28
March
2017
|
11:09
Asia/Singapore

Reducing hospital readmissions

NUS Pharmacy researchers have developed a novel online tool that uses hospital data to quickly and easily predict how likely a patient is to be readmitted within 15 days, allowing healthcare professionals to tailor interventions for high-risk individuals to prevent readmission. The development and validation of the model was published online in the journal Pharmacotherapy in January.

In Singapore, approximately 15 per cent of patients are readmitted within the month. Global rates can be as high as 20 per cent.

“Hospital readmissions place immense strain on the healthcare system,” explained Associate Professor Alexandre Chan. “By cutting down the number of preventable readmissions, hospital-related healthcare costs can be significantly reduced. Our simple tool helps healthcare teams identify high-risk patients and facilitates the administration of targeted interventions for these patients — during admission or post-discharge — to reduce readmission rates.”

Assoc Prof Chan, together with PhD candidate Sreemanee Raaj Dorajoo, tested the online “calculator” using data from 621 patients discharged from Singapore General Hospital and Khoo Teck Puat Hospital Singapore between August and September 2015.

“In this study, we looked at 15-day readmissions because studies have shown that this is the optimal cut-off for identifying potentially preventable readmissions. The web-based system instantaneously calculates the likelihood of readmission based on the presence of risk factors — such as age, presence of pre-existing conditions, number of discharge medications, discharge destination and evidence of premature discharge against medical advice — and the weightage attached to them. This tool can be used during the patient’s stay in hospital so that appropriate interventions, if necessary, can be administered in a timely manner,” said Sreemanee.

The study found that for each additional medication prescribed, the risk of 15-day readmission increased by about 6 per cent, suggesting that prescribing additional medication for discretionary use — for mild pain, nausea or constipation, for example — could be counterproductive as the added complexity may lead to confusion and errors during self-administration.

It also found that patients discharged to nursing homes had higher readmission risks, which indicates that ensuring patients enter appropriate post-discharge care facilities is an important consideration in stemming the cycle of readmissions, alongside other interventions such as medication counselling, caregiver training or home visits.

The web-based system instantaneously calculates the likelihood of readmission based on the presence of risk factors — such as age, presence of pre-existing conditions, number of discharge medications, discharge destination and evidence of premature discharge against medical advice — and the weightage attached to them.

The team is fine-tuning and validating the accuracy of the tool and hopes to integrate it into the existing electronic medical records system of healthcare providers in Singapore.

See press release and media coverage.