Effects of levels of automation and non-driving related tasks on driver performance and workload: A review of literature and meta-analysis.

This study assessed the effects of different levels of automation and non-driving related tasks (NDRT) on driver performance and workload. A systematic literature review was conducted in March 2021 using Compendex, Google Scholar, Web of Science, and Scopus databases. Forty-five studies met the inclusion criteria. A meta-analysis was conducted and Cochrane risk of bias tool and Cochran's Q test were used to assess risk of bias and homogeneity of the effect sizes respectively. Results suggested that drivers exhibited safer performance when dealing with critical incidents in manual driving than partially automated driving (PAD) and highly automated driving (HAD) conditions. However, drivers reported higher workload in the manual driving mode as compared to the HAD and PAD conditions. Haptic, auditory, and visual-auditory takeover request modalities are preferred over the visual-only modality to improve takeover time. Use of handheld NDRTs significantly degraded driver performance as compared to NDRTs performed on mounted devices.

The interaction effects of automation and population aging on labor market.

Automation and population aging are two major forces that will shape the nature of works in the future. However, it is not clear how these forces will interact with each other and affect the labor market. This paper examines the interaction effects of computerization and population aging on the labor market. We found that computerization and population aging have large and statistically significant effects on employment growth but not earnings growth. Also, their interaction terms are statistically significant only for employment growth but not for earnings growth.

Prevalence, types and severity of medication errors associated with the use of automated medication use systems in ambulatory and institutionalized care settings: A systematic review protocol.

The use of automated systems within the medication use process has significantly reduce the occurrence of medication errors and the associated clinical and financial burden. However, automated systems lull into a false sense of security and increase the risk of medication errors that are often associated with socio-technical interactions, automation bias, workarounds and overrides. The objective of the systematic review is to determine the prevalence, types and severity of medication errors that are associated the use of automated systems in ambulatory and institutionalized care settings. The search strategy will be guided by PRISMA framework. Selected databases and relevant gray literature were searched and screening was done independently by two researchers between 01 April and 29 June 2021. These covered all relevant articles published from the inception of the use of automation in the medication use process (2000) until 2020. De-duplication and screening of all studies were done independently by two researchers with a clear inclusion / exclusion criteria. Data extraction and synthesis are currently on going (started on 06 July 2021) and being conducted independently but the validity and completeness of the processes will be confirmed by the third researcher. The Cochrane Risk of Bias tool and the Hoy et al's quality assessment checklist will be used for the assessment of methodological bias while the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system will be used for the quality of evidence assessment. Detailed qualitative synthesis of key findings will be done with thematic and descriptive analyses. If the number and types of included studies permit, fixed or random effect model meta-analysis will be conducted based on the degree of homogeneity in the sampling frame used in the included studies. Heterogeneity will be assessed with I2 statistics and I2 > 50% will be considered a high statistical heterogeneity. The systematic review may provide new perspective especially from developing settings about the prevalence, types and severity of medication errors associated with the use of automated systems at all the stages of medication use process, and in all categories of patients. This may add to global knowledge in the research area. Systematic review registration: The systematic review was registered and published by PROSPERO (CRD42020212900).

Automated office BP measurement: The new standard in HTN screening.

Obtain greater accuracy in blood pressure measurement with an automated office device.

What humanlike errors do autonomous vehicles need to avoid to maximize safety?

INTRODUCTION: The final failure in the causal chain of events in 94% of crashes is driver error. It is assumed most crashes will be prevented by autonomous vehicles (AVs), but AVs will still crash if they make the same mistakes as humans. By identifying the distribution of crashes among various contributing factors, this study provides guidance on the roles AVs must perform and errors they must avoid to realize their safety potential. METHOD: Using the NMVCCS database, five categories of driver-related contributing factors were assigned to crashes: (1) sensing/perceiving (i.e., not recognizing hazards); (2) predicting (i.e., misjudging behavior of other vehicles); (3) planning/deciding (i.e., poor decision-making behind traffic law adherence and defensive driving); (4) execution/performance (i.e., inappropriate vehicle control); and (5) incapacitation (i.e., alcohol-impaired or otherwise incapacitated driver). Assuming AVs would have superior perception and be incapable of incapacitation, we determined how many crashes would persist beyond those with incapacitation or exclusively sensing/perceiving factors. RESULTS: Thirty-three percent of crashes involved only sensing/perceiving factors (23%) or incapacitation (10%). If they could be prevented by AVs, 67% could remain, many with planning/deciding (41%), execution/performance (23%), and predicting (17%) factors. Crashes with planning/deciding factors often involved speeding (23%) or illegal maneuvers (15%). CONCLUSIONS: Errors in choosing evasive maneuvers, predicting actions of other road users, and traveling at speeds suitable for conditions will persist if designers program AVs to make errors similar to those of today's human drivers. Planning/deciding factors, such as speeding and disobeying traffic laws, reflect driver preferences, and AV design philosophies will need to be consistent with safety rather than occupant preferences when they conflict. Practical applications: This study illustrates the complex roles AVs will have to perform and the risks arising from occupant preferences that AV designers and regulators must address if AVs will realize their potential to eliminate most crashes.

