Overtreatment in the United States Lyu, Heather; Xu, Tim; Brotman, Daniel ...
PloS one,
09/2017, Letnik:
12, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Overtreatment is a cause of preventable harm and waste in health care. Little is known about clinician perspectives on the problem. In this study, physicians were surveyed on the prevalence, causes, ...and implications of overtreatment.
2,106 physicians from an online community composed of doctors from the American Medical Association (AMA) masterfile participated in a survey. The survey inquired about the extent of overutilization, as well as causes, solutions, and implications for health care. Main outcome measures included: percentage of unnecessary medical care, most commonly cited reasons of overtreatment, potential solutions, and responses regarding association of profit and overtreatment.
The response rate was 70.1%. Physicians reported that an interpolated median of 20.6% of overall medical care was unnecessary, including 22.0% of prescription medications, 24.9% of tests, and 11.1% of procedures. The most common cited reasons for overtreatment were fear of malpractice (84.7%), patient pressure/request (59.0%), and difficulty accessing medical records (38.2%). Potential solutions identified were training residents on appropriateness criteria (55.2%), easy access to outside health records (52.0%), and more practice guidelines (51.5%). Most respondents (70.8%) believed that physicians are more likely to perform unnecessary procedures when they profit from them. Most respondents believed that de-emphasizing fee-for-service physician compensation would reduce health care utilization and costs.
From the physician perspective, overtreatment is common. Efforts to address the problem should consider the causes and solutions offered by physicians.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Vascular access for hemodialysis in the elderly Arhuidese, Isibor J.; Cooper, Michol A.; Rizwan, Muhammad ...
Journal of vascular surgery,
February 2019, 2019-Feb, 2019-02-00, 20190201, Letnik:
69, Številka:
2
Journal Article
Recenzirano
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The objective of this study was to compare the outcomes of arteriovenous fistulas (AVFs) with arteriovenous grafts (AVGs) in a large population-based cohort of elderly patients in the United States.
...A retrospective analysis was performed of all patients ≥75 years old in the prospectively maintained United States Renal Database System who had an AVF or AVG placed for hemodialysis (HD) access between January 2007 and December 2011. Outcomes were mortality, conduit patency, maturation, time to catheter-free dialysis, and infection. A χ2 test, Student t-test, Kaplan-Meier analysis, and multivariable Cox regression analysis were employed.
Of the 124,421 patients studied, there were 19,173 (15%) AVF initiates, 4480 (4%) AVG initiates, 29,872 (24%) AVF converts, 10,712 (9%) AVG converts, and 59,824 (48%) patients who persisted on HD catheters. Compared with AVF initiates, relative mortality was significantly higher for AVG initiates (adjusted hazard ratio aHR, 1.24; P < .001), AVF converts (aHR, 1.36; P < .001), AVG converts (aHR, 1.62; P < .001), and catheter-persistent patients (aHR, 2.23; P < .001). Primary patency (aHR, 1.21; P < .001) and primary assisted patency (aHR, 1.31; P < .001) were higher for AVF. Secondary patency was higher for AVGs within the first 4 months (aHR, 1.12; P < .001) but higher for AVFs beyond that time point (aHR, 1.25; P < .001). Maturation rate and median time to maturation were 80% vs 84% (P < .001) and 46 vs 26 days (P < .001) for AVF vs AVG.
Pre-emptive AVF remains the best mode of HD in elderly patients who can tolerate surgery. Patients who cannot tolerate pre-emptive surgery or have to initiate HD on an urgent basis with a catheter should convert to AVF when it is feasible if life expectancy is >4 months. If life expectancy is <4 months, surgical risk and quality of life should be considered in making the decision to persistently dialyze through HD catheter or to convert to AVG.
Postoperative acute kidney injury is common after major vascular surgery and is associated with increased morbidity, mortality, and cost. High-performance risk stratification using a machine learning ...model can inform strategies that mitigate harm and optimize resource use. It is hypothesized that incorporating intraoperative data would improve machine learning model accuracy, discrimination, and precision in predicting acute kidney injury among patients undergoing major vascular surgery.
A single-center retrospective cohort of 1,531 adult patients who underwent nonemergency major vascular surgery, including open aortic, endovascular aortic, and lower extremity bypass procedures, was evaluated. The validated, automated MySurgeryRisk analytics platform used electronic health record data to forecast patient-level probabilistic risk scores for postoperative acute kidney injury using random forest models with preoperative data alone and perioperative data (preoperative plus intraoperative). The MySurgeryRisk predictions were compared with each other as well as with the American Society of Anesthesiologists physical status classification.
Machine learning models using perioperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification (accuracy: 0.70 vs 0.64 vs 0.62, area under the receiver operating characteristics curve: 0.77 vs 0.68 vs 0.61, area under the precision-recall curve: 0.70 vs 0.58 vs 0.48).
In predicting acute kidney injury after major vascular surgery, machine learning approaches that incorporate dynamic intraoperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification. Machine learning methods have the potential for real-time identification of high-risk patients who may benefit from personalized risk-reduction strategies.
