Abstract
Background:
Demographic and hospital-level factors associated with red blood cell (RBC), plasma, and platelet transfusions in hospitalized patients across the U.S. are not well characterized.
Methods:
We conducted a retrospective analysis of the National Inpatient Sample (2014). The unit of analysis was a hospitalization; sampling weights were applied to generate nationally-representative estimates. The primary outcome was having ≥1 RBC transfusion procedure; plasma and platelet transfusions were similarly assessed as secondary outcomes. For each component, factors associated with transfusion were measured using adjusted prevalence-ratios(adjPR) and 95% confidence intervals (95%CI) estimated by multivariable-Poisson regression.
Results:
The prevalence of RBC, plasma, and platelet transfusion was 5.8%, 0.9%, and 0.7%, respectively. RBC transfusions were associated with older age (≥65 vs. <18 years;adjPR=1.80;95%CI=1.66–1.96), female sex (adjPR=1.13;95%CI=1.12–1.14), minority race/ethnic status, and hospitalizations in rural hospitals compared to an urban teaching hospitals. Prevalence of RBC transfusion was lower among hospitalizations in the Midwest compared to the Northeast (adjPR=0.73;95%CI=0.67–0.80). All components were more likely to be transfused in patients with a primary hematologic diagnosis, patients with a higher number of total diagnoses, patients who experienced a higher number of other procedures, and patients who eventually died in the hospital. In contrast to RBC transfusions, prevalence of platelet transfusion was greater in urban teaching hospitals (vs. rural;adjPR=1.71;95% CI=1.49–1.98) and lower in Blacks (vs. whites;adjPR=0.80;95%CI=0.76–0.85).
Conclusions:
Nationally, there is heterogeneity in factors associated with transfusion between each blood component, including by hospital type and location. This variability presents patient blood management programs with potential opportunities to reduce transfusions.
Keywords: Red blood cell, platelet, plasma, transfusion, United States, patient blood management
Introduction
Blood transfusions are among the most common hospital procedures in the United States (U.S.). However, there is clear evidence that red blood cell (RBC) and plasma transfusions have been decreasing across the nation.1–4 The medical evidence to guide transfusion practice has dynamically evolved over the past two decades. The immediate decision to transfuse remains guided by bleeding and laboratory values, such as hemoglobin and hematocrit levels, the international normalized ratio for blood clotting tendency, and platelet counts, for the three primary components: RBCs, plasma, and platelets.
Factors associated with blood transfusion beyond active bleeding and pre-transfusion laboratory data remain poorly defined. Surveys conducted by the AABB and U.S. Centers for Disease Control and Prevention have indeed provided important data on blood component collections, hospital distributions, and transfusion trends in the United States.3–6 However, these surveys do not account for important patient-level factors beyond basic demographics. Other studies examining predictors of transfusion have either been conducted among a limited number of hospitals and/or certain patient populations.7–15 For instance, the Recipient Epidemiology and Donor Evaluation Study-III (REDS-III) program evaluated laboratory parameters, sociodemographic data and transfusion reactions associated with RBC and plasma transfusions but were limited to <15 hospitals for each component.16,17 We are unaware of nationally representative studies evaluating non-laboratory predictors of RBC, plasma, or platelet transfusions in U.S. hospitalized patients while accounting for patient- and hospital-level factors.
In this study, we evaluate patient- and hospital-level factors associated with allogenic transfusions among adult and pediatric hospitalizations using nationally representative data.
Methods
Data Source:
The National Inpatient Sample (NIS) is the largest all-payer administrative database of inpatient hospitalizations in the U.S., and was developed as part of the Healthcare Cost and Utilization Project (HCUP) by the Agency for Healthcare Research and Quality (AHRQ). In 2012, the NIS began systematically sampling 20% of discharges from all non-long-term acute care HCUP hospitals, stratified by Census division, hospital ownership, urban vs. rural location, teaching status, and bedsize categories.18 This creates a self-weighted sample of hospitalizations (discharges) that represents 96% of the U.S. population.19 Since the unit of observation is a hospital discharge (or hospitalization), patients may be included more than once in the database. Data from the 2014 NIS were used in this analysis, as this is the final year preceding the transition from ICD-9-CM to ICD-10-CM coding.
