20230901_Blood_NBCUS_SectionBStatisticalMethods

Section B - Statistical Methods
National Blood Collection and Utilization Survey
OMB No. 0990-0313 - Revision

B. Collection of Information Employing Statistical Methods.
1. Respondent Universe and Sampling Methods
Respondent Universe. The population of inference for the 2023 NBCUS will be all
blood collection and utilization facilities in the United States. The target population for
the 2023 NBCUS will consist of all blood collection centers and all hospitals subject
to certain ownership, service and location criteria. Some practical restrictions were
also placed on the target population – specifically, hospitals reporting fewer than 100
inpatient surgeries per year were excluded since they contribute little to either
collections or blood product utilization.
Sampling Frame and Sample Design. We used the American Hospital
Association’s (AHA) annual survey of hospitals, U.S. Food and Drug Administration’s
(FDA) Blood Establishment Registration database, and America’s Blood Center’s
(ABC) contact list together to construct a sampling frame that covers virtually all
collection, processing, and transfusion of blood. Hospitals in the AHA file will be
included in the 2023 NBCUS sampling frame subject to ownership, services, location
and surgical volume criteria as follows:
1) Ownership – The AHA ownership (CNTRL) must be:
Veterans Affairs (45) or
Other non-Federal
State (12)
County (13)
City (14)
City-county (15)
Hospital district or authority (16)
Church operated (21)
Other not-for-profit (23)
Individual (31)
Partnership (32)
Corporation (33)
Public Health Service Indian Service (47)
AND
2) Services – The AHA primary service (SERV) must be:
General medical and surgical (10) or
Surgical (13) or
Cancer (41) or
Heart (42) or

Obstetrics and Gynecology (44) or
Eye, ear, nose and throat (45) or
Orthopedic (47) or
Other specialty treatment (49) or
Children’s general (50) or
Children’s orthopedic (57) or
Children’s other specialty (59)
AND
3) Location – Located within the 50 United States (or the District of Columbia).
AND
4) Surgical Volume – The hospital must conduct 100 or more inpatient surgeries per
year.
Hospitals that could be matched to the AHA file (i.e., hospitals found on both
files) were included in the NBCUS frame and sample subject to the information
available in the AHA file and the eligibility criteria described above.
For the previous 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2019, and 2021
National Blood Collection and Utilization Surveys, we drew a stratified, single stage
sample of blood banks and hospitals with equal probability within stratum. We
stratified hospitals on the AHA file by size (annual inpatient surgical volume), and
selected hospitals in the larger size strata with certainty. Table B1-1 below gives the
total population, sample size and sampling rate for the various types of facilities. We
plan a similar sampling strategy for the 2023 NBCUS.
Table B1 – 1 Total population, sample size and sampling rate by type of facility

Type of facility
Hospitals (AHA) – annual
inpatient surgical volume

Total population

Sample

Sampling rate (%)

100-999
1,672
669
40.00
1,000-1,3999
350
350
100.00
1,400-2,399
589
589
100.00
2,400-4,999
682
682
100.00
5,000-7,999
281
281
100.00
≥8,000
237
237
100.00
Community-based blood
53
53
100.00
collection center
Hospital-based blood
90
90
100.00
collection center
Total
3,954
2,951
74.6
* Institutions such as the American Red Cross will have their central data repository
(ARCNET) reporting for all Red Cross centers. Therefore, the number of blood
centers sampled does not correspond to the total number of blood centers in the
United States.

The response rates for the 2019 NBCUS were 92.5% (49/53) for communitybased blood collection facilities, 74.7% (62/83) for hospital-based blood collection
facilities, and 76.3% (2102/2754) for transfusing hospitals. Based on the previous
three iterations of the NBCUS, we expect an overall response rate of almost 75%
across all types of facilities.
As with all establishment samples, we anticipate that units on the sampling frame
(whether they are sampled or not) can merge with one another, split into multiple
units, etc. Such events have implications for calculating overall probabilities of
selection. We plan to implement procedures that can be reflected in the table capture
the information relevant to calculating correct overall probabilities of selection and
that also could deal with the phenomenon of sampled units reporting for different
organizational levels.
2. Procedures for the Collection of Information
Initial Contact. An introductory email will be sent to the Director of Transfusion
Services of each sampled institution. The letter describes the purpose of the survey,
the authority for data collection, and provides a pre-notification on the types of
information that will be requested on the questionnaire. This will give institutions the
opportunity to gather information from 2023 to ease in completing the survey. The
introductory email will be sent via email asking for confirmation of the name and
contact information of the person who would most likely complete the survey at the
specified institution. Verification of the appropriate contact within the selected
hospital or blood bank will help increase response rates.
Survey Mailing. To maximize response rates as well as the quality of response
data, a unique survey link will be sent via email. This packet will contain a unique,
secure link to the online survey instrument. The person assigned to complete the
questionnaire will be given a unique login and password. A cover letter co-signed by
the Department of Health and Human Services (HHS) and Blood Organ and Other
Tissue Safety (BOOTS) Office will accompany the survey packet. The cover letter
will come from a significant HHS official such as the Assistant Secretary of Health or
the Director of the BOOTS Office.
Follow-up. Follow up efforts will include additional email reminders, paper letters vial
mail, and/or phone calls to non-respondent facilities.
Monitoring Data Collection and Quality Control. A survey receipt control system
will be used to track and monitor distribution of questionnaires and responses,

