Abstract
Background:
The American Society of Anesthesiologists’ (ASA) Choosing Wisely Top-5 list of activities to avoid includes: “Don’t obtain baseline laboratory studies in patients without significant systemic disease (ASA I or II) undergoing low-risk surgery - specifically complete blood count, basic or comprehensive metabolic panel, coagulation studies when blood loss (or fluid shifts) is/are expected to be minimal.” Accordingly, we define low value preoperative tests (LVTs) as those performed prior to minor surgery in patients without significant systemic disease. The objective of the current study was to examine the extent, variability, drivers, and costs of LVTs prior to carpal tunnel release (CTR) surgeries in the US Veterans Health Administration (VHA).
Methods:
Using Fiscal Year (FY) 2015–17 data derived from the VHA Corporate Data Warehouse, we determined the overall national and facility-level rates and associated costs of receiving any of eight common LVTs in the 30 days prior to CTR in ASA Physical Status (ASA-PS) I-II patients. We also examined the patient, procedure, and facility factors associated with receiving at least one LVT with mixed-effects logistic regression, and the number of tests received with mixed-effects negative binomial regression.
Results:
From FY15–17, 10,000 ASA Class I-II patients received a CTR by 699 surgeons in 125 VHA facilities. Overall, 47.0% of patients had a CTR that was preceded by at least one LVT, with substantial variability between facilities (range = 0–100%; Interquartile Range = 36.3%), representing $339,717 in costs. Older age and female gender were associated with higher odds of receiving at least one LVT. Local vs. other modes of anesthesia was associated with lower odds of receiving at least one LVT. Several facilities experienced large (>25%) increases or decreases from FY15 to FY17 in the proportion of patients receiving at least one LVT.
Conclusions:
Counter to guidance from the ASA, we found that almost half of CTRs performed on ASA Class I-II VHA patients were preceded by at least one LVT. Although the total cost of these tests is relatively modest, CTR is just one of many low-risk procedures (e.g., trigger finger release, cataract surgery) that may involve similar preoperative testing practices. These results will inform site selection for qualitative investigation of the drivers of low value testing, and the development of interventions to improve preoperative testing practice, especially in locations where rates of LVT are high.
Introduction
Preoperative screening tests are valuable only if they have a reasonable likelihood of revealing actionable data that might alter clinical management or patient outcomes. Preoperative screening tests, especially for patients without significant systemic disease undergoing low-risk surgery, often do not change perioperative management, may lead to unnecessary follow-up testing and invasive interventions, and can unnecessarily delay surgery.1–7 Accordingly, the American Society of Anesthesiologists’ (ASA) Choosing Wisely Top-5 list of activities to avoid includes: “Don’t obtain baseline laboratory studies in patients without significant systemic disease (ASA I or II) undergoing low-risk surgery - specifically complete blood count, basic or comprehensive metabolic panel, coagulation studies when blood loss (or fluid shifts) is/are expected to be minimal.”8 The United States (US) Agency for Healthcare Research and Quality (AHRQ) and the United Kingdom National Institute for Health and Care Excellence (NICE) have issued similar guidance.9–11 Therefore, we define low value preoperative tests (LVTs) as those performed prior to minor surgery in patients without significant systemic disease.
Unfortunately, low value preoperative tests continue to be a common and major contributor to unnecessary health care spending in the US and Canada6,7,12–14, highlighting the need to better understand its drivers and what strategies might be effective to improve practice. Over 500,000 carpal tunnel releases (CTR) are performed each year in the US.15 CTR is a highly standardized operation with infrequent complications16,17, making it well suited to examine the extent, variability, drivers, and costs of low value preoperative testing in the US Veterans Health Administration (VHA), where over 10,000 CTRs are annually performed. Specifically, we had the following goals: 1) Determine the overall and facility-level rates, and changes in rates between Fiscal Year (FY) 2015–17, of receiving any of eight common low value preoperative tests in the 30 days prior to ASA Physical Status Classification (ASA-PS) I or II patients; 2) Examine the patient, procedure, and facility factors that are associated with receiving at least one low value test and the number of tests received; and 3) Estimate the overall and facility-level costs, and changes in costs between FY 2015–17. Knowing more about patient and context factors that drive low value preoperative testing is essential to inform site selection for qualitative investigation of the drivers of low value testing, and development of interventions to improve practice, especially in locations where use of LVTs is high.
