TEST 1 Flashcards

1
Q

Anything that is dates, numbers, images, symbols, letters, words, anything that represents basic facts and observations that go into the EHR about the people, processes, measurements, and conditions

A

Data

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2
Q

What is the data that is collected?

A
  1. Number of Diagnostic Tests
  2. Services Provided – by admissions
  3. Costs and Payment
  4. Diagnosis and Procedure codes
  5. Number of procedures preformed
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3
Q

Task of transforming, summarizing, or modeling data to allow the end user to make meaningful conclusions – uses data to make decisions

A

Data Analysis

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4
Q

The use of data for its primary purpose

EX: Billing and claims data’s primary use it to determine services rendered and payment to from a patient or third party payer

Performing an analysis of typical payment received from a payer for emergency visits

information collected for the specific purpose at hand
Example: checking glucose level to see if patient has diabetes

A

Primary Data

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5
Q

The use of data beyond its primary purpose

EX: ICD-9 diagnosis codes are assigned to a patient to record diseases present or discovered during an encounter

Using a profile of the most common ICD-9 diagnosis categories for the purposes of determining the patient load by service line

data previously collected for any purpose other than the one at hand
example: checking glucose post op

A

Secondary Data

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6
Q

Summarize or describes a given data set, which can be either a representation of the entire population or a sample of a population. Broken down into measures of central tendency and measures of variability (spread).

Uses mean, median, and mode – measures of central tendency

o Characterizes the distribution of the data
o Estimates the center or ‘typical’ value
o Measures the spread or variation in the data

EX: Graphs and Charts

A

Descriptive Statistics

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7
Q

very high error rate

o Using sample data to make conclusions or decisions regarding a population
o Not practical to observe the entire population
o Often accompanied with a probability of making an incorrect decision based on the sample

allows you to make predictions (“inferences”) from that data.
you take data from samples and make generalizations about a population.

EX: Hypothesis Tests

A

Inferential Statistics

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8
Q

Elements that are stored in fields specifically designed for that data element. Concrete data that uses a drop box or you can key in to complete the entire field.

EX: Gender or date of admissions, ETC

Typically have a set of valid values or a range of acceptable values to ensure data integrity.

A

Structured Data

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9
Q

Free-form text data that is captured in a narrative form and Not designed for database querying based on the field values.

EX: Progress notes, radiology reports, all narrative reports, etc

Queries can be complied to search for key words but will not be nearly as reliable as querying a structured data element

A

Unstructured Data

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10
Q
  • Not naturally numeric
  • Evaluates Observations
  • Assesses the quality of the object or encounter
  • Commonly unstructured
  • Can recategorize it and put it in the number form
A

Qualitative Analysis

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11
Q

What are the 2 Ways Qualitative Data can be categorized?

A

Nominal and Ordinal

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12
Q

Categories without a natural order

EXAMPLES
• Diagnosis codes
• Clinical units
• Colors

A

Nominal

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13
Q

Categories with a natural order

EXAMPLES
• Patient satisfaction surveys
• Patient severity scores
• Evaluation and management code levels

A

Ordinal

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14
Q

Naturally numeric. You can use this to confirm qualitative data

A

Quantitative Analysis

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15
Q

What are the 2 Forms of Quantitative Data analysis?

A

Interval and Ratio

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16
Q

Numeric values where the distance between two values has meaning, but there is no true zero and the interpretation is not preserved when multiplying/dividing

EX: Temperature and Dates

A

Interval

17
Q

Numeric values where zero has meaning and multiplying/dividing values has meaning

EXAMPLE

  • Length of stay
  • Age
  • Weight
A

Ratio

18
Q

__________ data will be either Discrete –OR – Continuous

A

Quantitative

19
Q

Includes a finite number of values.

Example: One admission…you cannot have a half of an admission.

A

Discrete data

20
Q

Can take on fractional and whole number values.

Example: Charges can be in fractions of a dollar amount (50 cents)

A

Continuous data

21
Q

Includes evaluating the quality and adequacy of the documentation of a medical record.

A

Qualitative analysis

22
Q

Examines the accuracy and completeness of the contents of the medical record.

A

Quantitative analysis

23
Q

_______ = average

A

Mean

24
Q

______ = Midpoint or middle number

A

Median

25
Q

______ = The most frequently occurring score(s) in a distribution

A

Mode

26
Q

A range calculated based on a sample that is likely to include the true population value of a parameter.

EX: A patient satisfaction survey result of 90 percent plus or minus two percentage points. (88 percent to 92)

A

Confidence Interval

27
Q

Used to uncover patterns in data

Typically a secondary use of data

Primarily graphical analysis (plots, trends, etc.)

A

Exploratory Data Analysis (EDA)

28
Q

Also looking for patterns in data

Adds in descriptive statistics and more formal statistical techniques

May be used for benchmarking and determining high/lower performers

May also be used to improve financial performance

Used to identify the potentially best predictors

A

Data Mining

29
Q

Historical data is used to build models to determine most likely outcome in future

Examples
Used by CMS for pre-payment reviews to fight fraud
Used by credit card companies to prevent fraud
Used by providers to identify missed charges

Historical payment data can be used to identify potentially fraudulent claims such as a facility submitting a claim for an appendectomy when the patient has already had an appendectomy claim paid.

A

Predictive Modeling

30
Q

Used to formulate models that determine the most likely outcome in predictive modeling

A

Statistical models

31
Q

Random sample of records.

Sample size is based on the desired precision and confidence of the estimate and the sampling technique.

A

Auditing

32
Q

What are the 2 audit sample techniques?

A

Internal and external audits

33
Q

Compliance Charge Audits

A

Internal Audits

34
Q

Example: Recovery Audit Contractors (RAC)

A

External Audits

35
Q

_________= the difference between the highest and lowest scores in a distribution

A

RANGE

36
Q

“typical value” descriptive statistic example:

A

Mean, Median, Mode

37
Q

descriptive statistic variance example:

A

range and standard deviation