Medically Necessary: Data, Data, Data

Investing In Data Management

The world of supply chain management in health care is evolving extremely fast, as COVID-19 (see graph) has been a significant influencer of technology development. However, like COVID, the state of some organizations’ data was a shock; many were unprepared for the future and the cost associated with modernizing. It is estimated that most companies will be increasing their technology budgets, but with a worldwide shortage of semiconductors and other parts, the reality might be more of a decrease in spending.

Importance of Accuracy and Consistency

If we genuinely want to understand the importance of accurate information within supply chain management, it all begins with data. You can spend countless hours reading articles that focus on big data, smart data, data analytics, AI, DL, ML, integrating data, data mining, dumb data, predictive analytics and high-performing computers. There is an endless sea of “how to” in the technology world; it just keeps coming from various sources — a far cry from telephones and fax machines. And there is no easy panacea to this data challenge. The Daily Covid-19 graph highlights how quickly a disruptor can get of ahead of current capabilities and lead to supply shortages. 

Evolution of Data Analytics

Excel and Power BI, everything was manually logged. The age of computing in the early ’80s consisted of processing centers and big computers that were given data from keypunch cards, but that was all transactional, more of what we did versus what we should be doing.

Importance of Digital Information

Switching to digital: It’s said we are already digital, but to what extent? There is analog, then comes digital. Remember DVDs before HD, UHD, Blu-ray? Digital is condensed information, and its compatibility in today’s technology is critical to building information integrity.
Safety in data is something we cannot ignore in health care. Data is critical in identifying medical devices and supplies that the manufacturer could recall. Inaccurate, inconsistent or poor classification of item information directly impacts the data audit trail. The saying “garbage in, garbage out” originated from dirty data/information.