Pediatric occupant human body model kinematic and kinetic response variation to changes in seating posture in simulated frontal impacts - with and without automatic emergency braking.

OBJECTIVE: The study quantifies the kinematics of children in booster child restraint systems (CRSs) in various naturalistic seating postures exposed to frontal impacts in a full-vehicle environment, with and without the application of pre-crash automatic emergency braking. METHODS: The PIPER 6YO and 10YO pediatric human body models were positioned in CRSs. The 6YO was restrained on a lowback (LBB) and highback (HBB) booster, while the 10YO was positioned on an LBB and in a NoCRS condition. All simulations used the 3-point seatbelt. The child models were pre-positioned (gravity settled, seatbelt tensioned) in four naturalistic seating postures: leaning-forward, leaning-forward-inward, leaning-forward-outward, and a pre-submarining position, along with a baseline reference seating position. A 2012 Toyota Camry finite element (FE) model was used as the vehicle environment. A standard 3-point lap-shoulder belt system was modeled to restrain the child and CRS in the left-rear vehicle seat. Two vehicle impact cases were considered: with and without a pre-crash AEB. For with-AEB cases, a pre-crash phase was run to incorporate postural changes due to the application of AEB. All seating positions were ultimately subjected to a full-frontal rigid-barrier impact at 35 MPH. A total of 40 conditions were simulated in LS-DYNA. RESULTS: Injury metrics varied widely for both occupants. Shoulder belt slippage was observed for the 6YO leaning-forward-inward on HBB. No head contact was observed for any simulated cases. Forward-leaning and forward-inward-leaning postures generally had greater head excursion across all seating postures. The lap belt rode over the pelvis for pre-submarining postures. Injury metrics for cases with pre-crash AEB were lower compared to their corresponding without-AEB cases. HIC15, head acceleration, upper neck tension force, and upper neck flexion moment were similar or lower for with-AEB scenarios. CONCLUSIONS: Pre-crash AEB reduces the effect of the impact despite the same collision speed as cases without-AEB. This is primarily due to the limited travel distance of the occupant, thus, starting an earlier ride-down during the crash. Moreover, different initial seating postures lead to a wide range of injury exposures. Vehicle and child restraint design should incorporate these seating postures to ensure robust protection of the occupant in a crash.

Kidney Disease-Specific Scores and Health Utility of Continuous Ambulatory Peritoneal Dialysis and Automated Peritoneal Dialysis Patients and Their Caregivers.

OBJECTIVES: This study aimed to compare the EuroQol 5-dimension 5-level questionnaire (EQ-5D-5L), the visual analogue scale (VAS), and the Kidney Disease Quality of Life 36-Item Short-Form Survey (KDQOL-36) scores of Thai continuous ambulatory peritoneal dialysis (CAPD) and automated peritoneal dialysis (APD) patients and to compare the utility scores with the EQ-5D-5L and VAS scores of caregivers. METHODS: This was a cross-sectional study completed between April 2016 and May 2017. In total, 34 CAPD patients, 30 APD patients, and their caregivers were recruited from a large university hospital in Thailand. A trained interviewer conducted face-to-face interviews. We collected demographic data and used the KDQOL-36 and EuroQol questionnaires (EQ-5D-5L and VAS) to assess the health-related quality of life. Caregivers were asked to assess their own health status using the EQ-5D-5L and VAS. RESULTS: The EQ-5D-5L and VAS responses of the CAPD and APD patients and their caregivers were not significantly different (P > .05). More than 50% of both patient groups had mobility problems, whereas most patients had no problems with self-care, doing usual activities, pain or discomfort, and anxiety or depression. As for the KDQOL-36, the physical and mental component summaries were not significantly different, and neither were the scores for all of the kidney disease-specific dimensions, including symptoms or problems, effects of kidney disease, and burden of kidney disease (all were P > .05). CONCLUSIONS: The results indicated that the quality of life of CAPD and APD patients and their caregivers were mostly equivalent. A further longitudinal study of utility score assessments of the differences in modality would be advantageous.

