Scientific Data DocumentationNational Hospital Discharge Survey, 1999DSN: CC36.NHDS99
This material provides documentation for users of the 1999 NHDS Public Use Data File. The NHDS
is conducted annually by the National Center for Health Statistics (NCHS) and is a principal source of
information on inpatient hospital utilization in the United States.
Section I describes the survey and includes information on the history and scope of the NHDS; the
methodology, including data collection and medical coding procedures; population estimates; measurement
errors and sampling errors.
Section II provides technical details about the file.
Section III provides a detailed description of the contents of each data record.
Appendix Adefines certain terms used in this document; Appendix B lists the ICD-9-CM Addenda;
Appendix C provides population estimates to allow for the calculation of rates; Appendix D provides
unweighted and weighted frequencies for selected variables; and Appendix E shows copies of the
NHDS Medical Abstract Form.
Table Of Contents
Section I. Description of the National Hospital Discharge Survey
Section II. Technical Description of Data File
Section III. Record Layout: Location and Coding of Data Elements
Appendix A Definitions of Certain Terms Used in This Document
Appendix B ICD-9-CM Addenda
Appendix C Population Estimates
Appendix D Unweighted & Weighted Frequencies of Selected NHDS Variables
Appendix E Medical Abstract Form
I. Description of The National Hospital Discharge Survey
Introduction. This document and its appendices contain information for users of the 1999 National Hospitalfrom a national sample of non-Federal, short-stay hospitals. The data serve as a basis for calculating statistics
Discharge Survey (NHDS) public use data file. Conducted annually by the National Center for Health
Statistics, NHDS collects medical and demographic information from a sample of discharge records selected
on inpatient hospital utilization in the United States. For a description of the survey design and data collection procedures, see below. For a more detailed description of the survey design, data collection procedures, and the estimation process, see Reference 1. Publications based on the data for each survey year can be obtained from the NCHS website at: http://www.cdc.gov/nchs/about/major/hdasd/listpubs.htm
History. To provide more complete and precise information on the utilization of the Nation's hospitals and
on the nature and treatment of illness among the hospitalized population, in 1962 the NCHS began exploring possibilities for surveying morbidity in hospitals. A national advisory group was established. The NCHS conducted planning discussions with other officials of the Public Health Service. Hospitalization material from
the Survey Research Center of the University of Michigan, the American Hospital Association, and the Professional Activities Study was examined and evaluated. In 1963, a study by the School of Public Health
of the University of Pittsburgh under contract to the NCHS demonstrated the feasibility of an NHDS type of program. An additional pilot study using enumerators from the Bureau of the Census was conducted in late
1964 and confirmed the University of Pittsburgh's findings.
Finally, with advice and support from the American Hospital Association, the American Medical Association,individual experts, other professional groups, and officials of the U.S. Public Health Service, the NCHS
initiated the National Hospital Discharge Survey in 1964.
Source of the Data. The National Hospital Discharge Survey (NHDS) covers discharges from noninstitutional hospitals, exclusive of Federal, military, and Veterans Administration hospitals, located in the 50 States and
the District of Columbia. Only short-stay hospitals (hospitals with an average length of stay for all patients of
less than 30 days) or those whose specialty is general (medical or surgical) or children's general are included
in the survey. These hospitals must also have six or more beds staffed for patient use.
These criteria, used from 1988 through the current survey year, differ slightly from those used prior to 1988.Beginning in 1988, the NHDS sampling frame consisted of hospitals that were listed in the April 1987 SMG Hospital Market Data File (2), met the above criteria, and began accepting patients by August 1987. The hospital sample was updated in 1991, 1994, and 1997, to allow for hospitals that opened later or changed their eligibility status since the previous sample update. In 1999, the sample consisted of 513 hospitals. Of the 513 hospitals, 26 were found to be out-of-scope (ineligible) because they went out of business or otherwise failed to meet the criteria for the NHDS universe. Of the 487 in-scope (eligible) hospitals, 458 hospitals responded to the survey.
Sample Design and Data Collection. The NCHS has conducted the NHDS continuously since 1965. The original sample was selected in 1964 from a frame of short-stay hospitals listed in the National Master Facility Inventory (NMFI). That sample was updated periodically with samples of hospitals that opened later. Sample hospitals were selected with probabilities ranging from certainty for the largest hospitals to 1 in 40 for the smallest hospitals. Within each sample hospital, a systematic random sample of discharges was selected. A report on the design and development of the original NHDS has been published (3).
In 1988, the NHDS was redesigned to provide geographic sampling comparability with other surveys conducted by the NCHS; to update the sample of hospitals selected into the survey; and to maximize the
use of data collected through automated systems. As did the original design, the redesigned NHDS sample included with certainty the largest hospitals. The remaining sample of hospitals was based on a stratified, three-stage design. The first stage consisted of selecting 112 primary sampling units (PSU's) that comprised a probability subsample of PSU's used in the 1985-94 National Health Interview Survey. The second stage consisted of selecting non-certainty hospitals from the sample PSU's. At the third stage a sample of discharges was selected by a systematic random sampling technique.
