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Providers struggle with the current segmented, “Unmanaged” care system, and patients are overburdened and stressed having to know what is relevant to their current medical needs and remembering to share all of the pertinent details with each provider.
Given the time-constraints and pressures that physician groups face on a daily basis, they are rarely able to get that comprehensive picture and/or follow up with the patient’s other providers.
A National Health Record could allow practitioners to care for their patients in the current visit or limit the number of referrals and follow ups.
A reduced number of follow ups could also give the practitioner more time with each patient, subsequently improving each patient’s experience and health.
Patients as Consumers: Member-Driven Healthcare With the prevalence of high-dollar deductible health plans, members have to assume the role of consumer as well as patient.
Caring for our Vulnerable Populations The most vulnerable patients with complex medical situations utilize healthcare at the highest rate.
National Health Record Given the complexity of patients in critical care situations, they are likely to not be able to report thorough medical histories and provide accurate prescription lists.
Source: Perficient

Below are some of the major use cases where data science is making a big difference in the healthcare industry.

• Drug discovery
• Wearables
• Diagnostics
• Public health
• Reduced healthcare costs
• Optimal staffing

Data science can leverage various sets of structured and unstructured biomedical data obtained from numerous tests, treatment results, case studies, social media etc.
Data science methods are also able to integrate with genomic data in research to provide accurate insights into genetic issues arising out of specific drugs and diseases.
Data scientists can look into billing data and information from clinical systems pertaining to categories of charges and variables.
Clearly, in addition to transforming patient care, data is helping healthcare providers in tackling issues related to resource management, inadequate medical staff, and high treatment costs.
Needless to say, this amount of data would be impossible to interpret if not for data science and AI. “By one estimate, AI could help reduce health care costs by $150 billion by 2026 in the U.S. alone,” according to Stanford Medicine’s 2018 Health Trends Report.
As the developments in healthcare data science continue, we can look forward to a revamped healthcare model in the days to come.
Source: Crayon Data

Cut through the noise and we find that Asia is on the rise in medtech just as it is in other industries-indeed, Asia today already represents 23 percent of the global market.
To take the pulse of where Asia medtech stands today, and to understand its challenges, opportunities, and priorities, we surveyed 160 APAC presidents and Asian country general managers from some 30 multinational medtech companies via a survey conducted amongst members of APACMed and selected executive interviews.
Asia medtech executives paint a mixed picture of overall market trends.
Grappling with the Asia market: Three hard nuts to crack for medtech leaders a) The blessing and curse of premium-oriented portfolios.
The growth of medtech in Asia has been largely driven by a single commercial model: growing the sales force plus expansion and heavy reliance on distributor networks.
As Asia’s medtech market continues to grow and mature, so too will the stakes for medtech leaders.
In reality, we see room for improvement in most Asia medtech organizations and hence consider this an important area for investments into future business success in Asia.
Source: McKinsey

As a result more and more healthcare providers and payers are leveraging mobile apps to connect with consumers-patients-members to make their services more accessible and efficient.
You may have a patient or member portal app with secure access to medical records, communicating with physicians, managing health benefits, healthcare costs, and more.
General information apps are also popular with useful information on location directions and parking, find a doctor tools, health library information and many others.
Other mobile apps within the healthcare industry include ER wait times or service-line specific apps.
As a result, it’s imperative to measure the performance of mobile apps.
Understanding user engagement, satisfaction, and app performance are critical to measuring the success of your mobile app.
By monitoring mobile app analytics in addition to performing deeper dives into mobile app data this will assist you in identifying areas for improvement and optimization of the mobile app digital experience to create delightful experiences for those that use it.
Source: Perficient

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.
Source: Perficient

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.

1. Artificial Intelligence (AI) and Big Data
2. Telemedicine
3. Mobility and Cloud Access
4. Wearables and IoT
5. 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.
Source: Perficient

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.
Source: revenuexl

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.
Source: Perficient

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.
Source: healthsystemCIO