CDC-Data-2025/attachments/NHCS-DOCUMENTATION_AND_USERS_GUIDE_djvu.txt

National Hospital Care Survey - Research Data Center Documentation 


National Hospital Care Survey 
Research Data Center 


Documentation 


Last Updated: 09/27/2023 


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National Hospital Care Survey - Research Data Center Documentation 


Table of Contents 


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1. The National Hospital Care Survey Background................cscsscssscssscssccssscsssscssscssscsesssesssesessscssssssssssssssessoesees 4 
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3. Hospital Frame and Sample Design...............sccsccsssssssccsscssscssscssssssssnessssssesssessssssscssscscssscsssessssssssesssesesssesssesses 4 
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Abstract 


This document provides an overview of the National Hospital Care Survey (NHCS), NHCS datafiles available in 
the Federal and National Center for Health Statistics Research Data Centers (RDC), and analytic considerations 
for NHCS data users. NHCS is a national probability sample survey from the National Center for Health Statistics 
that collects hospital patient and encounter data from the inpatient and emergency department settings. Data are 
available in the RDC for calendar years 2013-2016, and 2019-2021. Beginning in 2020, preliminary NHCS data 
from selected hospitals are available in the RDC. The descriptions and analytic considerations in the RDC 
documentation apply to all NHCS survey years unless otherwise noted. For information on the available data 


variables for each year, please see: https://www.cdc.gov/rdc/b1datatype/dt1224h.htm 


Researchers interested in using NHCS data can develop a proposal, including a list of variables needed to create 
their research dataset, which will be delivered to researchers in the RDC upon approval. For more information on 
how to develop a proposal, please see: https://www.cdc.gov/rdc/b3prosal/pp300.htm. 


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1. The National Hospital Care Survey Background 


The National Hospital Care Survey (NHCS) provides data on health care utilization patterns in hospital-based 
settings. Data collection for NHCS began in 2011, integrating two long-standing National Center for Health 
Statistics (NCHS) surveys: 
e National Hospital Discharge Survey, the longest continuously fielded sample of inpatient care from 1965- 
2010; and 
e National Hospital Ambulatory Medical Care Survey, which has surveyed hospital emergency departments 
(ED) (1992-2022), outpatient departments (OPD) (1992-2017), hospital Ambulatory Surgery Locations 
(2009-2017), and freestanding Ambulatory Surgery Centers (2010-2017). 


The survey collects data on hospital encounters including diagnosis and procedure codes, length of patient stay, 
and patient demographics. NHCS also collects patient personal identifiable information (PII), allowing 
researchers to identify patients with multiple hospital encounters and link NHCS to external datasets. Encounter 
data is collected from the inpatient and ED settings, OPD data was collected from 2013-2016. 


NHCS sample includes non-federal non-institutional hospitals with six or more staffed inpatient beds in the 50 
states and the District of Columbia. Every three years the sample is updated to include newly opened hospitals. 
The 2011-2016 NHCS sample included 581 eligible hospitals. In 2019, the sample increased to 598 hospitals and 
608 hospitals in 2020. However, not all sampled hospitals provide data. As a result, the response rates for the 
2013-2016 and 2019 NHCS were not high enough to produce weighted national estimates. However, the 
response rates for 2020 and 2021 were high enough to produce national estimates for the 2020 and 2021 NHCS. 
Nationally representative data from the 2020 and 2021 NHCS are expected to be available very soon. 


Numerous scientific publications using unweighted NHCS data for healthcare research are available, and can be 
found here: https://www.cdc.gov/nchs/nhcs/data_uses.htm 


2. Advantages of the National Hospital Care Survey 


NHCS is a unique data source that contains longitudinal data on hospital utilization and patient care. Another 
unique aspect of NHCS is the data are publicly available to the researchers in the Federal and NCHS RDCs. With 
an approved proposal, researchers can access longitudinal data on millions of inpatient and ED encounters from 
participating hospitals. 


Due to the collection of PII, NHCS allows linkage of patients within survey years. Linkage capabilities also 
include the following: 
e Counting the number of encounters per patient; 
e Identifying the number of encounters in each hospital setting by patient; 
e Identifying ED patients who were transferred to the inpatient department; 
e Linking the NHCS to external datafiles that provide supplementary patient information not collected by 
the NHCS. 


