UNASSIGNED: The COVID-19 pandemic affected the utilization of various healthcare services differentially. Sleep testing services utilization (STU), including Home Sleep Apnea Testing (HSAT) and Polysomnography (PSG), were uniquely affected. We assessed the effects of the pandemic on STU and its recovery using the Veterans Health Administration (VHA) data.
UNASSIGNED: A retrospective cohort study from the VHA between 01/2019 and 10/2023 of veterans with age ≥ 50. We extracted STU data using Current Procedural Terminology codes for five periods based on STU and vaccination status: pre-pandemic (Pre-Pan), pandemic sleep test moratorium (Pan-Mor), and pandemic pre-vaccination (Pan-Pre-Vax), vaccination (Pan-Vax), and postvaccination (Pan-Post-Vax). We compared STU between intervals (Pre-Pan as the reference).
UNASSIGNED: Among 261,371 veterans (63.7±9.6 years, BMI 31.9±6.0 kg/m², 80% male), PSG utilization decreased significantly during Pan-Mor (-56%), Pan-Pre-Vax (-61%), Pan-Vax (-42%), and Pan-Post-Vax (-36%) periods all compared to Pre-Pan. HSAT utilization decreased significantly during the Pan-Mor (-59%) and Pan-Pre-Vax (-9%) phases compared to the Pre-Pan and subsequently increased during Pan-Vax (+6%) and Pan-Post-Vax (-1%) periods. Over 70% of STU transitioned to HSAT, and its usage surged five months after the vaccine Introduction.
UNASSIGNED: Sleep testing services utilization recovered differentially during the pandemic (PSG vs HSAT), including a surge in HSAT utilization post-vaccination.

暂无摘要。

UNASSIGNED: Modifier 22 is a mechanism designed for surgeons to identify cases that are more complex than their Current Procedural Terminology code accounts for. However, empirical studies of the use and efficacy of modifier 22 are lacking.
UNASSIGNED: To assess the use of modifier 22 in common surgical procedures and the association of use with compensation.
UNASSIGNED: This was a cross-sectional analysis of the 2021 Physician/Supplier Procedure Summary Limited Data Set including all Part B carrier and durable medical equipment fee-for-service claims. Claims for 10 common surgical procedures were evaluated, including mastectomy, total hip arthroplasty, total knee arthroplasty, coronary artery bypass grafting, laparoscopic right colectomy, laparoscopic appendectomy, laparoscopic cholecystectomy, kidney transplant, laparoscopic total abdominal hysterectomy and bilateral salpingo-oophorectomy, and lumbar laminectomy. Data were analyzed from August to November 2023.
UNASSIGNED: Rate of modifier 22 use, rate of claim denial, mean charges, mean payment for accepted claims, and mean payment for all claims.
UNASSIGNED: The sample included 625 316 surgical procedures performed in calendar year 2021. The proportion of modifier 22 coding for a procedure ranged from 5725 of 251 521 (2.3%) in total knee arthroplasty to 1566 of 18 459 (8.5%) in laparoscopic total abdominal hysterectomy and bilateral salpingo-oophorectomy. Submitted charges were 11.1% (95% CI, 9.1-13.2) to 22.8% (95% CI, 21.3-24.3) higher for claims with modifier 22, depending on the procedure. Among accepted claims, those with modifier 22 had increased payments ranging from 0.8% (95% CI, 0.7-1.0) to 4.8% (95% CI, 4.5-5.1). However, claims with modifier 22 were more likely to be denied (7.4% vs 4.0%; P < .001). As a result, overall mean payments were mixed, with 4 procedures having lower payments when modifier 22 was appended, 4 procedures having higher payments with modifier 22, and 2 procedures with no difference. The largest increase in mean payment for modifier 22 claims was for kidney transplant with an increased payment of $71.46 (95% CI, 55.32-87.60), which translates to a relative increase of 3.4% (95% CI, 2.9-4.6).
UNASSIGNED: The findings in this study suggest that modifier 22 had little to no financial benefit when appended to claims for a diverse panel of surgical procedures. In the current system, surgeons have little reason to request modifier 22, and no mechanisms currently exist for surgeons to recoup payment for difficult operations.

