Vital and Health Statistics · 2016. 7. 1. · Series 1: Programs and Collection Procedures No. 39 Hyattsville, Maryland December 2000 DHHS Publication No. (PHS) 2001-1315 Vital and

Design and Operation of theNational Hospital DischargeSurvey: 1988 Redesign

Series 1:Programs and CollectionProceduresNo. 39

Hyattsville, MarylandDecember 2000DHHS Publication No. (PHS) 2001-1315

Vital andHealth Statistics

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICESCenters for Disease Control and PreventionNational Center for Health Statistics

Copyright Information

All material appearing in this report is in the public domain and may bereproduced or copied without permission; citation as to source, however, isappreciated.

Suggested Citation

Dennison C, Pokras R. Design and operation of the National Hospital DischargeSurvey: 1988 redesign. Vital Health Stat 1(39). 2000.

Library of Congress-in-Publication Data

Dennison, Charles F.Design and operation of the National Hospital Discharge Survey / [by

Charles Dennison and Robert Pokras].p. cm.—(Vital and health statistics. Series 1, Programs and collection

procedures ; no. 39) (DHHS publication ; no. (PHS) 2001-1315)‘‘October 2000.’’Includes bibliographical references.ISBN 0-8406-0565-X1. National Hospital Discharge Survey (U.S.) 2. Hospital utilization—United

States—Statistics. 3. Medical care surveys—United States 4. Healthsurveys—United States. I. Pokras, Robert. II. National Center for HealthStatistics (U.S.) III. Title IV. Series. V . Series: DHHS publication ; no. (PHS)2001-1315.RA409.U44 no. 39[RA407.3]362.1’07’23 s—dc21[362.1’1’0973] 00-064743

For sale by the U.S. Government Printing OfficeSuperintendent of DocumentsMail Stop: SSOPWashington, DC 20402-9328Printed on acid-free paper.

National Center for Health Statistics

Edward J. Sondik, Ph.D.,Director

Jack R. Anderson,Deputy Director

Jack R. Anderson,Acting Associate Director forInternational Statistics

Jennifer H. Madans, Ph.D.,Associate Director for Science

Lester R. Curtin, Ph.D.,Acting Associate Director forResearch and Methodology

Jennifer H. Madans, Ph.D.,Acting Associate Director forAnalysis, Epidemiology, and Health Promotion

P. Douglas Williams,Acting Associate Director for DataStandards, Program Development, and Extramural Programs

Edward L. Hunter,Associate Director for Planning, Budget,and Legislation

Jennifer H. Madans, Ph.D.,Acting Associate Director forVital and Health Statistics Systems

Douglas L. Zinn,Acting Associate Director forManagement

Charles J. Rothwell,Associate Director for InformationTechnology and Services

Division of Health Care Statistics

Linda Demlo, Ph.D.,Director

Thomas McLemore,Deputy Director

Irma Arispe, Ph.D.,Associate Director for Science

Robert Pokras,Chief, Hospital Care Statistics Branch

Contents

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Sample Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2First Stage Sampling—Primary Sampling Units. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Second Stage Sampling—Hospitals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Third Stage Sampling—Discharges. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Confidentiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Survey Operations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4Manual Data Collection and Processing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4Automated Data Collection and Processing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Estimation Procedures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Inflation by Reciprocals of Probabilities of Selection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Adjustment for Nonresponse. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Population Weighting Ratio Adjustment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Reliability of Estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Estimation of Standard Errors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Standard Error Approximations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Relative Standard Error for Estimates of Percents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Nonsampling Errors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Data Dissemination. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Text Tables

A. Definition of noncertainty hospital specialty-size groups used as secondary strata in the National Hospital DischargeSurvey sample design, 1988 sample design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

B. Number of hospitals in the National Hospital Discharge Survey sample, number of in-scope and responding samplehospitals, response rates, and number of abstracts collected: United States, 1988–97. . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

C. Estimated parameters for approximate relative standard error equations by selected characteristics: National HospitalDischarge Survey, 1997. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Appendixes

I. Legislative Authorization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

II. Induction Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

III. American Hospital Association Endorsement Letter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

IV. Confidentiality Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

V. Hospital Interview Questionnaire (HDS-11). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

VI. Medical Abstract—National Hospital Discharge Survey. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

iii

VII. Sample Selection Sheet (HDS-5) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

VIII. Statement of Agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

IX. Abstract Service Agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

X. Transmittal Notice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

XI. Automated File Layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

XII. Information Request Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

XIII. Definitions of Terms Related to Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

iv

The National Hospital DischargeSurvey (NHDS), a national probabilitysample survey of discharges fromnon-Federal hospitals, began in 1965and has been conducted annually sincethen. The original design of NHDS wasin place through 1987. This reportprovides information about the surveydesign, instruments, data collectionprocedures, and survey methodologyused for NHDS since theimplementation of its redesign in 1988.

Keywords: inpatients, hospital,hospital discharges, NationalHospital Discharge Survey

Design and Operation of theNational Hospital DischargeSurvey: 1988 Redesignby Charles Dennison and Robert Pokras, M.A., Division of HealthCare Statistics

Page 1

Introduction

I n 1965 the National Center forHealth Statistics (NCHS) initiatedthe National Hospital Discharge

Survey (NHDS) to collect anddisseminate data on inpatient utilizationof short-stay non-Federal hospitals inthe United States and District ofColumbia. The importance of measuringinpatient care made NHDS the firstsurvey of medical care deliveryconducted by the NCHS (1,2) andinpatient care continues to play a majorrole in health care delivery (3). TheNHDS has been conducted annuallysince its inception.

Authority for the NHDS derivedfrom the National Health Survey Act of1956 (Public Law 84–652) and it hascontinued under various acts ofCongress, principally under Section306(b)(1)(F) (appendix I) of the PublicHealth Service Act (42 USC 242k) andits amendments to collect dataconcerning the public’s use of healthcare services.

The NHDS was conducted underthe same design from 1965 through1987. A previous report describes thedevelopment and design of the NHDSduring this period (4). A redesign for thesurvey was implemented in 1988. Thisreport describes the design andoperation of the NHDS, which beganwith the 1988 survey year and majorchanges to NHDS resulting from thenew design. These changes include theuse of a 3-stage sample design, the use

of automated data, and the ability to useSUDAAN to estimate variances.

Background

The impetus to redesign the NHDSwas to select a new independentnational probability sample of

hospitals. The initial sample of hospitalsfor NHDS was used for the 23-yearperiod 1965–87. The redesign focusedon improving the efficiency and analyticcapability of the survey by 1) linkingthe NHDS to the design of NCHS’sNational Health Interview Survey(NHIS), 2) incorporating hospitaldischarge data available in electronicform, and 3) allowing the use ofexisting statistical software to estimatevariances.

The redesign included linkage withthe design of NHIS (5), the principalsource of information on the health ofthe civilian noninstitutionalizedpopulation of the United States. Before1988 the NHDS used a two-stagesample design (a sample of hospitalsand a sample of records withinhospitals); the redesign included a thirdstage prior to sampling hospitals, theselection of geographic primarysampling units (PSU’s). The redesignused a sub-sample of PSU’s selected forthe 1985–94 NHIS. This modificationwas intended to enhance the analyticcapabilities of both surveys and toreduce the field costs of the surveys byconducting them in the same geographicareas.

Page 2 [ Series 1, No. 39

The redesign also took into accountthe increasing availability of dischargedata in electronic (automated) form.Before the redesign, the NHDSdepended almost entirely on manualsampling and abstraction of informationfrom medical records. The exception tothis was that automated data wereobtained for about 75 hospitals annuallyduring the period 1985–87. With theimplementation of the new design in1988, information on the characteristicsof a majority of discharges in NHDSwere obtained from existing hospitaldischarge data bases. However, amajority of hospitals provide data bymeans of manual sampling andabstraction. This seeming contradictionis explained by the fact that, as part ofthe redesign, more records are sampledfrom hospitals providing automated datathan are sampled from hospitals inwhich data are manually abstracted frommedical records. The target sample sizeis 250 discharges from manual hospitalsand 2,000 discharges from automatedsystem hospitals.

Also, the new redesign allows theuse of available statistical software toestimate variances for estimates. Before1988 NCHS used a program written atNCHS specifically for the NHDS tocalculate variances. The redesign allowsthe use of SESUDAAN and SUDAAN(6, 7) for this purpose. This is moreefficient for data dissemination and itallows researchers to more readilygenerate variances for specific areas ofinterest.

There are a number of lesssignificant differences between theoriginal and new designs that have beendocumented (8,9). These include adifferent source as the operationaldefinition of the hospital universe andminor differences in the statical designof the survey. The changes introduceddo not compromise the ability toconduct trend analysis; however, theaddition of clustering introduced byincluding a third stage of sampling(PSU’s) reduced the precision ofestimates.

Sample Design

The NHDS is based on a nationalprobability sample of dischargesfrom noninstitutional hospitals

exclusive of Federal, military, andDepartment of Veterans Affairshospitals, located in the 50 States andthe District of Columbia. Onlyshort-stay hospitals (hospitals with anaverage length of stay for all patients ofless than 30 days) or those whosespeciality is general (medical orsurgical) or children’s general regardlessof length of stay are included in thesurvey. Also, a hospital must have six ormore beds staffed for patient use to bein scope for the survey. The 1988NHDS sampling frame consisted ofhospitals that were listed in the April1987 SMG Hospital Market Database(10) and that began to accept inpatientsby August 1987.