Each hospitalization record (or discharge) included information on patient demographics (age, sex, and race), type of admission (elective vs. non-elective), patient outcomes (length of stay and in-patient mortality), up to 30 ICD-9-CM diagnosis code, up to 15 ICD-9-CM procedure codes, and hospital characteristics (census region, location and teaching status). The hospital location and teaching status variable was derived from either having an Accreditation Council for Graduate Medical Education (ACGME) approved residency program, membership in the Council of Teaching Hospitals (COTH), or a ratio of full-time equivalent interns and residents to beds of .25 or higher. No distinction was made by teaching status among rural hospitals as rural teaching hospitals were rare. The AHRQ also developed a clinical classification software (CCS) for use with HCUP data. This software categorizes ICD-9-CM codes into clinically meaningful diagnostic groups,20 and multi-level CCS diagnostic categories are provided in the NIS database. For this analysis, multi-level CCS categories for the patient’s primary diagnosis was collapsed into 13 groups. Data on laboratory values, number of units transfused, and pharmacological therapies administered during hospitalization were not available.
As the NIS is a de-identified, publicly available dataset, informed consent was not needed and Johns Hopkins Medical Institutions Institutional Review Board deemed the study exempt from review. HCUP data use agreement guidelines were followed.
Statistical Analyses:
Data analysis was performed using svy commands in Stata/MP, version 15.2 (Statacorp, College Station, TX). Sampling weights provided by HCUP were used to generate nationally-representative estimates. Taylor series linearization was used to estimate standard errors.
The unit of analysis was a hospitalization (i.e., not individual patients). The primary outcome was the percentage of hospitalizations with 1 or more allogenic RBC transfusion procedures, as the majority of transfusions are RBCs. Secondary outcomes included the percentage of hospitalizations with 1 or more plasma transfusions and 1 or more platelet transfusions. The ICD-9-CM procedure codes used to indicate RBC, plasma, and, platelet transfusions were 99.04, 99.07 and 99.05, respectively. This study focused on allogenic transfusions and did not include autologous, whole blood, or exchange transfusions as potential outcomes. For each blood component, the reported data do not reflect associations with the number of units transfused, but rather an overall decision to transfuse (versus no transfusion) during the entire course of a hospitalization.
Adjusted prevalence ratios (adjPR) and corresponding 95% confidence intervals (95%CI) were estimated by multivariable Poisson regression. The multivariable models included all covariates determined to be clinically and/or operationally important a priori, including sex, age group, race, elective admission status, length of stay (days), total number of diagnoses, total number of non-transfusion-related procedures, in-patient mortality status, hospital teaching status and location, hospital census region, and the primary diagnostic CCS category. All multivariable models were assessed for multi-collinearity. All p-values are two-sided and the threshold of statistical significance was 0.05. We used a complete-case analytic approach such that persons with missing data were excluded from analysis.
Results
Of 7,071,762 hospitalizations recorded in 2014, 6,621,151 (93.6%) had complete data for analysis. The analytic sample for this study represents 33,105,765 hospitalizations in the United States. Weighted characteristics of the study population are shown in Table 1. The majority of hospitalizations were among patients who were female (57.3%), aged ≥45 years (60.2%), and white (65.9%). Most hospitalizations were non-elective admissions (78.4%). Among all hospitalizations, patients had a median of 9 diagnoses (interquartile range [IQR], 5–14) and a median 1 non-transfusion-related procedures (IQR, 0–2) during their hospital stay. Most hospitalizations were in urban settings (90.8%). Overall, the prevalence of 1 or more RBC transfusions was 5.8% (95% CI, 5.7%−6.0%), the prevalence of 1 or more platelet transfusions was 0.7% (95% CI, 0.7%−0.8%), and the prevalence of 1 or more plasma transfusions was 0.9% (95% CI, 0.8%−0.9%). Table 1 presents characteristics of the study population by a composite status for blood transfusion (1 or more RBC, plasma, or platelet transfusions).
Table 1:
Characteristics of study population by transfusion status (red blood cells, platelets, or plasma).