Autonomous Vehicles and Public Health.

Autonomous vehicles (AVs) have the potential to shape urban life and significantly modify travel behaviors. "Autonomous technology" means technology that can drive a vehicle without active physical control or monitoring by a human operator. The first AV fleets are already in service in US cities. AVs offer a variety of automation, vehicle ownership, and vehicle use options. AVs could increase some health risks (such as air pollution, noise, and sedentarism); however, if proper regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments. Healthy models of AV use include fully electric vehicles in a system of ridesharing and ridesplitting. Public health will benefit if proper policies and regulatory frameworks are implemented before the complete introduction of AVs into the market.

Effect of automated versus manual emergency braking on rear seat adult and pediatric occupant precrash motion.

Objective: Emergency braking can potentially generate precrash occupant motion that may influence the effectiveness of restraints in the subsequent crash, particularly for rear-seated occupants who may be less aware of the impending crash. With the advent of automated emergency braking (AEB), the mechanism by which braking is achieved is changing, potentially altering precrash occupant motion. Further, due to anatomical and biomechanical differences across ages, kinematic differences between AEB and manual emergency braking (MEB) may vary between child and adult occupants. Therefore, the objective of this study was to quantify differences in rear-seated adult and pediatric kinematics and muscle activity during AEB and MEB scenarios. Methods: Vehicle maneuvers were performed in a recent model year sedan traveling at 50 km/h. MEB (acceleration ∼1 g) was achieved by the driver pressing the brake pedal with maximum effort. AEB (acceleration ∼0.8 g) was triggered by the vehicle system. Inertial and Global Positioning System data were collected. Seventeen male participants aged 10-33 were restrained in the rear right passenger seat and experienced each maneuver twice. The subjects' kinematics were recorded with an 8-camera 3D motion capture system. Electromyography (EMG) recorded muscle activity. Head and trunk displacements, raw and normalized by seated height, and peak head and trunk velocity were compared across age and between maneuvers. Mean EMG was calculated to interpret kinematic findings. Results: Head and trunk displacement and peak velocity were greater in MEB than in AEB in both raw and normalized data (P ≤ .01). No effect of age was observed (P ≥ .21). Peak head and trunk velocities were greater in repetition 1 than in repetition 2 (P ≤ .006) in MEB but not in AEB. Sternocleidomastoid (SCM) mean EMG was greater in MEB compared to AEB, and muscle activity increased in repetition 2 in MEB. Conclusions: Across all ages, head and trunk excursions were greater in MEB than AEB, despite increased muscle activity in MEB. This observation may suggest an ineffective attempt to brace the head or a startle reflex. The increased excursion in MEB compared to AEB may be attributed to differences in the acceleration pulses between the 2 scenarios. These results suggest that AEB systems can use specific deceleration profiles that have potential to reduce occupant motion across diverse age groups compared to sudden maximum emergency braking applied manually.

A predictive epilepsy index based on probabilistic classification of interictal spike waveforms.

