Failure to Rescue and Mortality Differences After Appendectomy in a Low-Middle-Income Country and the United States

KEY POINTS

Question: Are there differences in postoperative complications, mortality, and failure to rescue after appendectomy in Colombia, a low-middle–income country, compared to the United States, a high-income country? Findings: Despite lower rates of complications, the adjusted in-hospital mortality rate was about 9× higher, and the failure to rescue rate was, on average, 17× higher in Colombia. Meaning: Mortality after appendectomy was higher in Colombia, despite an observed lower rate of complications, suggesting that higher mortality in Colombia may be driven by higher rates of failure to rescue rather than by higher incidence of complications.

There is wide variation in access to surgical care and postoperative outcomes across nations.1–3 Of >311 million surgical interventions performed annually worldwide, only about 6% occur in low- or middle-income countries (LMICs).4 Compared to high-income countries (HICs), postoperative outcomes are significantly inferior in LMICs,5–7 both for elective and emergency surgeries.7–10 Appendectomy is the emergency abdominal surgical procedure performed most frequently throughout all levels of country income,4 and has been used as a global indicator of access to surgical care. Outcomes after appendectomy have been proposed as a metric to evaluate gaps in the quality of surgical care between LMICs and HICs.11 Studies have found that compared to HICs, postoperative complications and mortality after appendectomy are higher in LMICs.5–7 However, previous research on this topic has been limited to small, single-center studies or to literature reviews using summarized data with inability to produce direct comparisons at the patient level.7–10

It is unclear whether higher mortality after appendectomy in LMICs is due to increased incidence of postoperative complications or to barriers to recognize and treat complications after they occur (ie, failure to rescue [FTR]). FTR has been widely used as a quality metric to compare hospital differences in perioperative care. It is recognized that variations in mortality across hospitals within countries are not necessarily linked to increased incidence of complications but rather to increased rates of FTR.12,13 Seemingly, a similar phenomenon may explain differences in postoperative mortality between countries with different levels of income.14 However, data on surgical outcomes in LMICs from Latin America are scanty.15

The primary aims of the study were to investigate differences in the incidence of FTR, postoperative mortality, and major complications in patients undergoing appendectomy in Colombia, a Latin American LMIC, and the United States, an HIC. We hypothesized that after adjusting for patient-level factors, in-hospital mortality, and FTR rates after appendectomy are higher in Colombia compared to the United States. Investigation of surgical outcomes between countries with different income levels may help to propose interventions to reduce international disparities in perioperative care.

METHODS

The study was determined to be exempt from full board review by the institutional review board of the University of Texas Southwestern Medical Center at Dallas and the ethics committee of the School of Medicine of Universidad Nacional de Colombia because the data used in the study are deidentified and publicly available. Therefore, written informed consent was not required. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines were followed for this study. The study population consisted of adult patients undergoing appendectomy in Colombia and 2 states of the United States (New York and Florida) during the years 2013 and 2014. These years were selected because 2014 was the most recent year of available data for both countries at the time of study initiation.

Source of Data

Data on patients undergoing appendectomy in NY and FL were extracted from the 2013 and 2014 State Inpatient Databases (SIDs) and Ambulatory Surgery and Services Databases (SASDs). These large administrative databases are developed for the Health Cost and Utilization Project (HCUP) and sponsored by the Agency for Healthcare Research and Quality (AHRQ). The SID collects clinical and nonclinical data from inpatient discharge records from all patients admitted to all community hospitals in a state. Similarly, the SASD consists of patient demographics and clinical and procedural data for ambulatory surgeries and other outpatient procedures performed in free-standing ambulatory centers and outpatient hospital departments within a state. The 2013–2014 HCUP databases contain encounter-level data on up to 25 diagnoses (stored as International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes) and a list of principal and secondary procedures (described as ICD-9 procedure codes in the SID and as Current Procedural Terminology [CPT] codes in the SASD). In addition, the databases contain information on patient demographics, discharge status, hospital charges, and length of hospital stay (LOS). The states of FL and NY were selected because of their high-quality data and large and ethnically diverse population. Two revisit analysis variables allow tracking of patients over time and across different facilities and permit identification of postoperative hospital readmissions.