Given fixed costs, the NHDS isdesigned to provide estimates ofinpatient hospital utilization based onthe following priority of objectives:national aggregate statistics, nationaltrend statistics, and aggregate statisticsfor the four major Census Regions of theUnited States. The NHDS uses amodified three-stage probability design,the stages are: 1) primary sampling units(PSU’s); 2) hospitals within PSU’s; and3) discharges within hospitals. Themodification was that the largest PSU’sand hospitals were selected withcertainty.

First Stage Sampling—Primary Sampling Units

The first stage of samplingconsisted of 112 primary sampling units(PSU’s) that comprised a probabilitysubsample of PSU’s used in the1985–94 NHIS. PSU’s are counties,groups of counties, county equivalents(such as parishes or independent cities),or towns and townships (for somePSU’s in New England). The NHDSsample included with certainty 26 PSU’swith the largest populations. In addition,the sample included one-half of the next26 largest PSU’s, and one PSU fromeach of the 73 PSU’s strata formed from

the remaining PSU’s in the NHISsample design. Those 73 PSU’s stratawere defined within four geographicregions and metropolitan statistical area(MSA) or non-MSA status (MSA was ametropolitan statistical area defined bythe U.S. Office of Management andBudget on the basis of the 1980 census).PSU’s were assigned to strata by using1980 Census of Population data and acomputer program that minimized thebetween-PSU variances for the NHISstratification variables. From the 73strata thus formed, the PSU’s wereselected with probability proportional tothe projected 1985 population. A moredetailed description of the NHIS PSUsample design has been published (5).

Second StageSampling—Hospitals

The second stage of samplingconsisted of a systematic random sampleof noncertainty hospitals selected fromthe sample PSU’s with probabilityproportional to their annual number ofdischarges. To assure distribution of thesample across PSU’s and to maximizethe potential for automated datacollection, the noncertainty hospitalswere stratified by region, PSU, and inthe 12 largest PSU’s, by data collectiontype (whether the hospital subscribed toa commercial abstracting service).Within the strata, the hospitals wereordered by PSU, whether the hospitalparticipated in the 1987 NHDS and byhospital size and speciality as defined intable A. Finally, hospitals were arrayedwithin speciality by their annual numberof discharges. The sampling rates weresuch that at least three hospitals wereselected from every PSU containingthree or more eligible hospitals. InPSU’s with fewer than three hospitals,all hospitals in the PSU were selected.

The sample design resulted in theselection of 542 hospitals for the NHDSin 1988. Of these, 11 hospitals were outof scope and 109 refused to participateor did not provide enough data to beconsidered responding. This resulted in422 hospitals participating in the survey,a response rate of 79.5 percent. Througha concerted effort to increase thehospital response rate, this was raised to

Table A. Definition of noncertainty hospital specialty-size groups used as secondarystrata in the National Hospital Discharge Survey 1988 sample design

Hospital group Bed size Type of service

Group 1 . . . . . . . . . . . . . . . . . . . 6–999 beds Selected specialties1

Group 2 . . . . . . . . . . . . . . . . . . . 6–174 beds General (medical and surgical) and other specialties2



1Includes psychiatry, tuberculosis and other respiratory disease, rehabilitation, chronic disease, mental retardation, alcoholismand other chemical dependancy, and children’s psychiatry.2‘‘Other specialties’’ include obstetrics and gynecology: eye, ear, nose and throat; orthopedics; other specialty; children’s general;children’s tuberculosis and other respiratory disease; children’s eye, ear, nose, and throat; children’s rehabilitation; children’sorthopedics; children’s chronic disease; and children’s other specialty.

Series 1, No. 39 [ Page 3

91.3 percent in 1990 and it did not fallbelow 90 percent through 1997. Table Bprovides information on hospitalparticipation for the NHDS from 1988through 1997.

NCHS conducts several activities tokeep the sample of hospitals in theNHDS current with the changinguniverse of hospitals in the UnitedStates: hospitals in the NHDS samplethat no longer meet eligibilityrequirements for the survey areremoved; methods were developed andimplemented for hospitals that merge;and NCHS samples a ‘‘ birth panel’’ ofhospitals every 3 years from all newhospitals that came into existence sincethe previous set of birth panel hospitalswere selected. Research has shown thatadding hospitals from birth panels waseffective in ensuring that estimates fromthe survey reflect the changing universeof hospitals (11).

Table B. Number of hospitals in the National Hin-scope and responding sample hospitals, recollected: United States, 1988–97

YearSamplehospitals Total

1988 . . . . . . . . . . . . . . . . . . . . . 542 5311989 . . . . . . . . . . . . . . . . . . . . . 542 5261990 . . . . . . . . . . . . . . . . . . . . . 542 5191991 . . . . . . . . . . . . . . . . . . . . . 1528 5211992 . . . . . . . . . . . . . . . . . . . . . 528 5141993 . . . . . . . . . . . . . . . . . . . . . 528 5131994 . . . . . . . . . . . . . . . . . . . . . 1525 5121995 . . . . . . . . . . . . . . . . . . . . . 525 5081996 . . . . . . . . . . . . . . . . . . . . . 525 5071997 . . . . . . . . . . . . . . . . . . . . . 1513 501

1Changes reflect triannual updates to the NHDS hospital universe

Third StageSampling—Discharges

At the third stage, a sample ofdischarges from each hospital is selectedby a systematic random samplingtechnique. For hospitals using themanual system of data collection,sampling rates for discharges aredesigned to generate samples ofapproximately equal numbers regardlessof hospital size. This characteristic ofthe design allows efficiencies in fieldoperations by ensuring that the numberof medical records sampled andabstracted in the field can be completedin a single day, thereby avoidingrepeated trips to a hospital by censuspersonnel (see Manual Data Collectionand Processing). To achieve thisoperational goal, discharges are sampledin inverse proportion to hospital size

ospital Discharge Survey sample, number ofsponse rates, and number of abstracts

In-scope hospitals

Hospitalresponse

rateDischarges

sampled

Response typeTotal

respondentsManual Automated

Number Percent Number

255 167 422 79.5 250,243256 152 408 77.6 233,493299 176 475 91.3 265,556323 161 484 92.9 274,311311 183 494 96.1 274,273303 163 466 90.8 235,411298 180 478 93.4 276,533299 167 466 91.7 262,809299 181 480 94.7 282,008284 187 474 94.6 300,464

.

with a target of 20–25 dischargessampled per month.

For hospitals whose data arecollected via the automated system,discharges are sampled in one of twomethods depending on whether NCHSreceives a sample or a census file ofdischarges for the hospital. Someautomated sources prefer to provide asample of discharges. For these sourcesNCHS provides instructions andsampling specifications to use terminaldigits of medical records to sampledischarges as described above formanual data collection. For automateddata that contains all discharges forhospitals, NCHS samples dischargesafter sorting by the first two digits ofthe International Classification ofDiseases, Clinical Modification, NinthRevision, or ICD–9–CM code (12) ofthe first-listed diagnosis, patient agegroup at time of admission (under 1year, 1–14 years, 15–44 years, 45–64years, 65–74 years, 75–84 years, 85years and over, and age unknown), sex,and date of discharge. Discharges aresampled by starting with a randomlyselected discharge and taking every kthdischarge thereafter.

The third-stage sampling rate isdetermined by the hospital’s samplingstratum and the data collection method(manual or automated) used to collectdata from the hospital. One percent and5 percent of discharges in the certaintyhospitals are selected under the manualand automated systems. Except forcertainty hospitals, the target samplesize is 250 discharges annually frommanual system hospitals, from theautomated system hospitals that hadfewer than 4,000 discharges annuallyaccording to the 1987 sampling framedata, and from automated hospitals thatprovided sample data. Samples of 2,000discharges are targeted for each of theremaining noncertainty automatedsystem hospitals that provide files of alldischarges to NCHS. The sample designresulted in the selection of 300,464discharges for the NHDS in 1997.Table B provides information on thenumber of sampled discharges includedin the NHDS from 1988 through 1997.


Confidentiality

Participation in surveys conductedby the National Center for HealthStatistics (NCHS) is voluntary,

and information on individuals and/orfacilities is confidential. For the NHDS,assurance of confidentiality wasprovided to all hospitals according toSection 308(d) of the Public HealthService Act (42 U.S.C. 242m), whichstates that:

‘‘ No information, if anestablishment or person supplyingthe information or described in itis identifiable, obtained in thecourse of activities undertaken orsupported under section ...306,...may be used for any purpose otherthan the purpose for which it wassupplied unless such establishmentor person has consented (asdetermined under regulations ofthe Secretary) to its use for suchother purpose and in the case ofinformation obtained in the courseof health statistical orepidemiological activities undersection ...306, such informationmay not be published or releasedin other form if the particularestablishment or person supplyingthe information or described in itis identifiable unless suchestablishment or person hasconsented (as determined underregulations of the Secretary) to itspublication or release in otherform.’’

Strict procedures are utilized toprevent disclosure of confidential data insurvey operations and datadissemination. Names or otheridentifying information for individualpatients are not obtained from thesampled hospitals. Data received inelectronic form are maintained at theCDC Atlanta computer processingcenter. Under provisions of the DHHSguidelines for storage of health records,all original data collected for the surveyare transferred to the Federal RecordsCenter located in Atlanta, Georgia.These records are retained for 7 yearsbefore they are destroyed. To preventidentification of sampled hospitals or

patients from publicly available researchfiles, variables such as medical recordnumber, date of birth, admission anddischarge dates, and patient ZIP Codeare not released.

