Understanding and Using NAMCS and NHAMCS Data Data Tools and Basic Programming Techniques 2010 National Conference on Health Statistics August 16, 2010.

Slides:



Advertisements
Similar presentations
Prerequisites Recommended modules to complete before viewing this module 1. Introduction to the NLTS2 Training Modules 2. NLTS2 Study Overview 3. NLTS2.
Advertisements

Tobacco Use Supplement To The Current Population Survey Users’ Workshop June 2009 Tips and Tricks of Handling the TUS Data James “Todd” Gibson Information.
9. Weighting and Weighted Standard Errors. 1 Prerequisites Recommended modules to complete before viewing this module  1. Introduction to the NLTS2 Training.
Predictors of Emergency Department Utilization by Homeless Persons: A National Study Clarilee Hauser PhD, RN.
19.Multivariate Analysis Using NLTS2 Data. 1 Prerequisites Recommended modules to complete before viewing this module  1. Introduction to the NLTS2 Training.
Using past visit information to enhance analysis of National Ambulatory Medical Care Survey (NAMCS) data Session 25 July 13, :30-noon.
1 Mental Health Data from the NAMCS and NHAMCS Susan M. Schappert, M.A. Ambulatory and Hospital Care Statistics Branch Division of Health Care Statistics.
1 How to understand and use National Ambulatory Medical Care Survey (NAMCS) and National Hospital Ambulatory Medical Care Survey (NHAMCS) data for clinical.
1 Understanding and Using NAMCS and NHAMCS Data Part 1 – Survey Overview and SETS Susan M. Schappert Ambulatory Care Statistics Branch Division of Health.
Clustered or Multilevel Data
15a.Accessing Data: Frequencies in SPSS ®. 1 Prerequisites Recommended modules to complete before viewing this module  1. Introduction to the NLTS2 Training.
15b. Accessing Data: Frequencies in SAS ®. 1 Prerequisites Recommended modules to complete before viewing this module  1. Introduction to the NLTS2 Training.
Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop
Overview of the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey Farida Bhuiya M.P.H., National Center.
SW318 Social Work Statistics Slide 1 Using SPSS for Graphic Presentation  Various Graphics in SPSS  Pie chart  Bar chart  Histogram  Area chart 
Patient Characteristics and the Use of Health Care Services by Persons with HIV Esther Hing and Christine Lucas, Ambulatory and Hospital Care Statistics.
FINAL REPORT: OUTLINE & OVERVIEW OF SURVEY ERRORS
Analysis of National Health Interview Survey Data
Electronic Medical Record Use and the Quality of Care in Physician Offices National Conference on Health Statistics August 17, 2010 Chun-Ju (Janey) Hsiao,
Physician Acceptance of New Medicaid Patients by State in 2011 Sandra Decker, Ph.D. National Center for Health Statistics NCHS National.
Which physicians and practices are using electronic medical records? Catharine W. Burt, Ed.D. Chief, Ambulatory Care Statistics Branch July 19, 2006 The.
17 June, 2003Sampling TWO-STAGE CLUSTER SAMPLING (WITH QUOTA SAMPLING AT SECOND STAGE)
July, 2008 Presentation at Los Angeles Basin SAS Users Group Meeting The Dangers and Wonders of Statistics Using SAS or You Can Have it Right and You Can.
Joint Canada/U.S. Health Survey Catherine Simile, National Center for Health Statistics Patrice Mathieu, Statistics Canada Ed Rama, Statistics Canada NCHS.
1 Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Susan M. Schappert Donald K. Cherry.
NHANES Analytic Strategies Deanna Kruszon-Moran, MS Centers for Disease Control and Prevention National Center for Health Statistics.
National Center for Health Statistics DCC CENTERS FOR DISEASE CONTROL AND PREVENTION NAMCS/NHAMCS WORKSHOP Catharine W. Burt Susan M. Schappert Nghi Ly.
1 Linda McCaig and David Woodwell Ambulatory Care Statistics Branch Division of Health Care Statistics Overview of the NAMCS and NHAMCS.
Medication Data from Nationally Representative Provider- and Population-Based Surveys Lisa L. Dwyer, MPH Saeid Raofi, MS Pharmacy Karen A. Lees, MPH Ryne.
Sampling. Concerns 1)Representativeness of the Sample: Does the sample accurately portray the population from which it is drawn 2)Time and Change: Was.
DESIGN FEATURES OF NCHS SURVEYS By Iris Shimizu Mathematical Statistician Office of Research and Methodology, NCHS Disclaimer: The opinions in this presentation.
TRANSLATING VISITS INTO PATIENTS USING AMBULATORY VISIT DATA (Hypertensive patient case study) by Esther Hing, M.P.H. and Julia Holmes, Ph.D U.S. DEPARTMENT.
1 Using NAMCS and NHAMCS Drug Data: A Hands-On Workshop Susan M. Schappert, M.A. Elizabeth A. Rechtsteiner, M.S. Division of Health Care Statistics.
Increasing the sample: How can state-based estimates help monitor healthcare reform? 2012 National Conference on Health Statistics Monitoring Health Care.