Methods
Data Source and Cohort Definition:
This study was approved by the Stanford University Institutional Review Board that granted a waiver of informed consent. All data were derived from the VHA Corporate Data Warehouse (CDW), a nationwide relational database of VHA healthcare records. The cohort consisted of unilateral or bilateral CTRs received in FYs 2015–17 by all VHA patients who were clinically determined to be ASA-PS I (A normal healthy patient) or ASA-PS II (patient with mild systemic disease without substantive functional limitations)18,19.
Preoperative Screening Tests:
Preoperative tests were identified using Common Procedural Terminology (CPT) procedure codes recorded in the VHA CDW. Tests included basic metabolic panel (BMP); complete blood count (CBC); cardiac stress tests, urinalysis; chest x-ray; pulmonary function testing (PFT); electrocardiography (EKG), and trans-thoracic echocardiograms (TTE). We were also interested in the receipt of a common “legacy bundle” of tests, specifically EKG, X-ray, CBC, and BMP.20 We did not examine tests used to make or refine the presenting clinical diagnosis, for example nerve conduction tests for the diagnosis of carpal tunnel syndrome.
Defining the tests as preoperative:
No administrative or billing data element in VHA CDW marks a particular test as “preoperative.” Therefore, we developed a method to identify screening tests that were ordered prior to CTR (Figure 1). A test was considered preoperative if it occurred within 30 days prior to CTR21, and within 30 days after an encounter in a specific VHA clinic where preoperative CTR screening tests are typically ordered, including those that are explicitly dedicated to preoperative care (i.e., 416 - Pre-Surgery Evaluation by Non-MD; 419 - Anesthesia Pre-Op/Post-Op Consult; 432 - Pre-Surgery Evaluation by MD; 433 - Pre-Surgery Evaluation by Nursing) or are likely preoperative (e.g., Hand Surgery, Neurosurgery, Plastic Surgery, Orthopedic clinic before CTR). A test was omitted if it also occurred within 30 days before a major non-CTR procedure (e.g., total knee arthroplasty) that justified the test being ordered.
Figure 1:
A Method for Determining Which Tests are Preoperative for a Target Procedure vs. Ordered for Other Procedures or Purposes
Statistical Analysis:
Overall and facility-level rates of CTRs that were preceded by at least one low value test were calculated. Rates of CTRs preceded by each specific test were also calculated. Mixed-effects logistic regression was used to examine associations between patient characteristics (e.g., demographics, comorbidities), procedural characteristics (e.g., bilateral, anesthetic technique) and facility characteristics (i.e., facility surgical complexity, annual CTR volume) and receipt of at least one low value test, with random intercepts for VHA facility and surgeon nested within facility where the CTR was performed.22 Mixed-effects negative binomial regression was used to examine associations between the same patient, procedure, and facility characteristics and the number of low value tests received. We also conducted a mixed effects logistic regression to examine associations between patient, procedure, and facility characteristics and receipt of a “legacy bundle” of preoperative screening tests (i.e., EKG, X-ray, CBC, and BMP). We conducted sensitivity analyses to examine if an interaction effect existed between cardiopulmonary comorbidities and choice of anesthetic technique. Odds ratios,95% confidence intervals and p-values were produced for all logistic regression model coefficients. Further, due to the large number of coefficients estimated in these exploratory/descriptive models, we calculated Benjamini-Hochberg False Discovery Rate adjusted p-values to determine statistical significance at p<0.05 while controlling false positive findings to 5%.