Survey Operations

This section describes the surveyoperations for manual andautomated data collection

procedures. With minor exceptions thesurvey forms, manuals, and operatingprocedures used for manual datacollection during the initial design werecontinued with the redesigned survey in1988. As described in the Introduction,there were three major factors thatinfluenced the redesign of the NHDS,one of which was the use of existingdischarge data in electronic (automated)form. Data for the NHDS were collectedmanually from 1965 through 1984. Forthe 3 years, 1985–87, NCHS purchaseddischarge data for about 75 hospitalsannually from a contractor. Beginning in1988 NCHS began purchasingautomated data for approximately 170hospitals annually.

Manual Data Collectionand Processing

The Bureau of the Census hasserved as the agent for data collectedmanually in the NHDS since itsinception in 1965. The Census Bureau iscomposed of a headquarters and 12regional offices. In collaboration withNCHS, Census Headquarters staffdeveloped the survey operationprocedures; wrote, printed, anddistributed all field manuals and formsfor the NHDS; made modifications tothese documents as variables wereintroduced or changed; and, generallyoversaw operations of the manual datacollection. Regional office staff areresponsible for daily operations of thesurvey, training new field staff, andsupplying survey forms and materials tohospital staff.

The major elements of the NHDSfield operations consist of inductingsampled hospitals into the survey,sampling discharges, and abstracting

data from medical records. Thesefunctions are described below.

Hospital Induction

Hospital induction is the process ofgetting sampled hospitals to participatein NHDS. As a voluntary survey,NCHS, through the Census, must obtainwritten permission from each sampledhospital to abstract data from its medicalrecords. While hospital participation isthe primary purpose of induction, otherimportant activities are performed.

Hospital induction begins when theCensus regional office mails anintroductory letter (appendix II)provided by the NCHS to the hospitaladministrator or chief executive officer.Enclosures with this letter include aninformation packet containing a factsheet about the NHDS, a publication listand a description of data productsavailable from the survey, anendorsement letter from the AmericanHospital Association (appendix III), arecent NHDS publication, and a letterthat addressed confidentiality (appendixIV).

Approximately 5 days after mailingthe introductory letter, Census staff callthe hospital administrator to arrange anappointment for an induction interview.Since part of the interview relates toinformation about medical records andthe medical records department, arepresentative from the medical recordsdepartment (usually the MedicalRecords Administrator) is usuallypresent at this meeting. The functions ofthe initial interview are to explain thepurpose of the NHDS, to gain thehospital’s cooperation in the survey, todescribe the data collection methodsavailable for survey participation(described below), to obtain informationabout the hospital by completing theHospital Interview Questionnaire(appendix V), to set up sampling anddata collection procedures, and todistribute manuals and forms.

During induction, a HospitalInterview Questionnaire is completed.Information about the facility such asownership, service type, bed size, andaverage length of stay is collected toverify the hospital’s eligibility for thesurvey. Information about the medical


records department, where and howrecords are kept and stored, and whereto locate the survey variables in themedical records is collected to assist insurvey operations. In addition,reimbursement rates are established forhospital personnel who work on surveyactivities. The level of involvement ofhospital personnel in the NHDS isdetermined by the data collectionmethod. Methods for manual datacollection are described in the nextsection.

There was a large scale induction ofhospitals in 1988 as a result of selectinga new sample of hospitals in theredesign. Although less frequent,inductions also take place asnonresponding hospitals agree toparticipate in the survey.Nonresponding hospitals are contactedannually in an effort to gain theirparticipation. Also, hospitals that areadded to the NHDS sample as part ofthe universe update (see StatisticalDesign) go through the inductionprocess.

Manual Data CollectionMethods

There were three options for manualdata collection: primary, alternate, andprintout. In the primary method, hospitalpersonnel in the medical recordsdepartment sample discharges forinclusion in the survey and abstract datafrom the sampled medical records ontothe survey form (appendix VI). As thename implies, this is the preferredmethod because hospital staff are morefamiliar with their medical records anddata than are Census personnel. In theprimary method hospital staff are givenfield manuals, detailed instructions, andtrained by Census personnel to performthe sampling and abstracting. In 1997about 40 percent of all manual hospitalsin the NHDS provided data using theprimary method.

The alternate method is used whenhospitals are unwilling or unable to havetheir personnel perform the samplingand abstracting. In this method, theCensus Field Representative selects thesampled discharges, arranges with thehospital medical records staff to have

the medical records pulled forabstracting, and the Field Representativeabstracts the records. Every effort ismade to select experienced Census FieldRepresentatives who have anunderstanding of medical terminologyand are familiar with working withmedical records professionals. Thirtypercent of manual hospitals participatedin this mode of manual data collectionfor the 1997 NHDS.

Hospitals also provide data in the‘‘ manual’’ mode by supplyingcomputerized printouts of informationfor sampled discharges. This isconsidered manual data collectionbecause patient information on theprintouts required manual data entry(see Medical Coding and Data Entry).Hospitals using this mode providedefinitions for coded variables (that is,1 = male; 2 = female) to ensure correctdata entry. Computerization of inpatientdata has made printouts more commonin the NHDS; this method of datacollection accounted for about 8 percentof manual data collection in 1988 risingto about 30 percent in 1997.

Sampling Discharges

Discharges within hospitals areselected using systematic randomsampling with the sampling intervalsbased on the statistical design of thesurvey and specified by NCHS. This isusually accomplished using daily ormonthly discharge lists and selectingdischarges with specified terminal digitsof medical record numbers. In somecases an admission number, billingnumber, or other patient number is used.If patient specific numbers useful forsampling are not available, dischargesare selected by using a random startingnumber and then physically countingthrough a discharge list and selectingevery kth discharge thereafter. In a fewhospitals discharges are sampled usingthe terminal digits of the medical recordnumbers on in-house computer files.

Information about sampleddischarges is recorded on a SampleListing Sheet (appendix VII). A SampleListing Sheet is completed for eachmonth’s sample of records. It includesinformation such as medical recordnumbers and dates of discharges that

allowed medical records to be identifiedand pulled for abstracting. Samplingschemes that require a physical count ofdischarges (as described above) are keptcontinuous by tracking on the SampleListing Sheet where the sample selectionprocess stopped in the previous period.

Medical Record Abstracting

Using the Sample Listing Sheets,completed medical records are pulledfor abstracting. Records that are notcomplete or not available are located ata later time for abstracting. The NHDSwas designed to sample approximately20–25 discharges per month per hospitalthat allow Census personnel to sampleand abstract 2 months of medicalrecords in a single day.

Primarily using the medical recordface sheet and discharge summary,patient information is abstracted ontothe survey form (appendix VI).Variables collected in the NHDSconform with the Uniform HospitalDischarge Data Set (UHDDS) (13,14).These variables include birth date orage; sex; race; ethnicity; marital status;admission, discharge, and surgery dates;discharge status; patient ZIP Code;expected source(s) of payment; medicalrecord number; and information ondiagnoses and procedures. The NHDSsurvey methods instruct that, wherepossible, narrative information fordiagnoses and procedures be collected,but in many instances only InternationalClassification of Diseases, NinthRevision, Clinical Modification orICD–9–CM (12) codes are available. In1997 about 30 percent of all manuallyabstracted records included onlyICD–9–CM codes for diagnoses andprocedures.

Additional variables are entered onthe abstract form for survey operations.These included the hospital number (anumber assigned to the hospital forprocessing by NCHS) and the HDSnumber (a number assigned to thesampled record for processing byNCHS).

Medical abstracts and SampleListing Sheets are sent to the CensusRegional Offices where forms for eachmonth are logged in and reviewed forcompleteness. This allows Regional


Office staff to track survey activities andensure that forms were completedcorrectly. Monthly shipments ofabstracts and Sampling Listing Sheetsfrom the Regional Offices are sent to theNCHS processing center in ResearchTriangle Park, North Carolina, formedical coding and data entry.

Medical Coding and DataEntry

For the 1965–97 survey years allmaterials sent from the Census RegionalOffices were processed by the Divisionof Data Processing at the NCHS facilityin Research Triangle Park, NorthCarolina. Beginning with the 1998NHDS survey year these activities arebeing done by a contractor. SampleListing Sheets and abstracts received byNCHS are recorded and tracked througha receipt and control process to monitordata flow and completeness. During thisprocess, batches consisting ofapproximately 1,000 abstracts areformed and identified to track andconduct medical coding, data entry, andquality control

Trained medical coding personnelcode diagnoses and procedures using theICD–9–CM. A minimum of one and amaximum of seven diagnostic codes areassigned for each sample abstract. If anabstract included surgical and/ordiagnostic procedures, a maximum offour codes are assigned.

Beginning in 1986 annualmodifications or addenda have beenmade to the ICD–9–CM. Theseaddenda, which go into effect onOctober 1 of each year, added, deleted,or modified existing codes. However,because the NHDS is conducted forcalendar years, the addenda are notincorporated into the manual codingprocess until the next survey year(beginning January 1, 3 months after theeffective date). This results in consistentcoding for all medical data for thecalendar survey year.

There is quality control for medicalcoding and data entry. This procedure isbased on a 5-percent sample for eachbatch (group of 1,000 abstracts) inwhich abstracts are independently codedby a second coder, with discrepanciesadjudicated by a chief coder. Batches for

which the quality control sample havean error rate greater than 5 percent formedical data or 1 percent fornonmedical data are rejected andrecoded. The overall error rate forrecords manually coded for the 1997data year was 1.0 percent for finaldiagnoses, 0.7 for surgical anddiagnostic procedures, and 0.2 percentfor nonmedical data entry.

