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Objective: We compared post-partum outcomes between sickle cell disease (SCD) and non-sickle cell populations.Methods: We conducted a retrospective analysis of discharge data for 6,911,916 inpatient deliveries in the states of California, Florida, New York, Maryland, and Kentucky from 2007 to 2014 using data from the State Inpatient Databases, Healthcare Cost and Utilization Project. We compared unadjusted rates and adjusted odds of 30- and 90-d readmission rates, in-hospital mortality, length of stay (LOS), and total hospital charges in SCD, sickle cell trait, and non-sickle cell patients.Results: Compared to non-sickle cell patients, SCD patients were more than two times as likely to die in-hospital (aOR: 2.16, 95% CI: 1.15-4.04, p < .05), 27% as likely to be readmitted up to 30 d postdelivery (aOR: 1.27, 95% CI: 1.13-1.43, p < .001), and 92% as likely to be readmitted up to 90 d postdelivery (aOR 1.92, 95% CI: 1.75-2.11, p < .001). The SCD group also had a longer median LOS, greater total hospital charges, were more likely to experience a postpartum complication, and receive a blood transfusion than the non-SCD group.Conclusions: SCD in pregnancy is associated with increased inpatient mortality, readmissions, postpartum complications, LOS, and hospital charges. [ABSTRACT FROM AUTHOR]

Abstract Background Administrative database research is widely applied in the field of epidemiology. However, the results of the studies depend on the type of database used and the algorithms applied for case ascertainment. The optimal methodology for identifying patients with rheumatic diseases from administrative databases is yet not known. Our aim was to describe an administrative database as a source for estimation of epidemiological characteristics on an example of systemic lupus erythematosus (SLE, ICD-10 code M32) prevalence assessment in the database of the Estonian Health Insurance Fund (EHIF). Methods Code M32 billing episodes were extracted from the EHIF database 2006–2010. For all cases where M32 was assigned by a rheumatologist less than four times during the study period, diagnosis verification process using health care providers’ (HCP) databases was applied. For M32 cases assigned by a rheumatologist four times or more, diagnoses were verified for a randomly selected sample. Results From 677 persons with code M32 assigned in EHIF database, 404 were demonstrated having “true SLE”. The code M32 positive predictive value (PPV) for the whole EHIF database was 60%; PPV varies remarkably by specialty of a physician and repetition of the code assignment. The false positive M32 codes were predominantly initial diagnoses which were not confirmed afterwards; in many cases, a rheumatic condition other than SLE was later diagnosed. Conclusions False positive codes due to tentative diagnoses may be characteristic for conditions with a complicated diagnosis process like SLE and need to be taken into account when performing administrative database research.

Asta Linauskas,1,2 Kim Overvad,3 Martin Berg Johansen,4 Kristian Stengaard-Pedersen,1,5 Annette de Thurah1,5 1Department of Rheumatology, Aarhus University Hospital, Aarhus, Denmark; 2Department of Rheumatology, North Denmark Regional Hospital, Hjoerring, Denmark; 3Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark; 4Unit of Clinical Biostatistics, Aalborg University Hospital, Aalborg, Denmark; 5Department of Clinical Medicine, Aarhus University, Aarhus, Denmark Purposes: To assess whether the positive predictive value (PPV) of first-time rheumatoid arthritis (RA) diagnosis registration in the Danish National Patient Registry increases when data are linked to the RA treatment codes and to assess the PPV of first-time RA diagnoses according to RA serological subtypes.Methods: Participants from the Danish Diet, Cancer, and Health cohort with at least one RA diagnosis, registered at one of the Central Denmark Region hospitals in the Danish National Patient Registry during the period 1977–2016, were identified. Register-based RA diagnoses were verified by scrutinizing medical records against RA classification criteria or clinical case RA. PPVs for overall RA, seropositive RA, and other RA were calculated for two models: first-time RA diagnosis registration ever in the Danish National Patient Registry and first-time RA diagnosis registration ever where subsequently a prescription had been redeemed for a synthetic disease-modifying antirheumatic drug.Results: Overall, 205 of 311 first-time register-based RA diagnoses were verified (PPV: 61.9%; 95% CI: 56.9–67.0). Regarding RA serological subtypes, 93 of 150 register-based seropositive RA (PPV: 62.0; 95% CI: 53.9–69.5) and 36 of 144 other RA (PPV: 25.0; 95% CI: 18.5–32.8) were confirmed. When register-based RA diagnosis codes were linked to RA treatment codes, the PPVs increased substantially: the PPV for overall RA was 87.7% (95% CI: 82.5–91.5), the PPV for seropositive RA was 80.2% (95% CI: 71.6–86.7), and the PPV for other RA was 41.1% (95% CI: 30.2–52.9).Conclusion: The first-time RA diagnoses in the Danish National Patient Registry should be used with caution in epidemiology research. However, linking registry-based RA diagnoses to the subsequent RA treatment codes increases the probability of identifying true RA diagnoses, especially overall RA and seropositive RA. Keywords: administrative database research, Danish National Prescription Registry, Anatomical Therapeutic Chemical codes, seropositive rheumatoid arthritis, Denmark

