measurable quantities not restricted to a whole number
• Data that fall into the category of “measured to the nearest” • Data can be measured in fractions or decimals |
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• Data measured in decimal fractions, but recorded to the nearest whole number, are -
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still continuous data
• Examples: height, weight, and age |
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Categorical Data
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• Four types of categorical data:
– Nominal– Ordinal– Interval– Ratio • Represent values or observations that can be sorted into a category • Also referred to as scales of measurement |
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Nominal Data
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• Qualitative data in which a number is assigned to elements within a category
• The data is often coded information (i.e., distinguishing a person’s eye color with a code number, such as #1 for blue eyes, #2 for brown eyes) • Examples: sex, insurance carrier • It is inappropriate to perform arithmetic operations on nominal data • Nominal data is unordered data |
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Ordinal Data (Ranked Data)
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• Data of values or observations that can be ranked or ordered
• Ordinal number represents a specified (or ordered) position in a numbered series • Grouping in “low”, “middle”, or “high” scores • Ranking from “high to low” or “worst to best” • Surveys ranked on a scale from “1 to 5” • Examples:– cancer is the third leading cause of death (3 is the ordinal #) – IQ scores or test scores ranked in some manner • Principal weakness of ordinal scale is that the number separating each score may not be equal |
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Interval Data
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• Represents values or observations that can be measured on an evenly distributed scale beginning at a point other than true zero
• Includes units of equal size beginning at a point other than true zero; there is no zero point • Examples:– temperature measured in Fahrenheit degrees– time (the time between each hour is always 60 minutes) • The most important characteristic is that intervals between values are equal |
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Ratio Data (Ratio Scale)
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• Similar to interval data in that the intervals between successive units are of equal size; however, there is a zero starting point; therefore it can be manipulated mathematically
• Examples: – Age distribution • the difference between 18 and 20 is exactly the same number as between 65 and 67—2 years • There is a zero point, in that, zero means unborn • Also a person 75 years old is three times as old as a 25-year-old |
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Ungrouped Data (Raw Data)
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• Recorded scores as they are obtained
• Refers to a distribution in which scores are ranked from “highest to lowest”, or“lowest to highest”, but each score has its own place in the array |
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Grouped Data (Aggregate Data)
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• Involves some type of grouping or combining of scores
• Most common method of grouping is by counting or tallying like scores • All identical scores are tallied and the number recorded after the score • Example: – If 50 students took the same exam and 8 received the same score of 92, then a tally of 8 would be placed after the score of 92 |
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Population
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• Refers to an entire group
• A set of persons (or objects) having a common observable characteristic • Examples: – U.S. Census conducts a population census – A hospital consists of a specific population (a group of patients admitted for purposes of receiving medical treatment and care) |
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Sample
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• A subset or small part of a population
• Information obtained from a sample is often used to generalize from it to the entire population • Example: a transcription supervisor lacks the time to check the accuracy of every report transcribed by every transcriptionist; therefore a sample is taken and the accuracy and quality of work is based on this sample |
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*Cross-Section Data
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• *Contains information on different elements of a population or sample for the same period of time
– Example: incomes of 200 patients recorded for 2010 |
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Time-Series Data
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• Contains information on the same element for different periods of time
– Example: information on U.S. exports in the past 10 years |
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Primary Data Source
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• The major primary patient data source is found in the the patient health record
– All the facts and data regarding a patient’s care are entered at the point of care |
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Secondary Data Source
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• Abstracted information taken from the health record and recorded into another document
– Examples: list, register, index, and data abstracted from websites |
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Representative Sample
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• A sample that represents the characteristics of the population as closely as possible
• Example: to find the average income of families living in Las Vegas, the sample must contain families who belong to different income groups in almost the same proportion as they exist in the population |
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Random Sample
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• A sample drawn in such a way that each element of the population has a chance of being selected
• One way to select a random sample is by lottery or draw (every fifth person or randomly pulling 50 names) |
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Constant
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• Something that assumes only one value
• It is a value that is replaceable by one and only one number, a fixed value • That which does not change and has only one value • When constants are expressed as symbols, they are generally represented by the letters at the beginning of the alphabet (a, b, c) • Example: date of birth |
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Variable
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• Something that can change, in contrast to a constant which remains the same
• Often represented by the letters at the end of the alphabet (X, x, Y, y) • “N” is commonly used to represent the number of cases in the distribution • Often desirable to compare variables and determine the relationship between them • Example: compare age with occupation |
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Demographic Variable
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• Study of characteristics of human population
• Include the size of a population and how it changes over time, the composition of the population (such as age, sex, ethnicity), and geographic density • Invaluable to CEO's to analyze the healthcare service needs of their communities and service areas |
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*Vital Statistics
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• Refers to data that record significant events and *dates in human events
• Vital statistics include *births, deaths, marriages, and divorces • Vitals statistics also includes morbidity (disease) data |
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• Morbidity (disease)
