Do changes in health reveal the possibility of undiagnosed pancreatic cancer? Development of a risk-prediction model based on healthcare claims data.

Background and objectiveEarly detection methods for pancreatic cancer are lacking. We aimed to develop a prediction model for pancreatic cancer based on changes in health captured by healthcare claims data.MethodsWe conducted a case-control study on 29,646 Medicare-enrolled patients aged 68 years and above with pancreatic ductal adenocarcinoma (PDAC) reported to the Surveillance Epidemiology an End Results (SEER) tumor registries program in 2004-2011 and 88,938 age and sex-matched controls. We developed a prediction model using multivariable logistic regression on Medicare claims for 16 risk factors and pre-diagnostic symptoms of PDAC present within 15 months prior to PDAC diagnosis. Claims within 3 months of PDAC diagnosis were excluded in sensitivity analyses. We evaluated the discriminatory power of the model with the area under the receiver operating curve (AUC) and performed cross-validation by bootstrapping.ResultsThe prediction model on all cases and controls reached AUC of 0.68. Excluding the final 3 months of claims lowered the AUC to 0.58. Among new-onset diabetes patients, the prediction model reached AUC of 0.73, which decreased to 0.63 when claims from the final 3 months were excluded. Performance measures of the prediction models was confirmed by internal validation using the bootstrap method.ConclusionModels based on healthcare claims for clinical risk factors, symptoms and signs of pancreatic cancer are limited in classifying those who go on to diagnosis of pancreatic cancer and those who do not, especially when excluding claims that immediately precede the diagnosis of PDAC

Acute pain pathways:protocol for a prospective cohort study

INTRODUCTION: Opioid analgesics are often used to treat moderate-to-severe acute non-cancer pain; however, there is little high-quality evidence to guide clinician prescribing. An essential element to developing evidence-based guidelines is a better understanding of pain management and pain control among individuals experiencing acute pain for various common diagnoses. METHODS AND ANALYSIS: This multicentre prospective observational study will recruit 1550 opioid-naïve participants with acute pain seen in diverse clinical settings including primary/urgent care, emergency departments and dental clinics. Participants will be followed for 6 months with the aid of a patient-centred health data aggregating platform that consolidates data from study questionnaires, electronic health record data on healthcare services received, prescription fill data from pharmacies, and activity and sleep data from a Fitbit activity tracker. Participants will be enrolled to represent diverse races and ethnicities and pain conditions, as well as geographical diversity. Data analysis will focus on assessing patients’ patterns of pain and opioid analgesic use, along with other pain treatments; associations between patient and condition characteristics and patient-centred outcomes including resolution of pain, satisfaction with care and long-term use of opioid analgesics; and descriptive analyses of patient management of leftover opioids. ETHICS AND DISSEMINATION: This study has received approval from IRBs at each site. Results will be made available to participants, funders, the research community and the public. TRIAL REGISTRATION NUMBER: NCT04509115

Quality Measures for the Diagnosis and Non-Operative Management of Carpal Tunnel Syndrome in Occupational Settings

Introduction: Providing higher quality medical care to workers with occupationally associated carpal tunnel syndrome (CTS) may reduce disability, facilitate return to work, and lower the associated costs. Although many workers’ compensation systems have adopted treatment guidelines to reduce the overuse of unnecessary care, limited attention has been paid to ensuring that the care workers do receive is high quality. Further, guidelines are not designed to enable objective assessments of quality of care. This study sought to develop quality measures for the diagnostic evaluation and non-operative management of CTS, including managing occupational activities and functional limitations. Methods: Using a variation of the well-established RAND/UCLA Appropriateness Method, we developed draft quality measures using guidelines and literature reviews. Next, in a two-round modified-Delphi process, a multidisciplinary panel of 11 U.S. experts in CTS rated the measures on validity and feasibility. Results: Of 40 draft measures, experts rated 31 (78%) valid and feasible. Nine measures pertained to diagnostic evaluation, such as assessing symptoms, signs, and risk factors. Eleven pertain to non-operative treatments, such as the use of splints, steroid injections, and medications. Eleven others address assessing the association between symptoms and work, managing occupational activities, and accommodating functional limitations. Conclusions: These measures will complement existing treatment guidelines by enabling providers, payers, policymakers, and researchers to assess quality of care for CTS in an objective, structured manner. Given the characteristics of previous measures developed with these methods, greater adherence to these measures will probably lead to improved patient outcomes at a population level