3. Hospital Frame and Sample Design 


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The initial frame for NHCS was constructed in 2011 using the 2010 IQVIA hospital database (previously known 
as SDI, Verispan, SMG, IMS Health, and IMS Government Solutions). The initial frame file consists of 6,622 
non-federal and non-institutional hospitals with at least six staffed inpatient beds. From that initial file, a sample 
of 1,000 eligible hospitals were selected stratified by hospital bed size, type of hospital, and urban/rural 
designation. The initial sample of 1,000 hospitals was split into two groups of 500 — a base sample and a reserve 
sample. The base sample hospitals were selected for data collection and the reserve sample of hospitals were held 
to replenish the base sample if more hospitals were needed. 


In 2013, 81 general acute hospitals with at least 500 staffed inpatient beds from the reserve sample were added to 
the base sample for data collection. From 2013 through 2016, 581 hospitals were eligible to participate in the 
survey. The 2017 sample frame was refreshed with a sample of newly constructed hospitals from a new IQVIA 
source file. These new hospitals (referred to as “birth hospitals”) were selected from the 2015 IQVIA file. Of the 
598 hospitals in the base sample, 566 hospitals were from the 2013 augmented base sample file, and 32 hospitals 
were from birth hospitals from the 2015 IQVIA file. The 2017 refreshed base sample had 598 hospitals. In 2020, 
the base sample was increased from 598 to 608 hospitals due to the addition of newly sampled birth hospitals. 


3.1 Participating Hospitals 


Table | presents the number of hospitals, encounters, and response rates of NHCS by setting and survey year. 
Note, the NHCS was not fielded in 2017 due to budget limitations and data collection resumed in 2018. 


Table 1. Number of Hospitals and Encounters by Department by Year 


Inpatient ED OPD Total 
Response 


Year Hosp Encounters Hosp Encounters Hosp Encounters Hosp Encounters Rate 


2013 97 1,474,478 82 3,784,397 87 15,144,448 97 20,403,323 16.7 
2014 994 1,653,622 83 4,530,360 86 19,005,777 95 25,189,759 16.4 
2015-114 2,204,258 97 5,900,738 101. = 26,455,149 = 118 34,560,145 20.3 
2016 = 145 2,591,722 124 7,032,304 128 35,692,420 150 44,572,315 25.8 


2019-112 2,228,190 106 5,549,330 N/A N/A 112 7,244,537 18.7 
2020 150 2,832,062 199 7,978,530 N/A N/A 205 10,072,917 33.7 
2021 197 3,672,491 236 9,980,942 N/A N/A 247 12,745,505 40.6 


Note: Hosp is hospital, ED is emergency department, and OPD is outpatient department. Emergency Department 
patients transferred to the inpatient department are counted in both the inpatient and emergency department 
settings. NHCS collected outpatient data from 2013-2016, outpatient data was not collected in 2019-2021. 


4. Data Sources 


In 2011, NHCS collected Uniform Billing (UB)-04 administrative claims data from participating hospitals. UB-04 
administrative claims data are the accepted electronic standard for hospital billing mandated by the Centers for 
Medicare & Medicaid Services (CMS) for payment of charges for Medicare and Medicaid recipients. UB-04 data 
collects information on patient sex and age, hospital setting, length of stay, discharge status, and up to 25 
diagnosis and procedure codes. 


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Beginning in 2015, sampled hospitals could provide data from two additional data sources: Vizient and electronic 
health record (EHR) data. Vizient is a member-driven health care services company that collects encounter data 
from hospitals prior to submitting to data to NHCS. Vizient data are similar to UB-04 claims data in structure but 
include laboratory and medications data. Due to privacy concerns, Vizient data does not provide patient person 
identifiable information (PII), and the exact date of the hospital visit are defaulted to the first of the month. 


Unlike UB-04 claims and Vizient, EHR data contain an unlimited number of diagnosis and procedure codes, 
laboratory, and medication data. Another benefit of EHR data is the submission of unstructured clinical notes 
providing researchers a unique opportunity to have additional context to patients’ hospital visits. Due to privacy 
concerns the notes, medication, and laboratory data are not available in the RDC. However, the information 
collected in the clinical notes, medications, and laboratory data is used to identify and extract opioid-involved 
encounters. The information on opioid-involved encounters can be found in the supplemental datasets (see section 
6.2 and 6.3). 