These changes in the survey may affect trend data. That is, some of the differences between NHDS statistics based on the 1965-87 sample and statistics based on the sample drawn for the new design may be due to sampling error rather than actual changes in hospital utilization.
Two data collection procedures were used for the survey. The first was a manual system of sample selection
and data abstraction, used for approximately 60 percent of the responding hospitals. The second was an automated method, used for approximately 40 percent of the respondent hospitals, that involved the purchase
of computerized data files from abstracting service organizations, state data systems, or from the hospitals themselves.
In the manual system, the sample selection and the transcription of information from the hospital records to abstract forms were performed at the hospitals. Of the hospitals using this system in 1999, about 30 percent
had the work performed by their own medical records staff. In the remaining hospitals using the manual system, personnel of the U.S. Bureau of the Census did the work on behalf of NCHS. The completed forms, along
with sample selection control sheets, were forwarded to NCHS for coding, editing, and weighting.
For the automated system, NCHS purchased files containing machine-readable medical record data from
which records were systematically sampled by NCHS.
The Medical Abstract Form (Appendix E) and the automated data contain items relating to the personal characteristics of the patient, including birth date or age, sex, race, and marital status, but not name and
address; administrative information, including admission and discharge dates, discharge status, and medical record number; and medical information, including diagnoses and surgical and nonsurgical procedures. Since 1977, patient zip code, expected source of payment, and dates of surgery have also been collected. (The medical record number, date of birth, and patient zip code are confidential information and are not available
to the public).
Medical Coding and Edits. The medical information that was recorded manually on the sample patient
abstracts was coded centrally by NCHS staff. A maximum of seven diagnostic codes was assigned for each sample abstract. In addition, if the medical information included surgical or nonsurgical procedures, a maximum of four codes for these procedures was assigned. The system currently used for coding the diagnoses and procedures on the medical abstract forms as well as on the commercial abstracting services data files is the International Classification of Diseases, 9th Revision, Clinical Modification, or ICD-9-CM (4).
NHDS usually presents diagnoses and procedures in the order they are listed on the abstract form or obtained from abstract services; however, there are exceptions. For women discharged after a delivery, a code of V27 from the supplemental classification is entered as the first-listed code, with a code designating either normal or abnormal delivery in the second-listed position. In another exception, a decision was made to reorder some acute myocardial infarction diagnoses. If an acute myocardial infarction is listed with other circulatory diagnoses and is other than the first entry, it is reordered to first position. If a symptom appears as a first-listed code and a diagnosis appears as a secondary code, the diagnosis replaces the symptom which is moved back.
Following conversion of the data on the medical abstract to a computer file and combining it with the
automated data files, a final medical edit was accomplished by computer inspection and by a manual review
of rejected records. Priority was given to medical information in the editing decision.
A new edit program was developed for the NHDS and was implemented beginning in the 1996 data year. The updated edit program, while following the same general specifications as the previous edit program, was designed to make as few changes as possible in the data. Thus, there may be some minor anomalies in certain areas which would be apparent when examining data over time, performing trend analyses, or examining combinations of variables. Particular features of the new edit program which may affect certain variables are:
- An improved imputation procedure for missing age and sex data was developed, which maintains the known distribution of these variables, according to categories of the First-Listed Diagnosis.
- There is no longer a re-ordering of the procedure codes.
- Principal and additional expected sources of payment are no longer re-ordered, with one exception: "Self-Pay" is listed as the principal source only if there are no other sources, or the only other source is "Not Stated"; otherwise it must be listed after every other source (except "Not Stated").
- An arbitrary month of admission is no longer assigned to records received from abstract services which do not provide the exact date of admission and discharge.
Users of the National Hospital Discharge Survey (NHDS) diagnostic and/or procedure data, which is coded to the ICD-9-CM, must take into account annual ICD-9-CM addenda. The addenda lists new codes, new fourth or fifth digits to existing codes, as well as other modifications. Changes go into effect October 1 of the calendar year. A list of the changes for 1986 through 1998 are listed in Appendix B. All coding of the 1999 data is consistent with the ICD-9-CM and the addendum effective October 1, 1998. Information provided by automated systems for the last three months of 1999 which was coded using the October 1999 addendum was converted back to the previous code assignment. This was done in order to prevent NHDS data users
from mistaking partial year estimates for annual estimates. For more information about the ICD-9-CM, visit: http://www.cdc.gov/nchs/icd9.htm
The Uniform Hospital Discharge Data Set (UHDDS). Starting with 1979 data, the NHDS has followed guidelines of the Uniform Hospital Discharge Data Set (UHDDS) within the confines of its contractual
agreement with participating hospitals. The UHDDS is a minimum data set of items uniformly defined (4).