To determine the effect of preoperative opioid use disorder (OUD) on postoperative outcomes in patients undergoing coronary artery bypass grafting (CABG) and heart valve surgery. Retrospective, observational study using data from the State Inpatient Database and the Healthcare Cost and Utilization Project. Inpatient data from Florida, California, New York, Maryland, and Kentucky between 2007 and 2014. A total of 377,771 CABG patients and 194,469 valve surgery patients age ≥18 years. None. The prevalence of OUD was 2,136 (0.57%) in the CABG group and 2,020 (1.04%) in the valve surgery group. There was no significant difference in mortality between the OUD and non-OUD groups in both surgical cohorts (both p > 0.05). On adjusted analyses, preoperative OUD was significantly associated with increased adjusted odds ratios (aORs) of 30-day hospital readmission (CABG aOR 1.47 [95% confidence interval {CI} 1.30-1.66]; valve surgery aOR 1.41 [95% CI 1.27-1.56]) and 90-day hospital readmission (CABG aOR 1.47 [95% CI 1.31-1.64]; valve surgery aOR 1.33 [95% CI 1.23-1.43]). Preoperative OUD was significantly associated with increased adjusted risk ratios (aRRs) of hospital length of stay (CABG aRR 1.13 [95% CI 1.10-1.16]; valve surgery aRR 1.63 [95% CI 1.54-1.72]) and total hospitalization charges (CABG aRR 1.05 [95% CI 1.03-1.07]; valve surgery aRR 1.28 [95% CI 1.24-1.32]). Preoperative OUD is significantly associated with poorer outcomes after cardiac surgery, including increased 30- and 90-day readmissions, hospital length of stay, and total hospitalization charges. Opioid use should be considered a modifiable risk factor in cardiac surgery, and interventions should be attempted preoperatively. [ABSTRACT FROM AUTHOR]

Abstract Background This was a diagnostic accuracy study to develop an algorithm based on administrative database codes that identifies patients with Chronic Rhinosinusitis (CRS) who have endoscopic sinus surgery (ESS). Methods From January 1st, 2011 to December 31st, 2012, a chart review was performed for all hospital-identified ESS surgical encounters. The reference standard was developed as follows: cases were assigned to encounters in which ESS was performed for Otolaryngologist-diagnosed CRS; all other chart review encounters, and all other hospital surgical encounters during the timeframe were controls. Algorithm development was based on International Classification of Diseases, version 10 (ICD-10) diagnostic codes and Canadian Classification of Health Interventions (CCI) procedural codes. Internal model validation was performed with a similar chart review for all model-identified cases and 200 randomly selected controls during the following year. Results During the study period, 347 cases and 185,007 controls were identified. The predictive model assigned cases to all encounters that contained at least one CRS ICD-10 diagnostic code and at least one ESS CCI procedural code. Compared to the reference standard, the algorithm was very accurate: sensitivity 96.0% (95%CI 93.2–97.7), specificity 100% (95% CI 99.9–100), and positive predictive value 95.4% (95%CI 92.5–97.3). Internal validation using chart review for the following year revealed similar accuracy: sensitivity 98.9% (95%CI 95.8–99.8), specificity 97.1% (95%CI 93.4–98.8), and positive predictive value 96.9% (95%CI 93.0–99.8). Conclusion A simple model based on administrative database codes accurately identified ESS-CRS encounters. This model can be used in population-based cohorts to study longitudinal outcomes for the ESS-CRS population.

