Resource utilization and charges of patients with and without diagnosed venous thromboembolism during primary hospitalization and after elective inpatient surgery: a retrospective study

Abstract

Aims: To assess incremental charges of patients experiencing venous thromboembolisms (VTE) across various types of elective inpatient surgical procedures with administration of general anesthesia in the US.

Methods: The authors performed a retrospective study utilizing data from a nationwide hospital operational records database from July 2014 through June 2015 to compare a group of inpatients experiencing a VTE event post-operatively to a propensity score matched group of inpatients who did not experience a VTE. Patients included in the analysis had a hospital admission for an elective inpatient surgical procedure with the use of general anesthesia. Procedures of the heart, brain, lungs, and obstetrical procedures were excluded, as these procedures often require a scheduled ICU stay post-operatively. Outcomes examined included VTE events during hospitalization, length of stay, unscheduled ICU transfers, number of days spent in the ICU if transferred, 3- and 30-day re-admissions, and total hospital charges incurred.

Results: The study included 17,727 patients undergoing elective inpatient surgical procedures. Of these, 36 patients who experienced a VTE event were matched to 108 patients who did not. VTE events occurred in 0.2% of the study population, with most events occurring for patients undergoing total knee replacement. VTE patients had a mean total hospital charge of $60,814 vs $48,325 for non-VTE patients, resulting in a mean incremental charge of $11,979 (p < .05). Compared to non-VTE patients, VTE patients had longer length of stay (5.9 days vs 3.7 days, p < .001), experienced a higher rate of 3-day re-admissions (3 vs 0 patients) and 30-day re-admissions (7 vs 2 patients).

Conclusions: Patients undergoing elective inpatient surgical procedures with general anesthesia who had a VTE event during their primary hospitalization had a significantly longer length of stay and significantly higher total hospital charges than comparable patients without a VTE event.

Keywords:

• Venous thromboembolism
• VTE
• resource utilization
• healthcare resource utilization
• total hospital charge
• charge
• anesthesia
• retrospective

Introduction

Venous thromboembolism (VTE) occurs when the blood abnormally forms a thrombus in a vein. Traditionally, VTE has been further sub-divided into two specific types of thrombi, deep vein thrombosis (DVT) and pulmonary embolism (PE)¹. DVT refers to thrombi that form within deep veins; however, thrombi may also form in superficial veins¹. In some cases, a portion of the thrombus from a DVT will break off and lodge within a pulmonary artery, resulting in a PE¹. Occurrence of VTE, particularly PE, has been associated with a decrease in survival^1,2. Depending on the population assessed, studies have estimated that 10–30% of all patients experiencing a VTE event die within 30 days³. The annual incidence of VTE has been estimated at 1–2 events per 1,000 persons within the general population³.

Clinicians are able to proactively take measures to identify patients who may be at greater risk for a VTE event, and act accordingly to either prevent it or carefully monitor the patient. Risk factors for VTE include trauma, immobility, surgery, cancer, increasing age, pregnancy, and a wide range of genetic factors³. Surgical patients may be at risk of VTE to a greater extent, as they frequently are placed in situations in which multiple risk factors for VTE are present at once, such as: major surgery, immobility, anesthesia duration of 3.5 h or longer, and the use of general anesthesia vs regional anesthesia^4,5. In particular, the use of general anesthesia makes it more likely for blood to become hypercoagulable by enhancing venous stasis⁵. Venous stasis, which can occur from long surgical operations or prolonged immobility, is widely known as a contributor to VTE events⁶. Although the use of general anesthesia and longer general anesthesia/surgical time has been associated with increased risk of VTE post-operatively⁵, there remains a lack of data about the economic burden of VTE events amongst patients administered general anesthesia during surgery. Quantifying the economic burden of VTE events with regards to elective inpatient surgery performed under general anesthesia may lead to an improved allocation of hospital resources. The objective of this study was to assess the total hospital charges and resource utilization of patients with VTE events undergoing elective inpatient surgeries utilizing general anesthesia during their primary hospitalization.