Intraoperative hypotension during major surgery is associated with adverse health outcomes. This phenomenon represents a potentially important therapeutic target for vascular surgery patients, who ...may be uniquely vulnerable to intraoperative hypotension. This review summarizes current evidence regarding the impact of intraoperative hypotension on postoperative complications in patients undergoing vascular surgery, focusing on potentially modifiable procedure- and patient-specific risk factors.
A scoping review of the literature from Embase, MEDLINE, and PubMed databases was conducted from inception to December 2019 to identify articles related to the effects of intraoperative hypotension on patients undergoing vascular surgery.
Ninety-two studies met screening criteria; 9 studies met quality and inclusion criteria. Among the 9 studies that defined intraoperative hypotension objectively, there were 9 different definitions. Accordingly, the reported incidence of intraoperative hypotension ranged from 8% to 88% (when defined as a fall in systolic blood pressure of >30 mm Hg or mean arterial pressure <65). The results demonstrated that intraoperative hypotension is an independent risk factor for longer hospital length of stay, myocardial injury, acute kidney injury, postoperative mechanical ventilation, and early mortality. Vascular surgery patients with comorbid conditions that confer increased vulnerability to hypoperfusion and ischemia appear to be susceptible to the adverse effects of intraoperative hypotension.
There is no validated, consensus definition of intraoperative hypotension or other hemodynamic parameters associated with increased risk for adverse outcomes. Despite these limitations, the weight of evidence suggests that intraoperative hypotension is common and associated with major postoperative complications in vascular surgery patients.
Machine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using ...Society for Vascular Surgery (SVS) and Society of Thoracic Surgeons (STS)-defined aortic zones. The purpose of this study was to establish a trained, automatic machine learning aortic zone segmentation model to facilitate performance of an aortic zone volumetric comparison between patients with auTBAD based on the rate of aortic growth.
Patients with auTBAD and serial imaging were identified. For each patient, imaging characteristics from two computed tomography (CT) scans were analyzed: (1) the baseline CT angiography (CTA) at the index admission and (2) either the most recent surveillance CTA or the most recent CTA before an aortic intervention. Patients were stratified into two comparative groups based on aortic growth: rapid growth (diameter increase of ≥5 mm/year) and no or slow growth (diameter increase of <5 mm/year). Deidentified images were imported into an open source software package for medical image analysis and images were annotated based on SVS/STS criteria for aortic zones. Our model was trained using four-fold cross-validation. The segmentation output was used to calculate aortic zone volumes from each imaging study.
Of 59 patients identified for inclusion, rapid growth was observed in 33 patients (56%) and no or slow growth was observed in 26 patients (44%). There were no differences in baseline demographics, comorbidities, admission mean arterial pressure, number of discharge antihypertensives, or high-risk imaging characteristics between groups (P > .05 for all). Median duration between baseline and interval CT was 1.07 years (interquartile range IQR, 0.38-2.57). Postdischarge aortic intervention was performed in 13 patients (22%) at a mean of 1.5 ± 1.2 years, with no difference between the groups (P > .05). Among all patients, the largest relative percent increases in zone volumes over time were found in zone 4 (13.9%; IQR, −6.82 to 35.1) and zone 5 (13.4%; IQR, −7.78 to 37.9). There were no differences in baseline zone volumes between groups (P > .05 for all). The average Dice coefficient, a performance measure of the model output, was 0.73. Performance was best in zone 5 (0.84) and zone 9 (0.91).
We describe an automatic deep learning segmentation model incorporating SVS-defined aortic zones. The open source, trained model demonstrates concordance to the manually segmented aortas with the strongest performance in zones 5 and 9, providing a framework for further clinical applications. In our limited sample, there were no differences in baseline aortic zone volumes between patients with rapid growth and patients with no or slow growth.
Objective This study compared the performance of the Aorfix endograft (Lombard Medical, Oxfordshire, United Kingdom) in standard (<60°), highly angled (60°-90°), and severely angled (>90°) aortic ...necks in the PYTHAGORAS study and evaluated changes in neck morphology over time. Methods PYTHAGORAS is a prospective nonrandomized clinical trial of the Aorfix endograft. We divided the endovascular aneurysm repair (EVAR) cohort into groups by standard, high, and severe neck angle. The primary control group was patients concurrently undergoing open repair. Mortality at 30 days, 1 year, and 2 years and 30-day freedom from Society for Vascular Surgery major adverse events for the EVAR groups was compared with the open control. Aneurysm sac change, type I and III endoleaks, graft migration, and the reintervention rate at 1 and 2 years was compared between the standard, highly, and severely angled populations. The relative risk of graft complications with a neck diameter increase >10% was also calculated. At predetermined anatomic points, the effect of oversizing on aortic diameter was evaluated by calculating oversize percentage (1 − outer aortic diameter measured at a given time/stent graft diameter × 100%) preoperatively and at 3 years. In addition, the average oversizing percentage at 30 days and annually at 1 to 5 years was compared with the preoperative oversizing percentage. Finally, complication rates with ≥30% vs <30% planned oversizing were compared. Results The adverse event rate was lower for every EVAR group than the open control. In addition, the mortality rates at 30 days, 1 year, and 2 years were similar between the standard-angle (1.5%, 3.0%, 4.5%), high-angle (0.9%, 7.3%, 13.8%), and severe-angle (4.8%, 9.5%, 14.3%) EVAR groups and the open control groups (1.3, 6.6%, 10.5%). At 1 and 2 years, there was no difference in graft complications among the EVAR groups. However, with neck dilatation of >10% at 5 mm above the proximal renal and 1 mm below the distal renal, there was an increased risk of graft migration (relative risk, 4.38 P = .01 and 4.33 P = .002, respectively). For all predetermined anatomic points, the oversizing percentage decreased over time. The rate of oversize percentage decrease was faster at more distal aortic locations, reaching <10% at 30 days 15 mm below the renal, at 2 years 7 mm below the renal, and at 5 years 1 mm below the renal ( P < .001 for all). Half the oversize percentage achieved at the index procedure remained at 3 years (Pearson correlation coefficient = 0.5). However, there was no difference in complications between the ≥30% and <30% planned oversize groups. Conclusions The Aorfix endograft has performed well in excluding aneurysms with standard and highly angled aortic neck anatomy.
