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Impact of Bias in Data Collection of COVID-19 Cases.
Manchanda, Raj Kumar; Miglani, Anjali; Chakraborty, Moumita; Meena, Baljeet Singh; Sharma, Kavita; Gupta, Meeta; Sharma, Ashok; Chadha, Vishal; Rani, Purnima; Singh, Rahul Kumar; Rutten, Lex.
  • Manchanda RK; Directorate of AYUSH, Health and Family Welfare Department, Government of NCT of Delhi, New Delhi, India.
  • Miglani A; Homeopathic Unit, Delhi Government Health Centre, Government of NCT of Delhi, New Delhi, India.
  • Chakraborty M; Homeopathic Unit, GTB Hospital, Government of NCT of Delhi, New Delhi, India.
  • Meena BS; Homeopathic Unit, SRHC Hospital, Government of NCT of Delhi, New Delhi, India.
  • Sharma K; Homeopathic Unit, Delhi Government Health Centre, Government of NCT of Delhi, New Delhi, India.
  • Gupta M; Directorate of AYUSH, Government of NCT of Delhi, New Delhi, India.
  • Sharma A; Homeopathic Unit, Delhi Secretariat, Government of NCT of Delhi, New Delhi, India.
  • Chadha V; Homeopathic Unit, DHAS Hospital, Government of NCT of Delhi, New Delhi, India.
  • Rani P; Homeopathic Unit, GTB Hospital, Government of NCT of Delhi, New Delhi, India.
  • Singh RK; Homeopathic Unit, SRHC Hospital, Government of NCT of Delhi, New Delhi, India.
  • Rutten L; Independent Researcher, Breda, The Netherlands.
Homeopathy ; 111(1): 57-65, 2022 02.
Article in English | MEDLINE | ID: covidwho-1402156
ABSTRACT

BACKGROUND:

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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Homeopathy Type of study: Controlled clinical trial / Observational study / Prognostic study / Randomized controlled trials / Risk factors Limits: Humans Language: English Journal: Homeopathy Journal subject: Complementary Therapies Year: 2022 Document Type: Article Affiliation country: S-0041-1731314

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Homeopathy Type of study: Controlled clinical trial / Observational study / Prognostic study / Randomized controlled trials / Risk factors Limits: Humans Language: English Journal: Homeopathy Journal subject: Complementary Therapies Year: 2022 Document Type: Article Affiliation country: S-0041-1731314