Beginning in 2020, NCHS worked with the American College of Emergency Physicians (ACEP) to receive data 
from their hospital database for sampled non-participating hospitals. The ACEP data was originally collected to 
provide ED quality measures for participating hospitals. The data from ACEP are only from EDs (it does not 
include any inpatient data) and they do not include any hospital or patient identifiers. A summary of NHCS data 
sources are presented below in Table 2. 


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Table 2. Summary of NHCS Data Sources 


https://www.vizientinc.com/. 


Data Source Year Description Considerations 
UB-04 claims 2013- Data collected on the uniform bill (UB-04) for institutional providers e Administrative data used for billing 
2016, approved by the National Uniform Billing Committee and is the electronic rather than clinical purposes (may 
2019- standard for hospital billing. For more information about UB-04 see: exclude clinically important data 
2021 https://www.cms.gov/Outreach-and-Education/Medicare-Learning- that was not needed for billing) 
Network-MLN/MLNProducts/Downloads/837I-FormCMS-1450- e Allows tracking of ED encounters 
ICN006926.pdf. who were later admitted as 
inpatients 
e Maximum of 25 diagnosis and 
procedure codes provided 
e Revenue code indicator variables 
are available 
Vizient 2015- Vizient is a large provider-driven, health care performance improvement e Administrative data used for billing 
2016, organization. Vizient collects data from the hospitals prior to submitting it rather than clinical purposes. May 
2019- to NHCS. Similar to UB-04 claims but includes medication and laboratory exclude clinically important data 
2021 data. For more information see: that was not needed for billing 


No PII (e.g., patient name) 
collected and patients cannot be 
linked to external data sources 

The exact date of the start and end 
of the hospital encounter is not 
collected. Only the month and year 
of the end of the encounter is given 
No data on length of stay 
Maximum of 25 diagnosis and 
procedure codes provided 

Does not allow for tracking of ED 
encounters who were later admitted 
as inpatients 

Revenue code indicator variables 
are available 


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(IG). For more information, please visit the HL7 CDA R2 IG: National 
Health Care Surveys (NHCS), R1 STU Release 3 - US Realm website: 


https://www.hl7.org/implement/standards/product_brief.cfm?product_id= 
385 


The IG was developed to submit data in the exact format needed for the 
NHCS and other NCHS National Health Care Surveys. All EHR data are 
extracted from the hospitals’ EHR according to specifications provided by 
NCHS. 


Data Source Year Description Considerations 
EHR (Custom 2015- An electronic version of a patient’s medical history maintained by the e Data has clinical rather than billing 
Extracts and CCDs) 2016 hospital over time see https://www.cms.gov/Medicare/E- focus 
Health/EHealthRecords/index.html. e No limit on the number of 
diagnoses and procedures collected 
In 2016, EHR data was collected as Consolidated-clinical document per encounter 
architecture (C-CDA) and EHR Custom Extracts. ¢ Does not allow for tracking of ED 
encounters who were later admitted 
C-CDA is a set of HL7 Clinical Document Architecture submitted using as inpatients 
implementation templates such as Continuity of Care Documents (CCD). | ¢ Primary diagnosis is not available 
CCDs are an electronic document exchange standard for sharing patient, © Pll collected, which allows for 
transfer, and discharge summary information. Summaries include linkage of patients to external data 
information about current and past health status that can be shared by soubces 
computer applications including web browsers and electronic medical and 
health record software systems. In 2016, NCHS received discharge 
summaries, history and physical summaries, and transfer summaries. 
EHR Custom Extract data are extracted from a hospital’s EHR according 
to specifications provided by NCHS. The specifications for these extracts 
are based on the National Health Care Surveys Implementation Guide 
(IG). 
EHR (IG) 2019- Beginning in 2019, the NHCS only accepted EHR in the format of e Data collected has a clinical not 
2021 National Health Care Surveys CDA Release 1.2 Implementation Guide billing focus 


No limit on the number of 
diagnoses and procedures collected 
Does not allow for tracking of ED 
encounters who were later admitted 
as inpatients 

Primary diagnosis is not available. 
PII included, which allows for 
linkage to external data sources 


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EHR data, and includes diagnoses, medications, laboratory results, and 
clinical notes. 