Methods

Data source

We conducted a retrospective cohort study utilizing data extracted from the IQVIA Hospital Charge Data Master (CDM) database from July 1, 2014 to June 30, 2015. The CDM captures hospital operational records sourced from records that roll up to the UB-04 billing forms, which are submitted for payment from over 450 hospitals. These data originate from non-federal, acute-care short-stay hospitals, covering both inpatient and outpatient services, including emergency room (ER) utilization with information on diagnoses, procedures, treatment, and daily charge details. Also included are patient and hospital characteristics. The CDM database sources ∼7 million inpatient visits and 85 million outpatient visits per year. Charge details captured at the patient-level are available on a daily basis. Re-admissions in the CDM database are captured if a patient is re-admitted either to the original hospital or another hospital captured in the database’s panel. In compliance with the Health Insurance Portability and Accountability Act of 1996 (HIPAA), the CDM database consists of fully de-identified data to protect the identities of both the patients and other data contributors. Ethics approval was not required, as this was a retrospective data analysis of a secondary data source. All data utilized were de-identified, pre-existing, and retrospective, with no risk of identifying patients.

Sample selection

The study population included all adult patients (≥18 years) with a procedural code for elective surgeries of interest, as identified by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes or Current Procedural Terminology (CPT) codes between July 1, 2014 and June 30, 2015. Surgeries included those defined by the following ICD-9-CM and CPT codes (defined as “index hospitalization”): 00-86 ICD-9-CM and 10000-69999 CPT with an inpatient flag^7–10. The CDM database defines an “inpatient flag” as a patient who was ordered an overnight stay by their physician. We limited our analysis to elective surgeries in order to avoid potential risk factors for VTE events that may be associated moreso with emergent procedures, such as major trauma. Patients were excluded if they were admitted from the emergency room, or if they were not administered an inhaled anesthetic (sevoflurane, isoflurane, or desflurane). In addition, patients were excluded if they were scheduled for obstetrical surgeries or elective surgeries of the nervous, respiratory, or cardiovascular systems. Some of these procedures require a planned ICU stay post-operatively, and, therefore, were excluded in order to avoid unnecessary confounding in our analysis of the economic burden of VTE. In order to focus our analysis on the inpatient setting, patients were also excluded if they underwent elective outpatient surgical procedures, denoted by a hospital stay of less than 24 h. To minimize any confounding from potential re-admissions, we excluded patients with evidence of a hospitalization within the 30 days prior to the index hospitalization. Figure 1 displays patient attrition for our study. A sub-analysis was included of the 10 most frequently occurring surgeries for the inpatients included in our study (Figure 2).

Figure 1. Patient attrition diagram. * Refers to the following instances: patient’s hospital did not have a report in the CDM database ≥30 days prior to the surgery or ≥30 days after patient was discharged from the initial hospital stay, or patient report had missingness of gender, payer type, or total hospital charge. ^ VTE, Venous thromboembolism. ^▴ 36 cases (patients experiencing a VTE) matched to 108 controls (patients who did not experience a VTE). Four VTE cases were removed due to being above 4 SD of the mean for either total hospital charge and/or length of stay.

Figure 2. Percentage of patients experiencing a VTE event in the overall inpatient cohort for the top 10 more frequently occurring inpatient surgeries in our study over the course of 1 year: July 1, 2014–June 30, 2015.

Study outcomes

Any VTE event that occurred at any time during the index hospitalization period was identified using the ICD-9-CM diagnosis codes listed in Table 1^7–10. Patients who experienced a VTE event at any time during their hospitalization were identified as “cases”, while patients who did not experience a VTE event during their hospitalization were identified as “controls”. To only include patients who experienced new VTE events while admitted, we did not include ICD-9-CM V-codes for history of VTE. Demographic and hospital characteristics were assessed. The primary study outcome was total hospital charges for VTE cases and controls. No cost-to-charge ratio was applied to the charges. We utilized the hospital perspective when analyzing economic outcomes. Additional study outcomes assessed included length of stay (LOS), 3- and 30-day re-admission, whether the patient was transferred to the ICU, the number of days spent in the ICU, and mortality at any time during the hospital stay.