These items were selected on the basis of their usefulness to a broad range of organizations and agencies requiring hospital information, uniformity of definition, and general availability from medical records and
Population Estimates. Appendix C shows estimates of the civilian population of the United Stated as of
July 1, 1999, which have been provided by the U.S. Bureau of the Census. Figures are consistent with
national population estimates in US-99-SIS-7 (U.S. Population Estimates by Age, Sex, Race and Hispanic Origin: 1999) and have been adjusted for net underenumeration using the 1990 National Population
Adjustment Matrix. NOTE THAT PRIOR TO THE 1997 DATA YEAR, CENSUS ESTIMATES OF
THE CIVILIAN POPULATION PROVIDED WITH THE NHDS PUBLIC USE DATA FILE DOCUMENTATION WERE NOT ADJUSTED FOR THE UNDERCOUNT.
Confidentiality. Persons using the public use file agree to abide by the confidentiality restrictions thatdata. Specifically, they agree that, in the event of inadvertent discovery of the identity
accompany use of the
of any individual or establishment, then: (a) no use will be made of this knowledge; (b) the director of NCHS
will be advised of the incident; (c) the information that would identify the individual or establishment will be safe-guarded or destroyed, as requested by NCHS; and (d) no one else will be informed of the discovered identity.
Maintaining the confidentiality of survey respondents, whether individuals or establishments, is a responsibilityof NCHS as described in section 308(d) of the Public Health Service Act. As such it may be necessary for NCHS to block the release of data or modify variables that may, because of their unique nature, lead to inadvertent disclosure of the identity of a participating facility or respondent.
Measurement Errors. As in any survey, results are subject to nonsampling or measurement errors, which
include errors due to hospital nonresponse, missing abstracts, information incompletely or inaccurately recorded on abstract forms, and processing errors. A very small proportion, (less than one-half of one percent) of the discharge records failed to include the sex, age, or date of birth of the patient. If the hospital record did not state either the age or sex of patient, it was imputed by assigning an age or sex value according to the specifications described earlier. In a very few cases (about a quarter of a percent of the records), the age or sex was edited, because it was inconsistent with the diagnosis. Data on race were missing for 23.2 percent of the discharges, and no attempt was made to impute for these missing values.
Other edit and imputation procedures may have been applied to data in the NHDS collected in automated
Sampling Errors and Rounding of Numbers. The standard error is primarily a measure of sampling variability that occurs by chance because only a sample rather than the entire universe is surveyed. The relative standard error of the estimate is obtained by dividing the standard error by the estimate itself. The resulting value is multiplied by 100, so the relative standard error is expressed as a percent of the estimate. Estimates of
sampling variability were calculated with SUDAAN software, which computes standard errors by using a first-order Taylor series approximation of the deviation of estimates from their expected values. A description
of the software and the approach it uses was published by Bieler and Williams (6).
Relative Standard Errors for Aggregate Estimates
Parameters for calculating approximate relative standard errors for aggregate estimates are presented in
Table 1. To derive error estimates that would be applicable to a wide variety of statistics, numerous estimates and their variances were produced. A regression model was then used to produce best-fit curves, based on
the empirically determined relationship between the size of an estimate X and its relative variance. The relative standard error of an estimate X [RSE(X)] is the square root of the relative variance and may be calculated from the formula:
RSE(X) = SQRT(a + b/X)
with a and b provided in Table 1. When multiplied by 100, the RSE(X) is expressed as a percent of X.
For example, in 1999 the estimated number of discharges from short-stay hospitals for children under age 15 with a first-listed diagnosis of asthma (ICD-9-CM code 493) was 190,000. Using the applicable constantsfrom Table 1 for estimates by age produces:
RSE(190,000) = SQRT(.016494 + (223.07202/190,000))
RSE(190,000) = .133
When multiplied by 100, the relative standard error for the estimate of interest becomes 13.3 percent. The standard error of the estimate is obtained by multiplying the relative standard error by the estimate itself:
SE(190,000) = 190,000 * .133 = 25,270
The standard error can be used to generate confidence intervals for statistical testing. In this example, the 95% confidence interval for the estimate of children under age 15 with a first-listed diagnosis of asthma is:
(190,000 - 2*25,270) <-> (190,000 + 2*25,270)
139460 <-> 240,540
Relative Standard Error for Estimates of Percents
Approximate relative standard errors for estimates of percents may also be calculated from Table 1. Therelative standard error for a percent, 100p (0<p<1), may be calculated using the formula:
RSE(p) = SQRT(b * (1 - p)/(p * X))
where 100p is the percent of interest, X is the base of the percent, and b is the parameter b in the formulafor approximating the RSE(X). The values for b are given in Table 1. When multiplied by 100, the RSE(p) is expressed as a percent of the estimate, p.