Automated Data Collectionand Processing

Of the factors that influenced theredesign of the NHDS, the use ofdischarge data in computerized formhas had the greatest impact on theongoing operations of the survey.Because hospital participation isvoluntary, NCHS cannot requirehospitals or their intermediaries whosupplied discharge data in machinereadable form to comply with standardfile and variable formats. And, withlimited survey resources, NCHS cannotafford to have automated data sent toNCHS in a defined format. As a result,in many instances unique procedures forprocessing electronic files weredeveloped, and these procedures havebeen subject to regular change as thesources of data changed. What becameknown as ‘‘ automated’’ data collectionin NHDS has been a dynamic process.This section provides background to anda general description of NHDSautomated data collection and itsprocessing.

Background

The concept of collecting data onhealth encounters through existingelectronic systems was formalized in the1970’s as part of the NCHS’sCooperative Health Statistics System(CHSS). The CHSS operated under thelegislative authority of the HealthServices Research, Health Statistics, andMedical Libraries Act of 1974 (PublicLaw 93–353) (15). A major emphasis ofthe CHSS was national data collectionthrough a ‘‘ bottom-up’’ cooperativearrangement, a system in which datawould be collected once, processedinitially at the State level, and submittedto the Federal level in machine readable

form to provide national data. Duringthe 1970’s, under the CHSS, NCHSfunded hospital discharge demonstrationprojects in 12 States. This activity endedat NCHS in February 1979, by adecision of the Secretary of Health,Education, and Welfare (16).

A general evaluation study of theNHDS conducted in the mid-1970’s (17)recommended that the NHDS collectdata from three frames: 1) hospitalscovered by the CHSS, 2) non-CHSShospitals that were members of a privateabstracting system, and 3) all otherhospitals for which no special datasource was available. In order toimplement a plan that incorporatedautomated data collection, two majorissues needed to be addressed: theavailability and quality of data fromthese sources. The evaluation studyconcluded that all the NHDS data items,with the exception of marital status,were widely available from automatedsources.

Studies conducted in the late 1970’son the reliability of hospital dischargeabstract service data (18) and on thereliability of the NHDS data (19)showed that data collected fromhospitals for discharges by abstractservices met and in some casesexceeded standards of data qualitytraditionally held by NCHS. Morerecently there has been evidence ofimprovement in the general quality ofhospital discharge data files as thisinformation became important fordetermining reimbursement by Medicareand other payers (20–22).

NCHS funded two studies on theoperational aspects of collecting data inelectronic form from abstract services.The first study, initiated in 1980 (23),focused on the suitability of purchasingand using data from discharge abstractservices in the NHDS. One of thefindings from this study was that thepurchase of data could greatly reduce,but not eliminate, the need for directdata collection. In 1981 approximately60 percent of hospitals in the UnitedStates subscribed to discharge abstractservice systems that serviced 10 or morehospitals. Without covering the universeof hospitals, these systems could notprovide a representative sample of allhospitals in the United States.

Under the second study, NCHSinitiated a demonstration project in 1984(24) to develop procedures foracquiring, processing, and validating thequality of existing discharge data inelectronic form. Under this contractautomated data were collected fromcommercial abstract services for 76hospitals that participated in the NHDS.Estimates from NHDS based on datacollected by both means (manual andautomated) produced comparable results(25). The study also demonstrated thatabstracting service organizations couldcomply with data delivery schedulesnecessary for NHDS. Based on theresults of this study, NCHS began to usedata in automated form in the 1985NHDS.

For the 3 years, 1985–87, NCHSacquired existing automated inpatientdata for some NHDS hospitals under acontract with the Center for HealthPolicy Studies (CHPS). CHPS providedNCHS with a census file for alldischarges for 78, 77 and 74 hospitals,respectively, for each of these years andNCHS sampled records from these filesbased on the sample design for manualdata collection.

Beginning in 1988 purchasing andprocessing of data in automated formwas conducted by NCHS. Automateddata collection increased to includeabout 170 hospitals annually (table B)and the design specifications providedfor a greater number of sampledischarges from hospitals that provideddata in machine readable form.

Data Sources

In 1987 NCHS requested client listsfrom 22 major hospital dischargeabstracting services. These lists wereused to identify the abstract service forhospitals sampled in the NHDS. Of the542 hospitals sampled for the 1988NHDS, 240 or 44.4 percent, used atleast one of these services.

Changes in computer technologyand the transition of automated datafrom commercial services to State-basedsystems resulted in a dynamic andevolving system for processingautomated data. The mix of thesesources changed dramatically from 1988to 1997: by 1997, most of the 22

commercial abstract processingorganizations used for the 1988 NHDShad either closed or transformed to aState-based system (hospitalassociations, State departments of healthand State contractors). State-basedsystems accounted for approximately95 percent of all machine readable dataused in the 1997 NHDS. In 1997 theNHDS collected automated data from 20different automated data systems and 12individual hospitals directly. Of the 20systems, 16 were State systems, 2 werecorporate owned, and 2 werecommercial abstract companies.

With some exceptions, automateddata sources other than individualhospitals (abstract services, hospitalassociations, and State organizations)were bound by contracts with theirclient hospitals or by State laws toobtain permission from hospitals beforethey could release data to NCHS. Thisrequired NCHS to go through a two-stepprocess in order to obtain data fromthese sources. First, NCHS had tosecure permission from each hospital toallow the automated data source torelease the hospital’s data to NCHS.Second, NCHS had to negotiate andestablish a formal relationship with eachautomated data source about issuesrelated to purchasing data files. Forpurchasing data from individualhospitals, elements of the process weresimilar, but the process was conductedwith a single entity—the hospital.

Data Release Agreements—Hospitals

To obtain data release agreementsfrom hospitals, NCHS sends anintroductory letter and packet ofinformation to each hospital to solicittheir participation in the survey. Thepacket contains a release agreement(appendix VIII), information about theNCHS and NHDS, an endorsementletter from the American HospitalAssociation (appendix III), selectedendorsements from State hospitalassociations, and recent publicationsfrom the National Center for HealthStatistics using data from the NHDS.

An initial telephone call by theNCHS staff is made to explain therelease request and obtain the name of

the hospital administrator. If the releaseform is not returned within 2 weeks, thehospital receives a follow-up telephonecall. The Census Bureau is advised ofall hospitals that were late or refused therequest, and they performed a finalfollow up with the hospital to obtain arelease form. At this stage a meetingwith the hospital administrator is usuallyrequired to obtain the hospital’scooperation. For individual hospitalsthat supply automated data directly toNCHS, this is the only agreement that isneeded. For hospitals that agree to havea third party release their data to NCHS,a copy of the release agreement betweenNCHS and the hospital are forwarded tothe organization that maintains thehospital’s discharge data.

Data Release Agreements—Automated Discharge DataSources

NCHS established standardguidelines and formal agreements(appendix IX) for purchasing hospitaldischarge data from medical recordabstract service organizations. Theseagreements delineated unit record costs,startup programming costs, deliveryschedules, tape formatting instructions,record layouts, field and data elementdefinitions, and assurances ofconfidentiality. Confidentiality issues inthese agreements work to each party’sbenefit: to ensure hospitals that NCHSwould not release identifyinginformation, and to protect NCHS fromthe automated data sources divulging theidentity of hospitals that participated inthe NHDS. Whenever possible releaseswere negotiated for multiple years orwere open ended to reduce theadministrative resources needed torenegotiate annually.

Beginning in 1993 NCHSincorporated nonconfidential data filesfrom State discharge data sources.Hospital release agreements were notrequired from these sources because thedata were not confidential and the datawere for research and statistical use. Forthese files NCHS receives somevariables in a modified form to ensureconfidentiality. For example, exactadmission and discharge dates arereplaced with length of stay, and exact



birth date is replaced with the patient’sage. Data were obtained for 110hospitals from nonconfidential sourcesfor the 1997 NHDS.

File Processing

Automated files of discharges andaccompanying documentation are sentdirectly to NCHS. Individual hospitalsalso provide statistical information aboutthe volume of discharges per month ona transmittal notice (appendix X) that isused in the estimation process.

NCHS developed a recommendedfile layout with variable structures(appendix XI) and processingprocedures for submission of automateddata. However, as a voluntary survey,NCHS does not have authority torequire the submission of data, itsstructure, or the form of its submission.To keep the hospital response rate ashigh as possible, NCHS is flexible in itsreceipt of automated data. As a result,electronic files are sent to NCHS onvarious media (cartridge tapes, reeltapes, CD-ROM, diskettes, and asE-mail attachments); in ASCII orEBCDIC; in various layouts andblocking factors; for varying timeframes (quarterly, semiannually, andannually); and often with uniquevariable structures. In addition,automated data files are accepted as acensus or sample of discharges. Censusfiles contain all discharges fromhospitals and sampling is performed byNCHS (see Statistical Design). Samplefiles consist of discharges that sampledby the automated source prior tosubmission to NCHS based on samplingspecifications provided by NCHS (seeStatistical Design). In all, NCHSreceives approximately 2,000,000discharges in automated form each yearfrom about 35 different sources onapproximately 60 physical files.