Proper codification of medical diagnoses and procedures is essential for optimized health care management, quality improvement, research, and reimbursement tasks within large healthcare systems. Assignment of diagnostic or procedure codes is a tedious manual process, often prone to human error. Natural Language Processing (NLP) has been suggested to facilitate this manual codification process. Yet, little is known on best practices to utilize NLP for such applications. With Large Language Models (LLMs) becoming more ubiquitous in daily life, it is critical to remember, not every task requires that level of resource and effort. Here we comprehensively assessed the performance of common NLP techniques to predict current procedural terminology (CPT) from operative notes. CPT codes are commonly used to track surgical procedures and interventions and are the primary means for reimbursement. Our analysis of 100 most common musculoskeletal CPT codes suggest that traditional approaches can outperform more resource intensive approaches like BERT significantly (P-value = 4.4e-17) with average AUROC of 0.96 and accuracy of 0.97, in addition to providing interpretability which can be very helpful and even crucial in the clinical domain. We also proposed a complexity measure to quantify the complexity of a classification task and how this measure could influence the effect of dataset size on model\'s performance. Finally, we provide preliminary evidence that NLP can help minimize the codification error, including mislabeling due to human error.

BACKGROUND: Preoperative knowledge of surgical risks can improve perioperative care and patient outcomes. However, assessments requiring clinician examination of patients or manual chart review can be too burdensome for routine use.
METHODS: We conducted a multicentre retrospective study of 243 479 adult noncardiac surgical patients at four hospitals within the Mass General Brigham (MGB) system in the USA. We developed a machine learning method using routinely collected coding and patient characteristics data from the electronic health record which predicts 30-day mortality, 30-day readmission, discharge to long-term care, and hospital length of stay.
RESULTS: Our method, the Flexible Surgical Set Embedding (FLEX) score, achieved state-of-the-art performance to identify comorbidities that significantly contribute to the risk of each adverse outcome. The contributions of comorbidities are weighted based on patient-specific context, yielding personalised risk predictions. Understanding the significant drivers of risk of adverse outcomes for each patient can inform clinicians of potential targets for intervention.
CONCLUSIONS: FLEX utilises information from a wider range of medical diagnostic and procedural codes than previously possible and can adapt to different coding practices to accurately predict adverse postoperative outcomes.

UNASSIGNED: In both Canada and the United States, workload measurement for anatomic pathology is mainly based on complexity and clinical significance of specimens, with gross examination being a considerable contributor. While Pathologists\' Assistants (PAs) play an increasing role in gross examination, there is little known regarding the time required for PAs to complete grossing tasks. This information is essential for effective staffing and workload management in pathology laboratories. The objective of our study was to determine the time required for PAs to gross second and third trimester singleton placentas in a large tertiary hospital with a significant perinatal pathology service.
UNASSIGNED: For our study, 7 certified PAs each grossed a minimum of 10 second and third trimester singleton placentas using a standard placental grossing protocol, an electronic laboratory information system, and voice recognition dictation software. Placental specimens requiring photography, sampling for ancillary studies, or immediate pathologist\'s consultation were excluded. We calculated average and standard deviation of grossing times for each PA, overall average grossing time, and 95% confidence interval using a mixed linear regression model. We analyzed the impact of PA job experience, degree obtained, and number of blocks prepared on overall average in a multivariate analysis.
UNASSIGNED: The mean grossing times for each PA ranged from 11.0 (standard deviation [sd] = 2.0) to 17.8 (sd = 4.5) minutes. The overall average grossing time was 14.5 minutes, with a 95% confidence interval of 11.7 to 17.3 minutes. In multivariate analysis, an increase in the number of blocks prepared was significantly associated with longer overall average grossing time. If 4 blocks were prepared consistently, the model predicted a slightly lower overall average of 13.3 minutes, with a 95% confidence interval of 10.9 to 15.7 minutes.
UNASSIGNED: To our knowledge, our study is the first to objectively report time required for PAs to perform gross examinations of routine second and third trimester singleton placentas. The methodology of our study is replicable and can be applied to other specimen types and laboratory settings. Previously, estimated grossing times for specimens were primarily based on retrospective surveys, which were susceptible to recall errors and subjectivity. However, our study demonstrates objective data collection is achievable. Furthermore, the data collected from this study offer valuable insights into the accuracy of previous and current pathology workload models for second and third trimester singleton placentas.

Professional reimbursement to neonatal providers is based on the level of Current Procedural Terminology (CPT®) coding in the NICU, newborn nursery and other areas where neonatal care is provided. Four levels of evaluation and management (E&M) care-critical, intensive, routine-hospital care or normal newborn care can be provided to neonates. The work relative value units (wRVUs) associated with these four levels of care vary widely. This manuscript provides a brief review of basic features associated with each of these four levels with a specific perspective on differences between critical and intensive care codes. Coding and billing are constantly evolving fields with significant variation in interpretation and readers are encouraged to review the current publications on CPT® coding and make an informed decision on the best codes to be used for their patients.