To determine differences in perioperative abdominal aortic aneurysm (AAA) repair outcomes based on patient sociodemographics. A retrospective analysis of patient hospitalization and discharge records. All-payer patients in nonpsychiatric hospitals in New York, Maryland, Florida, Kentucky, and California. A total of 92,028 patients from the State Inpatient Databases Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality from January 2007 to December 2014 (excluding California, ending December 2011) who underwent AAA repair. Data extraction and univariate and multivariate regression analysis. Patients in the highest income quartile were less likely to be readmitted compared with those in the poorest income quartile at both 30 days (odds ratio [OR] 0.89, 95% confidence interval [CI] 0.83-0.95) and 90 days (OR 0.85, 95% CI 0.81-0.91). Hospital readmissions were significantly greater for African American (OR 1.32, 95% CI 1.20-1.44) and Hispanic patients (OR 1.14, 95% CI 1.04-1.25) compared with white patients 30 days after AAA repair. These results were consistent 90 days after AAA repair. Patients insured with Medicare (OR 1.25, 95% CI 1.17-1.34) or Medicaid (OR 1.46, 95% CI 1.30-1.64) were more likely to be readmitted after both time points as compared with those with private insurance. The authors also found that patients with lower income, African American and Hispanic patients, and patients without private insurance were all significantly more likely to undergo emergency rather than elective repair. Lower socioeconomic status is shown to be an independent risk factor for increased postoperative morbidity in AAA repair. The authors believe the present study demonstrates the importance of socioeconomic status as a factor in perioperative risk stratification. [ABSTRACT FROM AUTHOR]

Background: Total hip arthroplasty (THA) is one of the most widely performed surgical procedures in the USA. Safety net hospitals, defined as hospitals with a high proportion of cases billed to Medicaid or without insurance, deliver a significant portion of their care to vulnerable populations, but little is known about the effects of a hospital's safety net burden and its role in healthcare disparities and outcomes following THA. We quantified safety net burden and examined its impact on in-hospital mortality, complications and length of stay (LOS) in patients who underwent THA.Methods: We analyzed 500 189 patient discharge records for inpatient primary THA using data from the Healthcare Cost and Utilization Project's State Inpatient Databases for California, Florida, New York, Maryland and Kentucky from 2007 to 2014. We compared patient demographics, present-on-admission comorbidities and hospital characteristics by hospital safety net burden status. We estimated mixed-effect generalized linear models to assess hospital safety burden status' effect on in-hospital mortality, patient complications and LOS.Results: Patients undergoing THA at a hospital with a high or medium safety net burden were 38% and 30% more likely, respectively, to die in-hospital compared with those in a low safety net burden hospital (high adjusted OR: 1.38, 95% CI 1.10 to 1.73; medium adjusted OR: 1.30, 95% CI 1.07 to 1.57). Compared with patients treated in hospitals with a low safety net burden, patients treated in high safety net hospitals were more likely to develop a postoperative complication (adjusted OR: 1.11, 95% CI 1.00 to 1.24) and require a longer LOS (adjusted IRR: 1.06, 95% CI 1.05, 1.07).Conclusions: Our study supports our hypothesis that patients who underwent THA at hospitals with higher safety net burden have poorer outcomes than patients at hospitals with lower safety net burden. [ABSTRACT FROM AUTHOR]

Background: Before embarking on administrative research, validated case ascertainment algorithms must be developed. We aimed at developing algorithms for identifying inflammatory bowel disease (IBD) patients, date of disease onset, and IBD type (Crohn's disease [CD] vs ulcerative colitis [UC]) in the databases of the four Israeli Health Maintenance Organizations (HMOs) covering 98% of the population. Methods: Algorithms were developed on 5,131 IBD patients and 2,072 controls, following independent chart review (60% CD and 39% UC). We reviewed 942 different combinations of clinical parameters aided by mathematical modeling. The algorithms were validated on an independent cohort of 160,000 random subjects. Results: The combination of the following variables achieved the highest diagnostic accuracy: IBD-related codes, alone if more than five to six codes or combined with purchases of IBD-related medications (at least three purchases or ≥3 months from the first to last purchase) (sensitivity 89%, specificity 99%, positive predictive value [PPV] 92%, negative predictive value [NPV] 99%). A look-back period of 2–5 years (depending on the HMO) without IBD-related codes or medications best determined the date of diagnosis (sensitivity 83%, specificity 68%, PPV 82%, NPV 70%). IBD type was determined by the majority of CD/UC codes of the three recent contacts or the most recent when less than three contacts were recorded (sensitivity 92%, specificity 97%, PPV 97%, NPV 92%). Applying these algorithms, a total of 38,291 IBD patients were residing in Israel, corresponding to a prevalence rate of 459/100,000 (0.46%). Conclusion: The application of the validated algorithms to Israel's administrative databases will now create a large and accurate ongoing population-based cohort of IBD patients for future administrative studies. [ABSTRACT FROM AUTHOR]