For example, in 1999 the estimated number of discharges from short-stay hospitals who were women was19,384,000. This is 60.3 percent of the estimated 32,132,000 total discharges for that year. Using the applicable constants from Table 1 for estimates by sex produces:
RSE(.603) = SQRT(334.61786 * (1 - .603)/(.603 * 32,132,000))
RSE(.603) = .002618
When multiplied by 100, the relative standard error for the estimate of interest becomes .2618 percent. Thestandard error is obtained by multiplying the relative standard error by the estimate itself:
SE(.603) = .603* .002618 = .0016
The standard error can be used to calculate confidence intervals for statistical testing. In this example, the95% confidence interval for the estimate of the percentage of female inpatients is:
(.603 - 2*.0016) <-> (.603 + 2*.0016)
.600 <-> .606
or, equivalently,60.0% <-> 60.6%
Relative Standard Error for Ratio Estimators
The approximate RSE of a ratio (X/Y) in which the numerator (X) and the denominator (Y) are bothestimated from the same survey, but the numerator is not a subclass of the denominator, is calculated using the formula:
RSE(X/Y) = SQRT(RSE^2(X) + RSE^2(Y))
The approximation is valid if the RSE of the denominator is less than 5 percent or the RSE's of the numeratorand denominator are both less than 10 percent. When multiplied by 100, the RSE(X/Y) is expressed as a percent of the ratio estimate, X/Y.
For example, average length of stay (ALOS) is considered a ratio estimator since it is the ratio of days of careto the number of discharges. In 1999, the estimated number of days of care for inpatients with a first-listed diagnosis of septicemia (ICD-9-CM code 038) was 2,880,000. The estimated number of discharges for inpatients with a first-listed diagnosis of septicemia was 341,000. The ALOS for inpatients with a first-listed diagnosis of septicemia was 2,880,000/341,000 = 8.4.
To compute the RSE for ALOS, first compute the RSE for the estimated number of days of care and theRSE for the estimated number of discharges. See the section above on Relative Standard Errors for Aggregate Estimates for computation of these RSE's.
RSE(2,880,000) = .0543
RSE(341,000) = .0509
Next, substitute those RSE's into the formula above to approximate the RSE for the ALOS estimate:
RSE(8.4) = SQRT((.0543)^2 + (.0509)^2)
RSE(8.4) = .0744
The standard error of the estimate is obtained by multiplying the relative standard error by the estimateitself:
SE(8.4) = .0744 * 8.4 = .625
The standard error can be used to generate confidence intervals for statistical testing. In this example,the 95% confidence interval for the estimate of the ALOS for inpatients diagnosed with septicemia is:
(8.4 - 2*.625) <-> (8.4 + 2*.625)
7.2 <-> 9.7
Table 1. Parameter values for relative standard errors for National Hospital Discharge Survey aggregate statistics by statistic
type: United States, 1999
First-Listed Diagnoses Days Of Care All-Listed Diagnoses All-Listed Procedures Characteristic a b a b a b a b TOTAL 0.001560 352.57520 0.002604 1000.94965 0.003105 412.75822 0.003187 357.68835 Sex Male 0.001633 359.91941 0.002981 1317.06683 0.004093 363.50935 0.003464 340.74739 Female 0.001578 334.61786 0.002666 1087.27514 0.003769 326.47722 0.003684 301.79493 AGE GROUP Under 15 years 0.016494 223.07202 0.025039 652.94193 0.018165 238.34924 0.025237 253.97288 15-44 years 0.001763 325.12768 0.003308 1033.44779 0.001589 343.08995 0.002402 305.64621 45-64 years 0.002044 377.51124 0.003097 1341.59977 0.002337 337.00450 0.004366 273.42803 65 yrs and over 0.002189 338.47209 0.002729 2033.88218 0.002026 346.43798 0.003618 341.62920 REGION Northeast 0.005121 193.54615 0.010383 269.39682 0.007518 197.33709 0.007950 230.43315 Midwest 0.009636 233.35485 0.013644 402.06132 0.011474 211.10520 0.012990 172.54412 South 0.003298 353.03917 0.005486 920.65327 0.003989 367.90190 0.008102 286.55150 West 0.004267 367.67568 0.008367 937.57802 0.004568 435.54443 0.004604 393.92609 RACE White 0.003218 378.46118 0.004791 1075.68925 0.005559 360.32901 0.005553 380.84500 Black 0.005020 234.73077 0.008239 762.36274 0.006288 222.52892 0.005923 221.28609 All other 0.020995 206.99187 0.035926 392.14896 0.017983 259.86584 0.022261 198.53245 Races not stated 0.018749 207.20756 0.021876 500.99287 0.020816 253.87708 0.020675 190.69041 ESOP Worker's comp 0.006348 300.78076 0.015928 705.37934 0.013841 209.66859 0.011021 300.33297 Medicare 0.002403 359.96851 0.002831 2254.19975 0.002217 378.71125 0.004039 346.82800 Medicaid 0.005705 286.42727 0.008866 984.24642 0.004944 291.07709 0.006874 250.49644 Other govt payments 0.010600 418.69824 0.022286 1401.28715 0.014075 397.23982 0.015924 278.79531 Blue Cross/Blue Sheild 0.004729 325.28607 0.008610 858.57823 0.005580 274.67671 0.007490 242.45169 HMO/PPO 0.004863 254.38988 0.007955 653.22454 0.004699 302.20596 0.008370 243.86402 Other Private 0.006475 294.90796 0.010133 771.30294 0.007743 256.53531 0.008985 245.38001 Self Pay 0.004571 261.64669 0.008564 988.39877 0.005208 255.86421 0.007486 231.63889 No charge 0.142475 189.60576 0.130227 657.69115 0.140911 44.56661 0.202030 -154.27572 Other 0.036444 123.22139 0.043781 583.40580 0.031121 150.79087 0.047181 107.96191 Not Stated 0.031556 398.01751 0.041554 1243.12340 0.033433 386.28658 0.038255 333.15455
Users of NHDS data are cautioned that computed estimates based on fewer than 30 unweighted records are not reliable and should not be reported. Because these estimates are based on so few data points, they are excluded from the calculation of the generalized variance curves. Thus, application of generalized variance curves is appropriate only for estimates based on at least 30 records.