| Characteristic | Overall (N = 33105765) |
Non-transfused (N = 30993004) |
Transfused * (N = 2112761) |
|||
|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | |
| Male | 14123169 | 42.7% | 13173274 | 42.5% | 949895 | 45.0% |
| Female | 18982596 | 57.3% | 17819730 | 57.5% | 1162866 | 55.0% |
| Age group, years | ||||||
| < 18 | 5023844 | 15.2% | 4946134 | 16.0% | 77710 | 3.7% |
| 18–44 | 8157756 | 24.6% | 7888546 | 25.5% | 269210 | 12.7% |
| 45–64 | 8240624 | 24.9% | 7649553 | 24.7% | 591070 | 28.0% |
| ≥65 | 11683541 | 35.3% | 10508770 | 33.9% | 1174771 | 55.6% |
| Race | ||||||
| White | 21823627 | 65.9% | 20447617 | 66.0% | 1376011 | 65.1% |
| Black | 4918867 | 14.9% | 4539212 | 14.6% | 379655 | 18.0% |
| Hispanic | 4011811 | 12.1% | 3795071 | 12.2% | 216740 | 10.3% |
| Asian/Pacific Islander | 960535 | 2.9% | 899950 | 2.9% | 60585 | 2.9% |
| Native American/Other | 1390924 | 4.2% | 1311154 | 4.2% | 79770 | 3.8% |
| Admission type | ||||||
| Non-elective | 25939518 | 78.4% | 24200917 | 78.1% | 1738601 | 82.3% |
| Elective | 7166247 | 21.6% | 6792087 | 21.9% | 374160 | 17.7% |
| Length of stay, days † | - | 3 (2–5) | - | 3 (2–5) | - | 6 (3–10) |
| Number of diagnoses † | - | 9 (5–14) | - | 8 (4–14) | - | 15 (10–20) |
| Number of procedures †‡ | - | 1 (0–2) | - | 1 (0–2) | - | 2 (1–4) |
| In-hospital mortality | 631795 | 1.9% | 503245 | 1.6% | 128550 | 6.1% |
| Hospital location/teaching status | ||||||
| Rural | 3056717 | 9.2% | 2883953 | 9.3% | 172765 | 8.2% |
| Urban non-teaching | 8813331 | 26.6% | 8239852 | 26.6% | 573480 | 27.1% |
| Urban teaching | 21235716 | 64.1% | 19869199 | 64.1% | 1366517 | 64.7% |
| Hospital Census region | ||||||
| Northeast | 6502407 | 19.6% | 6084482 | 19.6% | 417925 | 19.8% |
| Midwest | 6608279 | 20.0% | 6246379 | 20.2% | 361900 | 17.1% |
| South | 13380773 | 40.4% | 12475772 | 40.3% | 905001 | 42.8% |
| West | 6614306 | 20.0% | 6186371 | 20.0% | 427935 | 20.3% |
| Primary diagnosis category | ||||||
| Hematology | 504990 | 1.5% | 249160 | 0.8% | 255830 | 12.1% |
| Solid Tumors | 1284886 | 3.9% | 1132781 | 3.7% | 152105 | 7.2% |
| Infectious Diseases | 1625031 | 4.9% | 1417070 | 4.6% | 207960 | 9.8% |
| Endocrine | 1218856 | 3.7% | 1168036 | 3.8% | 50820 | 2.4% |
| Mental Illness | 1920679 | 5.8% | 1898309 | 6.1% | 22370 | 1.1% |
| Nervous/Sensory | 804585 | 2.4% | 788055 | 2.5% | 16530 | 0.8% |
| Circulatory | 4818822 | 14.6% | 4537342 | 14.6% | 281480 | 13.3% |
| Respiratory | 2784481 | 8.4% | 2671771 | 8.6% | 112710 | 5.3% |
| Gastrointestinal/Genitourinary | 4553392 | 13.8% | 4089327 | 13.2% | 464065 | 22.0% |
| Musculoskeletal | 2586842 | 7.8% | 2466267 | 8.0% | 120575 | 5.7% |
| OB-GYN/Congenital | 7482265 | 22.6% | 7393775 | 23.9% | 88490 | 4.2% |
| Injury/Poison | 2618186 | 7.9% | 2309026 | 7.5% | 309160 | 14.6% |
| Other | 902750 | 2.7% | 872085 | 2.8% | 30665 | 1.5% |
Refers to discharges with transfusion of allogenic red blood cells, platelets or plasma.
Data are the median and the corresponding interquartile range.
Excludes codes for red blood cell, platelet, and plasma transfusions.
A higher prevalence of RBC transfusion was associated with older patients (≥65 years compared to <18 years; adjPR, 1.80; 95% CI, 1.66–1.96), female sex (adjPR, 1.13; 95% CI, 1.12–1.14), and minority race/ethnic status (Table 2). White race was associated with the lowest prevalence of RBC transfusion (5.7%), and the highest prevalence of RBC transfusion was among hospitalizations of black patients (7.3%; adjPR, 1.39; 95% CI, 1.35–1.43). Having a higher number of diagnoses (adjPR 1.08; 95% CI, 1.08–1.08), higher number of non-transfusion procedures performed during the hospitalization (adjPR, 1.11; 95% CI, 1.10–1.11) and the occurrence of in-patient mortality (adjPR, 1.05; 95% CI, 1.03–1.08) were independent factors associated with a higher prevalence of RBC transfusion. Patients admitted with a primary hematologic diagnosis were the most common group to have a RBC transfusion. Upon geographic assessment, a lower prevalence of RBC transfusion was observed in hospitals based in the Midwest as compared to the Northeast (adjPR 0.73; 95% CI, 0.67–0.80). Hospitalizations in rural hospitals had a higher prevalence of RBC transfusion as compared with hospitalizations in urban teaching hospitals.