Table 1. List of ICD-9-CM diagnosis codes used to define a VTE event.

ICD-9-CM diagnosis code	Code description
415.11	Iatrogenic pulmonary embolism and infarction
415.12	Septic pulmonary embolism
415.13	Saddle embolus of pulmonary artery without acute cor pulmonale
415.19	Other pulmonary embolism and infarction
451.11	Phlebitis and thrombophlebitis of femoral vein (deep) (superficial)
451.19	Phlebitis and thrombophlebitis of deep veins of lower extremities, other
451.2	Phlebitis and thrombophlebitis of lower extremities, unspecified
451.83	Phlebitis and thrombophlebitis of deep veins of upper extremities
451.84	Phlebitis and thrombophlebitis of upper extremities, unspecified
451.89	Phlebitis and thrombophlebitis of other sites
451.9	Phlebitis and thrombophlebitis of unspecified site
452	Portal vein thrombosis
453.0	Budd-chiari syndrome
453.2	Other venous embolism and thrombosis of inferior vena cava
453.3	Embolism and thrombosis of renal vein
453.40	Acute venous embolism and thrombosis of unspecified deep vessels of lower extremity
453.41	Acute venous embolism and thrombosis of deep vessels of proximal lower extremity
453.42	Acute venous embolism and thrombosis of deep vessels of distal lower extremity
453.82	Acute venous embolism and thrombosis of deep veins of upper extremity
453.83	Acute venous embolism and thrombosis of upper extremity, unspecified
453.84	Acute venous embolism and thrombosis of axillary veins
453.85	Acute venous embolism and thrombosis of subclavian veins
453.86	Acute venous embolism and thrombosis of internal jugular veins
453.87	Acute venous embolism and thrombosis of other thoracic veins
453.89	Acute venous embolism and thrombosis of other specified veins
453.9	Other venous embolism and thrombosis of unspecified site

Statistical analysis

Matching

Patients who experienced a VTE event (cases) were directly matched to patients who did not experience a VTE event (controls), based on their exact primary procedure code and major category of the ICD-9-CM admitting diagnosis code. Cases were further propensity matched 1:3 to controls. To calculate the propensity score, a logistic regression model was developed with the following variables: age group, gender, hospital geographic location, hospital location, hospital bed size, and hospital teaching status. For analysis of study outcomes, outliers 4 SD above the mean total hospital charges and/or length of stay were removed for VTE cases and controls.

Descriptive statistics were used to summarize and compare the demographic and hospital characteristics of the overall inpatient study population, and separately between matched VTE cases and controls. Mean, standard deviation (SD), and median were reported for continuous data, and counts and percentages were reported for categorical data. Tests of statistical significance between cases and controls in the unmatched population were conducted using the Wilcoxon rank-sum test for continuous variables, while the Chi-square test was used for categorical variables. Comparisons between matched cases and controls were conducted using the Student’s t-test (on the mean for key outcomes) and the Wilcoxon signed-rank test (on the median) for continuous and count variables, while McNemar’s test was used for categorical variables. A p-value of .05 was pre-specified to determine statistical significance. All statistical analyses were carried out using SAS 9.3 (SAS Institute Inc., Cary, NC).

Results

Study population, baseline demographics, and hospital characteristics

In total, 17,727 patients undergoing inpatient elective surgery were included in our study (Figure 1). Baseline demographics for the overall inpatient study population and for the unmatched and matched VTE cohorts are presented in Table 2. The mean (SD) age of the overall inpatient population was 56.3 (15.2) years. The majority of patients were female (61.2%). Of the entire study population, 71.4% had third party insurance. Of the hospitals included in our analysis, 47.2% were located in the South. Most of the hospitals were from urban areas (94.9%), and most had a bed size of 300–499 beds (39.4%). A little over half of the hospitals captured were teaching hospitals (52.7%). The majority of surgeries included in our study were musculoskeletal procedures. Gender, hospital region, and hospital teaching status distributions were similar for patients experiencing a VTE event compared to those who did not. Post-matching, the proportions of cases and controls appeared balanced for most covariates.