Study Objective: To confirm the relationship between primary payer status as a predictor of increased perioperative risks and post-operative outcomes after total hip replacements.Design: Retrospective cohort study.Setting: Administrative database study using 2007-2011 data from California, Florida, and New York from the State Inpatient Databases (SID), Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality.Patients: 295,572 patients age≥18years old who underwent total hip replacement with non-missing insurance data were collected, using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnoses and procedures code (ICD-9-CM code 81.51).Interventions: Patients underwent total hip replacement.Measurements: Patients were cohorted by insurance type as either Medicare, Medicaid, Uninsured, Other, and Private Insurance. Demographic characteristics and comorbidities were compared. Unadjusted rates of in-hospital mortality, postoperative complications, LOS, 30-day, and 90-day readmission status were compared. Adjusted odds ratios were calculated for our outcomes using multivariate linear and logistic regression models fitted to our data.Main Results: Medicaid patients incurred a 125% increase in the odds of in-hospital mortality compared to those with Private Insurance (OR 2.25, 99% CI 1.01-5.01). Medicaid payer status was associated with the highest statistically significant adjusted odds of mortality, any complication (OR, 1.26), cardiovascular complications (OR, 1.37), and infectious complications (OR, 1.66) when compared with Private Insurance. Medicaid patients had the highest statistically significant adjusted odds of 30-day (OR, 1.63) and 90-day readmission (OR, 1.58) and the longest adjusted LOS.Conclusions: We found higher unadjusted rates and risk adjusted odds ratios of postoperative mortality, morbidity, LOS, and readmissions for patients with Medicaid insurance as compared to patients with Private Insurance. Our study shows that primary payer status serves as a predictor of perioperative risks and that primary payer status should be viewed as a peri-operative risk factor. [ABSTRACT FROM AUTHOR]

Background: This was a diagnostic accuracy study to develop an algorithm based on administrative database codes that identifies patients with Chronic Rhinosinusitis (CRS) who have endoscopic sinus surgery (ESS). Methods: From January 1st, 2011 to December 31st, 2012, a chart review was performed for all hospital-identified ESS surgical encounters. The reference standard was developed as follows: cases were assigned to encounters in which ESS was performed for Otolaryngologist-diagnosed CRS; all other chart review encounters, and all other hospital surgical encounters during the timeframe were controls. Algorithm development was based on International Classification of Diseases, version 10 (ICD-10) diagnostic codes and Canadian Classification of Health Interventions (CCI) procedural codes. Internal model validation was performed with a similar chart review for all model-identified cases and 200 randomly selected controls during the following year. Results: During the study period, 347 cases and 185,007 controls were identified. The predictive model assigned cases to all encounters that contained at least one CRS ICD-10 diagnostic code and at least one ESS CCI procedural code. Compared to the reference standard, the algorithm was very accurate: sensitivity 96.0% (95%CI 93.2-97.7), specificity 100% (95% CI 99.9-100), and positive predictive value 95.4% (95%CI 92.5-97.3). Internal validation using chart review for the following year revealed similar accuracy: sensitivity 98.9% (95%CI 95.8-99.8), specificity 97.1% (95%CI 93.4-98.8), and positive predictive value 96.9% (95%CI 93.0-99.8). Conclusion: A simple model based on administrative database codes accurately identified ESS-CRS encounters. This model can be used in population-based cohorts to study longitudinal outcomes for the ESS-CRS population. [ABSTRACT FROM AUTHOR]

