Implementation of cloud delivery services in healthcare lagged the overall IT industry for many years but recent surveys show accelerating movement in that direction.
In addition to the SaaS model for application access we are also seeing more and more healthcare organizations migrating databases, legacy applications, and services like disaster recovery provisioning to the cloud.
A survey from HIMSS Analytics conducted in early 2017 found that 65% of all healthcare organizations were utilizing cloud based offerings.
The healthcare cloud delivery market is estimated to triple in expenditures from 2015 to 2020 resulting in total spend of almost $10 billion.
In order to avoid access related problems it is critical you work with a proven partner regarding your cloud migration.
In summary, any reluctance the healthcare industry had to cloud based application delivery and use of the cloud for infrastructure and storage is largely in the past.
Achieving all the benefits of cloud migration requires careful planning and working with an experienced partner.
It’s no secret that technology has the grand potential to completely revolutionize how we approach healthcare. Actually, transforming the healthcare industry is much more challenging.
- Artificial Intelligence (AI) and Big Data
- Mobility and Cloud Access
- Wearables and IoT
- Patient Empowerment
While these trends have been in the works for years, they are continuing to gain momentum and should not be ignored for those who want to stay at the forefront of healthcare evolution.
EHR Software is a computer program that physicians use to create and manage Electronic Health Records which are “Real-time, patient-centered records that make information available instantly and securely to authorized users…an EHR system is built to go beyond standard clinical data collected in a provider’s office and can be inclusive of a broader view of a patient’s care.”
Begin the selection process for an EHR System with a clear understanding of what your EHR should deliver for your practice.
The Roadmap to Success: Best Practices and Key Considerations
Best Practice 1: Take Leadership & Build Your Team
Best Practice 2: List all ‘Required’ EHR Features
Best Practice 3: Find the Right EHR Vendor
Best Practice 4: Assess Your EHR Vendor
Best Practice 5: Opt to implement an Integrated EHR and Practice Management Software System
Best Practice 6: Vet the EHR Software Thoroughly for Workflow Adaptability, Customizability, Ease of Use, etc.
Best Practice 7: Ensure Adequate Training, Technical Support and Maintenance
Best Practice 8: Understand Total Cost of Ownership, Determine Budget & Negotiate Contract
Best Practice 9: Ensure EHR Certification (ONC-ATCB, MACRA, APM, MIPS, etc.)
Best Practice 10: Question your EHR Vendor on Incorporation of New Technology
Looking Ahead – Soon you will either be ready to install a new EHR system or ready to replace your existing software.
In healthcare, most data is exchanged electronically between partners via EDI, and “Big Data” is helping the industry become more efficient and productive.
EDI originated because it provided a structured mechanism for sharing data between disparate organizations and systems.
The more common means of transferring data from source to a data warehouse is ETL, but there are times when you might want to consider using ELT. EDI allows the healthcare industry to bring in information needed to help perform analytics.
There are still some issues with EDI regarding data quality, but that is getting better as each business is learning the need for reliable data to perform their analytics.
EHRs also play a big role in the ability to perform analytics, and there is an immense amount of raw data available in EHRs, EMRs and EDI. “Big Data” now provides a greater opportunity to use this information to perform critical analytics by applying business intelligence techniques.
When linked with the adjudication system, organizations can get a more complete view of what is happening in their business and deliver real-time analytics of clinical, financial, as well as fraud and HR. Analytics allow for the examination of patterns to determine how care can be improved while reducing the need for repetitive hospital stays and limiting excessive spending for testings etc.
“Big Data” allows them to store and go back in their data history to analyze large unstructured datasets to detect anomalies and patterns.
Artificial intelligence can keep us healthy, but providers don’t get reimbursed to keep you healthy; they get reimbursed for office visits and hospital admissions.
Being on the precipice of the great AI promise and adventure, here are my 4 things that can derail AI in medicine.
1. Ethics – There are more questions than answers here, but the reality is clear. AI has its risks as demonstrated by the recent Tesla fatality.
2. Fiscal states of hospital – According to a report from the North Carolina Rural Health Research Program, 83 rural hospitals closed between 2010 and 2018. More are on the way.
3. Privacy – Assuming that HIPAA guidelines will also govern AI, how will machine language comply?
4. Fear – Who really knows what is going on with data under the purview of Google and Facebook — the latter being a company falling victim to unforeseen nefarious actors. If I talk to Alexa, where is that data going?
As AI matures, these hospitals will fall further behind more affluent places of care.