Current Procedural Terminology Codes is a numerical coding system used to bill for medical procedures and services and crucially, represents a major reimbursement pathway. Given that pathology services represent a consequential source of hospital revenue, understanding instances where codes may have been misassigned or underbilled is critical. Several algorithms have been proposed that can identify improperly billed CPT codes in existing datasets of pathology reports. Estimation of the fiscal impacts of these reports requires a coder (i.e., billing staff) to review the original reports and manually code them again. As the re-assignment of codes using machine learning algorithms can be done quickly, the bottleneck in validating these reassignments is in this manual re-coding process, which can prove cumbersome. This work documents the development of a rapidly deployable dashboard for examination of reports that the original coder may have misbilled. Our dashboard features the following main components: (1) a bar plot to show the predicted probabilities for each CPT code, (2) an interpretation plot showing how each word in the report combines to form the overall prediction, and (3) a place for the user to input the CPT code they have chosen to assign. This dashboard utilizes the algorithms developed to accurately identify CPT codes to highlight the codes missed by the original coders. In order to demonstrate the function of this web application, we recruited pathologists to utilize it to highlight reports that had codes incorrectly assigned. We expect this application to accelerate the validation of re-assigned codes through facilitating rapid review of false-positive pathology reports. In the future, we will use this technology to review thousands of past cases in order to estimate the impact of underbilling has on departmental revenue.

Work relative value units (wRVUs) are an intricate component of physician reimbursement determination in the United States. This paper assesses whether wRVUs appropriately consider operative time in hand surgery.
The 50 most common single Current Procedural Terminology code hand surgery cases were queried from the 2013 to 2018 National Surgical Quality Improvement Program database. The average assigned wRVUs and median operative times were calculated for each CPT. Linear regressions were calculated between operative time, wRVUs, and wRVUs per hour. Cases deviating the most from the expected wRVUs based on operative time were identified.
In all, 46 800 cases comprising the top 50 most common hand surgery procedures were identified. Among these cases, the median (range) assigned operative time was 62 minutes (18-110), wRVUs were 7.5 (3.5-18.0), and wRVUs per hour was 8.3 (4.9-14.2). There was a positive linear correlation between operative time and wRVUs (R2 = 0.60). Each additional operative hour was associated with an additional 6.3 wRVUs (P < .001). Based on this relationship, the assigned wRVUs for included cases ranged from 59.7% to 172.6% of expected. There was a weak negative relationship between wRVUs per hour and operative time (R2 = 0.25). Cases shorter than 1 hour had more wRVUs per hour than those longer than 1 hour (10.0 vs. 8.1, P = .003). However, this relationship disappeared when considering case turnover.
This study suggests a moderately strong positive correlation between wRVUs and operative time in hand surgery. Yet, numerous outliers from this trend exist, suggesting some discrepancies in reimbursement.

Brachial plexus reconstruction (BPR) is a rapidly advancing field within hand surgery. BPR procedures are complex, time-intensive, and require microsurgical expertise. As physician reimbursement rates for BPR are poorly defined, relative to more common hand procedures, we sought to analyze compensation for BPR across different payor groups and understand the factors contributing to their reimbursement.
A retrospective review was performed of surgeries by a single senior staff member in a 4-year period to evaluate Current Procedural Terminology (CPT) codes from BPR cases. For comparison, all finger fracture fixations and skin graft reconstructions performed by the same surgeon over the same time period were analyzed as well.
A total of 57 BPR cases, 94 finger fracture fixation cases, and 69 skin grafting cases met inclusion criteria. Among the top 5 insurance providers, average work relative value unit (wRVU)/hour was 6.55, 3.49, and 12.67 for BPR, fracture fixation, and skin grafts, respectively. Reimbursements were an average $685.76/hour for BPR, compared to $590.10/hour for fracture fixation and $1,197.94/hour for skin grafts.
BPR demonstrates a relative undervaluation, in terms of reimbursement per hour, given the time and surgical skill required for such cases, particularly compared to shorter, less complex cases such as skin grafting and fracture fixation. We find that this discrepancy is amplified across multiple levels of coding, billing, and reimbursement. We suggest specific strategies for physician leadership to more directly participate in the financial decisions that affect themselves, their patients, and their specialty.