Healthcare

Now more than ever, the healthcare industry is stretching into a future it is destined to embrace.

Predictive analysis has the potential to shift the healthcare paradigm and make value-based care the norm. Predictive analytics will reduce the cost of healthcare, improve the patient experience, and provide doctors and nurses with more control over their patients. The introduction of technologies like, cloud computing, wearables, artificial intelligence (AI), machine learning (ML), and even 3D printing will revolutionize healthcare as well as optimize overall population health.

Modern telemedicine brings technology to patients, allowing them to discuss their symptoms with doctors in real-time, using video, online portals, and email to gain instant diagnosis. Caregivers can remotely monitor their patients, while doctors and providers can easily share a patient’s health information with each other. We've helped healthcare organizations perform strategic assessments of their infrastructure and it's paid dividends for them.

With a leveraged technological footprint, today’s healthcare organizations can finally proactively safeguard each patient’s safety as well as protect the organization’s assets. Healthcare risk management must reduce medical errors and strengthen cybersecurity protocols. Proper healthcare risk management should adherer to these tenets: detection, monitoring, assessment, mitigation, and prevention.

The technology advancements that have taken healthcare to entirely new levels have not gone unnoticed.

Improve Efficiency

Fragmented Point Solution

Inefficient, inconsistent versions of the truth.
Cumbersome internal and external reporting.

Enterprise Data Operating System

Collecting and integrating the core data content.

Standardized Vocabulary & Member Registries

Relating and organizing the core data content.

Reduce Variation

Automated Internal Reporting

Efficient, consistent production of reports & widespread availability in the organization.

Automated External Reporting

Efficient, consistent production of reports & adaptability to changing requirements.

Improve Health

Waste & Care Variability

Reducing variability in care processes. Focusing on internal optimization and waste reduction.

Population Health Management & Suggestive Analytics

Tailoring member wellness based upon population metrics. Fee-for-quality includes bundled per case payment

Clinical Risk Intervention & Predictive Analytics

Organizational processes for intervention are supported with predictive risk models. Fee-for-quality includes fixed per capita payment.

Personalized Medicine & Prescriptive Analytics

Tailoring member care based on population outcomes and genetic data. Fee-for-quality rewards health maintenance.

Direct-to-Consumer Analytics & Artificial Intelligence

Putting member data, analytics, and Al in member's hands so they can own more of their health and healthcare decisions.

Source: 2020 Health Catalyst "The Healthcare Analytics Adoption Model: A Roadmap to Analytic Maturity."

AI can help doctors and nurses diagnose illnesses through natural language processing, which can use metadata and cross-reference this with a collection of annotations that detect, normalize, and code medical findings from unstructured clinical data. AI’s insights provide critical contextual information for problems, procedures, and medications identified in medical literature.

Data-driven personalized medicine uses advanced analytical tools to scan the data of millions of patients to find patterns and identify subpopulations who respond to treatments differently. With electronic medical record silos starting to fall, the introduction of genetic testing, and powerful new analytics and AI tools available, the dream of personalized medicine is quickly becoming reality.

Fighting fraud, waste, and abuse is not easy in an industry as complex as healthcare. Both intentional and unintentional billing errors as well as deliberate acts of fraud that target Medicare and Medicaid can end up costing insurers money. However, AI and machine learning can uncover abnormal patterns and proactively guard against potential exploits.

Analytics can help healthcare companies avoid costly and preventable readmissions. A risk-score model driven by machine learning can analyze many variables pulled from the EHR and other patient outcomes to predict readmissions. Results from these models can provide early warning signs to doctors and nurses who can immediately administer treatment protocols.

No longer science fiction, AI and robotics are transforming healthcare. “No Longer Science Fiction, AI and Robotics Are Transforming Healthcare”

Marshall Cook, Chief Executive Officer at BalanceGenics

Learn how Product Perfect migrated a flagship Windows desktop application to a modern web app for a pharmaceutical benefits brokerage firm in Southern California.

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