For more information visit: https://www.acep.org/ 


Data Source Year Description Considerations 

American College of | 2020- ACEP is a United States professional organization of emergency e Only contains ED data, no inpatient 
Emergency 2021 physicians that collects UB-04 claims and EHR data to provide ED data was collected 

Physicians (ACEP) quality measures. Data collected from ACEP are similar to Vizient and e No PII (e.g., patient name) 


collected and patients cannot be 
linked to external data sources 


National Hospital Care Survey - Research Data Center Documentation 


5. Patient Identification 


NHCS collects PII allowing researchers to follow patients who have multiple encounters and link the survey to 
external datasets. Unique patients are identified by creating a Patient ID variable. To assign the Patient ID, the 
records are deduplicated and encounters that belong to the same person are identified. Probability-based linkage 
methods were used to de-duplicate the records by a person’s name, date of birth, sex, medical record number, 
address, and Social Security Number (if available). A probability-based linkage method is necessary for patient 
identification because data for the same person may not be identical on all hospital records for each encounter. 


6. Data Elements 


After data collection and processing, the NHCS data sources are harmonized into datasets. There are several 
NHCS datasets in the Federal and NCHS RDCs. For each survey year, the survey collects core data of hospital, 
patient, and encounter level information that are available from each data source. From each data source, NHCS 
collects information on the hospital encounter setting, diagnoses, services, discharge status, point of origin, and 
hospital encounter date. Refer to the data dictionaries linked below for detailed information on the type of data 
elements for each year available in the RDC including variable names, variable values, and variable availability 
by hospital setting. 


e = 2013-2014: https:/Awww.cdc.gov/rde/data/b1/2013_ NHCS.pdf 


e 2015: https://www.cdc.gov/rdc/data/b1/2015 NHCS RDC Data Dictionary.pdf 


e 2016: https://www.cdc.gov/rde/data/b 1/2016 NHCS DATA-DICTIONARY.pdf 
e 2019-2021: https://www.cdc.gov/rdc/data/b1/NHCS-RDC-Data-Dictionary.pdf 


7. Supplemental Datasets 


The collection of PII gives researchers the ability to link NHCS data to supplemental datasets to provide 
additional patient information that is not collected in the survey. This includes information on patients with 
opioid-involved and co-occurring disorder hospital encounters that were identified by enhanced algorithms 
utilizing natural language processing to analyze data items not available in the RDC, such as clinical notes and 
medication data. 


Additionally, the NCHS Data Linkage Program uses NHCS PII data to link the data to external data sources. The 
linkage of NHCS to other data sources increases the analytic power of NHCS by identifying patient outcomes 
before and after hospital visits. The datasets linked to NHCS currently include data from the National Death Index 
(NDJ), U.S. Housing and Urban Development (HUD), and Centers for Medicare & Medicaid Services (CMS). 
They are all available in both the NCHS and Federal RDCs. Information on each survey year’s linkage 
methodology, data dictionary, and analytical considerations can be found here: https://www.cdc.gov/nchs/data- 
linkage/nhcs-linkage.htm. A brief description of the supplemental datasets in the NCHS and Federal RDCs are 
listed below. 


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7.1 Enhanced Opioid Identification Dataset 


In fiscal year 2018, NCHS received funding to improve the identification of opioid-involved encounters in NHCS 
data using funding from the OS-Patient Centered-Outcome Research Trust Fund (OS-PCORTF, 
https://aspe.hhs.gov/sites/default/files/documents/8af8 9f6al 3 1cdc3572c2d3a78d9abba8/os-pcortf-portfolio- 
report.pdf ). The Enhanced Opioid Identification Algorithm utilizes Natural Language Processing (NLP) and 
machine learning techniques to analyze diagnostic codes and unstructured clinical data. The unstructured clinical 
data include the clinical notes, medication, and laboratory results collected from EHR and Vizient data. Due to the 
risk of PII disclosure, medication, laboratory, and clinical notes data are not currently available in the RDC. 