To better understand the magnitude of variance at the patient-level, surgeon-level, and facility-level, we calculated intraclass correlation coefficients (ICCs) and median odds ratios (MORs) for the random effects. ICCs can be conceptually interpreted as the proportion of variance at each level.23 MOR is the median value of the odds ratios between a facility (or surgeon) with higher risk of providing a LVT and a facility (or surgeon) with lower risk of providing a LVT.23
Centers for Medicare Services (CMS) reimbursement Fee Schedule, for physician and facility fees, and the CMS clinical laboratory fee schedule for 2017 were used to assign a cost to each preoperative test, which we then added to determine overall and facility-level costs. Finally, changes between FY15 and FY17 in testing rates were determined in order to select facilities for a future qualitative study. All statistical analyses were conducted using R.24
Results
From FY15–17, 10,000 ASA-PS I-II patients received CTRs by 699 surgeons in 125 VHA facilities. Characteristics of these patients, procedures, and facilities are summarized in Table 1. Overall, 47.0% of CTRs were preceded by at least one LVT. Of the 4,699 CTRs receiving at least one test, the number of tests obtained ranged from 1 to 14, with 85% receiving 4 or fewer tests (Figure 2). The total number of low value tests was 13,360 which cost $339,717 (Table 2). The most common tests prior to CTR were CBC (32.9% of CTRs), BMP (29.9% of CTRs), and EKG (27.6% of CTRs). Less than one percent of CTRs were preceded by a TTE or cardiac stress test. Even though only 14.7% of CTR were preceded by a chest x-ray, they accounted for almost half of the added costs of LVT ($151,510). Furthermore, only 7.2% of CTRs were preceded by a “legacy bundle” of preoperative tests (EKG, chest x-ray, CBC, BMP), but these accounted for 29.4% ($99,733) of total added costs.
Table 1:
Patient, Surgery, and Facility Characteristics of Veterans Health Administration Carpal Tunnel Release Patients in Fiscal Year 2015 – 2017 (N = 10,000)
| Any preop-test | Total | ||
|---|---|---|---|
| Patient characteristics | No (n=5301) | Yes (n=4699) | |
| Age, mean (SD) | 55.0 (13.7) | 55.7 (13.4) | 55.3 (13.5) |
| Gender, No. (%) | |||
| Male | 4524 (53.6) | 3920 (46.4) | 8444 (84.4) |
| Female | 777 (49.9) | 779 (50.1) | 1556 (15.6) |
| Race/Ethnicity, No. (%) | |||
| White, non-Hispanic | 4040 (54.4) | 3382 (45.6) | 7422 (74.2) |
| Black or African American | 617 (49.4) | 631 (50.6) | 1248 (12.5) |
| Hispanic white or other minority | 377 (47.2) | 422 (52.8) | 799 (8.0) |
| Unknown | 267 (50.3) | 264 (49.7) | 531 (5.3) |
| Marital Status, No. (%) | |||
| Married | 2959 (53.1) | 2618 (46.9) | 5577 (55.8) |
| Single or never married | 822 (53.8) | 706 (46.2) | 1528 (15.3) |
| Separated or widow(er) | 1484 (52.4) | 1350 (47.6) | 2834 (28.3) |
| Unknown | 36 (59.0) | 25 (41.0) | 61 (0.6) |
| Body Mass Index, No. (%) | |||
| Normal (healthy weight | 624 (53.1) | 552 (46.9) | 1176 (11.8) |
| Underweight | 14 (63.6) | 8 (36.4) | 22 (10.2) |
