Health Care Data And Sas / Edition 1

Health Care Data And Sas / Edition 1

by Marge Scerbo, Alan C. Wilson, Craig Dickstein
     
 

ISBN-10: 1580258654

ISBN-13: 9781580258654

Pub. Date: 03/15/2001

Publisher: SAS Institute Inc.

Finally! A book that draws together tried-and-true techniques for using SAS to work with health care data. New and experienced SAS programmers and analysts working in health care data analysis will find Health Care Data and SAS invaluable in their daily professional lives. Health care data can be diverse and complicated. With this book, you will learn how to use

Overview

Finally! A book that draws together tried-and-true techniques for using SAS to work with health care data. New and experienced SAS programmers and analysts working in health care data analysis will find Health Care Data and SAS invaluable in their daily professional lives. Health care data can be diverse and complicated. With this book, you will learn how to use SAS to access the information within the data. A terrific primer for new health care analysts and a reference for long-time practitioners, this book, written by Marge Scerbo, Craig Dickstein, and Alan Wilson, defines the types of health care data and explores a wide range of tasks, including reading, validating, and manipulating the data, and producing reports. The combination of basic information and tricks of the trade make this a must-have resource for health care programmers and analysts.

Product Details

ISBN-13:
9781580258654
Publisher:
SAS Institute Inc.
Publication date:
03/15/2001
Edition description:
New Edition
Pages:
288
Product dimensions:
7.50(w) x 9.25(h) x 0.60(d)