Table 2. Patient and hospital demographics for unmatched and matched cohorts.

		Unmatched			Matched
	Overall	Case	Control	p-value	Case	Control	p-value
Sample size (n)	17,727	40	17,687		36	108
Age
18–34 years	1,620	2.5%	9.2%	Not calculated	2.8%	0.0%	Not calculated
35–44 years	2,447	12.5%	13.8%		13.9%	15.7%
45–54 years	3,710	20.0%	20.9%		16.7%	16.7%
55–64 years	4,167	25.0%	23.5%		27.8%	29.6%
65–75 years	3,724	20.0%	21.0%		19.4%	19.4%
75+ years	2,059	20.0%	11.6%		19.4%	18.5%
Gender
Male	6,875	30.0%	38.8%	.2538	30.6%	29.6%	.9163
Female	10,852	70.0%	61.2%		69.4%	70.4%
Payer type
Third Party	12,654	60.0%	71.4%	Not calculated	61.1%	64.8%	Not calculated
Medicaid	961	2.5%	5.4%		2.8%	2.8%
Medicare	3,824	32.5%	21.6%		30.6%	27.8%
Cash	288	5.0%	1.6%		5.6%	4.6%
Hospital region
Midwest	2,370	25.0%	13.3%	.0915	25.0%	26.6%	.9831
Northeast	4,282	17.5%	21.2%		16.7%	18.5%
South	8,363	50.0%	47.2%		50.0%	46.3%
West	2,712	7.5%	15.3%		8.3%	8.3%
Hospital bed size
1–99 beds	767	5.0%	4.3%	.6733	5.6%	4.6%	Not calculated
100–199 beds	5,551	32.5%	31.3%		36.1%	39.8%
200–299 beds	1,526	5.0%	8.6%		5.6%	3.7%
300–499 beds	6,977	47.5%	39.3%		44.4%	43.5%
500+ beds	2,906	10.0%	16.4%		8.3%	8.3%
Hospital location
Urban	16,817	82.5%	94.9%	Not calculated	80.6%	80.6%	1.000
Rural	910	17.5%	5.1%		19.4%	19.4%
Hospital teaching status
Teaching	8,392	50.0%	47.3%	.7359	44.4%	41.7%	.7702
Non-teaching	9,335	50.0%	52.7%		55.6%	58.3%

Incidence of VTE events

Of the overall unmatched inpatient population (n = 17,727), 40 (0.23%) patients were identified as experiencing a VTE event post-operatively. Patients who experienced a VTE were mostly female (70%) and had a mean (SD) age of 60.2 (15.1) years. Of the 10 most frequent elective inpatient surgeries in our study, total knee replacement appeared to have the highest incidence of VTE events (0.37%). Figure 2 displays the distribution of VTE events occurring in the top 10 most frequent elective inpatient surgeries in our study. VTE events were identified in four out of these 10 procedures. Prior to identification of VTE cases and controls, of the overall inpatient population, 14 patients out of 17,727 (0.08%) experienced a re-admission with an admitting diagnosis of VTE within 30 days of the index hospitalization.

Resource utilization and economic burden

Matching between VTE cases and controls initially resulted in 36 VTE cases, matched to 108 controls. An economic analysis was conducted for matched cohorts of patients after removal of VTE case and control outliers that were 4 SD above the mean, resulting in 32 cases matched to 96 controls. Results for the outcomes of the initial 36 matched VTE cases are available upon request.

