=Paper=
{{Paper
|id=Vol-1468/bd2015_mcNair
|storemode=property
|title=Transfusion did not prevent complications of scheduled surgery in California hospitals during 2012-13
|pdfUrl=https://ceur-ws.org/Vol-1468/bd2015_mcNair.pdf
|volume=Vol-1468
}}
==Transfusion did not prevent complications of scheduled surgery in California hospitals during 2012-13==
https://ceur-ws.org/Vol-1468/bd2015_mcNair.pdf
Transfusion did not prevent complications
of scheduled surgery in California hospitals
during 2012-13
Peter McNAIR PhDa and Terri JACKSON, PhDb
a
Palo Alto Medical Foundation Research Institute
b
University of Melbourne
Abstract
Background: Transfusion for healthy, asymptomatic post-surgery patients with a
hemoglobin estimate > 7.0g/dL has been shown to be associated with increases in
morbidity and mortality including increased rates of a range of hospital-acquired
complications. Feedback to hospitals and physicians regarding transfusion rates in
orthopedic surgery reveals dramatic variations in allogeneic transfusion rates both
across California and among physicians. Physicians with high rates of allogeneic
and/or autologous transfusion identified outcomes (e.g., cardiac dysrhythmia) that
they were attempting to prevent with transfusion.
Objective: This study seeks to identify any unintended adverse patient outcomes
associated with reduced transfusion rates.
Methods: We calculate hospital level allogeneic transfusion rates for thirteen
scheduled surgery patient groups with a broad suite of patient outcomes using
California-wide data from the Office of Statewide Health Planning and
Development. Rates of common complications such as acute renal failure and
postoperative infection, or readmissions with unexpected mechanical ventilation,
with postoperative atelectasis, or heart failure were examined.
Results: Of the 50 complications associated with trasnfusion, only one was found
to have a negative association, that is, was associated with worse outcomes with
lower rates of allogeneic transfusion. For the suite of scheduled procedures
included in this California-wide dataset, the study found that lower transfusion
rates were not associated with an increase in adverse patient outcome.
Conclusion: There are well established guidelines defining when transfusion is
indicated. Outside of these guidelines, this study demonstrates transfusing
scheduled surgery patients to prevent complications of care is not warranted.
Keywords. Information systems, elective surgery, hospital-acquired diagnoses,
quality indicators, decision support
Introduction
Evidence supporting many common clinical practices such as blood transfusion is often
not available. Transfusion has undoubtedly saved the lives of many patients,
particularly in the context of wartime injuries. However, the net clinical benefit (benefit
minus harms) for transfusion in scheduled surgical procedures has only recently been
investigated.1 Transfusion for healthy, asymptomatic post-surgery patients with a
hemoglobin estimate > 7.0g/dL has been shown to be associated with increases in
morbidity and mortality including increased rates of hospital acquired infections,
Transfusion Related Acute Lung Injury (TRALI), Transfusion Related Immuno-
Modulation (TRIM), cardiac, respiratory, and post-operative complications.2-4
The Palo Alto Medical Foundation Research Institute developed the EXPLORE-
Clinical Practice (EXamining Patient Level Outcomes to Reveal Excellence in Clinical
Practice)5 program to feedback hospital inpatient surgery outcome data to California
hospitals and, in some cases, to individual clinicians. The program reports on average,
189 (range: 115 to 251) within-episode and 30-day readmission based outcomes for
every non-Federal California hospital across thirteen scheduled surgery patient groups
(AAA repair, bariatric procedures, cholecystectomy, colectomy, colo-rectal,
hysterectomy, lobectomy, lumpectomy, mastectomy, oophorectomy, prostatectomy,
Total Hip Replacement (THR) and Total Knee Replacement).