Data from Colombia were extracted from the 2013 and 2014 administrative Databases of the Contributory Regime (DCR) of the Social Security System in Health (SSSH) of Colombia. The databases are sponsored and administered by the Ministry of Health and Social Protection of Colombia and consist of claims data at the patient encounter level for health care services, including clinic visits, surgical procedures, emergency visits, and hospitalizations. The contributory regime is mandatory for employees and independent workers and covers contributors as well as their dependents. About 209 million people (44% of the Colombian population) were covered by the contributory regime in 2014.16 For each patient encounter, the DCR captures some demographic variables (age and sex), clinical diagnoses in the form of ICD-10 codes, and diagnostic and therapeutic procedures, coded using the Colombian Unique Classification of Healthcare Procedures System (CUPS), which is very similar to the CPT coding system. In addition, the DCR database collects data on dates of service and discharge, type of service setting (outpatient, inpatient, intensive care unit, and hospital ward), and hospital charges.17,18

Selection of Patients

Adult patients (age ≥18 years of age) who had appendectomy for treatment of acute appendicitis (ICD-9-CM codes 540.0–540.9 and ICD-10 codes K35.2–K35.8) were included in the study. Appendectomy cases were extracted from the Colombian DCR using CUPS codes 471100, 471110, 471200, and 471300,17 and from the US databases using ICD-9-CM procedure codes 47.0, 47.01, and 47.09. Cases of incidental appendectomy (removal of the appendix as part of another operation, without evidence of acute appendicitis) or appendectomy secondary to trauma were excluded.

Outcomes

Primary outcomes included in-hospital mortality, FTR, and major complications. In-hospital mortality for the US data was extracted directly from a variable present in the HCUP databases. In-hospital mortality for Colombian patients was determined by linking the DCR database with the death certificate database of the National Administrative Department of Statistics of Colombia. A common variable, not containing patient identifiers, is available in both databases and allows linkage of the data sets. Major postoperative complications were identified using specific ICD-9-CM or ICD-10 diagnosis codes and included respiratory failure, pneumonia, cardiac complications (myocardial infarction, cardiac arrest, or arrhythmias, except for chronic atrial fibrillation), deep venous thrombosis or pulmonary embolism, acute renal failure, postoperative hemorrhage, gastrointestinal bleeding, surgical site infection, sepsis, shock, and postoperative stroke. These complications were selected based on previous studies that have shown good agreement between chart review and ICD coding.19,20 FTR was defined as mortality after any major complication and was calculated as the number of patients who had one or more major complications and died in the hospital (numerator) divided by the total number of patients experiencing major complications. Incidence of 30-day hospital readmissions, hospital LOS, and hospital costs were explored as secondary outcomes. Hospital costs for US records were estimated applying the HCUP cost-to-charge ratio files to the reported hospital charges present in the databases, and then were converted to 2014 US dollars according to the consumer price index. Costs for Colombian cases were adjusted by parity purchasing power (PPP), according the World Bank,21 and reported as 2014 US dollars.

Covariates

Variables on patient demographics and comorbidities, type of diagnosis, and type of procedure were used to compare baseline characteristics between countries and for adjustment in the multivariable analyses. Appropriate ICD-9-CM or ICD-10 codes were used to create patient comorbidity variables. Comorbid conditions were summarized by calculating a modified Charlson Comorbidity Index (CCI), as described previously.22 Diagnosis severity was classified as acute appendicitis without peritonitis, appendicitis with localized peritonitis, or appendicitis with generalized peritonitis. Appendectomy route was categorized as laparoscopic or open.

Statistical Analysis

Univariate analyses were performed to describe baseline characteristics of patients undergoing appendectomy in Colombia or the United States. Discrete variables are presented as frequencies and group percentages and analyzed using χ2 or Fisher tests as appropriate. Continuous data are reported as means (standard deviation) or medians with interquartile range (IQR), as appropriate, and analyzed with t tests or Mann-Whitney tests. Unadjusted differences in outcomes between the 2 countries were assessed with univariate logistic regression and are presented as frequencies (percentage) and odds ratios (ORs) with 95% confidence intervals (CIs). Multivariable logistic regression analyses were conducted to assess the association between country and the outcomes in-hospital mortality, any major complications, and FTR. Country where procedure was performed, clinically relevant factors, including patient age and sex, comorbidity burden expressed as the CCI, appendectomy route, and diagnosis severity were included as independent variables in the models. To assess whether the appendectomy route was a mediator rather than a confounder of the association between country and primary outcomes, a sensitivity analysis was performed using logistic regression models including the same independent variables described above but excluding the appendectomy route. In addition, to confirm that the complication rates were appropriately coded in the Colombian database, a subgroup univariate analysis was performed to assess the complication rates in patients who contributed the most to mortality and FTR (ie, patients >64 years of age with generalized peritonitis). As the study had 3 primary outcomes, the Bonferroni correction method was applied to adjust for multiple comparisons. The significance level was set to a P value <0.0166 (ie, 0.05/3).