18b. PROC SURVEY Procedures in SAS ®. 1 Prerequisites Recommended modules to complete before viewing this module  1. Introduction to the NLTS2 Training.
The 2006 National Health Interview Survey (NHIS) Paradata File: Overview And Applications Beth L. Taylor 2008 NCHS Data User’s Conference August 13 th,
Design Effects: What are they and how do they affect your analysis? David R. Johnson Population Research Institute & Department of Sociology The Pennsylvania.
Secondary Data Analysis Linda K. Owens, PhD Assistant Director for Sampling and Analysis Survey Research Laboratory University of Illinois.
Analyzing NCHS Drug Data Amy B. Bernstein, Sc.D. Presented at the NCHS Board of Scientific Counselors Meeting January 28, 2005 U.S. DEPARTMENT OF HEALTH.
Women’s health: Data from the National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS) Esther.
Statistical Export and Tabulation System (SETS) Overview and SetX Debut Ann Aikin and Bob Sloss 2004 Data Users Conference Session #16 U.S. Department.
Exploring Features of the NCHS Web CDC/NCHS Office of Information Services Information Dissemination Staff U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES.
1 Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Part II-Using Raw Data Files Donald Cherry.
Using Data from NCHS: An Overview of NCHS Data Access Tools Monitoring the Public's Health: Using Data from the National Center for Health Statistics APHA.
JENNIFER SAYLOR, PHD, RN, ANCS-BC UNIVERSITY OF DELAWARE SEPTEMBER 14, 2012 Essentials of Complex Data Analysis Utilizing National Survey.
Studying Injuries Using the National Hospital Discharge Survey Marni Hall, Ph.D. Hospital Care Statistics Branch, Division of Health Care Statistics.
Analyzing data on medications collected in the National Health Care Survey Centers for Disease Control and Prevention National Center for Health Statistics.
Traumatic Brain Injury in the United States Emergency Department Visits, Hospitalizations, and Deaths 1995–2001 National Center for Injury Prevention and.
Sources of Errors in Estimating Community Health Center Physicians Centers for Disease Control and Prevention National Center for Health Statistics Catharine.
Using the SDA on the Web Ed Nelson, CSU Fresno Social Science Research and Instructional Council.
Enhancements to the NAMCS and NHAMCS 2012 National Conference on Health Statistics Monitoring Health Care Reform Through Provider-based Surveys: New Initiatives.
National Hospital Discharge Survey: A Hands-On Workshop Using Public-Use Data Files Michelle N. Podgornik, MPH 2006 Data Users Conference July 11, 2006.
1 Using National Hospital Ambulatory Medical Care Survey (NHAMCS) data for injury analysis Linda McCaig Ambulatory Care Statistics Branch Division of Health.
Introduction to Secondary Data Analysis Young Ik Cho, PhD Research Associate Professor Survey Research Laboratory University of Illinois at Chicago Fall,
The National Hospital Care Survey Linda McCaig, M.P.H. National Center for Health Statistics August 8, 2012.
Understanding and Using NAMCS and NHAMCS Data
Basics of Biostatistics for Health Research Session 1 – February 7 th, 2013 Dr. Scott Patten, Professor of Epidemiology Department of Community Health.
DTC Quantitative Methods Summary of some SPSS commands Weeks 1 & 2, January 2012.
CASE STUDY: NATIONAL SURVEY OF FAMILY GROWTH Karen E. Davis National Center for Health Statistics Coordinating Center for Health Information and Service.
Statistical Weights and Methods for Analyzing HINTS Data HINTS Data Users Conference January 21, 2005 William W. Davis, Ph.D. Richard P. Moser, Ph.D. National.
Using Data from the National Survey of Children with Special Health Care Needs Centers for Disease Control and Prevention National Center for Health Statistics.
1 Understanding and Using NAMCS and NHAMCS Data Part 2 –Using public-use files Eric Nawar Ambulatory Care Statistics Branch Division of Health Care Statistics.
NHANES Analytic Strategies Deanna Kruszon-Moran, MS Centers for Disease Control and Prevention National Center for Health Statistics.
Sample Design of the National Health Interview Survey (NHIS) Linda Tompkins Data Users Conference July 12, 2006 Centers for Disease Control and Prevention.
Session5 OVERVIEW OF THE NATIONAL HEALTH CARE SURVEY.
Healthy Women Statistics: A Resource for State Data on Women’s Health Kate Brett Centers for Disease Control and Prevention National Center for Health.
Data Entry, Coding & Cleaning SPSS Training Thomas Joshua, MS July, 2008.
U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention National Center for Health Statistics Injury and illness episodes.
Working with the ECLS-B Datasets Weights and other issues.
Confidence intervals for the difference between two means: Independent samples Section 10.1.
Presentation transcript:

Understanding and Using NAMCS and NHAMCS Data Data Tools and Basic Programming Techniques 2010 National Conference on Health Statistics August 16, 2010 Chun-Ju (Janey) Hsiao National Center for Health Statistics

2 Overview Some important features of NAMCS & NHAMCS File structure Exercises using SAS Proc Surveyfreq/Proc Surveymeans and STATA –Downloading data & creating a SAS/STATA dataset –Weighted and unweighted frequencies with/without standard errors –Creating a new variable-Asthma –Visit rates for asthma-male/female –Total number of digestive write-in procedures –Time spent with physician Considerations Summary

3 Organizational Structure-NAMCS Data Provider provider info practice info geographic info Visit patient & visit info treatment & outcome info medications Medications 1-8Primary reason for Visit MULTUM Categories Primary diagnosis Write-in scope procedure 1 Other Reason for Visit Other diagnosis Write-in scope procedure 2 Other test/service 1 Other test/service 2 Non-surgical procedure 1 Other surgical procedure 1 Non-surgical procedure 2 Other surgical procedure 2

4 Data Items Patient characteristics –Age, sex, race, ethnicity Visit characteristics –Source of payment, continuity of care, reason for visit, diagnosis, treatment Provider characteristics –Physician specialty, hospital ownership MULTUM drug characteristics added in 2006

5 Sample Weight Each NAMCS record contains a single weight, which we call Patient Visit Weight. –Same is true for OPD records and ED records This weight is used for both visits and drug/procedure mentions.

2007 NCHS Coding Convention Changes Starting in 2007, missing data have consistent negative codes –Blank= -9 –Unknown/Don’t know= -8 –Not applicable= -7 Prior to 2007, missing data had positive codes –Blank code varied –Unknown/Don’t know code varied –Not applicable=8 6

7 Enhanced Public-Use Files Download data and layout from website res.htm –Flat ASCII files for each setting and year: NAMCS: NHAMCS: –SAS input statements, variable labels, value labels, and format assignments for –SPSS syntax files for –STATA.do and.dct files for

8 Enhanced Public-Use Files (cont.) New survey items and facility level data Sample design variables – In 2001 and prior years, masked variables for 3- or 4-stage sampling are available. – In 2002, NAMCS & NHAMCS masked variables have been available for use in software using multi-stage and 1-stage sampling. – Starting in 2003, we only released masked variables for use in software using 1-stage.

or 4-Stage design variables Stage design variables only 1-Stage design variables 3- or 4-Stage design variables Design Variables—Survey Years

10 Creating a Usable STATA Dataset Three options: 1) Use the self-extracting file in the STATA folder to open a complete dataset for the NAMCS, NHAMCS-ED, & NHAMCS-OPD. 2) Use the DO file (*.do) and the dictionary file (*.dct) along with the flat data file (*.exe) to create a dataset. 3) StatTransfer