Feedback to hospitals and physicians regarding transfusion rates in orthopedic
surgery revealed dramatic variations in allogeneic transfusion rates both across
California5 and among physicians (not shown). Physicians with high rates of
allogeneic and/or autologous transfusion identified outcomes (e.g., cardiac
dysrhythmia) that they were attempting to prevent with transfusion. However, when
we investigated these outcomes we could not find an inverse correlation (negative
association) with transfusion nor literature consistently supporting association between
reduced transfusion rates and complications of care in scheduled surgery.
We followed up on this work with the Hospital Inpatient Transfusion Reduction
Study. The study identified hospitals with very low transfusion rates and demonstrated
that a suite of recommended structures and processes are being actively implemented to
successfully reduce transfusion rates (i.e., systematic variation is present). As hospitals
are increasingly implementing these structures and processes, this study sought to
identify any unintended adverse patient outcomes associated with reducing transfusion
rates. Associations only flag areas for further investigation, as a correlation or
association does not imply temporality or causality.
Method
This study compares hospital level allogeneic transfusion rates for thirteen
scheduled surgery patient groups with a broad suite of patient outcomes.
As part of the ExPLORE Clinical Practice Program, outcome rates are calculated
for each hospital across thirteen patient groups selected by scheduled procedure.
ExPLORE CP uses de-identified, linked, routinely collected patient data to facilitate
review of surgical outcome information, to identify opportunities for practice and
quality improvement, and to assist doctors and patients in making healthcare decisions.
For this study, rates for each outcome are correlated with transfusion rates where each
hospital-patient group pair is a separate observation.
The case threshold for inclusion for each pair is set at twice the inverse of the
California-wide outcome rate to ensure that the expected number of outcomes for any
measure for any hospital-patient group is at least two (e.g., where the complication rate
for an outcome was 5% only hospitals with more than 40 (2*(1/0.05)) cases are
included in the analyses; where the outcome rate is 0.2% hospitals with more than
1,000 (2*(1/0.002)) cases are included).
More hospitals are included in correlations for outcomes that occur more
frequently, increasing the power of these analyses. Correlation matrix confidence
intervals are tested at the 6% level (95% level Bonferroni corrected for 122 outcomes;
JMP 10. SAS Institute Inc., Cary, NC).
While other programs aggregate similar complications of care (e.g., the
Classification of Hospital Acquired Diagnoses),6 ExPLORE Clinical Practice identifies
every individual diagnosis not present on admission (hospital-acquired) and every
procedure undertaken, along with the surgical procedure of interest in the patient report
group (e.g., THR). The outcomes are ordered by descending frequency. In concert
with surgeons who perform each of the procedures, a suite of potential outcomes is
assembled. The suite is designed to be inclusive and in many cases outcomes are
clinically related (e.g., post-operative hemorrhage, anemia arising during the admission
and allogeneic transfusion).
Results
We used the ExPLORE Clinical Practice Program (aggregated) report data to test
for associations between the rates of transfusion and the rates of adverse patient
outcomes that either arose during the index (initial) admission or were present during a
readmission within 30 days. Of the 206 candidate outcomes, data was available for 122,
that is, for 84 outcomes, our threshold for adequate volume of cases was not met.
Statistically significant associations (i.e., the 99.96% confidence interval did not
include zero) are thus estimated for 50/122 outcomes (Table 1). Only one of these,
urinary retention, was found to have a negative association, that is, may have worse
outcomes at lower rates of allogeneic transfusion.
Table 1. Correlation coefficients for outcomes associated with allogeneic transfusion, selected
scheduled surgery, OSHPD* public discharge dataset 2012-13.