Table 2:
Factors associated with ≥1 red blood cell transfusion during an in-patient hospitalization.
| Characteristic | No. Transfused |
Percent Transfused |
Univariable | Multivariable | ||
|---|---|---|---|---|---|---|
| PR (95% CI) | p-value | PR (95% CI) | p-value | |||
| Sex | ||||||
| Male | 846430 | 6.0% | Ref. | Ref. | ||
| Female | 1086256 | 5.7% | 0.95 (0.95 – 0.96) | <0.001 | 1.13 (1.12–1.14) | <0.001 |
| Age group, years | ||||||
| < 18 | 70125 | 1.4% | Ref. | Ref. | ||
| 18–44 | 252435 | 3.1% | 2.22 (1.99–2.47) | <0.001 | 1.26 (1.17–1.36) | <0.001 |
| 45–64 | 537450 | 6.5% | 4.67 (4.17–5.24) | <0.001 | 1.44 (1.33–1.57) | <0.001 |
| ≥65 | 1072676 | 9.2% | 6.58 (5.86–7.38) | <0.001 | 1.80 (1.66–1.96) | <0.001 |
| Race | ||||||
| White | 1245286 | 5.7% | Ref. | Ref. | ||
| Black | 359930 | 7.3% | 1.28 (1.24–1.32) | <0.001 | 1.39 (1.35–1.43) | <0.001 |
| Hispanic | 198400 | 5.0% | 0.87 (0.83–0.91) | <0.001 | 1.23 (1.18–1.28) | <0.001 |
| Asian/Pacific Islander | 55930 | 5.8% | 1.02 (0.95–1.10) | 0.585 | 1.33 (1.24–1.44) | <0.001 |
| Native American/Other | 73140 | 5.3% | 0.92 (0.87–0.97) | 0.004 | 1.22 (1.17–1.28) | <0.001 |
| Admission type | ||||||
| Non-elective | 1583311 | 6.1% | Ref. | Ref. | ||
| Elective | 349375 | 4.9% | 0.80 (0.78–0.82) | <0.001 | 0.99 (0.96–1.01) | 0.279 |
| Length of stay (per day) | - | - | 1.02 (1.02–1.02) | <0.001 | 1.01 (1.01–1.01) | <0.001 |
| Number of diagnoses | - | - | 1.12 (1.12–1.12) | <0.001 | 1.08 (1.08–1.08) | <0.001 |
| Number of procedures* | - | - | 1.20 (1.19–1.21) | <0.001 | 1.11 (1.10–1.11) | <0.001 |
| In-hospital mortality | ||||||
| No | 1824301 | 5.6% | Ref. | Ref. | ||
| Yes | 108385 | 17.2% | 3.05 (2.99–3.12) | <0.001 | 1.05 (1.03–1.08) | <0.001 |
| Hospital location/teaching status | ||||||
| Rural | 162195 | 5.3% | Ref. | Ref. | ||
| Urban non-teaching | 528800 | 6.0% | 1.13 (1.05–1.22) | 0.001 | 0.98 (0.92–1.05) | 0.525 |
| Urban teaching | 1241692 | 5.9% | 1.10 (1.02–1.19) | 0.014 | 0.84 (0.78–0.90) | <0.001 |
| Hospital Census region | ||||||
| Northeast | 380380 | 5.9% | Ref. | Ref. | ||
| Midwest | 329340 | 5.0% | 0.85 (0.77–0.95) | 0.003 | 0.73 (0.67–0.80) | <0.001 |
| South | 838586 | 6.3% | 1.07 (0.99–1.16) | 0.085 | 1.01 (0.93–1.08) | 0.879 |
| West | 384380 | 5.8% | 0.99 (0.92–1.08) | 0.873 | 0.94 (0.87–1.00) | 0.056 |
| Primary diagnosis category | ||||||
| Hematology | 242305 | 48.0% | Ref. | Ref. | ||
| Solid Tumors | 142435 | 11.1% | 0.23 (0.22–0.24) | <0.001 | 0.22 (0.21–0.23) | <0.001 |
| Infectious Diseases | 187045 | 11.5% | 0.24 (0.23–0.25) | <0.001 | 0.15 (0.14–0.15) | <0.001 |
| Endocrine | 47430 | 3.9% | 0.08 (0.08–0.08) | <0.001 | 0.09 (0.08–0.09) | <0.001 |
| Mental Illness | 18775 | 1.0% | 0.02 (0.02–0.02) | <0.001 | 0.03 (0.03–0.04) | <0.001 |
| Nervous/Sensory | 13830 | 1.7% | 0.04 (0.03–0.04) | <0.001 | 0.04 (0.04–0.05) | <0.001 |
| Circulatory | 244330 | 5.1% | 0.11 (0.10–0.11) | <0.001 | 0.08 (0.08–0.09) | <0.001 |
| Respiratory | 103035 | 3.7% | 0.08 (0.07–0.08) | <0.001 | 0.08 (0.07–0.06) | <0.001 |
| Gastrointestinal/Genitourinary | 432555 | 9.5% | 0.20 (0.19–0.20) | <0.001 | 0.21 (0.20–0.21) | <0.001 |
| Musculoskeletal | 112900 | 4.4% | 0.09 (0.09–0.09) | <0.001 | 0.11 (0.11–0.12) | <0.001 |
| OB-GYN/Congenital | 82775 | 1.1% | 0.02 (0.02–0.02) | <0.001 | 0.05 (0.05–0.06) | <0.001 |
| Injury/Poison | 277425 | 10.6% | 0.22 (0.22–0.23) | <0.001 | 0.21 (0.20–0.21) | <0.001 |
| Other | 27845 | 3.1% | 0.06 (0.06–0.07) | <0.001 | 0.06 (0.06–0.07) | <0.001 |
Excludes codes for red blood cell, platelet, and plasma transfusions.