Presentation of Estimates. Publication of estimates for the NHDS is based on the relative standard errorof
the estimate and the number of sample records on which the estimate is based (referred to as the sample size). Estimates are not presented in NCHS reports unless a reasonable assumption regarding the probability distribution of the sampling error is possible.
Based on consideration of the complex sample design of the NHDS, the following guidelines are used forpresenting the NHDS estimates:estimate
If the sample size is less than 30, the value of the estimate is not reported.
If the sample size is 30-59, the value of the estimate is reported but should not be assumed reliable.
If the sample size is 60 or more and the relative standard error is less than 30 percent, the
If the relative standard error of any estimate is over 30 percent, the estimate is consideredto be
unreliable. It is left to the author to decide whether or not to present it. However, if the author
chooses to present the unreliable estimate, the consumer of the statistic must be informed that the
statistic is not reliable.
Monthly and Seasonal Estimates Under the New Design. An
important difference between the old and
new designs is the method used to adjust for nonresponse. In the old design, weights for responding
hospitals were adjusted each month to account for hospitals that did not respond for that month. In the new design, the type of nonresponse adjustment applied depended on whether the hospital was considered a nonrespondent or partial respondent. A nonresponding hospital was one which failed to provide at least
half of the expected number of discharges for at least half of the months for which it was in-scope. In this
case, weights of discharges from hospitals similar to the nonresponding hospital were inflated to account
for discharges of the nonrespondent hospital. However, this adjustment was performed just once, after the
close out of the survey for the year, instead of monthly as before.
For partially responding hospitals, one or both of two adjustments were made.
If the hospital provided at
least half, but not all, of the expected number of abstracts for a given month, the weights of the abstracts
actually collected for that month were inflated to account for the missing abstracts. If fewer than half of the expected number of abstracts were provided, the weights of the abstracts provided were inflated by a factor
of two, then a second adjustment was made to account for the excess nonresponse. In the second
adjustment, the weights of the discharges in the hospital's respondent months were inflated by ratios that
varied by category of first-listed ICD-9-CM diagnostic code. This adjustment ratio was based on the
hospital's month(s) of nonresponse and the month-by-month distributions of first-listed diagnostic groups
among discharges from hospitals which responded for all twelve months. The ratio accounts for the
seasonality in the occurrence of the first-listed diagnostic groups for annual statistics, but not for partial year estimates. As a result monthly and seasonal estimates may be skewed. While the effect is believed to be
small, it is recommended that
of the 458 responding hospitals provided data for all twelve months, and 95.9 percent provided at least nine months of data.
How to Use the Data File. The NHDS records are weighted to allow
inflation to national or regional
estimates. The weight applied to each record is found in location 21-25. To produce an estimate of the
number of discharges, the weights for the desired records must be summed. To produce an estimate for
number of days of care, the weight must be multiplied by the days of care (location 13-16) and these
products are summed. Average length of stay data can be obtained by dividing the days of care by the
number of discharges as calculated above.
Appendix D contains unweighted and weighted frequencies for selected variables. These may be used asa cross-check when analyzing NHDS data.
Diagnosis-Related Groups (DRGs). Many users of the NHDS data
have expressed an interest in converting
the medical data to DRGs. This has been done using DRG Grouper Programs obtained from the Health
Care Financing Administration. The DRGs and the DRG Grouper Programs were developed outside of the
National Center for Health Statistics; any questions about DRGs, other than specific questions about how
they relate to NHDS data, should be addressed elsewhere.
Questions. Questions concerning NHDS data should be directed to:
Jennifer R. Popovic, M.A.
Centers for Disease Control and Prevention
National Center for Health Statistics
Division of Health Care Statistics
Hospital Care Statistics Branch
6525 Belcrest Road, Room 956
Hyattsville, Maryland 20782
For more information about the NHDS, visit our website:
For email discussions and dissemination of NHDS data, join our Hospital
Discharge and Ambulatory
Surgery Data listserv (HDAS-DATA). In the body of an email message (leaving the subject line blank),
subscribe hdas-data Your Name
Send this message to:email@example.com
1 Dennison C,
Pokras R. Plan and Operation of the National Hospital Discharge Survey.