The variety of file formats and datastructures precludes a uniform systemfor processing. NCHS developed andregularly modifies a process torestructure variables to commondefinitions, reformat files to a commonlayout, and to evaluate the quality of allautomated data. Evolution of the fileprocessing system resulted in manyadjustments to individual data files

depending on the problems encountered.Some activities or functions were usedonce for a single file while others havebeen used across years. The generalcharacteristics of this process aredescribed below. The goal was toproduce files containing data ofacceptable quality in a single formatwith identical variable definitions.

Each automated file is copied to amainframe computer and compared withthe previous year submission from thatdata source for changes in internal andexternal characteristics. If a file fails tocopy correctly, further investigation isconducted using a program to displaythe encoding structure, density, internallabeling, blocking, and record length ofthe file, and also to detect the existenceof extraneous data. If a file is physicallyunusable, NCHS requested areplacement and the process begananew.

After a file is determined to bephysically usable, a specific program isused for each file that is not in therecommended NCHS format to reformatall data elements to a uniform formatwith uniform data structures. At thispoint automated files are examined todetect and remove duplicate recordswithin hospitals.

Next, all ICD–9–CM codes on thefile are subjected to an annually updatedprogram that converts the ICD–9–CMaddenda effective on October 1 of thesurvey year back to valid codes beforeOctober 1 of the survey year. Thisprocess was required to make fiscal yearICD–9–CM codes compatible withcalendar year codes for the NHDS.Also, there were instances in whichhospitals had not properly instituted theaddenda from previous years andsubmitted files that contained codes thatwere no longer in use. A computerprogram was developed that changed alloutdated codes from previous years tovalid current-year codes. The firstprocess, changing the addenda to NHDSsurvey year codes, affected thousands ofcodes annually because it covered codesfrom all automated discharges for thelast quarter of the survey year; thesecond process involved very few codesand none in some years.

All records are checked for invalidor missing variables, inaccuracies,

outliers, and a detailed review isconducted for most variables for eachhospital. For diagnoses and procedurescodes, the review process generated alist of invalid ICD–9–CM codes,first-listed and all-listed diagnoses, the25 most frequently occurring diagnosesand procedures by age group, and thedistribution of discharges for all patientsby chapters of the ICD–9–CM. For allother variables the review involves acomparison of distributions for thecurrent year with data from previousyears. This review detected potentialproblems. If the problems cannot befixed at NCHS, a corrected file isrequested.

The final product of theseprocessing operations are files in astandard format with identical variablestructures, valid survey-year ICD–9–CMcodes, and data of acceptable quality.Using these files, data from hospitalsthat provided a census of discharges aremerged to form a single file forsampling (see Statistical Design).

To avoid disruption of the flow ofautomated data for the NHDS, NCHSneeds timely information about hospitalsthat changed or discontinued theirabstract service. Early knowledge ofthese changes provides time to obtainthe necessary data release agreementswith these hospitals and their newabstract service in time to process thedata. To learn about these changes,NCHS initiated semiannual contactswith each automated hospital asrecommended (24). In its initial formthis process was envisioned to beconducted by sending postcards tohospitals. The hospitals would completethe questions and mail theself-addressed, stamped postcard toNCHS. However, using actual postcardscould not be accomplishedadministratively, so letters are used(appendix XII).

This activity has evolved to providea measure of the completeness of databeing collected for each automatedhospital. In 1997 it was conductedsemiannually to get information directlyfrom automated hospitals to validatetheir total number of discharges,numbers of newborns, and total hospitalbeds.


Editing

Extensive computerized edits areapplied to each record. The computeredits are augmented by a manual reviewof selected records rejected by the editprogram. The edits include validity andrange checks for nonmedical variables,and consistency checks for dates ofadmission, discharge and birth. Themedical data (diagnoses and procedures)are verified against a list of all validICD–9–CM codes. Invalid ICD–9–CMcodes are removed. The edit performs aseries of consistency tests from decisionlogic tables for sex-specific andage-specific ICD–9–CM codes. Whenthe sex or age of a patient isincompatible with the recorded medicalinformation, priority is given to themedical information.

With two exceptions, the order ofdiagnoses and procedures for sampleddischarges is preserved to reflect theorder on the medical record face sheetor in the automated file. One exceptionis for women admitted for delivery forwhom a code of V27 from thesupplemental classification is assignedas the first-listed code in order toprovide an estimate of all deliveries. Inthe other exception, whenever an acutemyocardial infarction is present withanother circulatory diagnosis and isother than the first-listed diagnosis, it isreordered to the first position.

The computerized edit processidentifies some records for manualreview: records with ICD–9–CM codesthat are not valid as first-listed orsingle-listed codes; all records withlengths of stay longer than 100 days;records that indicate a delivery with alength of stay over 30 days; and allrecords with age equal to or greater than100 years. A nosologist at NCHSexamines these records and makeschanges as appropriate to eliminategross inconsistencies. In 1997, 276records were identified for manualreview.

Imputation

Before 1996 missing values of ageand sex were imputed by using randomassignment with female being assignedfirst for sex and a decision-logic table

was used to impute age. Beginning withthe 1996 NHDS a hot deck method formissing values of age and sex has beenused that maintains the known age orsex distribution of records within thesame 3-digit level of first-listedICD–9–CM diagnostic code.

Estimation Procedures

S tatistics from the NHDS arederived by a multistage estimationprocedure that produces

essentially unbiased national estimatesand has three basic components:inflation by reciprocals of theprobabilities of sample selection,adjustment for nonresponse, andpopulation weighting ratio adjustments.The second and third components aremade separately by admissiontypes—that is, for discharges ofnewborn infants (whose hospital staybegan with their own birth) and fordischarges other than newborn infants.

Inflation by Reciprocals ofProbabilities of Selection

The first two probabilities of thethree-stage sample design for the NHDSare known and fixed (see StatisticalDesign). However, the number ofdischarges for individual months is notalways constant or an integral multipleof the sampling fraction. For thesereasons, in the estimation process, thisprobability is the ratio of the actualnumber of discharges per month to thenumber of sampled discharges for themonth.

Adjustment forNonresponse

NHDS estimates are adjusted toaccount for nonresponse at two levels:hospitals and discharges withinhospitals. Within hospital adjustmentsare made for nonresponding months andwithin months for nonrespondingdischarges.

Hospital nonresponse occurs whenan in-scope (NHDS-eligible) samplehospital does not respond for at least

one-half of the months during which itwas in scope. In this case, the weightsof discharges from hospitals similar tothe nonrespondent hospitals are inflatedto account for discharges represented bythe nonrespondent hospitals. For thispurpose, hospitals are judged to besimilar if they are in the same region,hospital specialty-size group, and ifpossible, the same sampling stratum(that is, the same abstracting statusgroup if the nonrespondent hospital wasin the 12 largest PSU’s and in the samePSU, otherwise).

The adjustments for thisnonresponse are made separately foradmission types— that is, for dischargesof newborn infants and for all otherdischarges. The adjustment consists of aratio for which the numerator is theweighted number of discharges of theadmission type in all similar samplehospitals (regardless of response status)and the denominator is the weightedtotal of discharges of that admissiontype from the respondent hospitalssimilar to the nonrespondent hospitals.Data on the number of discharges foreach admission type for each hospitalcome from either the hospitals or theApril SMG Hospital Market Databasefor the survey year.

At the discharge level, respondinghospitals have a month(s) ofnonresponse when the number ofdischarges received for the month wasless than one-half of the expectednumber of discharges. For a hospital’smonth(s) of nonresponse, the weights ofdischarges in the hospital’s respondentmonths are inflated by ratios that variedwith discharge groups defined by theICD–9–CM diagnostic classes of thosedischarges’ fi rst-listed diagnoses. Theadjustment ratio for each partiallyrespondent hospital and each dischargegroup is calculated using only data fromsample hospitals that were NHDSeligible and respondent for all 12months of the data year. The ratio has asits numerator the weighted sum ofdischarges in that discharge group for allmonths in which the partially respondenthospital was in scope. The ratio has asits denominator the weighted sum ofdischarges in that discharge group thatoccurred in the months when the


partially respondent hospital did respondto the NHDS.

Discharge nonresponse also occurswhen NCHS fails to collect all of thedischarge abstracts expected for a month(the number expected was the productof the hospital’s total discharges eachmonth and the discharge sampling rateassigned to the hospital). In each monthwhen the hospital was respondent (atleast one-half of the expected abstractswere collected), the weights of abstractscollected for the month are inflated toaccount for the missing abstracts.

Population WeightingRatio Adjustment

The final adjustment consists of apopulation weighting ratio adjustmentthat is applied separately for newbornsand for other than newborns. Theseadjustments are made within each of 16noncertainty hospital groups defined byregion and hospital specialty-size classesto adjust for oversampling orundersampling of discharges reported inthe sampling frame for the data year.For discharges other than newborninfants, the adjustment is amultiplicative factor that has as itsnumerator the number of admissionsreported for the year at sampling framehospitals within each region-specialty-size group and as its denominator theestimated number of those admissionsfor that same hospital group. Theadjustment for discharges of newborninfants is similar, but numbers of birthsare used in place of admissions. Theratio numerators are based on the figuresobtained annually from the SMGHospital Market Database and the ratiodenominators are obtained through asimple inflation of the SMG figures forthe NHDS sample hospitals. NCHSperforms a review for outliers found bycomparing the SMG Hospital MarketDatabase file for the current andprevious years. The object of this reviewis to allow detection of potentialsystematic problems and to correct thefile prior to weighting.