| Overweight | 1747 (51.7) | 1633 (48.3) | 3380 (33.8) |
| Moderately obese | 1690 (52.7) | 1515 (47.3) | 3205 (32.0) |
| Severely obese | 729 (52.2) | 668 (47.8) | 1397 (14.0) |
| Very severely obese and up | 301 (55.9) | 237 (44.1) | 538 (5.4) |
| Unknown | 196 (69.5) | 86 (30.5) | 282 (2.8) |
| Service Connection | |||
| Not service connected | 614 (54.5) | 512 (45.5) | 1126 (11.3) |
| Less than 50% | 1269 (52.9) | 1130 (47.1) | 2399 (24.0) |
| More than 50% | 2278 (53.4) | 1989 (46.6) | 4267 (42.7) |
| Unknown | 1140 (51.6) | 1068 (48.4) | 2208 (22.1) |
| Elixhauser Comorbidities, No. (%) | |||
| Congestive heart failure | 32 (61.5) | 20 (38.5) | 52 (0.5) |
| Valvular disease | 44 (59.5) | 30 (40.5) | 74 (0.7) |
| Peripheral vascular disease | 76 (53.5) | 66 (46.5) | 142 (1.4) |
| Hypertension | 1568 (50.8) | 1518 (49.2) | 3086 (30.9) |
| Hypertension with complications | 75 (54.7) | 62 (45.3) | 137 (1.4) |
| Other neurological disorders | 133 (52.6) | 120 (47.4) | 253 (2.5) |
| Chronic pulmonary disease | 387 (54.6) | 322 (45.4) | 709 (7.1) |
| Diabetes Mellitus | 371 (50.8) | 359 (49.2) | 730 (7.3) |
| Diabetes Mellitus with complications | 243 (57.4) | 180 (42.6) | 423 (4.2) |
| Hypothyroidism | 264 (52.2) | 242 (47.8) | 506 (5.1) |
| Renal failure | 77 (50.3) | 76 (49.7) | 153 (1.5) |
| Liver disease | 133 (49.3) | 137 (50.7) | 270 (2.7) |
| Solid tumor w/o metastasis | 95 (47.5) | 105 (52.5) | 200 (2.0) |
| Rheumatoid arthritis | 89 (49.2) | 92 (50.8) | 181 (1.8) |
| Weight loss | 39 (59.1) | 27 (40.9) | 66 (0.7) |
| Fluid and electrolyte disorders | 106 (50.0) | 106 (50.0) | 212 (2.1) |
| Deficiency anemia | 170 (48.9) | 178 (51.1) | 348 (3.5) |
| Alcohol abuse | 382 (53.3) | 335 (46.7) | 717 (7.2) |
| Drug abuse | 227 (48.5) | 241 (51.5) | 468 (4.7) |
| Psychosis | 440 (50.9) | 425 (49.1) | 865 (8.6) |
| Depression | 970 (51.2) | 926 (48.8) | 1896 (19.0) |
| Obstructive sleep apnea, No. (%) | 696 (52.4) | 631 (47.6) | 1327 (13.3) |
| ASA Class, No. (%) | |||
| class I | 317 (68.2) | 148 (31.8) | 465 (4.6) |
| class II | 4984 (52.3) | 4551 (47.7) | 9535 (95.4) |
| Surgery characteristics | |||
| Bilateral CTR, No. (%) | 125 (47.5) | 138 (52.5) | 263 (2.6) |
| Local anesthesia, No. (%) | 996 (76.7) | 303 (23.3) | 1299 (13.0) |
| Surgery fiscal year, No. (%) | |||
| 2015 | 1739 (51.6) | 1629 (48.4) | 3368 (33.7) |
| 2016 | 1670 (52.4) | 1519 (47.6) | 3189 (31.9) |
| 2017 | 1892 (55.0) | 1551 (45.0) | 3443 (34.4) |
| Facility characteristics | |||
| Facility surgical complexity a | |||
| Ambulatory basic | 319 (53.7) | 275 (46.3) | 594 (5.9) |
| Ambulatory advanced | 244 (54.5) | 204 (45.5) | 448 (4.5) |
| Inpatient standard | 398 (67.1) | 195 (32.9) | 593 (5.9) |
| Inpatient intermediate | 1279 (56.5) | 986 (43.5) | 2265 (22.6) |
| Inpatient complex | 2961 (50.7) | 2882 (49.3) | 5843 (58.4) |
| Unknown | 100 (38.9) | 157 (61.1) | 257 (2.6) |
| Facilities annual CTR volume, mean (SD) | 40.0 (22.6) | 40.1 (23.2) | 40.0 (22.9) |
Note. ASA: American Society of Anesthesiologists, CTR: Carpal Tunnel Release.