Quantification of interictal spikes in EEG may provide insight on epilepsy disease burden, but manual quantification of spikes is time-consuming and subject to bias. We present a probability-based, automated method for the classification and quantification of interictal events, using EEG data from kainate- and saline-injected mice (C57BL/6J background) several weeks post-treatment. We first detected high-amplitude events, then projected event waveforms into Principal Components space and identified clusters of spike morphologies using a Gaussian Mixture Model. We calculated the odds-ratio of events from kainate- versus saline-treated mice within each cluster, converted these values to probability scores, P(kainate), and calculated an Hourly Epilepsy Index for each animal by summing the probabilities for events where the cluster P(kainate) > 0.5 and dividing the resultant sum by the record duration. This Index is predictive of whether an animal received an epileptogenic treatment (i.e., kainate), even if a seizure was never observed. We applied this method to an out-of-sample dataset to assess epileptiform spike morphologies in five kainate mice monitored for ~1 month. The magnitude of the Index increased over time in a subset of animals and revealed changes in the prevalence of epileptiform (P(kainate) > 0.5) spike morphologies. Importantly, in both data sets, animals that had electrographic seizures also had a high Index. This analysis is fast, unbiased, and provides information regarding the salience of spike morphologies for disease progression. Future refinement will allow a better understanding of the definition of interictal spikes in quantitative and unambiguous terms.

Unobserved automated office BP is similar to other clinic BP measurements: A prospective randomized study.

Results of the SPRINT study have been disputed, based on the assumption that unattended BP measurements do not correlate with usual BP measurements. In this study, the authors investigated the correlation of unattended SPRINT-like measurements with other conventional measurements. All BP measurements were taken with the patient seated in a comfortable chair with the legs uncrossed and not speaking during the procedure. For the purpose of this study, sixty-five patients, mostly male (93%), were recruited from our hypertension clinic and all were on antihypertensive medication (av 3.0 ± 1.1). Patients were at high cardiovascular risk with high rates of comorbidities, av age 68 ± 12 years, 49% with diabetes, 34% with mild CKD (CKD 1-3, average eGFR 55.0 ± 13 mL/min/1.73 m2 ), and 20% with history of stable coronary artery disease. All BP measurements were similar with no statistically significant difference (one-way ANOVA, P = 0.621). Compared to unattended SPRINT BP values (139.77 ± 19.22/75.42 ± 11.72 mm Hg), the clinic BP measurements were numerically slightly higher but with a NS P value (P = 0.163). Similarly, unattended BP measurements were similar to values taken by the clinic physician. In a smaller cohort of 11 patients, the authors compared unobserved vs observed SPRINT-like BP measurements, and in 13 patients, the authors compared unobserved SPRINT-like BP measurements to average home BP measurements (Table 3). There were no significant differences between any of the subgroups (one-way ANOVA, P = 0.816 for systolic and P = 0.803 for diastolic). The authors conclude that unattended BP measurements taken (the SPRINT way) are similar to other conventional office blood pressure measurements.

Poor health as a potential risk factor for job loss due to automation: the case of Norway.

OBJECTIVE: This study aimed to quantify the extent to which health characteristics of workers are related to the potential risk of experiencing job displacement due to automation. METHODS: Linking the 2015 Norwegian Statistics on Income and Living Conditions survey (n=6393) with predicted probabilities of automation by occupation, we used Kruskal-Wallis tests and multivariate generalised linear models to assess the association between long-standing illnesses and risk of job automation. RESULTS: Individuals with long-standing illnesses face substantially greater risks of losing their job due to automation. Whereas the average risk of job automation is 57% for men and 49% for women with long-standing illnesses, the risk is only 50% for men and 44% for women with limitations (p<0.001). Controlling for age, having a long-standing illness significantly increases the relative risk of facing job automation among men (risk ratio (RR) 1.13, 95% CI 1.09 to 1.19), as well as women (RR 1.11, 95% CI 1.05 to 1.17). While, among men, the association between long-standing illness and risk of job automation remains significant when controlling for education and income, it becomes insignificant among women. CONCLUSIONS: Individuals with poor health are likely to carry the highest burden of technological change in terms of worsening employment prospects because of working in occupations disproportionally more likely to be automated. Although the extent of technology-related job displacement will depend on several factors, given the far-reaching negative consequences of job loss on health and well-being, this process represents a significant challenge for public health and social equity.

Comparison on Human Resource Requirement between Manual and Automated Dispensing Systems.