Reliability ofEstimates

Because the statistics from thesurvey are based on a sample,they may be different from the

figures that would have been obtained ifa complete census had been taken usingthe same forms, definitions, instructions,and procedures. However, theprobability design of the NHDS permitsthe calculation of sampling errors. Thestandard error of a statistic is primarilya measure of sampling variability thatoccurs by chance because only a samplerather than the entire population issurveyed. The standard error, ascalculated for the NHDS, also reflectspart of the variation that arises in themeasurement process, but does notinclude any systematic bias that may bein the data. The relative standard error(RSE) of an estimate is obtained bydividing the standard error by theestimate itself and when multiplied by100 is expressed as a percent of theestimate. Generally, in tables of NCHSpublished data reports, an asterisk (*) isused to indicate the relative unreliabilityof estimates based on fewer than 30records or records that have a relativestandard error greater than 30 percent.

In repeated samples using the sameforms and procedures, the chances areabout 68 in 100 that an estimate fromthe sample would differ from a completecensus by less than the standard error.The chances are about 95 in 100 thatthe difference would be less than twicethe standard error, and about 99 in 100that it would be less than 2.5 times aslarge.

Estimation of StandardErrors

Beginning with the 1988 NHDS,estimates of sampling variability for theNHDS statistics presented in NCHSpublications have been computed usingsoftware that produces error estimatesfor statistics from complex sample

surveys. The software employs afirst-order Taylor Series approximationof the deviation of estimates from theirexpected values. A description of thissoftware and the approach it uses hasbeen published (6,7).

Standard ErrorApproximations

Parameters for calculatingapproximate relative standard errors foraggregate estimates are presented intable C. To derive error estimates thatwould be applicable to a wide variety ofstatistics, numerous estimates and theirvariances are produced. A least-squaresmethod is then used to produce best-fitcurves, based on the empiricallydetermined relationship between the sizeof an estimate X and its relativevariance. The relative standard error ofan estimate X [RSE(X)] is the squareroot of the relative variance and may becalculated from the formula:

RSE(X) = √a + b/X

with a and b provided in table C. Whenmultiplied by 100, the RSE(X) isexpressed as a percent of X.

For example, in 1997 the estimatednumber of discharges from short-stayhospitals for females with a first-listeddiagnosis of atherosclerotic heart disease(ICD–9–CM code 414.0) was 384,000.Using the applicable constants fromtable C for estimates by sex produces:

RSE�384,000� =

√.00127 + (325.984/384,000)

RSE(384,000) = .046

When multiplied by 100, therelative standard error for the estimateof interest becomes 4.6 percent. Thestandard error of the estimate isobtained by multiplying the relativestandard error by the estimate itself:

SE(384,000) = 384,000 * .046 = 17,664

The standard error can be employedto generate confidence intervals forstatistical testing. In this example, the95 percent confidence interval for the

Table C. Estimated parameters for approximate relative standard error equations, by selected characteristics: National Hospital DischargeSurvey, 1997

First-listed diagnosis Days of care All-listed diagnosis All-listed procedures

a b a b a b a b

Total . . . . . . . . . . . . . . . . . . . . . 0.00132 313.983 0.00242 1,036.029 0.00271 428.987 0.00288 323.247

Sex

Male . . . . . . . . . . . . . . . . . . . . . 0.00148 335.128 0.00299 1,309.507 0.00214 307.917 0.00268 380.213Female . . . . . . . . . . . . . . . . . . . 0.00127 325.984 0.00252 1,060.275 0.00127 311.394 0.00197 299.725

Age group

Under 15 years . . . . . . . . . . . . . . 0.01470 181.262 0.02393 346.675 0.01617 223.921 0.02639 196.71915–44 years . . . . . . . . . . . . . . . . 0.00137 294.357 0.00285 934.043 0.00151 309.115 0.00219 305.57445–64 years . . . . . . . . . . . . . . . . 0.00138 301.320 0.00284 1,248.476 0.00290 370.245 0.00235 298.26765 years and over . . . . . . . . . . . . . 0.00147 343.779 0.00275 1,866.761 0.00144 361.717 0.00239 292.252

Region

Northeast . . . . . . . . . . . . . . . . . . 0.00384 195.564 0.00863 495.447 0.00592 239.709 0.00695 219.126Midwest . . . . . . . . . . . . . . . . . . . 0.00609 191.492 0.00866 481.071 0.00853 180.424 0.00870 163.190South . . . . . . . . . . . . . . . . . . . . 0.00369 320.084 0.00572 1,581.301 0.00307 341.005 0.00498 274.548West . . . . . . . . . . . . . . . . . . . . . 0.00513 338.516 0.01008 926.285 0.00508 378.827 0.00663 288.835

Race

White. . . . . . . . . . . . . . . . . . . . . 0.00300 314.704 0.00480 1,103.096 0.00357 314.530 0.00463 369.830Black . . . . . . . . . . . . . . . . . . . . . 0.00529 248.048 0.00822 875.877 0.00519 236.801 0.00662 225.180All other . . . . . . . . . . . . . . . . . . . 0.01770 200.033 0.02524 581.314 0.01615 224.604 0.02070 211.065Race not stated . . . . . . . . . . . . . . 0.01973 196.517 0.02387 394.423 0.02002 187.166 0.02126 142.769

Expected source of payment

Worker’s compensation . . . . . . . . . 0.00721 320.711 0.01413 896.903 0.01093 337.073 0.01143 270.432Medicare . . . . . . . . . . . . . . . . . . 0.00171 325.698 0.00301 1,822.158 0.00157 372.529 0.00264 297.577Medicaid. . . . . . . . . . . . . . . . . . . 0.00438 293.366 0.00709 685.261 0.00379 287.541 0.00540 282.342Payment not stated . . . . . . . . . . . . 0.00962 313.407 0.01966 1,484.182 0.01219 310.942 0.01814 248.591Other government payments . . . . . . 0.00181 278.864 0.00345 617.794 0.00199 299.815 0.00265 289.092Private insurance . . . . . . . . . . . . . 0.00373 265.383 0.00994 854.606 0.00415 281.681 0.00689 227.293Self-pay . . . . . . . . . . . . . . . . . . . 0.02771 94.095 0.03240 244.803 0.03212 127.947 0.03297 94.813No charge/other . . . . . . . . . . . . . . 0.01828 394.867 0.02548 1,488.967 0.01931 386.315 0.02059 388.354


estimate of female inpatients with afirst-listed diagnosis of atheroscleroticheart disease is:

(384,000 – 2 *17,664) <->(384,000 + 2 * 17,664)348,700 <-> 419,300

Relative Standard Errorfor Estimates of Percents

Approximate relative standard errorsfor estimates of percents may becalculated from table C also. Therelative standard error for a percent,100 p (0 < p< 1) may be calculated usingthe formula:

RSE�p) = √ b * (1–p) / (p * X)

where 100p is the percent of interest, Xis the base of the percent, and b is theparameter b in the formula for

approximating the RSE(X). The valuesfor b are given in table C. Whenmultiplied by 100, the RSE(p) isexpressed as a percent of theestimate, p.

For example, in 1997 the estimatednumber of discharges from short-stayhospitals that were female was18,647,000. This is 60.3 percent of theestimated 30,914,000 discharges for thatyear. Using the applicable constantsfrom table C for estimates by sexproduces:

RSE�.603� =

√325.984 * (1 – .603) / (.603 * 30914000)

RSE(.603) = .002635

When multiplied by 100, therelative standard error for the estimateof interest becomes .2635 percent. Fromthis the standard error is obtained by

multiplying the relative standard errorby the estimate itself:

SE(.603) = .603 * 0.002635 = .0016

The standard error can be employed togenerate confidence intervals forstatistical testing. In this example, the95 percent confidence interval for theestimate of the percent of femaleinpatients is:

(.603 – 2 * .0016) <-> (.603 + 2 * .0016).5998 <-> .6062or, equivalently, 59.98 percent <->60.62 percent

The SUDAAN software can be usedto compute specific standard errors forthe NHDS estimates from which relativestandard errors may be derived. Thefiles needed to use SUDAAN have notbeen publicly released because theycontain information that is confidential(however, recently these files havebecome available for analysis, see Data


Dissemination). The generalizedprocedure for approximating relativestandard errors for the NHDS describedabove is widely applicable for a varietyof statistics and cost efficient. As aresult, standard errors computed fromthe generalized curves should beinterpreted as approximate rather thanexact for any specific estimate.

Nonsampling ErrorsEstimates from the NHDS are

subject to nonsampling as well assampling errors, as are estimates fromany survey. For the NHDS nonsamplingerrors may include those due tosampling frame errors, hospitalnonresponse, missing abstracts, anderrors introduced at the time of datacollection or electronic data entry.Although the magnitude of thenonsampling errors cannot be computed,these errors were kept to a minimum byprocedures built into the operation ofthe survey.

Errors resulting from the exclusionof in-scope hospitals from the samplingframe are believed to be small becausethe hospitals excluded were hospitalsthat opened after the frame wasconstructed and, hence, they tend tohave few discharges relative to hospitalsthat were in the frame. Othernonsampling errors were kept to aminimum by training the data collectorsin sampling and data abstraction, qualitycontrol procedures, and edit checksdiscussed in the data processing section.Because the survey results are subject tosampling and nonsampling errors, thetotal error is larger than the errordue to sampling variability alone.

Data Dissemination

Data are available for all years ofthe survey, but the mechanismsfor data release have changed to

reflect the needs of data users and newtechnology. This section summarizes thecurrent methods of data release for theNHDS.