Center for Health Statistics. Vital Health Stat 1(39). 2000. http://www.cdc.gov/nchs/data/sr1_39.pdf
Marketing Group, Inc. Hospital Market Database. Healthcare Information
1342 North LaSalle Drive, Chicago, IL. 1987, April 1991, April 1994, April 1997.
3 Simmons WR,
Schnack GA. Development of the Design of the NCHS Hospital Discharge Survey.
Center for Health Statistics. Vital Health Stat 2(39). 1977.
Classification of Diseases, 9 th
Modification, 6 th edition.
Health and Humans Services, National Center for Health Statistics, Health Care Financing Administration.
5 Office of
the Secretary, Department of Health and Human Services: Health Information
Policy Council: 1984
Revision of the Uniform Hospital Discharge Data Set. Federal Register, Volume 50, No. 147. July 31, 1985.
6 Bieler GS,
Williams RL. Analyzing
Survey Data Using SUDAAN Release 7.5.
Research Triangle Institute:
Research Triangle Park, N.C. 1997.
II. Technical Description Of Data File
|Data Set Name||NHDS99PU.TXT|
|Number of Records||300,460|
III. Record Layout: Location and Coding of Data Elements
This section provides detailed information for each sampled record on the file, with adescription of each
item included on the record. Data elements are arranged sequentially according to their physical location
on the file. Unless otherwise stated in the Item Description, the data are derived from the abstract form or
from automated sources. The SMG Hospital Market Data File and the hospital interview are alternate
sources of data; some other items are computer generated.
Item Number of Number Location Positions Item description Code description 1 1-2 2 Survey Year 99 2 3 1 Newborn status 1=Newborn 2=Not newborn 3 4 1 Units for age 1=Years 2=Months 3=Days 4 5-6 2 Age in years, If units=years: 00-99* months, or days If units=months: 01-11 If units=days: 00-31 *Ages 100 and over were recoded to 99 5 7 1 Sex 1=Male 2=Female 6 8 1 Race 1=White 2=Black 3=American Indian/Eskimo 4=Asian/Pacific Islander 5=Other 9=Not stated 7 9 1 Marital status 1=Married 2=Single 3=Widowed 4=Divorced 5=Separated 9=Not stated 8 10-11 2 Discharge month 01-12=January to December 99=Missing 9 12 1 Discharge status 1=Routine/discharged home 2=Left against medical advice 3=Discharged/transferred to short-term facility 4=Discharged/transferred to long-term care institution 5=Alive, disposition not stated 6=Dead 9=Not stated or not reported 10 13-16 4 Days of care Use to calculate number of days of care. Values of zero generated by the computer from admission and discharge dates were changed to one.(Discharges for which dates of admission and discharge are the same are identified in Item Number 11) 11 17 1 Length of stay 0=Less than 1 day flag 1=One day or more 12 18 1 Geographic region 1=Northeast 2=Midwest 3=South 4=West 13 19 1 Number of beds, 1=6-99 recode 2=100-199 3=200-299 4=300-499 5=500 and over 14 20 1 Hospital ownership 1=Proprietary 2=Government 3=Nonprofit, including church 15 21-25 5 Analysis weight Use to obtain weighted estimates 16 26-27 2 First two digits 19 of survey year 17 28-32 5 Diagnosis code #1 * 18 33-37 5 Diagnosis code #2 * 19 38-42 5 Diagnosis code #3 * 20 43-47 5 Diagnosis code #4 * 21 48-52 5 Diagnosis code #5 * 22 53-57 5 Diagnosis code #6 * 23 58-62 5 Diagnosis code #7 * 24 63-66 4 Procedure code #1 * 25 67-70 4 Procedure code #2 * 26 71-74 4 Procedure code #3 * 27 75-78 4 Procedure code #4 * 28 79-80 2 Principal expected 01=Worker's comp source of payment 02=Medicare 03=Medicaid 04=Other government 05=Blue Cross/Blue Shield 06=HMO/PPO 07=Other private 08=Self-pay 09=No charge 10=Other 99=Not stated 29 81-82 2 Secondary expected Same coding as item 28 above source of payment 30 83-85 3 Diagnosis-Related Grouper version 16.0 Groups (DRG)
*Diagnosis and procedure codes are in compliance with the International Classification of Diseases, 9th Revision, Clinical Modification, (ICD-9-CM). For diagnosis codes, there is an implied decimal between positions 3 and 4. For E-codes, the implied decimal is between the 4th and 5th position. For inapplicable 4th or 5th digits, a dash is inserted. For procedure codes, there is an implied decimal between positions 2 and 3. For inapplicable 3rd or 4th digits, a dash is inserted.
Definition Of Terms
Terms relating to hospitals and hospitalization
Hospitals: Short stay hospitals or hospitals whose specialty is general (medical or surgical), or children'sgeneral. Hospitals must have 6 beds or more staffed for patients use. Federal hospitals and hospital units of institutions are not included.
