Large Language Models to Identify Social Determinants of Health in Electronic Health Records

Social determinants of health (SDoH) have an important impact on patient outcomes but are incompletely collected from the electronic health records (EHR). This study researched the ability of large language models to extract SDoH from free text in EHRs, where they are most commonly documented, and explored the role of synthetic clinical text for improving the extraction of these scarcely documented, yet extremely valuable, clinical data. 800 patient notes were annotated for SDoH categories, and several transformer-based models were evaluated. The study also experimented with synthetic data generation and assessed for algorithmic bias. Our best-performing models were fine-tuned Flan-T5 XL (macro-F1 0.71) for any SDoH, and Flan-T5 XXL (macro-F1 0.70). The benefit of augmenting fine-tuning with synthetic data varied across model architecture and size, with smaller Flan-T5 models (base and large) showing the greatest improvements in performance (delta F1 +0.12 to +0.23). Model performance was similar on the in-hospital system dataset but worse on the MIMIC-III dataset. Our best-performing fine-tuned models outperformed zero- and few-shot performance of ChatGPT-family models for both tasks. These fine-tuned models were less likely than ChatGPT to change their prediction when race/ethnicity and gender descriptors were added to the text, suggesting less algorithmic bias (p<0.05). At the patient-level, our models identified 93.8% of patients with adverse SDoH, while ICD-10 codes captured 2.0%. Our method can effectively extracted SDoH information from clinic notes, performing better compare to GPT zero- and few-shot settings. These models could enhance real-world evidence on SDoH and aid in identifying patients needing social support.Comment: 38 pages, 5 figures, 5 tables in main, submitted for revie

The impact of responding to patient messages with large language model assistance

Documentation burden is a major contributor to clinician burnout, which is rising nationally and is an urgent threat to our ability to care for patients. Artificial intelligence (AI) chatbots, such as ChatGPT, could reduce clinician burden by assisting with documentation. Although many hospitals are actively integrating such systems into electronic medical record systems, AI chatbots utility and impact on clinical decision-making have not been studied for this intended use. We are the first to examine the utility of large language models in assisting clinicians draft responses to patient questions. In our two-stage cross-sectional study, 6 oncologists responded to 100 realistic synthetic cancer patient scenarios and portal messages developed to reflect common medical situations, first manually, then with AI assistance. We find AI-assisted responses were longer, less readable, but provided acceptable drafts without edits 58% of time. AI assistance improved efficiency 77% of time, with low harm risk (82% safe). However, 7.7% unedited AI responses could severely harm. In 31% cases, physicians thought AI drafts were human-written. AI assistance led to more patient education recommendations, fewer clinical actions than manual responses. Results show promise for AI to improve clinician efficiency and patient care through assisting documentation, if used judiciously. Monitoring model outputs and human-AI interaction remains crucial for safe implementation.Comment: 4 figures and tables in main, submitted for revie

Pain in patients with pancreatic cancer: prevalence, mechanisms, management and future developments

Pain affects approximately 80% of patients with pancreatic cancer, with half requiring strong opioid analgesia, namely: morphine-based drugs on step three of the WHO analgesic ladder (as opposed to the weak opioids: codeine and tramadol). The presence of pain is associated with reduced survival. This article reviews the literature regarding pain: prevalence, mechanisms, pharmacological, and endoscopic treatments and identifies areas for research to develop individualized patient pain management pathways. The online literature review was conducted through: PubMed, Clinical Key, Uptodate, and NICE Evidence. There are two principal mechanisms for pain: pancreatic duct obstruction and pancreatic neuropathy which, respectively, activate mechanical and chemical nociceptors. In pancreatic neuropathy, several histological, molecular, and immunological changes occur which correlate with pain including: transient receptor potential cation channel activation and mast cell infiltration. Current pain management is empirical rather etiology-based and is informed by the WHO analgesic ladder for first-line therapies, and then endoscopic ultrasound-guided celiac plexus neurolysis (EUS-CPN) in patients with resistant pain. For EUS-CPN, there is only one clinical trial reporting a benefit, which has limited generalizability. Case series report pancreatic duct stenting gives effective analgesia, but there are no clinical trials. Progress in understanding the mechanisms for pain and when this occurs in the natural history, together with assessing new therapies both pharmacological and endoscopic, will enable individualized care and may improve patients’ quality of life and survival