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– Refers to disease statistics and are gathered to provide data on the prevalence of disease
– Far more difficult to gather than mortality (death) data due to the lack of an adequate universal state and national reporting system |
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• Mortality (death)
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– Refers to death statistics
– Death certificate identifies the state in which the death occurred |
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Sources of Health Care Data
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• Primary data
– Patient health record • Secondary data – Abstracted information from patient records and recorded in other documents |
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Uses of Data
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• Management decisions
• Accountability and statistical reports • Research • Determining trends |
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Requestors of Health Care Data
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• Administration and Governing Board
• Medical staff • Other treatment facilities • Outside agencies and organizations • Insurers/payers • Researchers |
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Uses of Data
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• Management decisions
– * Medical Services – *Facilities and equipment – Staffing – Quality assessment/improvement – Efficiency and setting standards – Employee assessment • Patient care decisions – Reducing hospital-acquired infections – Reducing medication errors – Evaluating length of stay for a specific diagnosis |
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Data Use
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• Accountability and statistical reports
– Health care facilities must be accountable to state and federal licensing agencies, as well as third-party payers • Research – Improve treatment protocols • Determining trends – Health care providers are increasingly rated by outside agencies -news outlet report the best hospitals in America |
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*Users of Health Care Data
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• Internal users
– Healthcare facilities and caregivers – Management – Researchers • *External users – Licensing and accrediting agencies – Government – Insurers/third-party payers |
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Major Health Care Collection Entities
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• Governmental data collection (public health)
– National public heath data collection • National Center for Health Statistics (NCHS) • Department of Health and Human Services (DHHS) • Centers for Disease Control and Prevention (CDC) – State data collection – Local data collection |
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Major Health Care Collection Entities
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• Patient data collection
– Demographic and non-medical information – Counts – Test results – Diagnoses/procedures – Treatment outcomes and assessments |
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Abbreviations
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• Health care facilities routinely use abbreviations for efficiency
– Patient care – Statistical – Clinical units – Nonofficial and non universal |
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Descriptive Statistics
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Data that describe a population (group) without drawing conclusions about a larger group.
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Discrete Data
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Data that represent distinct values or observations and contain only finite numbers.
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Interval Data
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Data (observations) that can be measured on an evenly distributed scale.
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Morbidity
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Refers to disease (illness, injury, or an abnormal condition).
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Mortality
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Refers to death (incidence of death).
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Nominal Data
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Data values or observations that can be labeled or named and where values fall into unordered categories; also called dichotomous data.
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Ordinal Data
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Data (values or observations) that are ranked or ordered.
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Population
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An entire group under consideration from which a sample can be taken.
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Qualitative Variable
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An observation or value that can be characterized according to some characteristic or quality.
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Quantitative Data
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An observation or value that yields observations that can be measured. It includes discrete and continuous data.
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Ranked Data
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Observations that ranked high to low, with a number assigned to the placement in the sequence
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statistics
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the mathematics fo the collection, organization, and interpretation of numerical data
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data
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information, especially information organizaed for analysis or used as the basis for a decision; numerical information
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demography
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...include a patient's name, social security number, date of birth, occupation etc.
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vital statistics
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...data related to births, marriages, divorces, and deaths
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population
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...an entire group under consideration from which a sample can be taken
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sample
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...subset of a population
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variable
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...something that can change
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*constant
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*...something that assumes only one value and remains the same
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qualitative data
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...observations that can be cateagorized according to some characteristic or quality. examples of this type include a person's occupation, marital status, education level, race
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quantitative data
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...observations that can be measured. exam[ples of this type are height, weight, blood pressure, serum cholesterol, heart rate
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ungrouped data
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a listing of all scores as they are obtained. and refer to a distribution in which scores are ranked from highest to lowest, or lowest to highest, but each score has its own place in the array.
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grouped data
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involve some type of grouping or combing of scores.