Abbreviations: PR, prevalence ratio; CI, confidence interval
Similar to RBC transfusions, higher prevalences of platelet and plasma transfusions were associated with hospitalizations of patients with a greater number of total diagnoses and a greater number of non-transfusion procedures performed during their stay in the hospital (Table 3 and Table 4). The prevalence of platelet transfusion was also lower among hospitalizations in the Midwest compared to the Northeast region, and among hospitalizations in rural hospitals compared to urban hospitals. In contrast to RBC transfusions, however, the prevalence of platelet transfusion was lower among hospitalizations of females compared to males (adjPR, 0.75; 95% CI, 0.74–0.77) and blacks compared to whites (adjPR, 0.80; 95% CI, 0.76–0.85) (Table 3). The prevalence of platelet transfusions was highest among hospitalizations in which the patient eventually died in the hospital (adjPR, 2.18; 95% CI, 2.08–2.28) and among hospitalizations of patients with a primary hematologic diagnosis. Compared to those with a benign hematologic primary diagnostic code, those with a malignant hematologic diagnosis (cancer of the lymphatic and hematopoietic tissue, Hodgkin’s disease, Non-Hodgkin’s lymphoma, leukemia, multiple myeloma, and secondary malignancy of the lymph nodes) were more likely to receive a platelet transfusion (18.8% vs. 6.8%; RR, 2.75; 95% CI, 2.52–2.99).
Table 3:
Factors associated with ≥1 platelet transfusion during an in-patient hospitalization.
| Characteristic | No. Transfused |
Percent Transfused |
Univariable | Multivariable | ||
|---|---|---|---|---|---|---|
| PR (95% CI) | p-value | PR (95% CI) | p-value | |||
| Sex | ||||||
| Male | 133965 | 1.0% | Ref. | Ref. | ||
| Female | 102125 | 0.5% | 0.57 (0.56–0.58) | <0.001 | 0.75 (0.74–0.77) | <0.001 |
| Age group, years | ||||||
| < 18 | 20790 | 0.4% | Ref. | Ref. | ||
| 18–44 | 29680 | 0.4% | 0.88 (0.76–1.01) | 0.076 | 0.54 (0.49–0.60) | <0.001 |
| 45–64 | 78580 | 1.0% | 2.30 (1.98–2.68) | <0.001 | 0.65 (0.58–0.72) | <0.001 |
| ≥65 | 107040 | 0.9% | 2.21 (1.91–2.57) | <0.001 | 0.53 (0.47–0.60) | <0.001 |
| Race | ||||||
| White | 156730 | 0.7% | Ref. | Ref. | ||
| Black | 29940 | 0.6% | 0.85 (0.81–0.89) | <0.001 | 0.80 (0.76–0.85) | <0.001 |
| Hispanic | 29480 | 0.7% | 1.02 (0.95–1.10) | 0.555 | 1.18 (1.12–1.26) | <0.001 |
| Asian/Pacific Islander | 9205 | 1.0% | 1.33 (1.20–1.48) | <0.001 | 1.29 (1.16–1.44) | <0.001 |
| Native American/Other | 10735 | 0.8% | 1.07 (0.97–1.19) | 0.177 | 1.19 (1.10–1.28) | <0.001 |
