New Delhi, Aug 6 The Delhi High Court on Thursday asked the Centre and the Delhi government to act against the online health service aggregators who are operating illegally or in violation of the law and collecting diagnostic samples including Covid-19.
"We direct the authorities that if there is any illegal health service aggregator working in violation of law, action shall be taken against them after giving proper hearing before the concerned authorities," said a division bench of the High Court presided by Chief Justice D.N. Patel and Justice Prateek Jalan.
The observations came in while the court was hearing a Public Interest Litigation (PIL) seeking a ban on the alleged collection of diagnostic samples by online health service aggregators for testing of COVID-19 infection, posing as "medical diagnostic laboratories".
The petition filed by Rohit Jain, a practicing pathologist by profession in Jaipur, through advocate Shashank Deo Sudhi sought direction to issue guidelines for registration and minimum standards for sample collection centers operated by online aggregators.
Jain in his petition further sought ban on the illegal online health service aggregators which are not registered under Clinical Establishment (Registration & Regulation) Act 2010 or under any other regulations and are running without any medico legal liability for collecting and testing the patient samples for diagnosis.
It further claimed that a large number of unauthorized pathological labs are being run by under-qualified technic who are providing totally unscientific diagnostic test reports rendering the lives of common and innocent citizens vulnerable.
The petitioner further alleges that many of the online health service aggregators are also not following the Bio-Medical Waste Management Rules, 2016 for proper disposal of bio-medical waste.
"The illegal and fake online health service aggregators are not registered with state pollution control board or any pollution control committee as prescribed under the law," the petition said further.
( With inputs from IANS )