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Introduction ChatGPT is a large language model (LLM)-based chatbot that uses natural language processing to create humanlike conversational dialogue. It has created a significant impact on the entire global landscape, especially in sectors like finance and banking, e-commerce, education, legal, human resources (HR), and recruitment since its inception. There have been multiple ongoing controversies regarding the seamless integration of ChatGPT with the healthcare system because of its factual accuracy, lack of experience, lack of clarity, expertise, and above all, lack of empathy. Our study seeks to compare ChatGPT's knowledge and interpretative abilities with those of first-year medical students in India in the subject of medical biochemistry. Materials and methods A total of 79 questions (40 multiple choice questions and 39 subjective questions) of medical biochemistry were set for Phase 1, block II term examination. Chat GPT was enrolled as the 101st student in the class. The questions were entered into ChatGPT's interface and responses were noted. The response time for the multiple-choice questions (MCQs) asked was also noted. The answers given by ChatGPT and 100 students of the class were checked by two subject experts, and marks were given according to the quality of answers. Marks obtained by the AI chatbot were compared with the marks obtained by the students. Results ChatGPT scored 140 marks out of 200 and outperformed almost all the students and ranked fifth in the class. It scored very well in information-based MCQs (92%) and descriptive logical reasoning (80%), whereas performed poorly in descriptive clinical scenario-based questions (52%). In terms of time taken to respond to the MCQs, it took significantly more time to answer logical reasoning MCQs than simple information-based MCQs (3.10±0.882 sec vs. 2.02±0.477 sec, p<0.005). Conclusions ChatGPT was able to outperform almost all the students in the subject of medical biochemistry. If the ethical issues are dealt with efficiently, these LLMs have a huge potential to be used in teaching and learning methods of modern medicine by students successfully.
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BACKGROUND: High vaccine wastage results in escalation of budget of immunization program. OBJECTIVE: To analyze vaccine wastage at three levels of service delivery under public sector, such as at district level, community health Centre (CHC), and sub center (SC). STUDY DESIGN: A retrospective cross-sectional record based study in a north Indian state. MATERIALS AND METHODS: The record from January to June 2016 was taken from randomly selected 5 districts of the state at 3 levels; for number of doses of vaccine used and number of children vaccinated for BCG, OPV, Hepatitis B, Pentavalent, DPT, IPV, Measles, and TT (vaccines being given in state in the study year). A total of 67,550 vaccine doses in routine immunization were studied. STATISTICAL ANALYSIS USED: Data were presented in mean ± standard deviation. One-way ANOVA test was used to compare the means among three levels. RESULTS: Vaccine wastage for Pentavalent was remarkably low (4.86% at district level, 8.35% at CHC and 11.50% at SC) in contrast to other similar 10 dose vials of vaccines like DPT, TT, Hep B. For both the lyophilized vaccines, interestingly BCG wastage was not only significant but over the permissible levels at 60.39%, whereas it is not so for measles. Result indicated that mean difference of the vaccine wastage among three levels was significant for the BCG, OPV, Hepatitis B, Pentavalent, and TT (P < 0.05); while insignificant for the DPT, IPV, and Measles (P > 0.05). CONCLUSIONS: Not all vaccine wastage is preventable, but pruning the corners where feasible and allowing where it is desirable should depend on prioritizing stakeholders at the receiving end.
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CONTEXT: The spread of COVID-19 pandemic poses a great challenge to health care organizations and unprecedented need for information. This study aims to identify possible factors causing delay and losing precious time during diagnosis and treatment of COVID-19 at home and health facility level. It also aims to highlight perceptions and experiences of family members of deceased regarding diagnosis and treatment of COVID-19 infection in hospital. METHODS: A retrospective study was done to review COVID-19 deaths from 18th March to 5th June 2020 in Punjab, India. A total of 48 laboratory confirmed (RT-PCR) COVID-19 deaths were reported during this period. Socio demographic profile, sequence of events including clinical symptoms, medical aid taken, time of confirmation of diagnosis and treatment before death were noted from the records on a predesigned proforma. Family members of deceased were also interviewed and asked open-ended questions regarding their experiences at various health facilities. Descriptive statistics was presented in percentages, mean, and median. RESULTS: Mean age of subjects was 56.3 ± 18.3 years. Majority (82.2%) had three or more than three comorbidities. Median time from appearance of first symptom to first medical contact and confirmation of diagnosis was 1 and 5 days, respectively. On the basis of interview with deceased's relative, various themes like delay in diagnosis and treatment, dissatisfied with hospital system and lack of communication between relative and patient were generated. CONCLUSION: Presence of comorbidities was the most important risk factor. Health seeking behavior of patients immediately after appearance of symptoms was found to be satisfactory.