Summary data from NHDS havebeen published annually for three levelsof statistical detail: the Advance Data

From Vital and Health Statistics (26)utilizes a brief format for reporting ofinpatient statistics as soon as possibleafter the survey has been completed;more detailed summary statistics areavailable from Series 13 Vital andHealth Statistics (27); and dischargeestimates for individual ICD–9–CMdiagnostic and procedure codes havebeen published in Series 13, Vital andHealth Statistics (28). Series 13 Vitaland Health Statistics reports thatcombined ambulatory surgery andsurgery performed on hospital inpatientsfor 1994, 1995, and 1996 are available(29–31). In addition, there are reportscomparing hospital use in the UnitedStates and other countries under Series5, Comparative International Vital andHealth Statistics Reports; trend reportsunder Series 13, Vital and HealthStatistics; and, methodological reportsusing hospital survey data published inSeries 2, Vital and Health Statistics(32). Reports on topics of specialinterest have been published in AdvanceData From Vital and Health Statistics,Series 13 Vital and Health Statisticsreports, and in published journal articlesand papers presented at professionalmeetings (33–34). As resources permit,special tabulations and analyses areprovided to data requestors inside andoutside the Federal Government.

For each survey year, a public-usedata tape and documentation areprepared for distribution through theNational Technical Information Service(NTIS). NCHS has also produced amultiyear data file (1979–97), which isavailable on data tape and CD-ROM.For analysts interested in going beyondwhat is available in the public use files,NCHS has established a Research DataCenter that allows the use of SUDAANand linking NHDS data with othersources of information.

A Catalog of Publications and aCatalog of Public-Use Data Tapes fromthe National Center for Health Statisticsare available via the Internet (at:www.cdc.gov/nchswww/products/products.htm) or from NCHS (DataDissemination Branch, National Centerfor Health Statistics, 6525 BelcrestRoad, Room 1064, Hyattsville,Maryland 20782; Telephone (301)436–8500). Many of the publications,

data files and file documentationmentioned above are available at thisInternet site.

References

1. Origin, Program, and Operation of theU.S. National Health Survey. NationalCenter for Health Statistics. VitalHealth Stat 1(1). 1965.

2. Woolsey TD. ‘‘ Hospital Statistics fromthe U.S. National Health Survey.’’Presentation for Annual Conference forExecutives of Allied HospitalAssociation, Grand Hotel, MackinacIsland, Michigan. July 1963.

3. U. S. Bureau of the Census. Statisticalabstract of the United States: 1997.117th ed. Washington: 1997.

4. Simmons WR. Development of thedesign of the NCHS Hospital DischargeSurvey. National Center for HealthStatistics. Vital Health Stat 2 (39).1970.

5. Massey JT, Moore TF, Parsons VL,Tadros W. Design and estimation forthe National Health Interview Survey,1985–94. National Center for HealthStatistics. Vital Health Stat 2(110).1989.

6. Shah BV. SESUDAAN: Standard errorsprogram for computing of standardizedrates from sample survey data.Research Triangle Park, North Carolina.Research Triangle Institute. 1981.

7. Shah BV, Barnwell BG, Hunt PN,LaVange LM. SUDAAN user’s manual,release 5.50. Research Triangle Park,North Carolina: Research TriangleInstitute. 1991.

8. Haupt BJ, Kozak LJ. Estimates fromtwo survey designs: National HospitalDischarge Survey. National Center forHealth Statistics. Vital Health Stat13(111). 1992.

9. Shimizu I, Cole C. A comparison ofprecision between two- and three-stagedesigns for National Hospital DischargeSurvey. Proc Amer Statist Ass. SurveyResearch Methods Section. 1991.

10. SMG Hospital Marketing Group, Inc.Hospital market database. HealthcareInformation Specialists. Chicago,Illinois: 1987.

11. Moien M. The use of hospital dischargesurvey data to produce trend estimatesof hospital utilization. Proc AmerStatist Ass. Social Statistics Section.1978.

12. National Center for Health Statistics.International Classification of Diseases,

http://www.cdc.gov/nchswww/products/products.htm

1

1

1

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1

1

1

2

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9th Revision, clinical modification.Washington: Public Health Service.1980.

3. Report of the U.S. Committee on Vitaland Health Statistics. Uniform hospitalabstract: minimum basic data set.National Center for Health Statistics.Vital Health Stat. 4 (14). 1975.

4. Department of Health and HumanServices. Health information policycouncil: 1984 revision of the uniformhospital discharge data set. Office ofthe Secretary. Federal Register; vol 50no 147. 1985.

5. Task Force on Definitions. Thecooperative health statistics system: Itsmission and program. National Centerfor Health Statistics. Vital Health Stat.4 (19). 1977.

6. Final of the Panel to Evaluate theCooperative Health Statistics System.Directions for the 80’s. National Centerfor Health Statistics. Hyattsville,Maryland: 1980.

7. Lissler JT. Hospital discharge surveyevaluation study. Contract NCHS255U-1178. Research Triangle Park,North Carolina: Research TriangleInstitute. 1977.

8. Institute of Medicine. Reliability ofhospital discharge abstracts.Washington: National Academy ofSciences. 1977.

9. Institute of Medicine. Reliability ofNational Hospital Discharge Surveydata. Washington: National Academy ofSciences. 1980.

0. Green J, Wintfeld N. How accurate arehospital discharge data for evaluatingeffectiveness of care? Med care31:719–31. 1993.

1. Fisher ES, Whaley FS, Krushat, et al.Accuracy of Medicare’s hospital claimsdata: Progress has been made, butproblems remain. Am J Public Health82:243–8. 1992.

2. Hsia DC, Ahern CA, Ritchie, et al.Medicare reimbursement accuracyunder the prospective payment system,1985 to 1988. JAMA 268:896. 1992.

3. Duggar BC, et al. Alternative sourcesfor producing national statistics onhospital utilization. Contract NCHS223–81-2057. JRB Associates. 1981.

4. Miller H, et al. Optional methods forcollecting data for the NationalHospital Discharge Survey. ContractNCHS 282–84-2107. Center for HealthPolicy Studies. 1984.

5. Tompkins L. Comparison of manuallyabstracted and automated abstractservice data in the 1984 NHDS.Unpublished paper prepared by the

Office Research and Methodology forreview within NCHS. 1989.

26. Graves GJ, Owings MF. 1996Summary: National Hospital DischargeSurvey. Advance data from vital andhealth statistics; no 301. Hyattsville,Maryland: National Center for HealthStatistics. 1998.

27. Graves GJ, Kozak LJ. NationalHospital Discharge Survey: Annualsummary, 1996. National Center forHealth Statistics. Vital Health Stat13(140). 1999.

28. Graves GJ, Kozak LJ. Detaileddiagnoses and procedures, NationalHospital Discharge Survey 1996.National Center for Health Statistics.Vital Health Stat 13(138). 1997.

29. Pokras R, Kozak LJ, McCarthy E.Ambulatory and inpatient procedures inthe United States, 1994. NationalCenter for Health Statistics. VitalHealth Stat 13(132). 1997.

30. Kozak LJ, Owings MF. Ambulatoryand inpatient procedures in the UnitedStates, 1995. National Center forHealth Statistics. Vital Health Stat13(135). 1998.

31. Kozak LJ, Owings MF. Ambulatoryand inpatient procedures in the UnitedStates, 1996. National Center forHealth Statistics. Vital Health Stat13(139). 1998.

32. Harris KW, Hoffman KL. Qualitycontrol in the Hospital DischargeSurvey. National Center for HealthStatistics. Vital Health Stat 2(68). 1975.

33. Pappas G, Hadden WC, Kozak LJ,Fisher GF. Potentially avoidablehospitalizations: Inequalities in ratesbetween U.S. socioeconomic groups.Am J Public Health 87(5):811–6. 1997.

34. Wilcox SW, Koonin LM, Pokras R, etal. Hysterectomy in the United States,1988–1990. Obstet Gynecol83(4):549–55. 1994.

Appendix I.

Legislative Authorization

Public Health Service ActSection 306(a) & (b)

NATIONAL CENTER FOR HEALTH STATISTICS

Section 306. [242k](a) There is established in the Department of Health and Human Services the National Center for HealthStatistics (hereinafter in this section referred to as the ‘‘ Center’’ ) which shall be under the direction of a Director who shall beappointed by the Secretary and supervised by the Assistant Secretary for Health (or such officer of the Department as may bedesignated by the Secretary as the principal adviser to him for health programs).

(b) In carrying out section 304(a), the Secretary, acting through the Center-(1) shall collect statistics on-(A) the extent and nature of illness and disability of the population of the United States (or any groupings of peopleincluded in the population), including life expectancy, the incidence of various acute and chronic illnesses, and infant andmaternal morbidity and mortality,(B) the impact of illness and disability of the population on the economy of the United States and on other aspects of thewell-being of its population (or of such groupings),(C) environmental, social, and other health hazards,(D) determinants of health,(E) health resources, including physicians, dentists, nurses, and other health professionals by specialty and type of practiceand supply of services by hospitals, extended care facilities, home health agencies, and other health institutions,(F) utilization of health care, including utilization of (i) ambulatory health services by specialties and type of practice ofhealth professionals providing such service, and (ii) services of hospitals, extended care facilities, home health agencies,and other institutions,(G) health care costs and financing, including the trends in health care prices and costs, the sources of payments forhealth care services, and Federal, State, and local governmental expenditures for health care services, and(H) family formation, growth, and dissolution;(2) shall undertake and support (by grant or contract) research, demonstrations, and evaluations respecting new or

improved methods for obtaining current data on the matters referred to in a paragraph (1);(3) may undertake and support (by grant or contract) epidemiologic research, demonstrations, and evaluations on the

matters referred to in paragraph (1); and ....‘‘(4) may collect, furnish, tabulate, and analyze statistics, and prepare studies, on matters referred to in paragraph (1) upon

request of public and nonprofit entities under arrangements under which the entities will pay the cost of the service provided.Amounts appropriated to the Secretary from payments made under arrangements made under paragraph (4) shall be availableto the Secretary for obligation until expended.