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descriptive statistics
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describe and analyze a given group without drawing any conclusions or inferences about a larger group
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inferential statistics
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give information regarding kinds of claims or statements that can be reasonably made about the population based on data from a sample and are concerned with reaching conclusion
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nominal data
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pertains to "name"and are unordered data
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ordinal data
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refers to "order' or rank" and represents a specified (or ordered) position in a numbered series,
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discrete data
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always expressed as a whole number or integer.
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continuous data
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variables that fall into the category of "measured to the nearest"
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morbidity
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refers to disease (illness, injury, or an abnormal condition)
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mortality
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refers to death (incidence of death)
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what is statistics?
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the mathematics of the collection, organization, and interpretation of numerical data
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what is data?
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information, raw facts
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what is benchmarking?
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the process of comparing the performance of an organization to a standard of another like group
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what is primary data?
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the patient record
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what is the secondary source?
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from abstracted information, such as an index, register..
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what are demographics?
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information about a patient; such as name, social security number, occupation, consents... all nonmedical information
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what is population?
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refers to an entire group
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what is a sample?
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a small subset or part of a population
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*what is a constant?
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something that is permanent, and only has one value and does not change, like a *date of birth, represented by A,B,C,D sometimes..
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what is a variable?
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something that can change, like one's age, occupation,, represented by N
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what is a qualitative variable?
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some characteristic like a person's occupation, marital status, education level, race...
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*benchmark
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*process of comparing the performance of an organization to a standard
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what is a quantitative variable?
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Measurable things about a person, such as height, weight, blood tests..
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what is nominal data?
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identifiers of a person... like a name, phone number, zip code, driver's license, credit card number, can also be the number assigned to something like eye color.. 1 for blue, 2 for green, etc...
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what is ordinal data?
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refers to order or rank in a series..
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what is discrete data?
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whole numbers that wont change, like number of teeth, bones, pregnancies..
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what is continuous data?
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data that numbers can go on and on... like pi– 3.1415....numbers that can change like height weight, miles to work, etc...
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what is ungrouped data?
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listed as it comes
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what is grouped data?
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some type of combining of scores into little groups like school kids into grades
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*CDC
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*an entity is concerned with health promotion and prevention of diseases
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what is descriptive statistics?
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data given without any conclusions about what i means.. like a table or graph..
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what is inferential statistics?
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information given that conclusions can be drawn on it... like an opinion poll...
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what is morbidity?
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prevalence of disease
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what is mortality?
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death statistics
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what is vital statistics?
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data to record significant events in life
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*HIM professional, specific to statistical data, may :
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*collect data
*define the data elements *present the data |
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Descriptive Statistics
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Data that describe a population (group) without drawing conclusions about a larger group.
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Nominal Data
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Data values or observations that can be labeled or named and where values fall into unordered categories; also called dichotomous data.
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Discrete Data
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Data that represent distinct values or observations and contain only finite numbers.
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Interval Data
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Data (observations) that can be measured on an evenly distributed scale.
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*DIS or DC is:
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*Discharge
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Morbidity
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Refers to disease (illness, injury, or an abnormal condition).
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Mortality
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Refers to death (incidence of death).
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*U. S. census carried out by the U.S. government is an example of:
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*descriptive statistics
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Ordinal Data
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Data (values or observations) that are ranked or ordered.
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Population
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An entire group under consideration from which a sample can be taken.
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Qualitative Variable
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An observation or value that can be characterized according to some characteristic or quality.
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Quantitative Data
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An observation or value that yields observations that can be measured. It includes discrete and continuous data.
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Ranked Data
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Observations that ranked high to low, with a number assigned to the placement in the sequence
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*Financial data, medical service data, and staffing data are best defined as what type of data
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*Management statistical data
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*The coding supervisor plans to audit 10% of the total charts coded in the past quarter. In this example, the charts the supervisor plans to review is the ____________.
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*sample
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*tentative diagnosis aka
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*provisional diagnosis
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*Example ofdemographic information
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*Patient's date of birth
*Patient's date of admission |
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*When patients are admitted to the hospital they are assigned what kind of diagnosis
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*admitting or provisional
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*major primary data source
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*patient's medical record
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*examples of demographic data
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*Consents
*Date of surgical procedure *Date of admission |
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*data
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*defined as "information, especially when organized for analysis or used as the basis for a decision."
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*types of dispositions that are recorded when a patient is discharged from the hospital
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*D/C to home
*Transferred to nursing home *Expired or died |
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*A&D
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*a patient who was both admitted and discharged the same day
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*data that gathers data on the prevalence of disease
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*Morbidity
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