Overall, the resource utilization captured in this study was greater for patients experiencing a VTE compared to those who did not. The mean (SD) length of stay for patients experiencing a VTE event was longer compared to matched controls (5.9 vs 3.7 days, p < .001). The number of VTE cases who experienced a 3-day or 30-day re-admission appeared to be higher than the number of non-VTE controls (3 vs 0 patients for 3-day, 7 vs 2 patients for 30-day), although these differences were not tested for statistical significance, due to small samples. The mean number of ICU days for patients with a VTE event was greater compared to patients without a VTE event, although the differences were not statistically significant (4.9 vs 2.8 days, p = .1085). One death occurred within the VTE-event patient group, with none occurring in the matched non-VTE group, although the reason for this death was unknown. Further study outcome results are reported in Table 3. The mean total hospital charge for patients with VTE events was found to be significantly higher than patients without VTE events ($60,814 vs $48,835, p < .05). This resulted in a mean incremental charge of $11,979 (Table 3). The median total hospital charge for patients with VTE events was also found to be higher for patients with VTE events compared to those without VTE events, although this difference was not statistically significant ($50,381 vs $45,426, p = .09).

Table 3. Study outcomes for the matched VTE cohort, without outliers^a.

	Matched
	Cases	Controls	p-value
Sample size (n)	32	96
Total hospital charge ($)
Mean (SD)	$60,814 ($40,368)	$48,835 ($24,262)	.0456
Median	$50,381	$45,426	.0891
Min	$24,252	$14,660
Max	$229,286	$153,128
Length of stay (days)
Mean (SD)	5.9 (3.2)	3.7 (1.5)	<.001
Median	5	4	<.001
Min	2	2
Max	17	8
3-Day re-admission (n, %)	3 (9.4%)	0 (0.0%)	Not calculated
30-Day re-admission (n, %)	7 (21.9%)	2 (2.1%)	Not calculated
ICU transfer (n, %)	6 (16.7%)	6 (5.6%)	Not calculated
Total days spent in ICU
Mean (SD)	4.9 (2.3)	2.8 (1.8)	.1085
Median	5	2	.0813
Min	2	1
Max	8	6
Mortality (n, %)	1 (3.1%)	0 (0.0%)	Not calculated

^aOutliers 4 SD above the mean were removed.

Discussion

We investigated VTE events in a population cohort that underwent an elective surgical procedure with the use of general anesthesia. Our study was primarily intended to capture the economic burden associated with VTE post-operatively in a sub-set of surgical inpatients whose procedure did not require a planned ICU stay post-operatively, in order to highlight the residual charges associated with VTE in this specific setting. Therefore, our observed incidence rate of 0.23% is not reflective of the entire inpatient population. Our economic analysis found that patients who experienced VTE in this study had a statistically significant longer length of hospital stay by more than 2 days. Those patients also had significantly higher hospital charges of close to $12,000.

The incidence of VTE has been reported in peer-reviewed literature for a wide range of patient populations and settings. An analysis of inpatient claims data by Boulet et al.¹¹ reported a prevalence of VTE as high as 2.5 events per 1,000 patients. Their study did not distinguish between inpatients who had undergone a surgical procedure and those who did not. Another study of patients undergoing elective surgery within 2 days of admission to an acute public hospital by Assareh et al.¹² reported a VTE incidence of 0.2%. Of note, studies that followed patients post-discharge to identify VTE events reported much higher rates. A study by Nelson et al.⁷, that included a post-discharge observation period of 30 days among VA patients, reported an incidence of 0.4% for post-operative inpatients. A much higher incidence rate of 0.8% was reported by White et al.¹³ in a study that followed patients for VTE events during hospitalization for surgery and VTE-related re-hospitalizations up to 91 days from the day of surgery. Notably, VTE incidence rates can vary by procedure type. A study of elective gastrointestinal procedures by Mukherjee et al.¹⁴ reported an incidence rate of 1.5%. A much higher incidence rate of 17.7% was reported by Beccatini et al.¹⁵ for inpatients undergoing laparoscopic surgery among cancer patients, a known risk factor for VTE⁴. The impact of specific procedures, among other risk factors, has been addressed by various guidelines, such as the CHEST guidelines¹⁶. In our analysis of the 10 most frequent inpatient surgeries observed in our study, VTE events were identified in only four of the 10 procedures, suggesting a possible relationship between procedure and occurrence of VTE events, but further research is needed to evaluate this observation.