Patient Outcome (co-procedure or complication) Correlation (99.96%)
# CI)
Readmission with Unexpected Mechanical
0.88 (0.12-0.99)
Ventilation
#
Readmission with Postoperative Atelectasis 0.84 (0.17-0.98)
#
Readmission with Heart Failure - Diastolic 0.81 (0.06-0.98)
Anemia 0.66 (0.62-0.70)
Leukocytosis 0.64 (0.20-0.87)
Hemodialysis for Acute Renal Failure 0.63 (0.35-0.81)
#
Readmission with Intra-abdominal Drain Placement 0.62 (0.47-0.74)
Unexpected Mechanical Ventilation 0.60 (0.49-0.69)
Intra-abdominal Drain Placement 0.60 (0.39-0.74)
Insertion of Endotracheal Tube (outside the
0.56 (0.40-0.68)
operating room)
#
Readmission with Ileus and long hospital stay 0.53 (0.07-0.80)
Ileus with long hospital stay 0.52 (0.43-0.59)
#
Readmission with Peritonitis 0.51 (0.24-0.71)
#
Readmission with Bowel Obstruction 0.50 (0.21-0.71)
#
Readmission with Total Parenteral Nutrition 0.50 (0.11-0.76)
Total Parenteral Nutrition 0.50 (0.35-0.62)
#
Readmission with Transfusion 0.49 (0.39-0.59)
Complications of intestinal anastomosis 0.49 (0.40-0.57)
Postoperative infection 0.48 (0.34-0.60)
@
Respiratory Failure, Postoperative - AHRQ PSI 11 0.48 (0.28-0.64)
Ileus 0.48 (0.40-0.55)
@
Sepsis, Postoperative - AHRQ PSI 13 0.47 (0.29-0.62)
Abnormal Electrolytes 0.45 (0.37-0.51)
#
Readmission with Ileus 0.43 (0.24-0.60)
Iatrogenic hypotension 0.41 (0.29-0.52)
Tubular necrosis or Acute Renal Failure 0.40 (0.29-0.50)
#
Readmission with Sepsis, Postoperative - AHRQ
@ 0.39 (0.18-0.57)
PSI 13
Pulmonary insufficiency following surgery 0.38 (0.20-0.53)
#
Readmission with Complications of intestinal
0.37 (0.19-0.52)
anastomosis
Pleural Effusion with Catheter Insertion 0.36 (0.19-0.51)
^
Pneumonia (CMS Definition) 0.36 (0.18-0.51)
Patient Outcome (co-procedure or complication) Correlation (99.96%
# CI)
Readmission with Tubular necrosis or Acute Renal
0.34 (0.15-0.51)
Failure
Cardiac Dysrhythmia 0.34 (0.26-0.41)
Volume Depletion 0.33 (0.16-0.48)
Long Hospital Stay 0.33 (0.25-0.40)
Urinary tract infection 0.32 (0.19-0.44)
#
Readmission with Volume Depletion 0.32 (0.16-0.47)
Postoperative hemorrhage 0.32 (0.19-0.45)
Postoperative Atelectasis 0.32 (0.22-0.41)
#
Readmission with Heart Failure 0.31 (0.09-0.50)
@
Puncture or Laceration, Accidental - AHRQ PSI 15 0.31 (0.18-0.43)
Autologous Transfusion 0.31 (0.15-0.45)
#
Readmission with Abnormal Electrolytes 0.30 (0.19-0.41)
Urinary complications 0.28 (0.04-0.49)
#
Readmission with Postoperative infection 0.26 (0.13-0.38)
#
Readmission with Anemia 0.24 (0.14-0.34)
Hypotension 0.23 (0.06-0.39)
Cardiac Arrest 0.19 (0.03-0.33)
#
Readmission with Cardiac Dysrhythmia 0.12 (0.01-0.24)
Retention of urine -0.13 (-0.25- -0.02)
* OSHPD - State of California Office of Statewide Health Planning and Development
#
Readmissions are limited to those within 30 days of discharge
@
Agency for Healthcare Quality Patient Safety Indicators
^
US Centres for Medicare and Medicaid
The negative correlation between transfusion and retention of urine was further
investigated at the patient procedure group level. Retention of urine was found to be
associated with transfusion for scheduled cholecystectomy (r2=0.91; 99.96% CI: 0.79-
0.96), oophorectomy (r2=0.54; 99.96% CI: 0.19-0.77) and hysterectomy (r2=0.34;
99.96% CI: 0.05-0.58) procedures. Prostatectomy was the only procedure group for
which a significant negative association was detected (r2=-0.29; 99.96% CI: -0.53--
0.01).
