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Leaders in ai medication transcription
Leaders in ai medication transcription









Since this is an emerging area in health IT, there is no hard evidence as yet however, there is much optimism about its potential effectiveness in reducing medication errors. Furthermore, advanced PHRs provide decision support tools, such as checking for drug allergies and drug–drug interactions and allowing patients to anticipate potential medication errors and alert physicians to them. A patient-initiated medication reconciliation system is likely to be more accurate, as patients know not only what has been prescribed but what they are actually taking.

Leaders in ai medication transcription update#

Patients can access medication information from multiple providers, reconcile them, update them, and share them with their physician. Online medication lists are an essential component of most PHRs. Implementation of such a record may consist of a ‘stand-alone’ website for patients to enter their medical data, or a physician/hospital-hosted patient portal, giving patients access to their electronic health record (EHR), or an employer/payer portal giving patients access to claims data. An individual can maintain a paper-based record, but in the current context a PHR is defined as ‘a set of computer-based tools that allow people to access and coordinate their lifelong health information and make appropriate parts of it available to those who need it’. Personal health records (PHR) engage and empower patients in their own medical care. CPOE systems work by (i) making sure that the order is legible and complete, including all necessary information, such as dose, route, and dosage form (ii) checking for problems such as drug allergies and drug–drug interactions (iii) providing dosage adjustment calculations based on clinical features such as weight or renal function (iv) checking for appropriate baseline laboratory results, such as platelet count and international normalized ratio for patients receiving anticoagulants (v) computing drug–laboratory interactions, such as alerting the prescriber to a low potassium concentration when digoxin is being prescribed and (vi) updating the prescriber with the latest drug information, such as the need to avoid rofecoxib after it had been withdrawn by the manufacturer.įigure 1 shows a variety of decision support alerts embedded in an intravenous heparin prescribing screen. Common prescribing errors include using the wrong drug or dosage form, incorrect dose calculation, not checking for allergies, and failure to adjust dosages in patients with renal or hepatic dysfunction. Since most errors occur at the prescribing step, computerized physician order entry (CPOE) with patient-specific decision support is a potentially powerful intervention for improving patient safety. Here I review the current state of various IT systems in preventing medication errors.Ĭomputerized physician order entry with decision support Hospitals with automated notes and records, order entry, and clinical decision support have fewer complications, lower mortality rates, and lower costs.

leaders in ai medication transcription

IT systems have also been reported to have the potential to save up to $88 billion over 10 years in costs in the USA, with increasing adoption.

leaders in ai medication transcription

There is mounting evidence that systems that use information technology (IT), such as computerized physician order entry, automated dispensing cabinets, bedside bar-coded medication administration, and electronic medication reconciliation, are key components of strategies to prevent medication errors. Prevention of medication errors has therefore become a high priority worldwide. Medication errors are also costly – to healthcare systems, to patients and their families, and to clinicians. In the UK, of 1000 consecutive claims reported to the Medical Protection Society from 1 July 1996, 193 were associated with prescribing and medications. In Australian hospitals about 1% of all patients suffer an adverse event as a result of a medication error. In the USA, medication errors are estimated to harm at least 1.5 million patients per year, with about 400 000 preventable adverse events. A substantial body of evidence from international literature points to the risks posed by medication errors and the resulting preventable adverse drug effects.









Leaders in ai medication transcription