Type of ownership of hospital: The type of organization that controls and operates the hospital. Hospitalsare grouped as follows:
Not for Profit: Hospitals operated by a church or another not for profit organization.
Government: Hospitals operated by State and local government.
Proprietary: Hospitals operated by individuals, partnerships, or corporations for profit.
Patient: A person who is formally admitted to the inpatient service of a short-stay hospital for observation, care, diagnosis, or treatment, or by birth.
Discharge: The formal release of a patient by a hospital; that is, the termination of a period of hospitalization by death or by disposition to place of residence, nursing home, or another hospital. The terms "discharges" and "patients discharged" are used synonymously.
Discharge rate: The ratio of the number of hospital discharges during the year to the number of persons in the civilian population on July 1 of that year.
Days of care: The total number of patient days accumulated at time of discharge by patients discharged from short: stay hospitals during a year. A stay of less than 1 day (patient admission and discharge on the same day) is counted as 1 day in the summation of total days of care. For patients admitted and discharged on different days, the number of days of care is computed by counting all days from (and including) the date of admission to (but not including) the date of discharge.
Rate of days of care: The ratio of the number of patient days accumulated at time of discharge to the number of persons in the civilian population on July 1 of that year.
Average length of stay: The total number of days of care accumulated at time of discharge by patients discharged during the year, divided by the number of patients discharged.
Terms relating to diagnoses and procedures
Discharge diagnoses: One or more diseases or injuries (or some factor that influences health status and contact with health services that is not itself a current illness or injury) listed by the attending physician on the medical record of a patient. In the NHDS, discharge (or final) diagnoses listed on the face sheet (summary sheet) of the medical record are transcribed in the order listed. Each sample discharge is assigned a maximum of seven five-digit codes according to ICD-9-CM (4).
Principal diagnosis: The condition established after study to be chiefly responsible for occasioning the admission of the patient to the hospital for care.
First-listed diagnosis: The coded diagnosis identified as the principal diagnosis or listed first on the face sheet of the medical record if the principal diagnosis cannot be identified. The number of first-listed diagnoses is equivalent to the number of discharges.
Procedure : One or more surgical or nonsurgical operations, procedures, or special treatments listed by the physician on the medical record. In the NHDS, all terms listed on the face sheet (summary sheet) of the medical record under the caption "operation," "operative procedures," "operations and/or special treatment," and the like are transcribed in the order listed. A maximum of four procedures are coded.
Rate of procedures: The ratio of the number of all-listed procedures during a year to the number of persons in the civilian population on July 1 of that year determines the rate of procedures.
Age: Refers to the age of the patient on the birthday prior to admission to the hospital inpatient service.
Population: Civilian population is the resident population excluding members of the Armed Forces.
Geographic regions : Hospitals are classified by location in one of the four geographic regions of the United States corresponding to those used by the U.S. Bureau of the Census:
U.S. Census Regions
|Vermont||Illinois||District of Columbia||Wyoming|
|Connecticut||Wisconsin||West Virginia||New Mexico|
|Rhode Island||Minnesota||North Carolina||Arizona|
|New York||Iowa||South Carolina||Utah|
TheInternational Classification of Diseases, 9th Revision, Clinical Modification, which has been used for coding NHDS data since 1979, undergoes annual updating. Assignment of new diagnostic and procedure codes, fourth and fifth digit expansion of codes, as well as code deletions, are contained in addenda developed by the ICD-9-CM Coordination and Maintenance Committee and approved by the Director of NCHS and the Administrator of the Health Care Financing Administration. Addenda to the ICD-9-CM become effective on October 1 of the calendar year and have been released for 1986 through 1999.
As described earlier in this document, the 1999 NHDS involved two data collection modes: manual and automated abstract services. All data collected manually were coded using the third edition of the ICD-9- CM, which includes the addenda for 1986 through 1998. Data collected via automated abstract services were coded using two different ICD-9-CM revisions. For the first 9 months of 1999, the ICD-9-CM including the addendum of October 1, 1986-98 was used; for the last 3 months the October 1999 addendum was used.
Therefore, data provided by automated systems for the last three months of 1999 was converted back to the code assignment under the October 1998 addendum. This was done in order to prevent NHDS data users from mistaking partial year estimates for annual estimates.