OBJECTIVE: This study was conducted to compare human resource requirement among manual, automated, and modified automated dispensing systems. METHODS: Data were collected from the pharmacy department at the 2100-bed university hospital (Siriraj Hospital, Bangkok, Thailand). Data regarding the duration of the medication distribution process were collected by using self-reported forms for 1 month. The data on the automated dispensing machine (ADM) system were obtained from 1 piloted inpatient ward, whereas those on the manual system were the average of other wards. Data on dispensing, returned unused medication, and stock management processes under the traditional manual system and the ADM system were from actual activities, whereas the modified ADM system was modeled. The full-time equivalent (FTE) of each model was estimated for comparison. RESULTS: The result showed that the manual system required 46.84 FTEs of pharmacists and 132.66 FTEs of pharmacy technicians. By adding pharmacist roles on screening and verification under the ADM system, the ADM system required 117.61 FTEs of pharmacists. Replacing counting and filling medication functions by ADM has decreased the number of pharmacy technicians to 55.38 FTEs. After the modified ADM system canceled the return unused medication process, FTEs requirement for pharmacists and pharmacy technicians decreased to 69.78 and 51.90 FTEs, respectively. CONCLUSIONS: The ADM system decreased the workload of pharmacy technicians, whereas it required more time from pharmacists. However, the increased workload of pharmacists was associated with more comprehensive patient care functions, which resulted from the redesigned work process.

The Effect of Incorrect Reliability Information on Expectations, Perceptions, and Use of Automation.

OBJECTIVE: We examined how providing artificially high or low statements about automation reliability affected expectations, perceptions, and use of automation over time. BACKGROUND: One common method of introducing automation is providing explicit statements about the automation's capabilities. Research is needed to understand how expectations from such introductions affect perceptions and use of automation. METHOD: Explicit-statement introductions were manipulated to set higher-than (90%), same-as (75%), or lower-than (60%) levels of expectations in a dual-task scenario with 75% reliable automation. Two experiments were conducted to assess expectations, perceptions, compliance, reliance, and task performance over (a) 2 days and (b) 4 days. RESULTS: The baseline assessments showed initial expectations of automation reliability matched introduced levels of expectation. For the duration of each experiment, the lower-than groups' perceptions were lower than the actual automation reliability. However, the higher-than groups' perceptions were no different from actual automation reliability after Day 1 in either study. There were few differences between groups for automation use, which generally stayed the same or increased with experience using the system. CONCLUSION: Introductory statements describing artificially low automation reliability have a long-lasting impact on perceptions about automation performance. Statements including incorrect automation reliability do not appear to affect use of automation. APPLICATION: Introductions should be designed according to desired outcomes for expectations, perceptions, and use of the automation. Low expectations have long-lasting effects.

Effect of automated drug distribution systems on medication error rates in a short-stay geriatric unit.

RATIONALE, AIMS AND OBJECTIVES: To assess the impact of an automated drug distribution system on medication errors (MEs). METHODS: Before-after observational study in a 40-bed short stay geriatric unit within a 1800 bed general hospital in Valenciennes, France. Researchers attended nurse medication administration rounds and compared administered to prescribed drugs, before and after the drug distribution system changed from a ward stock system (WSS) to a unit dose dispensing system (UDDS), integrating a unit dose dispensing robot and automated medication dispensing cabinet (AMDC). RESULTS: A total of 615 opportunities of errors (OEs) were observed among 148 patients treated during the WSS period, and 783 OEs were observed among 166 patients treated during the UDDS period. ME [medication administration error (MAE)] rates were calculated and compared between the two periods. Secondary measures included type of errors, seriousness of errors and risk reduction for the patients. The implementation of an automated drug dispensing system resulted in a 53% reduction in MAEs. All error types were reduced in the UDDS period compared with the WSS period (P<0.001). Wrong dose and wrong drug errors were reduced by 79.1% (2.4% versus 0.5%, P=0.005) and 93.7% (1.9% versus 0.01%, P=0.009), respectively. CONCLUSION: An automated UDDS combining a unit dose dispensing robot and AMDCs could reduce discrepancies between ordered and administered drugs, thus improving medication safety among the elderly.

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction.

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case-control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC=0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC=0.838. In the case-control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.

The technological obsolescence of the Brazilian eletronic ballot box.