Appendix II

Induction Letter


Appendix III

American Hospital AssociationEndorsement Letter


Appendix IV

Confidentiality Letter


Appendix V

Hospital Interview Questionnaire (HDS-11)












Appendix VI

Medical Abstract—National Hospital Discharge Survey



Appendix VII

Sample Selection Sheet (HDS-5)


Appendix VIII

Statement of Agreement


Appendix IX

Abstract Service Agreement




Appendix X

Transmittal Notice


Appendix XI

Automated File Layout





Appendix XII

Information Request Letter



Appendix XIII

Definitions of TermsRelated to the Survey

Hospital—Hospital with an averagelength of stay of less than 30 days forall patients. Hospitals whose specialtywas general (medical or surgical) orchildren’s general were included,regardless of length of stay. Federalhospitals, hospital units of institutions,and hospitals with less than six bedsstaffed for patients’ use are not included.

Type of ownership of hospital—The type of organization that controlsand operates the hospital. Hospitals aregrouped as follows:

Not for profit—Hospital operated bya church or another not-for-profitorganization.

Government—Hospital operated byState and local government.

Proprietary—Hospital operated byindividuals, partnerships, or corporationsfor profit.

Inpatient—A person who isformally admitted to the inpatientservice of a short-stay hospital forobservation, care, diagnosis, ortreatment. The terms ‘‘ inpatient’’ and‘‘ patient’’ are used synonymously.

Newborn infant—A patient admittedby birth to a hospital.

Discharge—The formal release of apatient by a hospital; that is, thetermination of a period ofhospitalization by death or bydisposition to place of residence, nursinghome, or another hospital. The terms‘‘ discharges’’ and ‘‘ patients discharged’’are used synonymously.

Average length of stay—Thenumber of days of care accumulated bypatients discharged during the yeardivided by the number of thesedischarges.

Diagnosis—A disease or injury (orfactor that influences health status andcontact with health services that is notitself a current illness or injury) listedon the medical record of a patient.

Principal diagnosis—The conditionestablished after study to be chieflyresponsible for occasioning the

admission of the patient to the hospitalfor care.

First-listed diagnosis—Thediagnosis specified as the principaldiagnosis on the face sheet or dischargesummary of the medical record, or if theprincipal diagnosis is not specified, thediagnosis listed first on the face sheet ordischarge summary of the medicalrecord. The number of first-listeddiagnoses is equivalent to the number ofdischarges.

Procedure—A surgical ornonsurgical operation, diagnosticprocedure, or special treatment reportedon the medical record of a patient.

Rate of procedures—The ratio ofthe number of procedures during a yearto the number of persons in the civilianpopulation on July 1 of that yeardetermines the rate of procedures.

Population—The U.S. residentpopulation excluding members of theArmed Forces.

Age—Patient’s age at the birthdaybefore admission to the hospital.

Geographic region—Hospitals areclassified by location in one of the fourgeographic regions of the United Statesthat correspond to those used by theU.S. Bureau of the Census.

Region States included

Northeast Maine, New Hampshire,Vermont, Massachusetts,Rhode Island, Connecticut,New York, New Jersey,and Pennsylvania

Midwest Michigan, Ohio, Illinois,Indiana, Wisconsin,Minnesota, Iowa, Missouri,North Dakota, SouthDakota, Nebraska, andKansas

South Delaware, Maryland,District of Columbia,Virginia, West Virginia,North Carolina, SouthCarolina, Georgia, Florida,Kentucky, Tennessee,Alabama, Mississippi,Arkansas, Louisiana,Oklahoma, and Texas,

West Montana, Idaho, Wyoming,Colorado, New Mexico,Arizona, Utah, Nevada,Washington, Oregon,California, Hawaii, andAlaska

Vital and Health Statisticsseries descriptions

SERIES 1. Programs and Collection Procedures—These reportsdescribe the data collection programs of the National Centerfor Health Statistics. They include descriptions of the methodsused to collect and process the data, definitions, and othermaterial necessary for understanding the data.

SERIES 2. Data Evaluation and Methods Research—These reports arestudies of new statistical methods and include analyticaltechniques, objective evaluations of reliability of collected data,and contributions to statistical theory. These studies alsoinclude experimental tests of new survey methods andcomparisons of U.S. methodology with those of othercountries.

SERIES 3. Analytical and Epidemiological Studies—These reportspresent analytical or interpretive studies based on vital andhealth statistics. These reports carry the analyses further thanthe expository types of reports in the other series.

SERIES 4. Documents and Committee Reports—These are finalreports of major committees concerned with vital and healthstatistics and documents such as recommended model vitalregistration laws and revised birth and death certificates.

SERIES 5. International Vital and Health Statistics Reports—Thesereports are analytical or descriptive reports that compare U.S.vital and health statistics with those of other countries orpresent other international data of relevance to the healthstatistics system of the United States.

SERIES 6. Cognition and Survey Measurement—These reports arefrom the National Laboratory for Collaborative Research inCognition and Survey Measurement. They use methods ofcognitive science to design, evaluate, and test surveyinstruments.

SERIES 10. Data From the National Health Interview Survey—Thesereports contain statistics on illness; unintentional injuries;disability; use of hospital, medical, and other health services;and a wide range of special current health topics coveringmany aspects of health behaviors, health status, and healthcare utilization. They are based on data collected in acontinuing national household interview survey.

SERIES 11. Data From the National Health Examination Survey, theNational Health and Nutrition Examination Surveys, andthe Hispanic Health and Nutrition Examination Survey—Data from direct examination, testing, and measurement onrepresentative samples of the civilian noninstitutionalizedpopulation provide the basis for (1) medically defined totalprevalence of specific diseases or conditions in the UnitedStates and the distributions of the population with respect tophysical, physiological, and psychological characteristics, and(2) analyses of trends and relationships among variousmeasurements and between survey periods.

SERIES 12. Data From the Institutionalized Population Surveys—Discontinued in 1975. Reports from these surveys areincluded in Series 13.

SERIES 13. Data From the National Health Care Survey—These reportscontain statistics on health resources and the public’s use ofhealth care resources including ambulatory, hospital, and long-term care services based on data collected directly fromhealth care providers and provider records.

SERIES 14. Data on Health Resources: Manpower and Facilities—Discontinued in 1990. Reports on the numbers, geographicdistribution, and characteristics of health resources are nowincluded in Series 13.

SERIES 15. Data From Special Surveys—These reports contain statisticson health and health-related topics collected in specialsurveys that are not part of the continuing data systems of theNational Center for Health Statistics.

SERIES 16. Compilations of Advance Data From Vital and HealthStatistics—Advance Data Reports provide early release ofinformation from the National Center for Health Statistics’health and demographic surveys. They are compiled in theorder in which they are published. Some of these releasesmay be followed by detailed reports in Series 10–13.

SERIES 20. Data on Mortality—These reports contain statistics onmortality that are not included in regular, annual, or monthlyreports. Special analyses by cause of death, age, otherdemographic variables, and geographic and trend analysesare included.

SERIES 21. Data on Natality, Marriage, and Divorce—These reportscontain statistics on natality, marriage, and divorce that arenot included in regular, annual, or monthly reports. Specialanalyses by health and demographic variables andgeographic and trend analyses are included.

SERIES 22. Data From the National Mortality and Natality Surveys—Discontinued in 1975. Reports from these sample surveys,based on vital records, are now published in Series 20 or 21.

SERIES 23. Data From the National Survey of Family Growth—Thesereports contain statistics on factors that affect birth rates,including contraception, infertility, cohabitation, marriage,divorce, and remarriage; adoption; use of medical care forfamily planning and infertility; and related maternal and infanthealth topics. These statistics are based on national surveysof women of childbearing age.

SERIES 24. Compilations of Data on Natality, Mortality, Marriage,Divorce, and Induced Terminations of Pregnancy—These include advance reports of births, deaths, marriages,and divorces based on final data from the National VitalStatistics System that were published as supplements to theMonthly Vital Statistics Report (MVSR). These reports providehighlights and summaries of detailed data subsequentlypublished in Vital Statistics of the United States. Othersupplements to the MVSR published here provide selectedfindings based on final data from the National Vital StatisticsSystem and may be followed by detailed reports in Series 20or 21.

For answers to questions about this report or for a list of reports published inthese series, contact:

Data Dissemination BranchNational Center for Health StatisticsCenters for Disease Control and Prevention6525 Belcrest Road, Room 1064Hyattsville, MD 20782-2003

(301) 458-4636E-mail: [email protected]: www.cdc.gov/nchs/

http://www.cdc.gov/nchswww/

DEPARTMENT OFHEALTH & HUMAN SERVICES

Centers for Disease Control and PreventionNational Center for Health Statistics6525 Belcrest RoadHyattsville, Maryland 20782-2003

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