The Enhanced Opioid Identification Dataset identifies opioid-involved and opioid overdose ED and inpatient 
hospital encounters. The dataset identifies 13 commonly used opioids, generic mentions of opioids, and opioid 
antagonists’ naloxone and naltrexone mentioned during the patient encounter. The 2016 NHCS data was the first 
year to have a supplemental dataset based on results from the Enhanced Opioid Identification Algorithm. 
Subsequent years of the survey will include similar supplemental datasets with information on opioid-involved 
hospital encounters. The methodology used to develop the case definitions and algorithm is described elsewhere 
(https://www.cdc.gov/nchs/data/series/sr_02/sr2-188.pdf). 


e 2016: https:/Awww.cdc.gov/nchs/data/nhcs/Task-3-Doc-508.pdf 
e 2019-2020: https://www.cdce.gov/rdc/data/b 1/2020-Opioid-RDC-508.pdf 
e 2021: Coming soon! 


7.2 Enhanced Co-Occurring Disorders Dataset 


NCHS received additional OS-PCORTF funding in fiscal year 2019 to develop a supplemental file to the 
Enhanced Opioid Identification Dataset that identifies co-occurring disorders, substance use disorders, and mental 
health issues among patients with an opioid-involved hospital encounter. The Co-Occurring Disorder Algorithm 
created a dataset by utilizing coded medical data and NLP techniques to search the unstructured EHR clinical 
notes. The Enhanced Co-Occurring Disorders Dataset contains information on mental health issues such as 
anxiety, depression, and self-harm and selected substance use disorders. The methodology used to define the case 
definitions and algorithm development is described elsewhere (https://www.cdc.gov/nchs/data/series/sr_02/sr02- 
193 .pdf). 


e 2016: https://www.cdc.gov/nchs/data/nhes/FY 19-RDC-2021-06-01-508.pdf n 
e 2019-2021: Coming soon! 


7.3 National Death Index 


The PII collected from the NHCS was sent to the NCHS’s Division of Vital Statistics for linkage to the National 
Death Index (NDI). The NDI provides information on a decedents date of death, the underlying cause of death, 
and multiple causes of death. Below is a list of the NHCS survey years linked to the NDI: 


e 2014 NHCS linked to the 2014-2015 NDI 
e 2016 NHCS linked to the 2016-2017 NDI 


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Detailed information about the NDI, linkage methodology, and data dictionary can be found on the NDI 
homepage: https://www.cdc.gov/nchs/ndi/index.htm. 


7.4 U.S. Department of Housing and Urban Development 


Data available in the NHCS-U.S. Department of Housing and Urban Development (HUD) linked file include 
information on the type of housing assistance received by the patient, when the housing assistance was received, 
the structure of the housing, and household characteristics. Below is a list of the NHCS survey years linked to the 
HUD.: 


e 2014 NHCS linked to the 2013-2015 HUD Housing Assistance Program Files 
e 2016 NHCS linked to the 2015-2017 HUD Housing Assistance Program Files 


Information on the linkage methodology, data dictionary, and analytical considerations can be found on the 
NHCS-HUD data linkage webpage: https://www.cdc.gov/nchs/data-linkage/hud-restricted.htm. 


7.5 Centers for Medicare & Medicaid Services 


Linking NHCS data to CMS provides information on hospital utilization and charges among elderly adults and 
patients who receive Medicare disability. In 2014, NHCS was linked to the Centers for Medicaid and Medicare 
(CMS) Medicare Master Beneficiary Summary File (MBSF). The 2016 NHCS is linked to the Medicare MBSF, 
Claims/Encounters, and Assessment Data. Additionally, the 2016 NHCS data is linked to CMS Transformed 
Medicaid Statistical Information System (T-MSIS) data. Below is a list of the NHCS survey years linked to CMS 
data: 


e 2014 NHCS linked to the 2014-2015 CMS Medicare Master Beneficiary Summary File 
e 2016 NHCS linked to the 2016-2017 CMS Medicare Enrollment, Claims, and Assessment Data 
e 2016 NHCS linked to 2015-2017 CMS T-MSIS Claims Data 


Information on each survey year’s linkage methodology, data dictionary, and analytical considerations can be 
found on the NHCS-CMS data linkage webpage: https://www.cdc.gov/nchs/data-linkage/CMS-Medicare- 
Restricted.htm. 