| Admission type | ||||||
| Non-elective | 185920 | 0.7% | Ref. | Ref. | ||
| Elective | 50170 | 0.7% | 0.98 (0.92–1.04) | 0.447 | 1.39 (1.32–1.47) | <0.001 |
| Length of stay (per day) | - | - | 1.02 (1.02–1.02) | <0.001 | 1.01 (1.00–1.01) | <0.001 |
| Number of diagnoses | - | - | 1.14 (1.14–1.14) | <0.001 | 1.09 (1.09–1.10) | <0.001 |
| Number of procedures* | - | - | 1.29 (1.28–1.30) | <0.001 | 1.13 (1.12–1.14) | <0.001 |
| In-hospital mortality | ||||||
| No | 204365 | 0.6% | Ref. | Ref. | ||
| Yes | 31725 | 5.0% | 7.98 (7.70–8.27) | <0.001 | 2.18 (2.08–2.28) | <0.001 |
| Hospital location/teaching status | ||||||
| Rural | 9440 | 0.3% | Ref. | Ref. | ||
| Urban non-teaching | 46735 | 0.5% | 1.72 (1.47–2.00) | <0.001 | 1.38 (1.20–1.58) | <0.001 |
| Urban teaching | 179915 | 0.9% | 2.74 (2.34–3.22) | <0.001 | 1.71 (1.49–1.98) | <0.001 |
| Hospital Census region | ||||||
| Northeast | 48080 | 0.7% | Ref. | Ref. | ||
| Midwest | 41575 | 0.6% | 0.85 (0.68–1.06) | 0.150 | 0.74 (0.62–0.88) | 0.001 |
| South | 87165 | 0.7% | 0.88 (0.76–1.03) | 0.103 | 0.88 (0.77–1.00) | 0.048 |
| West | 59270 | 0.9% | 1.21 (1.03–1.43) | 0.024 | 1.12 (0.99–1.27) | 0.080 |
| Primary diagnosis category | ||||||
| Hematology | 46680 | 9.2% | Ref. | Ref. | ||
| Solid Tumors | 19385 | 1.5% | 0.16 (0.16–0.17) | <0.001 | 0.13 (0.13–0.14) | <0.001 |
| Infectious Diseases | 28210 | 1.7% | 0.19 (0.18–0.20) | <0.001 | 0.11 (0.10–0.11) | <0.001 |
| Endocrine | 2590 | 0.2% | 0.02 (0.02–0.03) | <0.001 | 0.03 (0.02–0.03) | <0.001 |
| Mental Illness | 4105 | 0.2% | 0.02 (0.02–0.03) | <0.001 | 0.04 (0.04–0.05) | <0.001 |
| Nervous/Sensory | 1805 | 0.2% | 0.02 (0.02–0.03) | <0.001 | 0.03 (0.03–0.04) | <0.001 |
| Circulatory | 45770 | 1.0% | 0.10 (0.09–0.11) | <0.001 | 0.09 (0.08–0.09) | <0.001 |
| Respiratory | 8365 | 0.3% | 0.03 (0.03–0.03) | <0.001 | 0.04 (0.03–0.04) | <0.001 |
| Gastrointestinal/Genitourinary | 29045 | 0.6% | 0.07 (0.06–0.07) | <0.001 | 0.08 (0.08–0.09) | <0.001 |
| Musculoskeletal | 5320 | 0.2% | 0.02 (0.02–0.02) | <0.001 | 0.03 (0.03–0.03) | <0.001 |
| OB-GYN/Congenital | 12915 | 0.2% | 0.02 (0.02–0.02) | <0.001 | 0.03 (0.03–0.04) | <0.001 |
| Injury/Poison | 30265 | 1.2% | 0.13 (0.12–0.13) | <0.001 | 0.12 (0.11–0.12) | <0.001 |
| Other | 1635 | 0.2% | 0.02 (0.02–0.02) | <0.001 | 0.02 (0.02–0.02) | <0.001 |
Excludes codes for red blood cell, platelet, and plasma transfusions.
Abbreviations: PR, prevalence ratio; CI, confidence interval
Table 4:
Factors associated with ≥1 plasma transfusion during an in-patient hospitalization.