Table of Contents

Prefacexi
Acknowledgmentsxiii
Chapter 1Health Care Data
Introduction1
People and Health Care2
Recipients/Users/Patients2
Providers3
Health Care Language4
Diagnoses4
Treatment Protocols5
Combinations of Diagnoses and Treatments5
Types of Administrative Files5
HCFA-15006
Pharmacy6
UB-926
Claims and Encounters7
Conclusion8
Chapter 2Health Care Codes
Introduction9
The Coding of Diagnoses11
ICD-9-CM Diagnosis Codes11
ICD-10-CM Diagnoses15
Diagnostic Related Groups15
Major Diagnostic Categories19
The Coding of Procedures21
ICD-9-CM Surgical Procedures22
Level ICPT codes24
Level IIHCPCS27
Level IIILocal Codes28
Pharmacy-Specific Codes29
National Drug Codes29
Therapeutic Class30
Generic Product Packaging Codes33
Billing Codes or Revenue Codes33
Location of Codes and Descriptors35
ICD-9 Diagnosis Codes35
DRGs37
ICD-9 Surgical Procedures37
CPT, HCPCS, and Local Codes37
Billing or Revenue Codes37
Short Example of Code Usage38
Conclusion39
Chapter 3Data Forms, Layouts, and Files
Introduction41
Data Forms42
HCFA-150042
Pharmacy45
UB-9245
Data Layouts49
HCFA-1500 File Layout50
Pharmacy File Layout52
UB-92 File Layout52
Data Files53
Source Data Format53
HCFA-1500 Data File53
Pharmacy Data File54
UB-92 Data File55
Data in Other Formats56
Conclusion57
Chapter 4Reading the Data
Introduction59
Step 1Write the SAS Code60
Reading the Variables62
Step 2Test the Code65
Step 3Correct the Code66
Diagnoses (Dx) and Solutions (Rx) to the Errors67
Step 4Re-Test the Code68
Step 5Check the Results69
Printing the Data70
Diagnoses (Dx) and Solutions (Rx) to the Errors70
Step 6Correct the Code71
Diagnoses (Dx) and Solutions (Rx) to Missing Dates71
Creating User-Defined Formats and Informats72
Step 7Check the Results73
Step 8Enhance the Code73
Comments73
The LENGTH Statement74
The FORMAT Statement75
Variable Labels75
Pharmacy Files: New ideas76
UB-92 Files: New Ideas77
ARRAY Statements77
Conditional Selection upon Input79
Putting It All Together81
Reading SAS Data Sets82
Data in Other Formats83
Working with Data and Files across Years84
Conclusion85
Chapter 5Validating the Data
Introduction87
The Data Content88
The CONTENTS Procedure89
Viewing the Data90
Quantity: Volume of Data92
Services94
Visits95
Users97
Selected Populations or Sub-groups97
Discharges and Stays100
Charges and Payments102
Quantity: Completeness102
Frequencies103
Frequency of Missing Values104
Dates105
Numeric Fields106
Quality: Accuracy108
Chart Review108
Frequency of Codes108
Two-Way Tables110
Means111
Comparative Data Sources112
Quality: Clinical Relevance113
Conclusion113
Chapter 6Manipulating the Data
Introduction116
Operators116
Missing Values118
Exclusion of Selected Observations118
Calculations119
Date Formats and Functions120
The MDY Function120
The TODAY Function120
Parsing Dates121
Date Formats121
Numeric Functions122
The INT Function122
The TRUNC and ROUND Functions123
Character Functions123
The COMPRESS Function124
The DEQUOTE Function124
The SUBSTR Function125
The SCAN and INDEX Functions125
The CONTAINS Operator in Where Statements126
The COLON Operator Modifier127
Other Character Functions129
Creating new variables129
Character-to-Numeric Recording130
Numeric-to-Character Recoding131
More about Formats132
Stratification and Aggregation132
Subset and Selection133
Reporting Options134
Transforming Data Sets135
Using Arrays137
PROC TRANSPOSE139
More Macros139
Conclusion141
Chapter 7Combining the Data
Introduction143
Data Structures and Terminology144
Concatenation and Appending145
Study Design145
Concatenation: The Set Statement146
Appending147
Interleaving150
Merging Data153
One-to-One Match Merge153
Many-to-One Match Merge158
Many-to-Many Match Merge159
Other Types of Merges165
Conclusion165
Chapter 8Analysis and Reporting: The Basics
Introduction167
Basic Statistical Concepts168
Variable Types168
Independent versus Dependent169
Population versus Sample170
The Normal Distribution171
SAS Procedures171
Descriptive Statistics172
Measures of Central Tendency173
Measures of Variability173
Useful Procedures174
Prescription for Use179
Data Summarization179
Summary Statistics179
Row and Column Totals184
Other Useful Procedures187
Prescription for Use187
Analytics187
Measures of Association188
Comparing Population Means189
Other Useful Procedures190
Prescription for Use191
Information Presentation192
Tables192
Plots, Charts, and Maps194
Other Useful Procedures196
Prescription for Use196
Conclusion196
Chapter 9Case Study
Introduction198
Study Design198
Data Files199
Initial Analytic Steps201
Identification of ER visits201
Preliminary Steps202
Demographic Field Identification202
Algorithm for Age Calculation202
Formatting Specifications203
Other Key Points203
Comparative Frequencies203
Study Design Modifications205
SAS Programs205
Step 1Identify Format Library and Create New Formats206
Step 2Build SAS Macros to Access Different Years206
Step 3Sort and Subset the Physician Claims Files206
Step 4Sort and Subset the Outpatient Claims Files208
Step 5Merge the Claims Files and Enrollment Files208
Step 6Summarize the Claims Dollars209
Step 7Create a Data Set to Store Charges210
Step 8Sort to Unduplicate Dates in Claims Files211
Step 9Merge the Visit Data Sets211
Step 10Produce a Report of Top 20 Diagnoses212
Step 11Produce Summarized Tables213
Step 12End the SAS Macro and Pass the Parameters213
Results214
Output Data Sets214
More about_TYPE_215
Tables216
Graphs217
Further Studies220
Conclusion221
Chapter 10The Future of Health Care Data
Introduction223
Future Information Flow224
HIPAA: Electronic Data Transmittal224
Standard Formats225
Electronic Data Submissions227
National Provider Identifier (NPI)227
Electronic Death Registration Systems (EDRS)227
Future Coding Systems228
ICD-10228
Current System: New Initiatives230
ICD-10-CM and ICD-10-PCS230
Future Technology230
Internet Health Care230
Medical Records Privacy231
Future Health Care Economics231
Risk Adjustment232
Some Predictive Models233
HEDIS234
Pharmacy-Based Models234
AIDS Risk Adjustment234
Health Care Data and the SAS System234
Appendix237
Glossary245
References253
Index255

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