8. Analytic Considerations 


The 2013-2016 and 2019 NHCS data available in the RDC are unweighted and are not nationally representative. 
The results and analyses produced from NHCS during those survey years data are based on participating 
hospitals. The 2020 and 2021 NHCS are nationally representative and the weighted file will be available in the 
RDC soon. 


8.1 Diagnosis Codes 


Due to the implementation of International Classification of Diseases, Tenth Revision (ICD-10-CM), the 2015 
NHCS datafiles have a mixture of International Classification of Diseases, Ninth Revision (ICD-9-CM) and ICD- 
10-CM codes for diagnoses and procedures. The first three quarters of the 2015 calendar year were coded as ICD- 
9-CM and the last quarter was coded as ICD-10-CM. Researchers can identify which coding system was used in 
the datafile by using the indicator variable that identifies diagnosis code system name. 


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Most of the diagnoses collected in the 2016, 2019-2021 NHCS are coded as ICD-10-CM. Hospitals also 
submitted diagnosis codes as ICD-9-CM, Systematized Nomenclature of Medicine—Clinical Terms (SNOMED- 
CT), and site/EHR vendor custom codes. When possible, the ICD-9-CM and SNOMED-CT diagnosis codes are 
translated to ICD-10-CM. The original and translated diagnosis codes are available to researchers in the RDC. 


Primary diagnosis cannot be identified in EHR data sources for NHCS survey years 2015-2016 or 2019-2021. 
Hospitals participating in the NHCS that submitted EHR data in 2016 and 2019-2021 are missing procedure and 
diagnosis information for some encounters. 


Further information on implementation of ICD-10-CM is available at: 
https://www.cms.gov/Medicare/Coding/ICD10/. Further information on cross-walking ICD-9-CM and ICD-10- 


CM codes is available at: https://www.cms.gov/Medicare/Coding/ICD10/2018-ICD-10-CM-and-GEMs. html. 


8.2 Procedure Codes 


Ambulatory procedures are coded in Current Procedural Terminology (CPT) for services, Healthcare Common 
Procedure Coding System (HCPCS) for products, supplies and services and ICD-9/10 Procedure Classification 
System (ICD-10-PCS) for inpatient encounters. 


Further information on procedure codes can be found at https://www.aapc.com/resources/links/ and 
https://www.cms.gov/Regulations-and-Guidance/Administrative-Simplification/Code-Sets/index.html. 


8.3 Revenue Codes 


Revenue Codes are descriptions and dollar amounts charged for hospital services provided to a patient. There are 
variables in the NHCS datafiles that provide information on the services provided via revenue codes. Revenue 
codes are only available for UB-04 claims and Vizient data. 


8.4 Discharge Status 


Discharge status indicates the outcome of the hospital visit. Examples of discharge statuses include discharged 
home, died in hospital, and transfer from the hospital to another facility. In the 2016 NHCS, hospitals that 
provided EHR data are missing discharge status on many hospital encounters or provided multiple discharge 
statuses for one encounter. Encounters in the 2013-2015, 2019, 2020, and 2021 data have one discharge status per 
encounter. 


8.5 Emergency Department Visits Admitted as Inpatients 


UB-04 claims data identifies patients presenting in the ED who were transferred then discharged from the 
inpatient department (ED-to-IP). To get an accurate account of ED discharge status in NHCS, inpatient records in 
the ED file had their discharge status changed to “admitted as an inpatient.” NHCS does not distinguish the 
treatment ED-to-IP patients received in the ED setting and the inpatient setting. As a result, the data collected 
from the ED-to-IP encounter are identical in both settings. To avoid over counting diagnoses and services 
provided to ED-to-IP transfers, researchers should count diagnoses and services in the inpatient or ED setting. 


Beginning in 2019, ED-to-IP was included as a setting value. When analyzing individual settings (ED or 
inpatient), encounters with a setting value of ED-to-IP should be included in both the ED and inpatient settings. 


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9. Additional Information and Contact Information 


For additional questions about the NHCS data please contact us at nhcs@cdc.gov. 


For more information on the NHCS data collection, please visit the survey website: 
https://www.cdc.gov/nchs/nhces/index.htm. 


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