Our study was the first to report resource utilization associated with VTE events for inpatients undergoing a wide range of elective surgical procedures with general anesthesia. We found that length of stay, rate of re-admission, and days spent in the ICU were higher for patients experiencing VTE compared to those who did not, although only length of stay was shown to be statistically significant. We speculate that additional resource utilization might partially explain the higher incremental charges associated with VTE that we observed.

Our study has shown an incremental charge associated with post-operative VTE of $11,979. The reported cost of VTE can vary tremendously, depending on study design and settings. A study of VTE events among patients recently hospitalized for acute medical illness in Olmstead County by Cohoon et al.¹⁷ showed an incremental charge associated with VTE of $38,374 per patient from their index hospitalization up to 5 years post-discharge. Studies that looked at shorter time frames reported lower incremental charges. A study of patients undergoing total knee arthroscopy (TKA) by Bohensky et al.¹⁸ reported an excess 30-day cost per patient per VTE event of $3,227. Another study of patients undergoing TKA procedures by Shahi et al.¹⁹ found an incremental charge associated with VTE of $14,516. Specific cost drivers of VTE were studied by Fanikos et al.²⁰, who reported that radiographic diagnostic testing alone for VTE carried an estimated cost of $672, while pharmacy costs for patients with PE tallied up to $966. Higher costs of care for initial VTE events have been attributed to longer length of stay, higher prescription rates, and other clinical services²¹. Societal costs associated with initial or recurrent VTE events have not been widely studied²¹. These costs may include years of reduced productivity and lower financial support for family members due to disability or fatal events, as well as costs from work loss or school absenteeism²¹.

VTE events are associated with high inpatient charges and are potentially preventable outcomes. Certain risk factors have been associated as major pro-thrombotic stimuli, such as age, comorbidities, type of surgery, and length of surgery¹⁶. Knowing these major risk factors before a patients’ surgery may allow for careful consideration and attention for VTE prophylaxis in patients with these risk factors. However, other lesser-known risk factors may also contribute to risk of VTE, which may also be identified in patients prior to surgery. According to the Surgeon General’s Call to Action to Prevent DVT/PE from 2008²², “It is often the combination of an individual with genetic and/or acquired risk factors who also experience one of these triggering events that leads to the development of a DVT or PE” (pg. 16). A systematic review from 2005 concluded that a significant association exists between the presence of Factor V Leiden (FVL) and Prothrombin gene (F2 G20210A) mutations and the risk of experiencing a first unprovoked VTE event²³. To put this in perspective, a computerized registry of patients with venous thromboembolism (RIETE) reported that 32% of patients tested for thrombophilia had either a FVL or PG mutation²⁴. In light of this, it may be of interest to physicians to more proactively assess not only their patients’ major risk factors, based on their history alone, but to include their genetics, allowing at-risk patients such as patients with FVL and F2 mutations to be more closely monitored or more aggressively managed after elective inpatient surgeries, potentially leading to reduction in VTE risk and associated costs. Few studies have assessed the potential economic impact of genetic testing in assessing risk for VTE events, but recent evidence has been promising, suggesting potential cost-savings of such testing for VTE risk²⁵. Future research is needed to further examine the relationship between a patient’s genetics and his or her incidence of VTE in order to determine if genetic testing indeed would reduce the perioperative incidence of VTE and, therefore, improve patient outcomes and reduce hospital costs described in our study

