Reduction in adverse events can offset costs of eMM systems
An Australian-first cost-effectiveness study of the use of an electronic medication management system over paper-based prescribing has shown that savings from reduced adverse drug events can more than offset the cost of implementing the system.
In a paper published recently in the Journal of the American Medical Informatics Association (JAMIA), researchers led by Macquarie University's Johanna Westbrook and clinical and IT staff from St Vincent's Hospital in Sydney found that the implementation of CSC's MedChart system could provide savings of about $100,000 a year in a 30-bed ward.
If extrapolated over the whole hospital, it would see savings of an estimated $2.5 million a year. In addition to reductions in adverse drug events affecting patient safety, the researchers argue that the results should provide some confidence to policy-makers, consumers and clinicians that the benefits of eMM systems provide a sound return on investment.
As the researchers point out, evidence of the cost-effectiveness of most clinical information systems remains scant, with one systematic review published in 2012 of medication-relation health information technology identifying only five full economic evaluations and 26 partial.
The authors of that international study found that the quality of the reviewed studies was generally poor and could not determine whether the additional costs of computerised physician order entry and clinical decision-support systems represented value for money.
In Australia, public health services are increasingly looking to implement commercial electronic medication management systems (eMMS) as part of plans to achieve clinical benefits as well as reduced healthcare costs. NSW, for example, has set a budget of $170 million over 10 years to roll out eMM systems statewide.
As the researchers write, however, these plans are often accompanied by “very modest procedures” for assessing or quantifying expected benefits.
They quote the Victorian Auditor-General's 2013 report on clinical ICT systems in the Victorian public health sector, which stated that there had been limited assessment of the benefits and outcomes of the various clinical systems put in place.
“Until this work is done, it will be difficult to convince taxpayers that public funds have been well spent on these systems and that any further investment on clinical ICT systems is justified, or will improve clinical and patient outcomes,” the Auditor-General wrote.
To help remedy this in part, the team undertook a cost-benefit analysis of MedChart in a 30-bed cardiology ward at St Vincent's versus paper-based prescribing in reducing medication errors and preventing adverse drug events (ADEs).
They devised an economic evaluation model based on the perspective of the NSW health system, with a time horizon for the evaluation set at 15 years from the time MedChart was implemented at the hospital in 2005.
Data was collected over 16 weeks before the introduction of MedChart and over 10 weeks post implementation. The collection of prescribing error data pre- and post-implementation allowed identification of potential adverse drug events.
There were 801 patient admissions to the cardiology ward in the pre-eMMS study period and 401 in the post-implementation period with no statistically significant differences in mean age, gender profile, or length of stay in the cardiology ward pre-eMMS and post-eMMS.
They then gathered information on the cost of the implementation from the vendor and hospital financial records. Costs included equipment and software, system configuration and implementation, operating costs such as an annual licence and subscriptions, training and system updates. These were estimated in 2012-2013 prices.
The total annual cost of the eMMS in the cardiology ward was $61,741, with the single largest cost component the MedChart software licence fee of $25,680.
They then performed two economic evaluations, one using published estimates of costs per ADE and the second using a combination of the published estimates of additional length of stay with the actual cost per bed day in the cardiology ward.
The first model showed savings resulting from eMMS implementation of an estimated $66.17 per admission, or about $102, 000 per annum on this ward. The second showed savings of $63.43 per admission, or an estimated $97,740 per annum.
The results show that across the hospital, with 39,900 annual admissions, the savings equate to about $2.5 million.
“This study is one of only a few full economic evaluations, which relate costs of implementation and maintenance of eMMS to incremental benefits in terms of reduced ADEs and their associated costs,” the researchers write.
“We modelled the entire medication error process from prescription to the occurrence of errors and harm to patients. Importantly, we were able to populate our model primarily with data about the costs and effectiveness of the eMMS from our hospital site. This has been a limitation of some previous cost-effectiveness studies ...”
They also say that other studies they have conducted on the implementation of Cerner's eMM at another Sydney hospital showed a very similar level of potential ADE reduction.
“The limited decision-support embedded in the eMMS at the time of our study also suggests that further improvements in the effectiveness of the eMMS to reduce ADE rates can be expected as decision-support is added to the system, if it is well-designed and targeted,” they write.
“Beyond reducing ADEs, eMMS with decision-support can also be effective in driving more appropriate drug therapy, such as improvements in the rates of venous thrombosis prophylaxis and appropriate antibiotic prescribing.
“Such effects should improve patient outcomes and long-term costs of care. However, monitoring and maintaining a safe and effective decision-support system is also likely to demand more hospital resources, consequently increasing the operating costs of an eMMS.”
The limitations of the study were that the model was sensitive to large variations in the probability of clinicians intercepting an error and the probability of error causing harm.
Posted in Australian eHealth