Atypical Cause for Back Pain and Sciatica in a 35-Yr-Old Woman With Fibromyalgia.

ABSTRACT: Spinal and extrapelvic lesions causing sciatic symptoms are well recognized in clinical research and practice. 1-5 We present a 35-yr-old woman with a history of axial back pain and fibromyalgia who presented with episodes of radicular type pain down her legs and associated bilateral tingling in her feet. Medicinal and therapeutic interventions for traditional sciatica etiologies failed to provide relief. Lumbar magnetic resonance imaging showed mild multilevel degenerative changes and partially visualized fibroids, but no other significant spinal pathology was appreciated. Subsequent pelvic magnetic resonance imaging revealed an enlarged retroverted uterus with multiple fibroid lesions. The patient elected for laparoscopic myomectomy, which improved her likelihood of fertility while drastically alleviating her axial spine and lower extremity symptomology. This case reinforces the importance of keeping a broad differential that includes intrapelvic etiologies when traditional workup and treatment for sciatic neuropathy fails. To our knowledge, this is the first reported case of sciatic neuropathy secondary to uterine fibroids treated with the intent of both fertility improvement and pain relief.

Measuring case severity: a novel tool for benchmarking and clinical documentation improvement.

BACKGROUND: Severity of illness (SOI) is an All Patients Refined Diagnosis Related Groups (APR DRG) modifier based on comorbidity capture. Tracking SOI helps hospitals improve performance and resource distribution. Furthermore, benchmarking SOI plays a key role in Quality Improvement (QI) efforts such as Clinical Documentation Improvement (CDI) programs. The current SOI system highly relies on the 3 M APR DRG grouper that is updated annually, making it difficult to track severity longitudinally and benchmark against hospitals with different patient populations. Here, we describe an alternative SOI scoring system that is grouper-independent and that can be tracked longitudinally. METHODS: Admission data for 2019-2020 U.S. News and World Report Honor Roll facilities were downloaded from the Vizient Clinical Database and split into training and testing datasets. Elixhauser comorbidities, body systems developed from the Healthcare Cost and Utilization Project (HCUP), and ICD-10-CM complication and comorbidity (CC/MCC) indicators were selected as the predictors for orthogonal polynomial regression models to predict patients' admission and discharge SOI. Receiver operating characteristic (ROC) and Precision-Recall (PR) analysis, and prediction accuracy were used to evaluate model performance. RESULTS: In the training dataset, the full model including both Elixhauser comorbidities and body system CC/MCC indicators had the highest ROC AUC, PR AUC and predication accuracy for both admission (ROC AUC: 92.9%; PR AUC: 91.0%; prediction accuracy: 85.4%) and discharge SOI (ROC AUC: 93.6%; PR AUC: 92.8%; prediction accuracy: 86.2%). The model including only body system CC/MCC indicators had similar performance for admission (ROC AUC: 92.4%; PR AUC: 90.4%; prediction accuracy: 84.8%) and discharge SOI (ROC AUC: 93.1%; PR AUC: 92.2%; prediction accuracy: 85.6%) as the full model. The model including only Elixhauser comorbidities exhibited the lowest performance. Similarly, in the validation dataset, the prediction accuracy was 86.2% for the full model, 85.6% for the body system model, and 79.3% for the comorbidity model. With fewer variables and less model complexity, the body system model was more efficient and was determined to be the optimal model. The probabilities generated from this model, named J_Score and J_Score_POA, successfully measured SOI and had practical applications in assessment of CDI performance. CONCLUSIONS: The J_Scores generated from the body system model have significant value in evaluating admission and discharge severity of illness. We believe that this new scoring system will provide a useful tool for healthcare institutions to benchmark patients' illness severity and augment Quality Improvement (QI) efforts.

Initial validation of the electronic form of the Michigan Body Map.