helping to ensure that actions are taken in a timely manner to maximize response
rates. All of the sampled institutions will be entered into a Microsoft Access database
to track the mailing, receipt and processing of the questionnaires. When a
questionnaire is returned, it will be entered into a table that tracks its processing
status. Key to obtaining good response rates and complete data in this type of study
is developing a rapport with the individual(s) who will be completing the
questionnaire and ensuring that the survey gets to the right person who has the
knowledge to respond. The use of the tracking system will assist with this process. In
addition, institutions that do not respond will be offered the opportunity to complete
the abbreviated version of the survey. This will help obtain critical information from as
many institutions as possible. The tracking system will be the vehicle for follow-up of
participation status.
Weighting. Base weights will be calculated for each unit as the reciprocal of its
overall probability of selection. These base weights will then be adjusted for nonresponse. We will use sampling strata as initial non-response adjustment cells, which
can be further refined through the use of Chi-squared Automatic Interaction Detector
(CHAID) or other response propensity modeling software to incorporate other
variables from the sampling frame that appear related to response propensity.
Minimum cell sizes and non-response adjustment factors will be considered in the
final non-response cell definition, in order to avoid unnecessarily large increases in
variance due to differential weighting. The use of post stratification raking or
calibration to adjust the weights to one or more known or estimated population totals
available from the sampling frame, the annual AHA survey data file and the member
list will be considered. These adjustments have the effect of increasing the precision
of estimates, while matching known population counts.
Imputation. All data items will be checked for internal consistency as part of the data
cleaning process and as a prelude to imputation. Missing data will be imputed in
continuous (i.e., interval or ratio-level) variables via regression or time series models
that take into account previously reported data for the same unit (when available), as
well as previously and presently reported data for similar, responding units. Separate
imputation models will be used for blood centers and hospitals including volumerelated variables (e.g., collection, transfusion and/or surgical counts) as predictor
variables. Imputation of nominal or ordinal-level variables, will be conducted using
SAS procedures. All imputed data items will be checked for internal consistency

using the same routines as the data cleaning process and imputation flags will be
provided in the analytic dataset to distinguish imputed from reported values.
3. Methods to Maximize Response Rates and Deal with Nonresponse
The CDC’s established relationships in the blood collection and transfusion
community, combined with lessons learned from conducting the 2005–2021 NBCUS
surveys, will help enhance participation in the 2023 NBCUS. Announcements will be
made at Annual Meetings to notify the community of the upcoming survey. BOOTS
will use its communication vehicles, distributed daily, weekly and monthly, to help
recruit blood centers and member hospitals and to provide updates and information
on the 2023 NBCUS.
Despite the methods described above, we still expect some eligible sampled
units to be non-respondents. We will deal with non-response and its potential impact
on survey estimates through a combination of weight adjustments and non-response
bias analysis. As described above (Section B2, Weighting), base weights will be
adjusted for non-response using CHAID or other response propensity modeling
software to incorporate variables from the sampling frame (other than the sampling
strata) that appear related to response propensity.
A non-response bias analysis will then take advantage of the detailed information
available for both responding and non-responding sampled units from the annual
AHA survey data file and the member list to assess the potential for non-response
bias due to both unit (i.e., complete) and item (i.e., item specific) non-response. We
will use differences in unit and item response rates across the various detailed data
items, both before and after weight adjustments, as a proxy for the potential for nonresponse bias. We will include a summary of the results of this non-response bias
analysis in technical and analytic reports.
4. Tests of Procedures or Methods to be Undertaken
The proposed 2023 survey instrument and data collection procedures are by and
large the same as the 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2019, and 2021
NBCUS surveys which received OMB approval and achieved satisfactory results. For
this reason, we will not be conducting pilot tests. However, consultation was sought
from individuals within HHS, blood center staff familiar with center operations, and
experts in transfusion medicine. Additionally, we have requested input from selected
stakeholders on the survey instrument by requesting feedback on the new questions.
5. Individuals Consulted on Statistical Aspects and Individuals Collecting and/or

Analyzing Data
The statistician responsible for the survey sample design is:
Matt Sapiano, PhD
Statistician
Lantana Consulting Group (CTR)
Division of Healthcare Quality Promotion
Centers for Disease Control and Prevention
1600 Clifton Rd.
Atlanta, GA 30329
Tel: 404.718.5761
lof6@cdc.gov
Data collection, analysis, and quality control will be under the supervision of:
Sridhar Basavaraju, MD, FACEP
Director - Office of Blood, Organ, and Other Tissue Safety
Division of Healthcare Quality Promotion
National Center for Emerging and Zoonotic Infectious Diseases
Centers for Disease Control and Prevention
1600 Clifton Road, NE MS V18-4
Atlanta, GA 30329
Tel: 404.498.0729
etu7@cdc.gov
James Berger, MS, MT (ASCP), SBB
Senior Advisor for Blood and Tissue Safety
Office of Infectious Diseases and HIV/AIDS Policy
Office of the Assistant Secretary for Health
U.S. Department of Health and Human Services
330 C Street, SW, Suite L127
Washington, DC 20024
Tel: 202.795.7608
james.berger@hhs.gov