Objective To determine casemix adjusted hospital level utilization of minimally invasive surgery for four common surgical procedures (appendectomy, colectomy, total abdominal hysterectomy, and lung ...lobectomy) in the United States.Design Retrospective review. Setting United States.Participants Nationwide inpatient sample database, United States 2010.Methods For each procedure, a propensity score model was used to calculate the predicted proportion of minimally invasive operations for each hospital based on patient characteristics. For each procedure, hospitals were categorized into thirds (low, medium, and high) based on their actual to predicted proportion of utilization of minimally invasive surgery.Main outcome measures The primary outcome measures were the actual and predicted proportion of procedures performed with minimally invasive surgery. Secondary outcome measures included surgical complications and hospital characteristics.Results Mean hospital utilization of minimally invasive surgery was 71.0% (423/596) for appendectomy (range 40.9-93.1% (244-555)), 28.4% (154/541) for colectomy (6.7-49.8% (36/541-269/541)), 13.0% (65/499) for hysterectomy (0.0-33.6% (0/499-168/499)), and 32.0% (67/208) for lung lobectomy (3.6-65.7% (7.5/208-137/208)). Utilization of minimally invasive surgery was highly variable for each procedure type. There was noticeable discordance between actual and predicted utilization of the surgery (range of actual to predicted ratio for appendectomy 0-1.49; colectomy 0-3.88; hysterectomy 0-6.68; lung lobectomy 0-2.51). Surgical complications were less common with minimally invasive surgery compared with open surgery, respectively: overall rate for appendectomy 3.94% (1439/36 513) v 7.90% (958/12 123), P<0.001; for colectomy: 13.8% (1689/12 242) v 35.8% (8837/24 687), P<0.001; for hysterectomy: 4.69% (270/5757) v 6.64% (1988/29 940), P<0.001; and for lung lobectomy: 17.1% (367/2145) v 25.4% (971/3824), P<0.05. High utilization of minimally invasive surgery was associated with urban location (appendectomy: odds ratio 4.66, 95% confidence interval 1.17 to 18.5; colectomy: 4.59, 1.04 to 20.3; hysterectomy: 15.0, 2.98 to 75.0), large hospital size (hysterectomy: 8.70, 1.62 to 46.8), teaching hospital (hysterectomy: 5.41, 1.27 to 23.1), Midwest region (appendectomy: 7.85, 1.26 to 49.1), south region (appendectomy: 21.0, 3.79 to 117; colectomy: 10.0, 1.83 to 54.7), and west region (appendectomy: 9.33, 1.48 to 58.8).Conclusion Hospital utilization of minimally invasive surgery for appendectomy, colectomy, total abdominal hysterectomy, and lung lobectomy varies widely in the United States, representing a disparity in the surgical care delivered nationwide.
Since its Food and Drug Administration (FDA) approval, robot-assisted laparoscopic surgery has grown with expanding indications. One factor used to expand indications is device-related complications. ...We designed a study to evaluate device-related robotic surgery complications reported to FDA.
We searched the FDA device-related complication database, LexisNexis, and PACER (Public Access to Court Electronic Records) to identify robotic surgery-related complications over a 12-year period (January 1, 2000 to August 1, 2012). Cases from LexisNexis and PACER were cross-referenced with the FDA database to determine cases where an FDA report was inaccurate, filed late or not filed.
A total of 245 events were reported to the FDA during the study period, including 71 deaths and 174 nonfatal injuries. Median time to report an event to the FDA was 30 days (range = 0-930 days). Eight cases were identified from the LexisNexis and PACER searches where FDA reports were improperly filed. In five of these, no report was filed with a mean follow-up of 4.1 years (range = 2.3-5.8 years). In the three cases where a report was filed, the mean time between the event and the FDA report was 20.4 months (611 days, range = 292-930 days).
It is important that the true incidence of complications with robotic-assisted laparoscopic surgery be known to ensure continued safe innovation.
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