Discussion
Adverse outcomes (e.g., mechanical ventilation), although they do occur on
occasion, are not on the expected clinical path for any of the scheduled surgery patient
groups studied here. We identified 50 adverse outcome types associated with
transfusion. The associations identified in this study only flag areas for further
investigation, as a correlation or association does not imply temporality or causality.
Clear examples from our findings include anemia and post-operative hemorrhage (i.e.,
anemia and post-operative hemorrhage are more likely to be treated with transfusion
rather than being the result of transfusion). What these findings do suggest, however,
is that ‘prevention of adverse outcomes’ by liberal transfusion policy may be unwise.
Urinary retention was the only outcome found to be negatively associated with
transfusion rates, and we found this to be limited to scheduled prostatectomy. There
could be a range of reasons for this finding, but the current study did not have the
capacity to further investigate this negative association. There may be outcomes
associated with lower transfusion rates that have not been detected in this analysis. The
most likely candidates are outcomes that occur infrequently and outcomes that arise
later than 30 days post-discharge.
For the suite of scheduled procedures included in this California-wide dataset, the
study found that lower transfusion rates (within the confines of current California
hospital practices) were not associated with an increase in any adverse patient outcome
with one exception. ExPLORE CP is one of many initiatives attempting to lever
available data to improve patient outcomes. The program has evolved from the initial
intent of automated, statistically robust, clinically relevant detailed data feedback alone
to a more sophisticated user friendly, web-based reporting service that identifies and
propagates exemplary practice.
Strategies, including pre-admission anemia correction and the implementation of
an evidence based transfusion trigger protocol, have been shown to reduce the need for
transfusion in scheduled surgery.5 There are well established guidelines defining when
transfusion is indicated.4 Outside of these guidelines, this study could not, with one
possible exception, identify complications of scheduled surgery that could be prevented
by transfusion.
References
[1] Carson JL, Grossman BJ, Kleinman S, et al on behalf of the Clinical Transfusion Medicine Committee of
the AABB. Red blood cell transfusion: a clinical practice guideline from the AABB. Ann Intern Med.
2012;157(1):49-58 doi: 10.7326/0003-4819-157-1-201206190-00429.
[2] Salpeter SR, Buckley JS, Chatterjee S. Impact of More Restrictive Blood Transfusion Strategies on
Clinical Outcomes: A Meta-analysis and Systematic Review. The American Journal of Medicine 2014
Feb:127(2);124–131. DOI: 10.1016/j.amjmed.2013.09.017.
[3] Glance LG, Dick AW, Mukamel DB, et al. Association between intraoperative blood transfusion and
mortality and morbidity in patients undergoing noncardiac surgery. Anesthesiology. 2011
Feb;114(2):283-92. doi: 10.1097/ALN.0b013e3182054d06.
[4] Engelbrecht S, Wood EM, Cole-Sinclair MF. Clinical transfusion practice update: haemovigilance,
complications, patient blood management and national standards. Medical Journal of Australia
2013;199(6):397-401.
[5] McNair, Peter D.; Fang, Jade; Schwarzwaelder, Stephan; and Jackson, Terri (2015) "Development and
Implementation of ExPLORE Clinical Practice, a Web-accessible Comparative Outcomes Tool for
California Hospitals and Physicians," eGEMs (Generating Evidence & Methods to improve patient
outcomes): Vol. 3: Iss. 1, Article 2. DOI: http://dx.doi.org/10.13063/2327-9214.1066 Available at:
http://repository.academyhealth.org/egems/vol3/iss1/2
[6] Jackson TJ, Michel JL, Roberts R, Jorm C, Wakefield J (2009). A Classification of Hospital Acquired
Diagnoses for use with routine hospital data. Medical Journal of Australia (2009) 191(10):544-548.