11 Hands-on Exercises Double-click: C:\AHDATA\SAS Open STATA In the command window type: –Set mem 100m –Set matsize 500 Under the “File” icon- double-click namcs07.dta Under “New Do File Editor”- double-click: STATA 07exercises.do Double-click: C:\AHDATA\SAS Double-click: SAS07exercise SAS/SUDAAN UsersSTATA Users

12 Visit Rate Estimates PhycodeSexPatwt(Patwt/Pop)*100Sexwt (100/800)* (300/800)* (50/800)* (120/800)* visits per 100 persons Female population=800 New variableCalculation* *Note: Rate=est/pop=Σ patwt/pop=1/pop*Σ patwt. Sample size=4 Visits=570

13 RecordProc1Proc2Proc3Proc4Proc5Proc6Proc7Proc8Totproc Note: 0000=No procedure recorded. Calculating Total Number of Write-in Procedures

14 Data Considerations

15 NAMCS vs. NHAMCS Consider what types of settings are best for a particular analysis –Persons of color are more likely to visit OPDs and EDs than physician offices –Persons in some age groups make disproportionately larger shares of visits to EDs than physician offices and OPDs

16 Which Statistical Program? ProgramCategorical Variables Continuous Variables SASPROC SURVEYFREQ PROC SURVEYMEANS STATASVY: TABSVY: MEAN SUDAANPROC CROSSTABPROC DESCRIPT

17 How Good are the Estimates? Depends … In general, OPD estimates tend to be somewhat less reliable than NAMCS and ED. Since 1999, our Advance Data Reports/National Health Statistics Reports include standard errors in every table so it is easy to compute confidence intervals around the estimates.

18 Reliability Criteria Estimates should be based on at least 30 sample records AND Estimates with a relative standard error (standard error divided by the estimate) greater than 30 percent are considered unreliable by NCHS standards. Both conditions should be met before considering estimates reliable.

19 Ways to Improve Reliability of Estimates Combine NAMCS, ED and OPD data to produce ambulatory care visit estimates Combine multiple years of data Use multiple variables to define construct

20 RSE Improves Incrementally with the Number of Years Combined RSE = SE/x RSE for percent of visits by persons less than 21 years of age with diabetes 1999 RSE =.08/.18 =.44 (44%) 1998 & 1999 RSE =.06/.18 =.33 (33%) 1998, 1999, & 2000 RSE =.05/.21 =.24 (24%)

21 Sampling Error NAMCS and NHAMCS are not simple random samples Clustering effects: – Providers within PSUs – Visits within physician practice or hospital Must use generalized variance curve or special software (e.g., SUDAAN) to calculate SEs for all estimates, percents, and rates

22 Calculating Variance with NAMCS/NHAMCS Estimates Old way (least accurate) = Generalized variance curves Better way (recommended) = Masked design variables –Multiple sampling stages for years –Single stage of sampling or ultimate cluster design Most accurate way (expensive) = Actual design variables

23 Comparisons of Relative Standard Errors (RSEs) for Patient Race Variances for clustered items (like race, diagnosis, type of provider) are predicted less accurately using the GVC. If you use the GVC, use p =.01, not.05

24 Comparison of SEs Produced Using GVC, SUDAAN-True, and SUDAAN WR

25 Some User Considerations NAMCS/NHAMCS sample visits, not patients No estimates of incidence or prevalence No state-level estimates May capture different types of care for solo vs. group practice physicians Data are only as good as what is documented in the medical record

26 Some User Considerations (cont.) High percentage of missing on some data items –2007 NAMCS Ethnicity (34.7%) –Imputed and unimputed data Race (31.5%) –Imputed and unimputed data Time spent with provider (26.2%)

27 If nothing else, remember… The Public Use Data File Documentation is YOUR FRIEND! Each booklet includes: –A description of the survey –Record format –Marginal data (summaries) –Various definitions –Reason for Visit Classification codes –Medication & generic names –Therapeutic classes

28 Where to get more information? Call the Ambulatory and Hospital Care Statistics Branch at