Figure 2:
Distribution of Numbers of Low Value Tests Received by ASA Class I or II Patients Prior to Carpal Tunnel Release
Table 2:
Low Value Preoperative Tests Received by Veterans Health Administration Patients Prior to 10,000 Carpal Tunnel Releases in Fiscal Year 2015–2017
| Preoperative Test | Percent Received >=1 Tests | Total Number | Total Cost |
|---|---|---|---|
| Complete blood count | 32.9% | 3,467 | $35,793 |
| Basic metabolic profile | 29.9% | 3,168 | $40,534 |
| Electrocardiography | 27.6% | 3,227 | $45,648 |
| Urinalysis | 13.3% | 1,476 | $5,338 |
| Chest x-ray | 14.7% | 1,485 | $151,510 |
| Pulmonary function tests | 3.8% | 448 | $3,762 |
| Transthoracic echocardiogram | <1% | 39 | $22,017 |
| Cardiac stress test | <1% | 50 | $35,115 |
| Total | 47.0% | 13,360 | $339,717 |
Mixed-effects logistic regression (Table 3) revealed that, after adjusting for the false discovery rate, older age and female gender were associated with higher odds of receiving at least one low value test. Patient’s receiving local versus other anesthetic techniques (e.g. general, monitored anesthesia care, regional block) had lower odds of receiving at least one low value test. We conducted sensitivity analyses to examine if an interaction effect existed between cardiopulmonary comorbidities and choice of a sedating anesthetic technique, but none was found (data not shown). The ICCs were 0.18 (p<.001) at the VHA facility level and 0.13 (p<.001) at the surgeon/facility level. Facility-level MOR was 2.39 with a bootstrapped credible interval of 2.12 to 2.54. Surgeon/facility-level MOR was 2.13 with a bootstrapped credible interval of 2.03 to 2.20.
Table 3:
Mixed-effects Logistic Regression Model Describing the Association Between Patient, Surgery and Facility Characteristics and Receipt of Any Pre-Operative Test Before Carpal Tunnel Release.
| OR (95% CI) | p-value | FDR Adjusted p-valuea |
|
|---|---|---|---|
| Facility surgical complexityb | 0.546 | ||
| Inpatient standard complexity | 1.00 | ||
| Ambulatory basic | 1.79 (0.57 – 5.68) | 0.321 | 0.703 |
| Ambulatory advanced | 2.91 (0.84 – 10.1) | 0.092 | 0.523 |
| Inpatient intermediate | 2.15 (0.85 – 5.43) | 0.106 | 0.523 |
| Inpatient complex | 2.12 (0.88 – 5.09) | 0.094 | 0.523 |
| Unknown | 2.59 (0.51 – 13.1) | 0.249 | 0.691 |
| Facilities annual CTR volume | 1.00 (0.99 – 1.01) | 0.409 | 0.790 |
| Distance to surgical facility (per 100 Mi.) | 0.99 (0.97 – 1.01) | 0.322 | 0.703 |
| Bilateral CTR (vs. unilateral) | 1.23 (0.90 – 1.69) | 0.202 | 0.593 |
| Age (per 10 years) | 1.11 (1.06 – 1.16) | < 0.001 | < 0.001 |
| Female (vs. male) | 1.32 (1.15 – 1.52) | < 0.001 | 0.002 |
| Race/Ethnicityb | 0.693 | ||
| non-Hispanic white | 1.00 | ||
| Black or African American | 0.97 (0.83 – 1.14) | 0.729 | 0.934 |
| Hispanic white or other minority | 1.08 (0.90 – 1.30) | 0.413 | 0.790 |
| Unknown | 1.08 (0.87 – 1.35) | 0.459 | 0.820 |