The sample size was based on the primary outcome, postoperative mortality. The reported mortality after appendectomy in various countries is 0.1% to 0.5%.23 A relative increase of 20% in odds of mortality between the countries (OR = 1.2) was considered clinically relevant. Assuming a baseline mortality incidence of 0.2% and a logistic regression analysis with 4 covariates, a sample size of 44,500 patients per group was required to detect a difference of 20% in the odds of mortality between the countries, with 80% power, a significance level of 0.016, and 2-sided testing. All the statistical tests were performed using Stata 16.2 (College Station, TX) and SAS 9.4 (SAS Institute) software.

RESULTS

A total of 120,325 appendectomy cases (62,338 in Colombia and 57,987 in the United States) were identified. Table 1 presents baseline characteristics of patients having appendectomy procedures in Colombia and the 2 US states. Compared to the United States, Colombian patients were younger (mean [SD] age, 36.0 [14.7] vs 41.8 [17.3] years; P < .0001) and had lower Charlson comorbidity scores (0.13 [0.58] vs 0.27 [0.76]; P < .0001). Most appendectomies in Colombia (94%) were performed by the open route. In contrast, most appendectomies in the United States (89.4%) were done via laparoscopic approach. There were differences in the severity of appendicitis at the time of diagnosis between the 2 countries. About 78% of patients in the United States and about 73% of patients in Colombia had a diagnosis of appendicitis not complicated by any type of peritonitis, while 7.4% and 13.3% of the patients had generalized peritonitis in Colombia and in the United States, respectively (Table 1). Among patients with peritonitis, 27% in Colombia had generalized peritonitis, and 73% had localized peritonitis. In contrast, among patients with peritonitis in the United States, about 60% had generalized peritonitis, and 40% had localized peritonitis.

Table 1. - Baseline Characteristics of Patients Having Appendectomy in Colombia and the United States (States of New York and Florida), 2013–2014 Characteristic Colombia, n = 62,338 United States, n = 57,987 P value Age group, y  18–39 42,737 (68.56) 29,236 (50.42) <.0001  40–64 16,150 (25.91) 21,642 (37.32)  65–74 2075 (3.33) 4556 (7.86)  ≥75 1376 (2.21) 2553 (4.40) Sex  Female 30,820 (49.44) 28,705 (49.50) .8289  Male 31,518 (50.56) 29,282 (50.50) Year  2013 33,552 (53.82) 29,463 (50.81) <.0001  2014 28,786 (46.18) 28,524 (49.19) Route of appendectomy  Open 58,657 (94.10) 6169 (10.64) <.0001  Laparoscopic 3681 (5.90) 51,818 (89.36) Type of appendicitis  Appendicitis no peritonitis 45,335 (72.72) 45,126 (77.82) .0214  Appendicitis with localized peritonitis 12,409 (19.91) 5126 (8.84)  Appendicitis with generalized peritonitis 4594 (7.37) 7735 (13.34) Charlson Comorbidity Index  0 57,245 (91.83) 47,596 (80.08) <.0001  1 to 2 4377 (7.02) 9232 (15.92)  3 or more 716 (1.15) 1159 (2.00) Hypertension 3924 (6.29) 12,050 (20.78) <.0001 Myocardial infarction 45 (0.07) 587 (1.01) <.0001 Congestive heart failure 623 (1.00) 545 (0.94) .2927 Vascular disease 18 (0.03) 619 (1.07) <.0001 Peripheral vascular disease 38 (0.06) 433 (0.75) <.0001 Cerebrovascular disease 120 (0.19) 209 (0.36) <.0001 Coagulopathy 33 (0.05) 553 (0.95) <.0001 Dementia 56 (0.09) 61 (0.11) .3929 Pulmonary circulatory disease 37 (0.06) 159 (0.27) <.0001 Chronic pulmonary disease 2567 (4.12) 4485 (7.73) <.0001 Rheumatic arthritis/collagenous disease 277 (0.44) 510 (0.88) <.0001 Peptic ulcer disease 33 (0.05) a(0.01) <.0001 Chronic blood loss anemia (0.00)a 139 (0.24) <.0001 Deficiency anemia 501 (0.80) 2067 (3.56) <.0001 Liver disease 74 (0.12) 646 (1.11) <.0001 Diabetes without complications 1150 (1.84) 3668 (6.34) <.0001 Diabetes with complications 151 (0.24) 310 (0.53) <.0001 Obesity 92 (0.15) 4503 (7.77) <.0001 Paraplegia 10 (0.02) 147 (0.25) <.0001 Chronic renal failure 478 (0.77) 817 (1.41) <.0001 Metastatic carcinoma 39 (0.06) 122 (0.21) <.0001 Solid tumor without metastasis 534 (0.86) 263 (0.45) <.0001 Hypothyroidism 1359 (2.18) 2799 (4.83) <.0001 Paralysis 10 (0.02) 147 (0.25) <.0001 Other neurological disorders 56 (0.09) 861 (1.48) <.0001 Psychoses 18 (0.03) 721 (1.24) <.0001 Depression 23 (0.04) 2400 (4.14) <.0001 AIDS/HIV 143 (0.23) 51 (0.09) <.0001

