Two weeks ago, while driving home in the pouring rain, the amber ‘engine warning’ icon lit up on my dashboard. The car appeared to be functioning normally until, on the freeway, it refused to exceed 70 kilometres an hour.
Going too slow in such conditions was dangerous. We pulled over to consult the manual. Possible causes included fuel, electrical, and mechanical faults. The solution: seek immediate investigation by an expert mechanic.
The national hospital-acquired complication (HAC) system is a ‘warning light’ for possible health system problems. This warning light is present in every health service. HACs include 41 serious conditions that arise during hospital care which may be amenable to risk mitigation. They are now visible through an interactive HAC dashboard available to authenticated users on the VAHI portal.
All complications warrant investigation, even if your hospital appears to be running smoothly. Ignoring them may simply drive us toward a serious 'accident’. Like my engine warning light, a high HAC rate has many possible causes and warrants investigation by clinical experts who can objectively assess patient safety.
Each hospital’s approach to HACs must be tailored to its services, circumstances, and resources. Common features include multidisciplinary engagement, clinical leadership, local ‘champions’, and a simple and transparent review process, with a focus on frequent and/or recent complications. There is no guarantee that today’s results will match yesterdays. Whether or not similar events can be prevented will only be answered by your expert ‘mechanics, and solutions from another hospital may not suit your services or patients.
One approach is to regularly ask each clinical service to review reported HACs in their patients. Another is to focus on a high-frequency complication (e.g. hypoglycaemia or delirium) to identify common threads. You need not review every case, unless the number is small. Analysing a selection of 20-30 cases may be sufficient to identify themes and provide some statistical validity to your results. Common questions for any investigation include:
Did the complication actually occur? 10-15% of HACs are inadvertently derived from (correctly coded) diagnoses that were only suspected but never present. Examples include some wound and urinary tract infections, and hypoglycaemia.
Was the ‘complication’ present on arrival to hospital? Examples include acute kidney injury and acute delirium that lack early diagnostic features and may be missed, or poorly documented, on arrival.
Which patient-related risk factors may have increased the likelihood of this complication? Was this risk identified on arrival and managed appropriately?
What hospital-related errors or system factors increased its likelihood? Local clinical practice guidelines and the Australian Commission on Safety and Quality in Health Care’s HAC Information Kit may be helpful as an objective standard.
Are there any common themes for risk mitigation solutions? Be wary of changing models of care based on a single HAC event. For example, prevention of hypoglycaemia may lead to an increased risk of hyperglycaemia and hospital acquired infections; the use of restraints to prevent patient falls may increase pressure injury, venous thromboembolism, and delirium.
Current evidence suggests the majority (>80%) of HACs are expected complications arising in patients requiring complex interventions to treat complex disease within a system fine-tuned to identify early clinical deterioration. Counterintuitively, a high HAC rate may reflect an efficient, high quality, health service.
As it transpired, there was nothing wrong with my car apart from an alarm system with an overly sensitive trigger setting. It may be that the national HACs system is over-sensitive too, but we cannot determine this until we look ‘under the bonnet’.
Dr Graeme Duke is VAHI’s Data Analytic Fellow, in addition to his roles as Deputy Director, Eastern Health Intensive Care Services in Melbourne, and clinical lead for intensive care research. To get in touch with Graeme about how we can collaborate to use data more effectively, contact [email protected]