| Marital Statusb | 0.503 | ||
| Married | 1.00 | ||
| Single or never married | 0.93 (0.80 – 1.07) | 0.323 | 0.703 |
| Separated/divorced or widow(er) | 1.01 (0.90 – 1.14) | 0.817 | 0.935 |
| Service Connection b | 0.433 | ||
| Not service connected | 1.00 | ||
| Less than 50% | 1.13 (0.94 – 1.36) | 0.191 | 0.593 |
| More than 50% | 1.13 (0.95 – 1.34) | 0.172 | 0.593 |
| Unknown | 1.17 (0.96 – 1.41) | 0.115 | 0.523 |
| Body Mass Index b | 0.192 | ||
| Normal (healthy) weight | 1.00 | ||
| Underweight | 0.36 (0.11 – 1.22) | 0.101 | 0.523 |
| Overweight | 1.04 (0.88 – 1.22) | 0.671 | 0.933 |
| Moderately obese | 0.99 (0.84 – 1.17) | 0.876 | 0.941 |
| Severely obese | 1.14 (0.94 – 1.39) | 0.188 | 0.593 |
| Very severely obese and up | 1.04 (0.80 – 1.34) | 0.783 | 0.935 |
| Unknown | 0.84 (0.59 – 1.19) | 0.323 | 0.703 |
| Elixhauser Comorbidities (yes vs. no) | |||
| Congestive heart failure | 0.69 (0.34 – 1.40) | 0.305 | 0.703 |
| Valvular disease | 0.96 (0.52 – 1.75) | 0.885 | 0.941 |
| Peripheral vascular disease | 1.01 (0.67 – 1.54) | 0.946 | 0.946 |
| Hypertension | 1.14 (1.02 – 1.28) | 0.022 | 0.183 |
| Hypertension with complications | 1.04 (0.67 – 1.63) | 0.864 | 0.941 |
| Other neurological disorders | 1.08 (0.80 – 1.46) | 0.623 | 0.933 |
| Chronic pulmonary disease | 0.96 (0.80 – 1.16) | 0.697 | 0.935 |
| Diabetes Mellitus | 1.14 (0.94 – 1.38) | 0.186 | 0.593 |
| Diabetes Mellitus with complications | 0.84 (0.65 – 1.08) | 0.168 | 0.593 |
| Hypothyroidism | 1.09 (0.88 – 1.36) | 0.427 | 0.790 |
| Renal failure | 1.10 (0.73 – 1.65) | 0.648 | 0.933 |
| Liver disease | 1.08 (0.80 – 1.45) | 0.611 | 0.933 |
| Solid tumor w/o metastasis | 1.12 (0.79 – 1.59) | 0.509 | 0.848 |
| Rheumatoid arthritis | 0.95 (0.66 – 1.35) | 0.758 | 0.935 |
| Weight loss | 0.94 (0.52 – 1.68) | 0.822 | 0.935 |
| Fluid and electrolyte disorders | 1.01 (0.72 – 1.42) | 0.939 | 0.946 |
| Deficiency anemia | 1.10 (0.84 – 1.44) | 0.480 | 0.828 |
| Alcohol abuse | 0.97 (0.79 – 1.19) | 0.773 | 0.935 |
| Drug abuse | 1.05 (0.83 – 1.34) | 0.672 | 0.933 |
| Psychosis | 1.08 (0.90 – 1.29) | 0.407 | 0.790 |
| Depression | 1.01 (0.89 – 1.16) | 0.823 | 0.935 |
| Obstructive Sleep Apnea (yes vs. no) | 1.01 (0.87 – 1.17) | 0.909 | 0.946 |
| ASA class (II vs. I) | 1.39 (1.08 – 1.80) | 0.011 | 0.136 |
| Surgery Fiscal Year b | 0.028 | ||
| 2015 | 1.00 | ||
| 2016 | 0.96 (0.84 – 1.10) | 0.560 | 0.903 |
| 2017 | 0.84 (0.74 – 0.97) | 0.016 | 0.164 |
| Local Anesthesia (yes vs. no) | 0.63 (0.51 – 0.78) *** | < 0.001 | < 0.001 |
Note. FDR: False Discovery Rate, OR: Odds Ratio, CI: Confidence Interval, CTR: Carpal Tunnel Release. Facility intraclass correlation coefficient (ICC) = 0.18 (p<.001), median odds ratio (MOR) = 2.39 (95% credibility interval 2.32 – 2.54); Surgeon-within-facility ICC = 0.13 (p<.001), MOR = 2.13 (95% credibility interval 2.03 – 2.20).
p-values adjusted for false discovery rate.
