How clinical decision support systems can save lives
“Prescription: A physician’s guess at what will best prolong the situation with least harm to the patient.” — Ambrose Bierce
I still vividly remember that morning. It was 8:00 am and it was a crowded ward with a long hallway and smell of bleach in the air. I was a green hospital intern at that time and I was administering routine medications to patients.
Suddenly, I heard a strange noise from the corner of the long corridor of the medical ward. I immediately rushed there and saw that a boy aged about 12 was sweating profusely and almost losing consciousness. Beside him was my colleague with a syringe in his hand. He looked extremely nervous. Apparently, there had been an error in drug administration. Our immediate priority was to stabilise the young boy and take him out of harm’s way, which we were able to do successfully.
Investigation revealed that my colleague had correctly followed the consultant physician’s prescription by administering the right drug, right dose and right route. However, the drug had interacted with another administered drug, which led to the patient’s sudden deterioration. The doctor was given neither a prompt nor warning about the potential drug-drug interaction. There was no way to alert him to rethink the decision to administer the drug, except his own memory and judgement.
This is just one of numerous examples of the sort of medication errors that affect patients across Australia every year. The prospect of reducing these errors and the harm they cause patients is one of the key drivers behind the Australian Government’s My Health Record. But how would a solution to the problem of drug-drug interactions or other common issues such as the reactions between allergies and drugs be achieved?
Health care has been rapidly transforming in the last couple of decades. Clinicians are adopting more technology than ever before and revolutionising conventional ways of practising medicine. Advancements in Electronic Medical Records (EMRs) and interoperability have enabled clinicians to deliver connected health care to patients and maximise the likelihood of successful outcomes.
Among the tools now at our disposal are Clinical Decision Support Systems (CDSSs) embedded in EMRs. CDSSs are computer-based information systems that are designed to aid healthcare providers in clinical decision-making at the point of care. CDSSs are based on specific assessments and the clinical profile of the patient and are able to support better clinical outcomes.
CDSSs can be applied at various levels of care, especially in acute care units, providing a range of useful functions, including:
- Recommend a drug’s maximum tolerated dose (MTD).
- Establish a diagnosis based on a patient’s clinical parameters and blood work.
- Recommend order sets/templates based on the diagnosis.
- Generate drug-to-drug and drug-to-allergy interactions, and therapeutic duplications alerts.
- Calculate paediatric and renal expert dosing.
- Assist in pre- and post-surgical monitoring of the patient.
- Preventative health reminders.
Despite the potentially life-saving benefits associated with these functions, there are still some challenges in implementation. In particular, CDSSs need to have well-defined and unambiguous guidelines to translate them into computable code.
Where these challenges have been overcome, it is evident that CDSSs are changing conventional care delivery methods. Wider adoption of EMRs, including the Australian Government’s My Health Record, and adoption of in-built or integrated CDSSs would help to further transform and standardise health care.
And that might even save us from the next preventable disaster at the end of the hospital corridor.
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