The electronic ballot box has played a significant role in the consolidation of Brazilian political process. It has enabled paper ballots extinction as a support for the elector's vote as well as for voting counting processes. It is also widely known that election automation has decisively collaborated to the legitimization of Brazilian democracy, getting rid of doubts about the winning candidates. In 1995, when the project was conceived, it represented a compromise solution, balancing technical efficiency and costs trade-offs. However, this architecture currently limits the ergonomic enhancements to the device operation, transportation, maintenance and storage. Nowadays are available in the market devices of reduced dimensions, based on novel computational architecture, namely tablet computers, which emphasizes usability, autonomy, portability, security and low power consumption. Therefore, the proposal under discussion is the replacement of the current electronic ballot boxes for tablet-based devices to improve the ergonomics aspects of the Brazilian voting process. These devices offer a plethora of integrated features (e.g., capacitive touchscreen, speakers, microphone) that enable highly usable and simple user interfaces, in addition to enhancing the voting process security mechanisms. Finally, their operational systems features allow for the development of highly secure applications, suitable to the requirements of a voting process.

Automated estimation of rare event probabilities in biochemical systems.

In biochemical systems, the occurrence of a rare event can be accompanied by catastrophic consequences. Precise characterization of these events using Monte Carlo simulation methods is often intractable, as the number of realizations needed to witness even a single rare event can be very large. The weighted stochastic simulation algorithm (wSSA) [J. Chem. Phys. 129, 165101 (2008)] and its subsequent extension [J. Chem. Phys. 130, 174103 (2009)] alleviate this difficulty with importance sampling, which effectively biases the system toward the desired rare event. However, extensive computation coupled with substantial insight into a given system is required, as there is currently no automatic approach for choosing wSSA parameters. We present a novel modification of the wSSA--the doubly weighted SSA (dwSSA)--that makes possible a fully automated parameter selection method. Our approach uses the information-theoretic concept of cross entropy to identify parameter values yielding minimum variance rare event probability estimates. We apply the method to four examples: a pure birth process, a birth-death process, an enzymatic futile cycle, and a yeast polarization model. Our results demonstrate that the proposed method (1) enables probability estimation for a class of rare events that cannot be interrogated with the wSSA, and (2) for all examples tested, reduces the number of runs needed to achieve comparable accuracy by multiple orders of magnitude. For a particular rare event in the yeast polarization model, our method transforms a projected simulation time of 600 years to three hours. Furthermore, by incorporating information-theoretic principles, our approach provides a framework for the development of more sophisticated influencing schemes that should further improve estimation accuracy.

Automated percutaneous lumbar discectomy for the contained herniated lumbar disc: a systematic assessment of evidence.

BACKGROUND: Lumbar disc prolapse, protrusion, and extrusion account for less than 5% of all low back problems, but are the most common causes of nerve root pain and surgical interventions. The typical rationale for traditional surgery is an effort to provide more rapid relief of pain and disability. It should be noted that the majority of patients will recover with conservative management. The primary rationale for any form of surgery for disc prolapse associated with radicular pain is to relieve nerve root irritation or compression due to herniated disc material. The primary modality of treatment continues to be either open or microdiscectomy, but several alternative techniques including automated percutaneous lumbar discectomy (APLD) have been described. However, there is a paucity of evidence for all decompression techniques, specifically alternative techniques including automated and laser discectomy. STUDY DESIGN: A systematic review of the literature. OBJECTIVE: To determine the effectiveness of APLD. METHODS: A comprehensive evaluation of the literature relating to automated lumbar disc decompression was performed. The literature was evaluated according to Cochrane review criteria for randomized controlled trials (RCTs), and Agency for Healthcare Research and Quality (AHRQ) criteria was utilized for observational studies. A literature search was conducted of English language literature through PubMed, EMBASE, the Cochrane library, systematic reviews, and cross references from reviews and systematic reviews. The level of evidence was classified as Level I, II, or III with 3 subcategories in Level II based on the quality of evidence developed by the United States Preventive Services Task Force (USPSTF). OUTCOME MEASURES: Pain relief was the primary outcome measure. Other outcome measures were functional improvement, improvement of psychological status, opioid intake, and return to work. Short-term effectiveness was defined as one year or less, whereas, long-term effectiveness was defined as greater than one year. RESULTS: Based on USPSTF criteria, the indicated evidence for APLD is Level II-2 for short- and long-term relief. LIMITATIONS: Paucity of RCTs in the literature. CONCLUSION: This systematic review indicated Level II-2 evidence for APLD. APLD may provide appropriate relief in properly selected patients with contained lumbar disc prolapse.