Variations in Medicaid Payment Rates for Radiation Oncology.

PURPOSE: Interstate variations in Medicaid reimbursements can be significant, and patients who live in states with low Medicaid reimbursements tend to have worse access to care. This analysis describes the extent of variations in Medicaid reimbursements for radiation oncology services across the United States. METHODS AND MATERIALS: The Current Procedural Terminology codes billed for a course of whole breast radiation were identified for this study. Publicly available fee schedules were queried for all 50 states and Washington, DC, to determine the reimbursement for each service and the total reimbursement for the entire episode of care. The degree of interstate payment variation was quantified by computing the range, mean, standard deviation, and coefficient of variation. The cost of care for the entire episode of treatment was compared to the publicly available Kaiser Family Foundation (KFF) Medicaid-to-Medicare fee index to determine if the pattern of payment variation in medical services generally is predictive of the variation seen in radiation oncology specifically. RESULTS: Data were available for 48 states and Washington, DC. The total episode reimbursement (excluding image guidance for respiratory tracking) varied from $2945 to $15,218 (mean, $7233; standard deviation, $2248 or 31%). The correlation coefficient of the KFF index to the calculated entire episode of care for each state was 0.55. CONCLUSIONS: There is considerable variability in coverage and payments rates for radiation oncology services under Medicaid, and these variations track modestly with broader medical fees based on the KFF index. These variations may have implications for access to radiation oncology services that warrant further study.

Promoting safety mindfulness: Recommendations for the design and use of simulation-based training in radiation therapy.

There is a need to better prepare radiation therapy (RT) providers to safely operate within the health information technology (IT) sociotechnical system. Simulation-based training has been preemptively used to yield meaningful improvements during providers' interactions with health IT, including RT settings. Therefore, on the basis of the available literature and our experience, we propose principles for the effective design and use of simulated scenarios and describe a conceptual framework for a debriefing approach to foster successful training that is focused on safety mindfulness during RT professionals' interactions with health IT.

Toward a better understanding of task demands, workload, and performance during physician-computer interactions.

OBJECTIVE: To assess the relationship between (1) task demands and workload, (2) task demands and performance, and (3) workload and performance, all during physician-computer interactions in a simulated environment. METHODS: Two experiments were performed in 2 different electronic medical record (EMR) environments: WebCIS (n = 12) and Epic (n = 17). Each participant was instructed to complete a set of prespecified tasks on 3 routine clinical EMR-based scenarios: urinary tract infection (UTI), pneumonia (PN), and heart failure (HF). Task demands were quantified using behavioral responses (click and time analysis). At the end of each scenario, subjective workload was measured using the NASA-Task-Load Index (NASA-TLX). Physiological workload was measured using pupillary dilation and electroencephalography (EEG) data collected throughout the scenarios. Performance was quantified based on the maximum severity of omission errors. RESULTS: Data analysis indicated that the PN and HF scenarios were significantly more demanding than the UTI scenario for participants using WebCIS (P < .01), and that the PN scenario was significantly more demanding than the UTI and HF scenarios for participants using Epic (P < .01). In both experiments, the regression analysis indicated a significant relationship only between task demands and performance (P < .01). DISCUSSION: Results suggest that task demands as experienced by participants are related to participants' performance. Future work may support the notion that task demands could be used as a quality metric that is likely representative of performance, and perhaps patient outcomes. CONCLUSION: The present study is a reasonable next step in a systematic assessment of how task demands and workload are related to performance in EMR-evolving environments.

Relating physician's workload with errors during radiation therapy planning.

PURPOSE: To relate subjective workload (WL) levels to errors for routine clinical tasks. METHODS AND MATERIALS: Nine physicians (4 faculty and 5 residents) each performed 3 radiation therapy planning cases. The WL levels were subjectively assessed using National Aeronautics and Space Administration Task Load Index (NASA-TLX). Individual performance was assessed objectively based on the severity grade of errors. The relationship between the WL and performance was assessed via ordinal logistic regression. RESULTS: There was an increased rate of severity grade of errors with increasing WL (P value = .02). As the majority of the higher NASA-TLX scores, and the majority of the performance errors were in the residents, our findings are likely most pertinent to radiation oncology centers with training programs. CONCLUSIONS: WL levels may be an important factor contributing to errors during radiation therapy planning tasks.