Data are n (%) and P values are Mantel-Haenszel χ2 values.

Abbreviations: AIDS/HIV, acquired immunodeficiency syndrome/human immunodeficiency virus; HCUP, Health Cost and Utilization Project.

aCounts <10 not reported per HCUP data agreement.

Overall, the combined major complications rate was significantly lower in Colombia (2.8% vs 6.6%; OR, 0.41; 95% CI, 0.39–0.44; Table 2). Furthermore, the incidence of most individual postoperative complications (except for gastrointestinal bleeding and stroke) was significantly lower in Colombia. However, subgroup univariate analysis in patients >64 years of age with generalized peritonitis revealed nonsignificant differences in combined complication rates between the countries. Furthermore, the incidence of most individual complications was not lower in Colombia compared to the United States (Supplemental Digital Content 1, Table 1, https://links.lww.com/AA/E166).

Table 2. - Unadjusted Postoperative Outcomes After Appendectomy in Colombia and the United States (States of New York and Florida), 2013–2014 Outcome Colombia United States OR (95% CI) P value Died during hospitalization 275 (0.44) 44 (0.08) 5.83 (4.24–8.02) <.0001 Failure to rescue 240 (13.6) 41 (1.03) 14.59 (10.42–20.43) <.0001 Any major complication 1769 (2.84) 3853(6.64) 0.41 (0.39–0.44) <.0001 Respiratory complications 306 (0.49) 907 (1.56) 0.31 (0.27–0.35) <.0001  Respiratory failure 126 (0.20) 563 (0.97) 0.21 (0.17–0.25) <.0001  Pneumonia 192 (0.31) 511 (0.88) 0.35 (0.29–0.41) <.0001 Cardiac complications 111 (0.18) 228 (0.39) 0.45 (0.36–0.57) <.0001  Acute myocardial infarction 68 (0.11) 73 (0.13) 0.87 (0.62–1.21) .3945  Cardiac arrest 13 (0.02) 23 0.04) 0.53 (0.27–1.04) .0594  Arrhythmia 32 (0.05) 149 (0.26) 0.20 (0.14–0.29) <.0001 Pulmonary embolism or deep vein thrombosis 37 (0.06) 78 (0.13) 0.44 (0.30–0.65) <.0001 Acute renal failure 72 (0.12) 1250 (2.16) 0.05 (0.04–0.07) <.0001 Gastrointestinal bleeding 770 (1.24) 261 (0.45) 2.77 (2.40–3.18) <.0001 Postoperative hemorrhage 78 (0.13) 223 (0.38) 0.33 (0.25–0.42) <.0001 Surgical site infection 98 (0.16) 322 (0.56) 0.28 (0.23–0.35) <.0001 Sepsis 373 (0.60) 1309 (2.26) 0.26 (0.23–0.29) <.0001 Shock 92 (0.15) 645 (1.11) 0.13 (0.11–0.16) <.0001 Postoperative stroke a(0.01) (0.01)a 1.40 (0.39–4.94) .6041 Readmission within 30 days 3335 (5.35) 2490 (4.29) 1.26 (1.19–1.33) <.0001 Length of hospital stay, days  Mean (SD) 6.3 (2.6) 2.3 (2.9) NA <.0001  Median (IQR) 2.0 (1.0–6.0) 1.0 (1.0–3.0) NA <.0001 Hospital costs, US dollarsb NA  Mean (SD) 1682 (3783) 9013 (6972) NA <.0001  Median (IQR) 984 (712–1536) 7674 (6035–9974) NA <.0001