In order to assist users in data retrieval, a conversion table is provided to show the date of introduction of each new code and the previously assigned code equivalent, which had been used for reporting the selected diagnosis or procedure prior to issuance of the new code.
|Current code(s) assignment||Effective |
|Previous code(s) assignment|
|041.04 (code title restated)||1997||041.04|
042.0-042.2, 042.9, 043.0-043.3,|
043.9, 044.0, 044.9 (Codes deleted)
305.10, 305.11, 305.12,|
305.13 (Codes deleted)
|415.11||1995||997.3 & 415.1|
|435.3||1995||435.0 & 435.1|
|438.0||1997||294.9 & 438|
|438.10||1997||784.5 & 438|
|438.11||1997||784.3 & 438|
|438.12||1997||784.4 & 438|
|438.19||1997||784.5 & 438|
|438.20||1997||342.90 & 438|
|438.21||1997||342.91 & 438|
|438.22||1997||342.92 & 438|
|438.30||1997||344.40 & 438|
|438.31||1997||344.41 & 438|
|438.32||1997||344.42 & 438|
|438.40||1997||344.30 & 438|
|438.41||1997||344.31 & 438|
|438.42||1997||344.32 & 438|
|438.50-438.52||1997||344.89 & 438|
|438.81||1997||784.69 & 438|
|438.82||1997||787.2 & 438|
|440.23||1993||440.20 & 707.1 or 707.8 or 707.9|
|440.24||1993||440.20 & 785.4|
|441.6||1993||441.1 & 441.3|
|441.7||1993||441.2 & 441.4|
|458.2||1995||997.9 & 458.9|
|474.0 (code title restated)||1997||474.0|
|483.1||1996||078.88 & 484.8|
|574.60||1996||574.00 & 574.30|
|574.61||1996||574.01 & 574.31|
|574.70||1996||574.10 & 574.40|
|574.71||1996||574.11 & 574.41|
574.30 & 574.40
574.31 & 574.41
|574.90||1996||574.20 & 574.50|
|574.91||1996||574.21 & 574.51|
|575.12||1996||575.0 & 575.1|
|655.70 & 655.71||1997||655.8|
|Note: The title for the subcategory, 665.1 has been changed, making the fifth-digit subclassification 665.12 and 665.14 invalid.|
|677||1994||No previous code assignment|
|690.11||1995||691.8 & 704.8|
|795.71||1994||795.8 (Code deleted)|
|959.0 (code title restated)||1997||959.0|
|995.81 (code title restated)||1996||995.81|
|997.02||1995||997.9 & 430-434, 436|
|V08||1994||044.9, 795.8 (Codes deleted)|
|V09.0-V09.91||1993||No previous code assignments|
|V15.82||1994||305.13 (Codes deleted)|
(Note: Codes V29.3-V29.7 have not been
|V64.4||1997||No previous code assignment|
|V66.7||1996||No previous code assignment|
|V69.0-V69.3||1994||No previous code assignment|
|V69.8-V69.9||1994||No previous code assignment|
|E967.3||1996||No previous code assignment|
|Current code(s) assignment||Effective |
|Previous code(s) assignment|
|03.90||1987||03.99 (Insertion of Catheter)|
|33.27||1987||33.22 + 33.27|
|33.6||1990||33.5 + 37.5|
|36.06||1995||36.01, 36.02, 36.03, 36.05|
|36.09||1991||36.00 (Code deleted)|
|37.70 (Leads only)||1987||37.70 (Leads/Device)|
|37.71-37.72 (Leads only)||1987||37.74 (Leads/Device)|
|37.73 (Leads only)||1987||37.73 (Leads/Device)|
|37.74 (Leads only)||1987||37.76 (Leads/Device)|
|37.75 (Leads only)||1987||37.89 (Leads/Device)|
|37.76 (Leads only)||1987||37.81 (Leads/Device)|
|37.77 (Leads only)||1987||37.83-37.84 (Leads/Device)|
|37.80-37.87||1992||89.49 (Code deleted, this procedure is included in the code for pacemaker insertion/replacement)|
|37.80 (Device only)||1987||37.73-37.77 (Leads/Device)|
|37.81 (Device only)||1987||37.73-37.77 (Leads/Device)|
|37.82 (Device only)||1987||37.73-37.77 (Leads/Device)|
|37.83 (Device only)||1987||188.8.131.52 (Leads/Device)|
|38.44 (Abdominal Aorta Only)||1986||38.44 (Entire Aorta)|
|38.45 (Thoracic Aorta Added)||1986||38.44-38.45|
|41.05||1997||No previous code assignment|
|41.06||1997||No previous code assignment|
|45.16||1988||45.14 (45.15 before 1987)|
|45.75 (Hartmann Resection Added)||1988||48.66 (Code deleted)|
|46.13||1992||46.12 (Code deleted)|
|51.22||1991||51.21 (Code deleted), 51.22|
|51.97||1986||52.91,51.99, or 51.82|
|74.3||1992||69.11 (Code deleted)|
|77.56||1989||77.89, 78.49, 81.18|
|77.57||1989||77.89, 80.48, 81.18, 83.85|
|78.21 (Invalid code)||1991||78.11,78.31|
|81.54-81.55||1989||81.41 (Code deleted)|
|81.73-81.74||1989||81.86 (Code deleted)|
|81.75||1989||81.87 (Code deleted)|
|96.70||1991||93.92 (Code deleted)|
|96.71||1991||93.92 (Code deleted)|
|96.72||1991||93.92 (Code deleted)|
|98.51-98.52||1989||59.96 (Code deleted)|
|98.59||1989||59.96 (Code deleted)|