The accuracy of French medico-administrative data concerning amyotrophic lateral sclerosis (ALS) is to date unknown. We aimed to assess the validity of hospital discharge data (HDD) and health insurance data (HID) related to ALS. A retrospective population-based study was performed. The French register of ALS in Limousin (FRALim) was used as gold standard (2000–2013 period). All patients discharged from the regional hospitals with a ‘G12.2’ code in their HDD (according to the International Classification of Disease-10th version) or having a G12 HID code were considered. In the study period, the register included a total of 322 incident ALS patients. Among 451 subjects identified through HDD, 290 were true incident ALS cases, corresponding to 90.1% (95% CI 86.3–93.1) sensitivity and 64.3% (95% CI 59.7–68.7) positive predictive value (PPV). A total of 184 subjects were identified through HID, 142 of which were true ALS cases. This corresponded to 44.1% (95% CI 38.6–49.7) sensitivity and 75.5% (95% CI 68.7–81.5) PPV. The combination of both HDD and HID led to 93.8% (95% CI 90.6–96.2) sensitivity and 60.8% (95% CI 56.3–65.1) PPV. This study shows that French HDD and HID, even if combined, are not per se suitable for accurate and exhaustive direct identification of ALS cases. [ABSTRACT FROM AUTHOR]

The purposes of this study were to assess direct medical resource utilization related to the treatment of nonvertebral osteoporotic fractures within 1 year postfracture and to evaluate whether age impacts resource utilization. A previously-validated algorithm for physician claims databases identified 15,327 women aged 50 years or older with incident fracture at nonvertebral osteoporotic sites between January 1, 2004 and December 31, 2005. Administrative databases of the health services available to all residents in Quebec served to study fracture-related health resource utilization in the year after fracture. Data were linked by a unique personal identifier, creating a longitudinal cohort of all fracture cases for health resource utilization. The proportions of fractures treated by open reduction, closed reduction, immobilization or follow-up by an orthopedic surgeon (OS) were evaluated. The mean number of claims for consultation with an OS or other clinicians in inpatient and outpatient visits, the hospitalization rate and length of stay (LOS) were assessed. Hip/femur fractures represented the highest rate of resource utilization because the majority of them required surgery (91.1%) and hospitalization (94.5%) with a mean (median) LOS of 39.2 (31) days. However, other nonvertebral fracture types needed significant clinical care related to surgery (27.9%), follow-up consultation with an OS (77.6%), and hospitalization (27.3% of total LOS). Even pelvic fractures, which often do not require surgical treatment, commanded high resource utilization due to the high hospitalization rate (67.4%) with mean (median) LOS of 34.2 (26) days. Moreover, age was an important determinant of health resource utilization, being associated with an increased number of visits to other physicians, hospitalization, and length of hospitalization (LOS), admissions to long term care (LTC), and death. Osteoporosis-related fractures accounted for substantial healthcare resource utilization. With an aging population and increased prevalence of fractures, strategies for osteoporosis management need to be introduced to reduce the healthcare burden. © 2013 American Society for Bone and Mineral Research [ABSTRACT FROM AUTHOR]

Abstract: Objective: The provision of health care frequently creates digitized data—such as physician service claims, medication prescription records, and hospitalization abstracts—that can be used to conduct studies termed “administrative database research.” While most guidelines for assessing the validity of observational studies apply to administrative database research, the unique data source and analytical opportunities for these studies create risks that can make them uninterpretable or bias their results. Study Design: Nonsystematic review. Results: The risks of uninterpretable or biased results can be minimized by; providing a robust description of the data tables used, focusing on both why and how they were created; measuring and reporting the accuracy of diagnostic and procedural codes used; distinguishing between clinical significance and statistical significance; properly accounting for any time-dependent nature of variables; and analyzing clustered data properly to explore its influence on study outcomes. Conclusion: This article reviewed these five issues as they pertain to administrative database research to help maximize the utility of these studies for both readers and writers. [Copyright &y& Elsevier]