Data are n (%). P values are Mantel-Haenszel chi-square values.

Abbreviations: CI, confidence interval; HCUP, Health Cost and Utilization Project; IQR, interquartile range; NA, not applicable; OR, odds ratio.

aCounts <10 not reported per HCUP data use agreement.

bCost calculated as 2014 power parity purchase adjusted US dollars.

The proportion of patients who died and had an associated major complication was 87.3% in Colombia and 93.2% in the United States. This proportion was not significantly different between the countries (P = .261). The univariable analyses revealed a higher incidence of postoperative mortality (0.44% vs 0.08%; OR, 5.83; 95% CI, 4.24–8.02) and FTR (13.6% vs 1.0%; OR, 14.59; 95% CI, 10.42–20.43) in Colombia compared to the United States. The rate of FTR was higher for more serious complications. For example, mortality rates after myocardial infarction were higher than those for surgical site infection (35% and 0%, respectively, in Colombia, and 5.5% and 0.9% in the United States) (Supplemental Digital Content 1, Table 2, https://links.lww.com/AA/E166). In addition, compared to the United States, the hospital LOS was significantly longer, the rates of 30-day readmission were higher, and the hospital costs were significantly lower in Colombia.

Table 3. - Logistic Regression Analysis of Factors Affecting In-Hospital Mortality, Failure to Rescue, and Complications After Appendectomy in Colombia and the United States (States of New York and Florida), 2013–2014 Variables In-hospital mortality In-hospital FTR Any major complication OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value Country <.0001 <.0001 <.0001  United States Reference Reference Reference  Colombia 8.92 (5.69–13.98) 17.01 (10.66–27.16) 0.32 (0.30–0.35) Age, per 1 y increase 1.09 (1.08–1.10) <.0001 1.06 (1.05–1.07) <.0001 1.03 (1.03–1.03) <.0001 Sex .102 .497 <.0001  Female Reference Reference Reference  Male 1.22 (0.96–1.54) 1.10 (0.83–1.46) 1.22 (1.15–1.29) Charlson comorbidity index 1.34 (1.25–1.43) <.0001 1.28 (1.17–1.40) <.0001 1.43 (1.40–1.46) <.0001 Appendectomy route .014 .014 <.0001  Laparoscopic Reference Reference Reference  Open 1.84 (1.63–3.00) 1.93 (1.14–3.26) 1.85 (1.71–2.01) Type of appendicitis <.0001 <.0001 <.0001  No peritonitis Reference Reference Reference  Localized peritonitis 1.34 (0.91–1.97) 1.09 (0.71–1.68) 2.47 (2.29–2.66)  Generalized peritonitis 8.02 (6.09–10.54) 2.80 (2.02–3.87) 3.27 (3.06–3.51) C statistic 0.960 0.915 0.776 Hosmer and Lemeshow goodness-of-fit test, P value 0.686 0.396 <.001

The multivariable model simultaneously included all the listed independent variables.

Abbreviations: CI, confidence interval; FTR, failure to rescue; OR, odds ratio.


Table 4. - Logistic Regression Analysis of Factors Affecting In-Hospital Mortality, Failure to Rescue, and Complications, Excluding Appendectomy Route From Independent Variables Variables In-hospital mortality In-hospital FTR Any major complication OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value Country <.0001 <.0001 <.0001  United States Reference Reference Reference  Colombia 13.52 (9.74–18.77) 26.14 (18.12–37.72) 0.52 (0.49–0.55) Age, per 1 y increase 1.09 (1.08–1.10) <.0001 1.06 (1.05–1.07) <.0001 1.03 (1.03–1.03) <.0001 Sex .112

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