Overall p-values for categorical predictors with > 2 levels based on likelihood-ratio test of the model with and without that predictor.
In the analysis of the number of tests received, we found that older age, female gender, hypertension, ASA-PS II vs I, and non-local anesthesia were associated with receiving a higher number of preoperative tests (see supplemental Table S1). The ICC was 0.06 (p<.001) at the facility-level and 0.04 (p<.01) at the surgeon within facility level. We also found that older age and non-local anesthesia were associated with higher odds of receiving a legacy bundle of preoperative tests (see supplemental Table S2). At the facility-level, the ICC was 0.57 (p<.001) and the MOR was 8.69 (95% credibility interval 6.58 – 9.86). At the surgeon within facility level the ICC was 0.07 (p<.01) and the MOR was 2.14 (95% credibility interval 2.05 – 2.23).
In Figure 3, black dots represent the percent of CTRs receiving at least one LVT at VHA Facilities in FY15 (Range 0–100%, IQR = 36.3%). There were 21 facilities in which over 75% of CTRs received at least one low value test, and 26 facilities in which less than 25% of CTRs received at least one low value test. The red bars indicate increases, and green bars decreases, in the percent of CTRs receiving at least one LVT from FY15 to FY17. Of the 48 facilities that performed at least 25 CTR in FY15, five reduced CTRs that were preceded by LVTs at least 25% in absolute terms (e.g., 75% to 50%) and five facilities increased at least 25% in absolute terms (e.g., 50% to 75%).
Figure 3:
Black dots represent the percent of patients receiving at least one LVT in FY15 in VA Facilities. The red bars indicate increases and green bars indicate decreases in the percent of CTRs that were preceded by at least one LVT from FY15 to FY17.
Discussion
The principles of high-value, patient-centered health care demand that patients not be subjected to testing procedures that do not improve their clinical management or outcomes, that can cause them unintended harm, waste their time, and that consume resources that might be used to improve the access and quality of care for them and other patients. Counter to guidance from the ASA and other professional organizations, we found that almost half of CTRs performed on generally healthy VHA patients were preceded by at least one low value preoperative test. Although the total cost of the tests is relatively modest ($339,717), it should be noted that CTR is just one of many low-risk procedures (e.g., trigger finger release, cataract surgery) that may involve similar preoperative testing practices and that could involve substantially higher added costs. Also, we chose CMS reimbursement fees for simplicity and because our goal was to roughly estimate and compare the burden of LVT across facilities, not necessarily pinpoint the exact financial implications. The use of actual charges (not relevant in VA) or costs would have resulted in different figures.
A main purpose of this study was to identify possible drivers of low value preoperative testing for CTR in VHA. We found that older patients and female patients were more likely to receive low value tests. Also, patients receiving local anesthesia vs. other anesthetic techniques were less likely to receive a low value test. Our analyses also revealed the limitations of using ASA-PS I or II as a marker for “patients without systemic disease.” There were, for example, a small number of patients included in our sample who had comorbidities that strongly suggest ASA-PS III or higher (e.g., congestive heart failure). However, these more serious comorbidities were relatively infrequent and did not predict receipt of preoperative tests.
One of the goals of multilevel analyses is to determine how much of the outcome variance exists at the patient-level versus at the surgeon and facility levels. Knowing how the outcome variance is partitioned can help guide qualitative study of potential drivers and ensure that quality improvement interventions are properly targeted. Regarding odds of receiving at least one LVT, significant variability existed at both the facility and surgeon-within-facility levels. This suggests that, even while controlling for patient factors, low value testing is much more common at some facilities compared to others, and also for some surgeons within the same facility. The odds of getting a legacy bundle of tests was even more clustered at the facility-level. Indeed, although legacy test bundles prior to CTR are relatively rare, a small number of facilities order legacy bundles for the vast majority of their CTR patients. These facilities are now being recruited for qualitative study to better understand their practice patterns and opportunities for quality improvement.