Abstract: Objective: Administrative database research (ADR) frequently uses codes to identify diagnoses or procedures. The association of these codes with the condition it represents must be measured to gauge misclassification in the study. Measure the proportion of ADR studies using diagnostic or procedural codes that measured or referenced code accuracy. Study Design and Setting: Random sample of 150 MEDLINE-cited ADR studies stratified by year of publication. The proportion of ADR studies using codes to define patient cohorts, exposures, or outcomes that measured or referenced code accuracy and Bayesian estimates for probability of disease given code operating characteristics were measured. Results: One hundred fifteen ADR studies (76.7% [95% confidence interval (CI), 69.3–82.8]) used codes. Of these studies, only 14 (12.1% [7.3–19.5]) measured or referenced the association of the code with the entity it supposedly represented. This proportion did not vary by year of publication but was significantly higher in journals with greater impact factors. Of five studies reporting code sensitivity and specificity, the estimated probability of code-related condition in code-positive patients was less than 50% in two. Conclusion: In ADR, diagnostic and procedural codes are commonly used but infrequently validated. People with a code frequently do not have the condition it represents. [Copyright &y& Elsevier]

The objective of this study was to determine differences in mortality after abdominal aortic aneurysm (AAA) repair based on insurance type. In this retrospective cohort study, data from all-payer patients in nonpsychiatric hospitals in New York, Maryland, Florida, Kentucky, and California from January 2007 to December 2014 (excluding California, ending December 2011) were extracted from the State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. There were 90,102 patients ≥18 years old with available insurance data who underwent open AAA repair or endovascular aneurysm repair (EVAR) identified using International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes 3844, 3925, and 3971. EVAR patients were identified using the procedure code 3971, and the remainder of cases were categorized as open. Patients were divided into cohorts by insurance type as Medicare, Medicaid, uninsured (self-pay/no charge), other, or private insurance. Patients were further stratified for subgroup analyses by procedure type. Unadjusted rates of in-hospital mortality, the primary outcome, as well as secondary outcomes, such as surgical urgency, 30-day and 90-day readmissions, length of stay, total charges, and postoperative complications, were examined by insurance type. Adjusted odds ratios (ORs) for in-hospital mortality were calculated using multivariate logistic regression models fitted to the data. The multivariate models included patient-, surgical-, and hospital-specific factors with bivariate baseline testing suggestive of association with insurance status in addition to variables that were selected a priori. Medicaid and uninsured patients had the highest rates of mortality relative to private insurance beneficiaries in all cohorts. Medicaid patients incurred a 47% increase in the odds of mortality, the highest among the insured, after all AAA repairs (OR, 1.47; 95% confidence interval [CI], 1.23-1.76), whereas uninsured patients experienced a 102% increase in the odds of mortality (OR, 2.02; 95% CI, 1.54-2.67). Subgroup analyses for open AAA repair and EVAR corroborated that Medicaid insurance (open repair OR, 1.37 [95% CI, 1.14-1.64]; EVAR OR, 2.06 [95% CI, 1.40-3.04]) and uninsured status (open repair OR, 1.85 [95% CI, 1.35-2.54]; EVAR OR, 2.96 [95% CI, 1.82-4.81]) were associated with the highest odds of mortality after both procedures separately. This study demonstrates that Medicaid insurance and uninsured status are associated with higher unadjusted rates and adjusted ORs for in-hospital mortality after AAA repair relative to private insurance status. Primary payer status therefore serves as an independent predictor of the risk of death subsequent to AAA surgical interventions. [ABSTRACT FROM AUTHOR]

Introduction: Sickle cell disease (SCD), the most commonly inherited hemoglobinopathy in the United States, increases the likelihood of postoperative complications, resulting in higher costs and readmissions. We used a retrospective cohort study to explore SCD's influence on postoperative complications and readmissions after cholecystectomy, appendectomy, and hysterectomy., Methods: We used an administrative database's 2007-2014 data from California, Florida, New York, Maryland, and Kentucky., Results: 1,934,562 patients aged ≥18 years were included. Compared to non-SCD patients, SCD patients experienced worse outcomes: increased odds of blood transfusion and major and minor complications, higher adjusted odds of 30- and 90-day readmissions, longer length of stay, and higher total hospital charges., Conclusion: Sickle cell disease patients are at high risk for poor outcomes based on their demographic characteristics. Therefore, perioperative physicians including hematologists, anesthesiologists, and surgeons need to take this knowledge into consideration for management and counselling of SCD patients on the risks of surgery and recovery., Competing Interests: Conflict of Interest None., (Copyright © 2020 National Medical Association. Published by Elsevier Inc. All rights reserved.)