Quantification of the impact of multifaceted initiatives intended to improve operational efficiency and the safety culture: a case study from an academic medical center radiation oncology department.

PURPOSE: We have systematically been incorporating several operational efficiency and safety initiatives into our academic radiation oncology clinic. We herein quantify the impact of these initiatives on prospectively collected, clinically meaningful, metrics. METHODS AND MATERIALS: The data from 5 quality improvement initiatives, each focused on a specific safety/process concern in our clinic, are presented. Data was collected prospectively: operational metrics recorded before and after implementation of the initiative were compared using statistical analysis. Results from the Agency for Health Care Research and Quality (AHRQ) patient safety culture surveys administered during and after many of these initiatives were similarly compared. RESULTS: (1) Workload levels for nurses assisting with brachytherapy were high (National Aeronautics and Space Administration Task Load Index (NASA-TLX) scores >55-60, suggesting, "overwork"). Changes in work flow and procedure room layout reduced workload to more acceptable levels (NASA-TLX <55; P < .01). (2) The rate of treatment therapists being interrupted was reduced from a mean of 4 (range, 1-11) times per patient treatment to a mean <1 (range, 0-3; P < .001) after implementing standards for electronic communication and placement of monitors informing patients and staff of the treatment machine status (ie, delayed, on time). (3) The rates of replans by dosimetrists was reduced from 11% to 6% (P < .01) through a more systematic pretreatment peer review process. (4) Standardizing nursing and resident functions reduced patient wait times by ≈ 45% (14 min; P < .01). (5) Standardizing presimulation instructions from the physician reduced the number of patients experiencing delays on the simulator (>50% to <10%; P < .01). To assess the overall changes in "patient safety culture," we conducted a pre- and postanalysis using the AHRQ survey. Improvements in all measured dimensions were noted. CONCLUSIONS: Quality improvement initiatives can be successfully implemented in an academic radiation oncology department to yield measurable improvements in operations resulting in improvement in patient safety culture.

Subjective and objective quantification of physician's workload and performance during radiation therapy planning tasks.

PURPOSE: To quantify, and compare, workload for several common physician-based treatment planning tasks using objective and subjective measures of workload. To assess the relationship between workload and performance to define workload levels where performance could be expected to decline. METHODS AND MATERIALS: Nine physicians performed the same 3 tasks on each of 2 cases ("easy" vs "hard"). Workload was assessed objectively throughout the tasks (via monitoring of pupil size and blink rate), and subjectively at the end of each case (via National Aeronautics and Space Administration Task Load Index; NASA-TLX). NASA-TLX assesses the 6 dimensions (mental, physical, and temporal demands, frustration, effort, and performance); scores > or ≈ 50 are associated with reduced performance in other industries. Performance was measured using participants' stated willingness to approve the treatment plan. Differences in subjective and objective workload between cases, tasks, and experience were assessed using analysis of variance (ANOVA). The correlation between subjective and objective workload measures were assessed via the Pearson correlation test. The relationships between workload and performance measures were assessed using the t test. RESULTS: Eighteen case-wise and 54 task-wise assessments were obtained. Subjective NASA-TLX scores (P < .001), but not time-weighted averages of objective scores (P > .1), were significantly lower for the easy vs hard case. Most correlations between the subjective and objective measures were not significant, except between average blink rate and NASA-TLX scores (r = -0.34, P = .02), for task-wise assessments. Performance appeared to decline at NASA-TLX scores of ≥55. CONCLUSIONS: The NASA-TLX may provide a reasonable method to quantify subjective workload for broad activities, and objective physiologic eye-based measures may be useful to monitor workload for more granular tasks within activities. The subjective and objective measures, as herein quantified, do not necessarily track each other, and more work is needed to assess their utilities. From a series of controlled experiments, we found that performance appears to decline at subjective workload levels ≥55 (as measured via NASA-TLX), which is consistent with findings from other industries.