| Characteristic | No. Transfused |
Percent Transfused |
Univariable | Multivariable | ||
|---|---|---|---|---|---|---|
| PR (95% CI) | p-value | PR (95% CI) | p-value | |||
| Sex | ||||||
| Male | 161060 | 1.1% | Ref. | Ref. | ||
| Female | 131685 | 0.7% | 0.61 (0.60–0.62) | <0.001 | 0.79 (0.77–0.80) | <0.001 |
| Age group, years | ||||||
| < 18 | 10430 | 0.2% | Ref. | Ref. | ||
| 18–44 | 30850 | 0.4% | 1.82 (1.58–2.10) | <0.001 | 1.04 (0.93–1.17) | 0.469 |
| 45–64 | 86355 | 1.1% | 5.05 (4.36–5.84) | <0.001 | 1.33 (1.18–1.49) | <0.001 |
| ≥65 | 165110 | 1.4% | 6.81 (5.87–7.89) | <0.001 | 1.50 (1.33–1.69) | <0.001 |
| Race | ||||||
| White | 205105 | 0.9% | Ref. | Ref. | ||
| Black | 37895 | 0.8% | 0.82 (0.78–0.86) | <0.001 | 0.93 (0.89–0.97) | 0.002 |
| Hispanic | 30110 | 0.8% | 0.80 (0.75–0.85) | <0.001 | 1.08 (1.02–1.14) | 0.009 |
| Asian/Pacific Islander | 08025 | 0.8% | 0.89 (0.80–0.98) | 0.002 | 1.01 (0.91–1.12) | 0.820 |
| Native American/Other | 11610 | 0.8% | 0.89 (0.82–0.96) | 0.004 | 1.12 (1.03–1.21) | 0.005 |
| Admission type | ||||||
| Non-elective | 248995 | 1.0% | Ref. | Ref. | ||
| Elective | 43750 | 0.1% | 0.64 (0.57–0.71) | <0.001 | 0.92 (0.84–1.00) | 0.054 |
| Length of stay (per day) | - | - | 1.02 (1.02–1.02) | <0.001 | 1.00 (1.00–1.00)† | 0.027 |
| Number of diagnoses | - | - | 1.16 (1.16–1.17) | <0.001 | 1.11 (1.11–1.12) | <0.001 |
| Number of procedures* | - | - | 1.30 (1.29–1.31) | <0.001 | 1.16 (1.15–1.17) | <0.001 |
| In-hospital mortality | ||||||
| No | 250150 | 0.8% | Ref. | Ref. | ||
| Yes | 42595 | 6.7% | 8.75 (8.45–9.07) | <0.001 | 2.30 (2.21–2.38) | <0.001 |
| Hospital location/teaching status | ||||||
| Rural | 19045 | 0.6% | Ref. | Ref. | ||
| Urban non-teaching | 72865 | 0.8% | 1.33 (1.18–1.49) | <0.001 | 1.03 (0.93–1.14) | 0.547 |
| Urban teaching | 200835 | 1.0% | 1.52 (1.34–1.71) | <0.001 | 1.03 (0.92–1.15) | 0.586 |
| Hospital Census region | ||||||
| Northeast | 56625 | 0.9% | Ref. | Ref. | ||
| Midwest | 52780 | 0.8% | 0.92 (0.78–1.08) | 0.298 | 0.70 (0.61–0.81) | <0.001 |
| South | 109730 | 0.8% | 0.94 (0.82–1.08) | 0.376 | 0.88 (0.77–1.00) | 0.056 |
| West | 73610 | 1.1% | 1.28 (1.12–1.46) | <0.001 | 1.15 (1.02–1.30) | 0.023 |
| Primary diagnosis category | ||||||
| Hematology | 10395 | 2.1% | Ref. | Ref. | ||
| Solid Tumors | 15435 | 1.2% | 0.58 (0.55–0.62) | <0.001 | 0.51 (0.48–0.55) | <0.001 |
| Infectious Diseases | 36745 | 2.3% | 1.10 (1.04–1.16) | <0.001 | 0.49 (0.45–0.52) | <0.001 |
| Endocrine | 4210 | 0.4% | 0.17 (0.15–0.18) | <0.001 | 0.19 (0.17–0.21) | <0.001 |
| Mental Illness | 7230 | 0.4% | 0.18 (0.17–0.20) | <0.001 | 0.39 (0.36–0.43) | <0.001 |
| Nervous/Sensory | 2635 | 0.3% | 0.16 (0.14–0.18) | <0.001 | 0.22 (0.20–0.24) | <0.001 |
| Circulatory | 55975 | 1.2% | 0.56 (0.53–0.60) | <0.001 | 0.40 (0.37–0.43) | <0.001 |
| Respiratory | 13635 | 0.5% | 0.24 (0.22–0.25) | <0.001 | 0.24 (0.22–0.25) | <0.001 |
| Gastrointestinal/Genitourinary | 71670 | 1.6% | 0.76 (0.73–0.81) | <0.001 | 0.85 (0.80–0.91) | <0.001 |
| Musculoskeletal | 11120 | 0.4% | 0.21 (0.15–0.30) | <0.001 | 0.30 (0.22–0.43) | <0.001 |
| OBGYN/Congenital | 12490 | 0.2% | 0.08 (0.07–0.09) | <0.001 | 0.29 (0.22–0.43) | <0.001 |
| Injury/Poison | 47830 | 1.8% | 0.89 (0.83–0.95) | <0.001 | 0.76 (0.70–0.81) | <0.001 |
| Other | 3375 | 0.4% | 0.18 (0.17–0.20) | <0.001 | 0.20 (0.18–0.22) | <0.001 |
Excludes codes for red blood cell, platelet, and plasma transfusions.
