Black History Month: What does this mean for digital leaders?

As Black History Month comes to close, will this mean that the achievements and contribution of black people in the UK and the need to take action will be packed away for another year, asks Dr Shera Chok, co-founder of the Shuri Network.

How Wake Forest Baptist Health uses RTLS to protect against communicable disease

Data from a real-time location system, covering nearly 4.3 million square feet, offers the ability to see patients and staff who may have come into proximity with an infected person.

COVID-19: What is different in our understanding of this pandemic to the accepted wisdom in the spring of 2020?

As we have heard repeatedly over the past few months, there is a need to think of managing this pandemic in the same way we prepare for a marathon rather than a sprint, says Dr Charles Alessi, chief clinical officer, HIMSS.  

Test and Trace: A three point plan to regain public trust

Whichever way you look at it, many countries across the globe are experiencing a rise in COVID-19 cases coinciding with the start of the Autumn/Winter seasons, says Dr Saif Abed, founding partner at The AbedGraham Group.

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Building a solid technology foundation enables transformation

As IT professionals, we need to be ahead of the game in terms of establishing and maintaining the capabilities of our technology foundation. This means being smart about understanding the business and staying ahead of its needs.

Terminology standards bridging gaps between health systems during COVID-19

The clinical manifestations of COVID-19 are varied, and patients are known to have rapidly changing signs and symptoms that must be tracked with laboratory testing. A patient may start his treatment journey with his primary care physician and will include lab centers, diagnostic centers, inpatient, and home quarantine centers. 

Proximity matters: Using machine learning and geospatial analytics to reduce COVID-19 exposure risk

Data science and clinical teams at PCCI, in collaboration with Parkland informaticists, have developed an AI-driven predictive model that predicts for individual COVID-19 exposure risk, based on population density and their proximity to positive cases.