Another major goal of the study was to identify sites for qualitative investigation. Implementation scientists often study sites with very high or low performance in order to learn about the barriers or facilitators of a particular practice, termed positive or negative deviance studies.25–28. Our analyses identified a wide distribution of preoperative testing practice, with many facilities ordering LVTs for nearly all or none of their generally healthy CTR patients. Interviewing key informants at these facilities to learn the structures, policies, beliefs, and decisions that underlie test ordering behavior will inform the development of strategies to change practice.
Perhaps more useful from an implementation science and quality improvement perspective, our analyses revealed several high-volume sites with large changes in LVT practice from FY15 to FY17 (Figure 3). Looking to sites with large recent changes is a novel approach to design change strategies. By interviewing key informants at these “delta sites”, we hope to learn how certain facilities improved and why testing appeared to increase substantially at other facilities. This information will then be used to develop and test a de-implementation intervention in a subsequent study.
Several limitations are worth noting. First, our method of identifying preoperative tests may have included some tests that were ordered for other purposes than the CTR, and may have excluded some tests that were ordered for the CTR. However, there is no reason to expect that the ambient level of misclassification would vary by facilities or surgeons. This provides some confidence that overall associations and distributions represent a meaningful, if imperfect, signal of preoperative testing practices. Our planned qualitative study of low value testing will shed light on this question. Second, VHA is a capitated publicly-funded healthcare system, so the patterns and drivers of preoperative test ordering behavior may be different than in other contexts. Third, anesthesia technique requested by the surgeon at time of scheduling was used, rather than the anesthesia technique applied, for which data are not readily available. Fourth, as noted, a small number of patients clinically determined to be ASA=PS I or II appeared to have comorbidities that suggest more severe illness. Fifth, potentially influential surgeon characteristics, such as specialty and years in practice, are not in the VA CDW and thus could not be examined. Sixth, it is important not to over-interpret null results for some levels of multi-category variables (e.g., BMI underweight), where sample size and precision are low, as reflected in descriptive data in Table 1 and confidence interval widths in Table 3. However, for the vast majority of regression coefficients in our models, especially for dichotomous variables, we had ample power to detect a 10% difference in the risk of getting a low value test - what might be considered a clinically important difference.
In summary, low value preoperative screening tests for generally healthy patients undergoing one minor procedure (CTR) appear to be common in VHA, especially at some facilities. Knowledge revealed by these analyses on the patient, procedure, and context factors will inform site selection and design of a our planned qualitative investigation of the drivers that underlie test ordering practices and change in practice, and the design of pilot inventions to reduce the burden of low value testing.
Supplementary Material
Key Points Summary.
Question:
What are the extent, variability and costs of LVTs for carpal tunnel release in the US Veterans Health Administration?
Findings:
Almost half of carpal tunnel releases performed on ASA-PS I or II VHA patients were preceded by at least one LVT.
Meaning:
These results will inform site selection for qualitative investigation of the drivers of low value testing, and development of interventions to improve preoperative testing practice, especially in locations where rates of low value preoperative testing are high.
The Glossary of Terms:
- ASA
American Society of Anesthesiologists
- ASA-PS
American Society of Anesthesiologists - Physical Status
- LVT
low value preoperative test
- CTR
carpal tunnel release
- VHA
US Veterans Health Administration
- FY
Fiscal Year
- US
United States
- AHRQ
Agency for Healthcare Research and Quality
- NICE
United Kingdom National Institute for Health and Care Excellence
- CDW
Corporate Data Warehouse
- CPT
Common Procedural Terminology
- BMP
basic metabolic panel
- CBC
complete blood count
- PFT
pulmonary function testing
- EKG
electrocardiography
- TTE
trans-thoracic echocardiograms
- ICC
intraclass correlation coefficients
- MOR
median odds ratios
- CMS
Centers for Medicare Services
Footnotes
None of the authors have competing financial interests. The views expressed do not reflect those of the US Department of Veterans Affairs (VA) or other institutions. This work was funded by grants from the VA HSR&D Service (IIR 16–216; RCS14–232; CDA 13–279).
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