BACKGROUND: The Michigan Body Map (MBM) was developed to assess pain location in a reliable and valid manner; however, electronic formats have not been validated. This study had two aims: (1) initial validation of the electronic form of the MBM (eMBM) and (2) preliminary test of assessing pain severity within body zones. METHODS: For the first aim, 68 participants with chronic pain completed paper and electronic forms of the MBM, then underwent scripted interviews to assess preferences among body maps and verbal confirmation of pain locations. For the second aim, a subset of the participants (n=40) completed the Brief Pain Inventory (BPI) pain severity subscale, as well as the eMBM again and endorsed pain severity using additional screens showing body zones that contained areas in which pain was endorsed. RESULTS: There were few discrepancies between MBM, eMBM and verbal report (1.9% and 1.6%, respectively), and no difference between forms in perceived ability to indicate areas of pain or ease of completion. Patients accurately indicated their bodily pain on both maps, with 84% and 87% reporting one or no errors on MBM and eMBM, respectively. Participants also reported no preference for which version best-depicted areas of pain or best distinguished left from right. Lastly, the most preferred measure was eMBM with pain severity zones, followed by eMBM without zones, followed by the BPI pain severity subscale. CONCLUSIONS: These data support the validity of the eMBM for patients with chronic pain. Further, an expanded form of the eMBM that assesses pain severity was preferred by most participants.

Improved Comorbidity Capture Using a Standardized 1-Step Quality Improvement Documentation Tool.

Objective To assess the impact of implementation of a "1-step" documentation query system on comorbidity capture and quality outcomes within the Department of Otolaryngology-Head and Neck Surgery. Methods Implementation of the 1-step documentation query system was instituted for all otolaryngology-head and neck surgery faculty at a single institution. Individual query responses and impact metrics were analyzed. Departmental case-mix index (CMI), risk of mortality (ROM), and severity of illness (SOI) were collated over a 14-month implementation period and compared to a 12-month preimplementation period. Results A total of 226 documentation queries occurred during the program pilot period, with an 86.7% response rate. Of queries with a response, 91.0% resulted in a significant impact for the hospitalization diagnoses-related group, ROM, or SOI. Departmental CMI increased from 2.73 to 2.91 over the implementation period, and observed/expected mortality ratio decreased from 0.50 to 0.42 pre- to postimplementation. Discussion With increasing emphasis on quality metrics outcomes within the United States health care system, there is a need for institutions to accurately capture the complexity and acuity of the patients they care for. There was a positive change in quality outcomes metrics, including ROM, SOI, and CMI over the first year of deployment of the 1-step documentation query process. Implications for Practice Clinical severity metrics are becoming increasingly important to otolaryngologists, as insurers move to severity-adjusted profiles. The 1-step documentation query process provides a reproducible and effective way for clinical documentation specialists and physicians to collaborate on improving departmental clinical severity metrics.

Preliminary validation of the Michigan Body Map.

We developed the Michigan Body Map (MBM) as a self-report measure to assess body areas where chronic pain is experienced and to specifically quantify the degree of widespread body pain when assessing for centralized pain features (eg, fibromyalgia-like presentation). A total of 402 patients completed the measure in 5 distinct studies to support the validation of the original and a revised version of the MBM. Administration is rapid 39 to 44 seconds, and errors for the original MBM were detected in only 7.2% of the possible body areas. Most errors underestimated the number of painful areas or represented confusion in determining the right vs left side. The MBM was preferred (P = 0.013) and felt to better depict pain location (P = 0.001) when compared with the Widespread Pain Index checklist of the 2011 Fibromyalgia Survey Criteria, but participants did not express any preference between the MBM and Brief Pain Inventory body map. Based on the data from the first 3 studies, a revised version of the MBM was created including a front and back body image and improved guidance on right-sidedness vs left. The revised MBM was preferred when compared with the original and was more accurate in depicting painful body areas (P = 0.004). Furthermore, the revised MBM showed convergent and discriminant validity with other self-report measures of pain, mood, and function. In conclusion, the MBM demonstrated utility, reliability, and construct validity. This new measure can be used to accurately assess the distribution of pain or widespread bodily pain as an element of the fibromyalgia survey score.