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A 40-year-old female presented to Outpatient Department of our hospital with the chief complaint of hard swelling in post auricular region for 3-4 years which was progressively increasing in size. She didn't complain of any pain or other symptoms related to swelling except for cosmetic deformity. On examination, there was a single pyramidal shaped swelling with smooth margin of size around 5.5 x 4.5 cm at left post auricular region [Table/ Fig-1]. Swelling was bony hard in consistency, covered with skin, non tender and its base fixed to underlying bone. Surrounding area was devoid of any sinus or fistula. Past history of patient didn't reveal any history of trauma or infection. Otoscopic examination and audiometry were normal.

Background/Objective Prognostic factor research (PFR), prevalence of symptoms and likelihood ratio (LR) play an important role in identifying prescribing indications of useful homeopathic remedies. It involves meticulous unbiased collection and analysis of data collected during clinical practice. This paper is an attempt to identify causes of bias and suggests ways to mitigate them for improving the accuracy in prescribing for better clinical outcomes and execution of randomized controlled studies. Methods A prospective, open label, observational study was performed from April 2020 to December 2020 at two COVID Health Centers. A custom-made Excel spreadsheet containing 71 fields covering a spectrum of COVID-19 symptoms was shared with doctors for regular reporting. Cases suitable for PFR were selected. LR was calculated for commonly occurring symptoms. Outlier values with LR ≥5 were identified and variance of LRs was calculated. Results Out of 1,889 treated cases of confirmed COVID-19, 1,445 cases were selected for pre-specified reasons. Nine medicines, Arsenicum album, Bryonia alba, Gelsemium sempervirens, Pulsatilla nigricans, Hepar sulphuricus, Magnesia muriaticum, Phosphorus, Nux vomica and Belladonna, were most frequently prescribed. Outlier values and large variance for Hepar sulphuricus and Magnesia muriaticum were noticed as indication of bias. Confirmation bias leading to lowering of symptom threshold, keynote prescribing, and deficiency in checking of all symptoms in each case were identified as the most important sources of bias. Conclusion Careful identification of biases and remedial steps such as training of doctors, regular monitoring of data, checking of all pre-defined symptoms, and multicenter data collection are important steps to mitigate biases.