Quantifying the impact of cross coverage on physician's workload and performance in radiation oncology.

PURPOSE: To quantitatively assess the difference in workload and performance of radiation oncology physicians during radiation therapy treatment planning tasks under the conditions of "cross coverage" versus planning a patient with whom they were familiar. METHODS AND MATERIALS: Eight physicians (3 experienced faculty physicians and 5 physician residents) performed 2 cases. The first case represented a "cross-coverage" scenario where the physicians had no prior information about the case to be planned. The second exposure represented a "regular-coverage" scenario where the physicians were familiar with the patient case to be planned. Each case involved 3 tasks to be completed systematically. Workload was assessed both subjectively (perceived) using National Aeronautics and Space Administration-Task Load Index (NASA-TLX), and objectively (physiological) throughout the task using eye data (via monitoring pupil size and blink rate). Performance of each task and the case was measured using completion time. Subjective willingness to approve or disapprove the generated plan was obtained after completion of the case only. RESULTS: Forty-eight perceived and 48 physiological workload assessments were obtained. Overall, results revealed a significant increase in perceived workload (high NASA-TLX score) and decrease in performance (longer completion time and reduced approval rate) during cross coverage. There were nonsignificant increases in pupil diameter and decreases in the blink rate during cross-coverage versus regular-coverage scenario. In both cross-coverage and regular-coverage scenarios the level of experience did not affect workload and performance. CONCLUSIONS: The cross-coverage scenario significantly increases perceived workload and degrades performance versus regular coverage. Hence, to improve patient safety, efforts must be made to develop policies, standard operating procedures, and usability improvements to electronic medical record and treatment planning systems for "easier" information processing to deal with cross coverage, while recognizing strengths and limitations of human performance.

Quantitative assessment of workload and stressors in clinical radiation oncology.

PURPOSE: Workload level and sources of stressors have been implicated as sources of error in multiple settings. We assessed workload levels and sources of stressors among radiation oncology professionals. Furthermore, we explored the potential association between workload and the frequency of reported radiotherapy incidents by the World Health Organization (WHO). METHODS AND MATERIALS: Data collection was aimed at various tasks performed by 21 study participants from different radiation oncology professional subgroups (simulation therapists, radiation therapists, physicists, dosimetrists, and physicians). Workload was assessed using National Aeronautics and Space Administration Task-Load Index (NASA TLX). Sources of stressors were quantified using observational methods and segregated using a standard taxonomy. Comparisons between professional subgroups and tasks were made using analysis of variance ANOVA, multivariate ANOVA, and Duncan test. An association between workload levels (NASA TLX) and the frequency of radiotherapy incidents (WHO incidents) was explored (Pearson correlation test). RESULTS: A total of 173 workload assessments were obtained. Overall, simulation therapists had relatively low workloads (NASA TLX range, 30-36), and physicists had relatively high workloads (NASA TLX range, 51-63). NASA TLX scores for physicians, radiation therapists, and dosimetrists ranged from 40-52. There was marked intertask/professional subgroup variation (P<.0001). Mental demand (P<.001), physical demand (P=.001), and effort (P=.006) significantly differed among professional subgroups. Typically, there were 3-5 stressors per cycle of analyzed tasks with the following distribution: interruptions (41.4%), time factors (17%), technical factors (13.6%), teamwork issues (11.6%), patient factors (9.0%), and environmental factors (7.4%). A positive association between workload and frequency of reported radiotherapy incidents by the WHO was found (r = 0.87, P value=.045). CONCLUSIONS: Workload level and sources of stressors vary among professional subgroups. Understanding the factors that influence these findings can guide adjustments to the workflow procedures, physical layout, and/or communication protocols to enhance safety. Additional evaluations are needed in order to better understand if these findings are systemic.