Growth Series BLOG

Its a Premium BLOG template and it contains Instagram Feed, Twitter Feed, Subscription Form, Blog Search, Image CTA, Topic filter and Recent Post.

All Posts

Reality of Healthcare Digitization: the Practical versus the Possible

Healthcare information technology is undergoing enormous changes with broad consumer impact. One major area of innovation is mobile healthcare or mHealth. mHealth has the potential to provide patients and physician’s with a broad range of interactive tools - the success of which depends on greater effectiveness in standardizing and structuring vocabularies across healthcare. Hence, why this is of great interest to me and our community of practitioners.

MHealth is resulting in new technologies and approaches for healthcare. Classes of application include patient monitoring, remote diagnostics, Rx compliance-monitoring, self-monitoring for wellness, patient tracking, home healthcare, and payment and reimbursement management systems, among others.

The challenges of data management and integration are magnified significantly by mHealth programs and initiatives. This nascent and developing field requires greater numbers of systems and tools to communicate and manage information - as it is, the healthcare IT industry is already a tower of babel of conflicting and confusing standards from MeSH, SNOMED, ICD-9, ICD-10, LOINC and others. This means that further fragmentation from new applications and new entrants into the field will cause problems and challenges to be even more magnified before things settle down into accepted methods for organizing and transmitting data.

Transaction Processing versus Quality of Patient Care

Although there are already standards in use (e.g. ICD-9), particularly for patient procedure and diagnosis coding,   these standards have limited utility.   They work well for insurance reimbursement but are insufficient to provide a full picture of a patient and the effectiveness of treatment. There is a significant opportunity to use mHealth to accelerate data capture for evidence-based medicine - that is practices that tie clinical decisions to scientifically-trusted data.

In order for some of the expected efficiencies of healthcare reform and data integration through Electronic Health Records (EHR), data needs to be analyzed in new ways that will yield insights into improved, safer, higher quality and more effective treatments. In order to achieve this end, there will need to much greater standardization and structuring of healthcare data to support analysis.

Remote Monitoring

Another area with great promise is in the continuous monitoring of patient conditions and biochemical markers (like blood sugar levels for diabetics). Noninvasive devices embedded in everyday items like articles of clothing will one day allow physicians to see an almost continuous feed of patient data and perform interventions or changes in protocol on a proactive and preventative basis

We can’t begin to describe all of the interesting areas where mHealth will transform our lives.

Taxonomy, Metadata, IA and Patient Experience

Taxonomy and metadata and overall information architecture play a central and pivotal role in these systems and processes. New devices will continue to fragment data and new approaches will require adoption of additional protocols and data standards. In order to make any system user friendly, we need to explore how data is surfaced to the user, whether that person is a physician, medical organization, intermediary, or patient. Humans interact with systems at every step of the process and usability will be paramount to patient engagement and adoption.

Need help with your own transformation program? Lay the foundation for your organization’s success with our Digital Transformation Roadmap. With this whitepaper, assess and identify the gaps within your company, then define the actions and resources you need to fill those gaps.

Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

Recent Posts

Designing AI Programs for Success - a 4 Part Series

Recorded - available as on demand webcast AI is plagued by inflated and unrealistic expectations due to a lack of broad understanding of this wide-ranging space by software vendors and customers. Software tools can be extremely powerful, however the services, infrastructure, data quality, architecture, talent and methodologies to fully deploy in the enterprise are frequently lacking. This four-part series by Earley Information Science and Pandata will explore a number of issues that continue to afflict AI projects and reduce the likelihood of success. The sessions will provide actionable steps using proven processes to improve AI program outcomes.

The Missing Ingredient to Digital Transformation: Scaling Knowledge Communities and Processes

The holy grail of digital transformation is the seemingly conflicting goals of high levels of customer service and pressure to reduce costs. “Digital Transformation” has become an all-encompassing term – in a piece in this column about customer data platforms, I asked whether the term has lost its meaning: The phrase “digital transformation” can mean anything and everything — tools, technology, business processes, customer experience, or artificial intelligence, and every buzzword that marketers can come up with. Definitions from analysts and vendors include IT modernization and putting services online; developing new business models; taking a “digital first” approach; and creating new business processes, and customer experiences. The overarching objective of a digital transformation program is to improve end-to-end efficiencies, remove friction from information flows, and create new value streams that differentiate a company’s offerings and strengthen the customer relationship. Having assisted large global enterprises with building the data architecture, supporting processes, and governance for multiple digital transformations, in my experience, there are two broad classes of initiatives that seem to get funding and others that miss the boat in terms of time, attention, and resources.

4 Reasons B2B Manufacturers need Strong Product Data

There are many manufacturers who have started to take the leap forward in the digital space, but there are still a great number who rely solely on their distributors to manage their product data. We are going to look at 4 key reasons why its so important that manufacturers own their product and dedicate the time and resources to build it out.