The estimate prior to rounding is: 1.0014 (95% CI, 1.0002–1.0025)
Abbreviations: PR, prevalence ratio; CI, confidence interval
Discussion
This study utilized the largest, all-payer, in-patient national database in the U.S. to provide a comprehensive evaluation of non-laboratory factors associated with RBC, plasma, and platelet transfusions in hospitalized patients—while accounting for the influence of patient demographics, diagnoses and procedures, and hospital-level characteristics. In the past decade, a number of guidelines have been published for RBC, plasma and platelet transfusion.21–26 Most of these recommendations have focused on laboratory parameters that vary with diagnosis. Despite these guidelines, significant variation in clinical transfusion practice persists. We provide evidence that various patient- and hospital-level characteristics may influence the inpatient transfusion decision and explain some of this variation.
Small studies of a few institutions in both the US and internationally have evaluated transfusions in hospitalized patients.4,27–32 Roubinian et al. examined in-hospital determinants of RBC transfusions using the Kaiser Health system database using data from 21 hospitals over a four-year period (2008–2011). While the Kaiser study identified that pre-transfusion hemoglobin was indeed the most important determining factor, patient comorbidities and severity of illness were independent and significant predictors as well.15 Similar to Roubinian, we find that RBC, platelet and plasma transfusions were all associated with increased number of total diagnoses and increased number of procedures. In this study, RBC transfusions were highest among rural (non-teaching) hospitals compared to urban teaching hospitals. This may be multifactorial, including different patient populations and blood banks that are often run by community practice pathologists that often focus on anatomic pathology with less focus on optimal transfusion thresholds and implementation of patient blood management programs. The higher risk of a RBC transfusion at small, rural hospitals may be an area of opportunity for further study (e.g., survey of community pathologists, evaluation of transfusion medicine training, etc.) and for implementing patient blood management initiatives. RBC, platelet and plasma transfusions were most common among hospitalizations of patients admitted with a hematologic diagnosis. RBC transfusions were also highest among hospitalizations of black patients, which may reflect the increased use of RBCs among those with hemoglobinopathies, while plasma and platelet transfusions were lowest among black patients. These associations have also been reported in the REDS III study.16 It is unclear why hospitalizations are more often associated with a transfusion in the Northeast than hospitalizations in the Midwest. It is likely multifactorial that may partially be explained by a slightly different patient population (e.g., higher numbers of sickle cell clinics are located in the Northeast).33
As one would expect, factors associated with RBC and plasma transfusion were similar, and differed from factors associated with platelet transfusions. In contrast to RBC transfusions, platelet transfusions were less common at rural hospitals. This may be reflective of the difficulty of maintaining a low inventory of short-dated products and the distance from the blood supplier with limited storage time. In addition, as oncology centers are generally located in large hospitals and urban teaching centers, it is not surprising that platelet transfusions are seen more often in these centers.
There are limitations of this study. The data are derived from an administrative dataset that is primarily used for billing purposes, so concerns exist regarding the retrospective nature of the study and accuracy of the data. Hospital discharge codes have been shown to correlate well with self-report34, and hospital discharge codes for RBC transfusions have been previously validated against blood bank transfusion records (83% sensitivity; 100% specificity) at one institution.35 The NIS database has also produced comparable results to the National Hospital Discharge Survey and Medicare Provider Analysis and Review Files.36 In addition, the NIS has also previously been used for transfusion-related research.37 It is a limitation, however, that individual patients may be multiply represented since the unit of observation was a hospital discharge. Unfortunately, laboratory data (e.g., hemoglobin level, coagulation profile, platelet count, etc.) were not available. Therefore, the descriptive associations presented in this study may be confounded despite adjustment for patient and hospital-level factors. In addition, the NIS does not document how many units were transfused. Thus, these findings should be confirmed with data that can incorporate laboratory data and number of transfusions. Patient blood management programs have had a substantial impact on RBC use. The data in this manuscript are from a period when RBC and plasma use were substantially declining.1 As these changes continue over time, the factors associated with transfusion may change as well, and this may limit the generalizability of these findings. Also, the these data among inpatient hospitalizations may not be applicable to outpatient settings.
While laboratory data are critically important to deciding when to transfuse patients, other variables are also appear to be associated with the decision to transfuse. There is significant heterogeneity between transfusion of RBCs and platelets among hospital types and locations. Further research is needed to understand these variations in practice, as this information may be valuable to the development and implementation of patient blood management programs.
Acknowledgments:
R.G., E.U.P. and A.A.R.T. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Sources of Support: A.A.R.T. was supported in part by the NIH 5R01AI120938 and 1R01AI128779. R.G. received support from the Clinical and Translational Research services from Dept. of Pathology, Weill Cornell Medical College.
Footnotes
Conflict of Interest: The authors declare that they have no conflicts of interest relevant to the manuscript submitted to TRANSFUSION.
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