Beyond performance status

Oncologists should recognise the need to move beyond the Eastern Cooperative Oncology Group Performance Status (ECOG PS) score. ECOG PS is a longstanding and ubiquitous feature of oncology. It was evolved 40 years ago as an adaption of the 70-year-old Karnofsky performance score. It is short, easily understood and part of the global language of oncology. The wide prevalence of the ECOG PS attests to its proven utility and worth to help triage patient treatment. The ECOG PS is problematic. It is a unidimensional functional score. It is mostly physician assessed, subjective and therefore open to bias. It fails to account for multimorbidity, frailty or cognition. Too often the PS is recorded only once in wilful ignorance of a patient's changing physical state. As modern oncology offers an ever-widening array of therapies that are ‘personalised’ to tumour genotype, modern oncologists must strive to better define patient phenotype. Using a wider range of scoring and assessment tools, oncologists can identify deficits that may be reversed or steps taken to mitigate detrimental effects of treatment. These tools can function well to identify those patients who would benefit from comprehensive assessment. This overview identifies the strengths of ECOG PS but highlights the weaknesses and where these are supported by other measures. A strong recommendation is made here to move to routine use of the Clinical Frailty Score to start to triage patients and most appropriately design treatments and rehabilitation interventions

Anaesthetic management of children with craniopharyngioma

The perioperative management of craniopharyngioma in children is quite challenging not only to the neurosurgeons and anaesthesiologists but also to the oncologists, endocrinologists and intensivists. The various concerns include size of the tumour and its effects on intracranial pressure, vicinity of the tumour to nearby vessels and neural structures, endocrine disturbances, compressive symptoms, paediatric age, obesity-related problems, high recurrence rate of the tumour, undesired effects of radiotherapy, high morbidity and mortality. As anaesthesiologists, we deal with most of the challenges. The success of the outcome depends on the proper identification of the patient, pre-operative optimisation, surgical decision, awareness of the complications, timely intervention and optimal post-operative care

Neurocognitive function monitoring

Neuro-cognitive dysfunction quite frequently occurs after major surgery particularly in elderly patients. Cognitive function monitoring becomes an important tool in the perioperative period, especially for patients undergoing neurosurgical procedures as these patients are at a greater risk because of the nature of surgery. Many cognitive assessment tools were described, but selecting a tool or combination of tools to assess depends on preoperative patient condition, availability of informant and post-operative course. The cognitive functioning monitoring is crucial for risk stratification to allow for subsequent prophylaxis, surveillance, and treatment of post-operative cognition dysfunction

Influence of changing trends in anaesthetic practice on morbidity and mortality in elderly patients undergoing lower limb surgery

Background and Aims: Several changes in the management protocols of anaesthesia for geriatric patients were introduced into clinical practice to improve the outcome. Very few studies have evaluated the impact of these management protocols. The aim of our study was to evaluate impact of some of the changes in the peri-operative management protocols of geriatric patients undergoing elective orthopaedic lower limb surgeries on the outcomes. Methods: A retrospective chart review of thirty-eight surgical patients from 1999 (Group 1999) before the introduction of changes and 107 patients from 2007 (Group 2007) after establishing changes was performed and data of peri-operative variables were collected and analysed. The primary outcome measured was in-hospital mortality. The secondary outcomes were occurrence of intra-operative and post-operative complications. Comparison of continuous variables between the two groups was performed using independent sample T test and categorical variables using Chi-square test. Multivariate logistic regression was done to identify independent predictors of mortality. Results: The use of beta blockers, deep vein thrombosis prophylaxis with low molecular weight heparin and epidural technique for post-operative analgesia was higher in group 2007. Despite higher prevalence of patients with electrocardiographic changes and anaemia, the incidence of intra-operative or post-operative complications was lower in 2007, though the mortality rate in both the groups was comparable. The independent risk factors for mortality in these geriatric patients were intra-operative hypotension (Odds Ratio (OR) =11.33) and post-operative myocardial ischaemia (OR = 34.5), pulmonary embolism (OR = 17.1) and neurologic changes (OR = 17.1). Conclusions: Implementation of new management practices had significantly reduced the incidence of intra- and post-operative complications

Autonomic disturbances in diabetes: Assessment and anaesthetic implications

Diabetes mellitus is the most common medical condition and with increased awareness of heath and related issues, several patients are getting diagnosed with diabetes. The poor control of sugar and long-standing status of disease affects the autonomic system of body. The autonomic nervous system innervates cardiovascular, gastrointestinal, and genitourinary system, thus affecting important functions of the body. The cardiovascular system involvement can manifest as mild arrhythmias to sudden death. Our search for this review included PubMed, Google Search and End Note X6 version and the key words used for the search were autonomic neuropathy, diabetes, anesthesia, tests and implications. This review aims to highlight the dysfunction of autonomic system due to diabetes and its clinical presentations. The various modalities to diagnose the involvement of different systems are mentioned. An estimated 25% of diabetic patients will require surgery. It has been already established that mortality rates in diabetic patients are higher than in nondiabetic patients. Hence, complete workup is needed prior to any surgery. Diabetic autonomic neuropathy and its implications may sometimes be disastrous and further increase the incidence of in hospital morbidity and mortality. Overall, complete knowledge of diabetes and its varied effects with anaesthetic implications and careful perioperative management is the key guiding factor for a successful outcome