Limitations

Our study was retrospective in nature; a prospective study would have provided more robust data. Due to limitations of the database used, we may have captured patients who initially had a scheduled outpatient surgical procedure, but who were then admitted as inpatients if they experienced a complication within 3 days post-operatively. Such patients were included with the patients who were admitted as inpatients for the purpose of having a surgical procedure. Additionally, while we were able to assess admitting diagnosis, we could not be certain of all cause(s) of any 3-day or 30-day re-admissions captured. Similarly, the incidence of re-admissions captured does not include hospital stays from patients who were re-admitted to hospitals that are not currently part of the CDM database. Additionally, we were unable to track patient cases past 30 days, excluding the significant fraction of patients that are frequently re-admitted due to VTE, particularly within the 3–12-month window post-operatively. Due to the rarity of VTE cases, only a small number of non-VTE controls (n = 108) were matched to VTE patients. Therefore, the small number of matched non-VTE controls may not be representative of the unmatched non-VTE population (n = 17,687). There are several other limitations that are inherent to retrospective studies utilizing charge master data that apply to this study. We cannot be certain that the diagnosis codes used were truly clinically diagnosed VTE events, nor can we be fully certain of the completeness of the data utilized. We did not consider major confounders such as comorbidities in our analysis, which are likely associated with higher risk of VTE, as this was outside the scope of the study design. Conversely, we cannot be certain that the claims captured in this study included asymptomatic VTE events that often go undiagnosed in this population, as claims are typically reported for symptomatic VTE events that are recognized and treated by clinicians, while asymptomatic VTE events may go unrecognized and untreated due to lack of signs and symptoms Thus, coding discrepancies with charge master data may have resulted in an under-reported VTE incidence, as they may not necessarily include undiagnosed asymptomatic VTE events. We also specifically studied only elective surgical inpatients in certain procedure categories, excluding procedures of the heart, brain, lungs, and obstetric surgeries. An analysis of all surgical procedures may have provided different results. We also did not follow these patients post-discharge to identify subsequent VTE events. Furthermore, we did not evaluate the context of anticoagulation use. While all codes in the CDM database contain a date stamp, they lack a time stamp. Additionally, information on drug dosing is absent from the CDM database. Therefore, we could not be certain without assumption whether any anticoagulant administered was used therapeutically (e.g. day of surgery or after) or prophylactically (e.g. given the day prior to surgery), especially considering how therapeutic and prophylactic doses of the same anticoagulant often differ. We did not apply a cost-to-charge ratio when assessing hospital charges for total hospital stay, due to unavailability. Thus, our reported hospital charges may not necessarily translate to the hospital costs accrued for patients in this study, as charges are often over-inflated when compared to hospital costs and reimbursed payments. The incremental charge reported in our study is reflective of resource utilization and charges accrued specifically for hospital-related VTE events. This does not include any additional costs, direct or indirect, that may be associated post-discharge. Therefore, it is likely that the charges reported by our study are more conservative, as we did not take into account outpatient charges post-discharge, charges associated with VTE recurrences, charges for re-admission, or societal costs associated with post-operative VTE events.

Conclusion

This study assessed the charges of patients with VTE events for inpatients undergoing elective surgery with general anesthesia, exclusive of procedures of the heart, brain, lungs, and obstetrics. Patients undergoing elective inpatient surgical procedures had a significantly longer length of stay and significantly higher charges than comparable patients without a VTE event.

Transparency

Declaration of funding

This study and manuscript was supported by Millennium Health. The design, study conduct, and financial support for the study were provided by Millennium Health. Millennium Health participated in the study design, research, interpretation of data, writing, review, and approval of the manuscript.

Declaration of financial/other relationships

VD and MDK were/are salaried employees of IQVIA, who received consultancy fees from Millennium Health. FC and RBJ are employees of Millennium Health, and may own Millennium Health stock or stock options. AS has received post-doctoral fellowship funding from UCSD. RG and AM are employees of UC San Diego Health Systems and received consultancy fees from Millennium Health for providing clinical expertise for the design of this study. AM is also receiving a mentored training grant from the International Anesthesia Research Society. The authors have no other relevant affiliations or financial involvement with any organization or entity with financial interest in, or financial conflict with, the subject matter or materials discussed in the manuscript, apart from those disclosed. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgments

We would like to acknowledge Sanyi Zhao, MS, for her input on the statistical analysis plan for this study.