Four (4) Predictions for Healthcare Analytics and Artificial Intelligence (AI) in 2022-23

I would like to dedicate this blogpost to our fearless Doctors, Clinicians, Nurses, Technicians and First Responders in the US of A and across the World, as they put their health and their lives at risk to heal and save the rest of us, in the days and weeks ahead – God bless them!

Context

After the Pandemic induced Maelstrom in 2020-21, 2022 shows immense promise of ushering in the advent of the “Post-Pandemic New Normal”.

Leaders in healthcare see tremendous potential in AI and Analytics to deliver on the promise of higher quality care at a lower cost by empowering their executives, business leaders, clinicians and nurses by harnessing the power of predictive and prescriptive analytics. Many healthcare organizations are seeking to harness the vast potential of artificial intelligence (AI) and its four components — machine learning (ML), natural language processing (NLP), deep learning, and robotics — to transform their clinical and business processes. They seek to apply these advanced technologies to make sense of an ever-increasing ‘Tsunami’ of structured and unstructured data, and to automate iterative operations that previously required manual processing.

Given these trends, here are four (4) predictions for analytics and artificial intelligence (AI) in healthcare for consideration by CXOs to inform their analytics and AI innovation blueprints and roadmaps in 2022-23.  

1.   The convergence between Analytics and Artificial Intelligence (AI) is accelerating in Healthcare

In a 2020 HIMSS research report [Ref 1] cited in my previous blogpost, 53% of AI platforms, tools, investments and resources are applied to clinical use cases, while 47% are applied to the back-office ones. The top areas for immediate implementation in the clinical arena are identifying at-risk patients, predicting patient utilization, and risk scoring for chronic diseases.

Additional areas of investment identified were as below:

• Blending data from multiple EMRs, standardize curated data sets to secure a ‘single version of the truth’ re: the patient
• Minimizing issues with reimbursement and payments including fraud, waste, abuse and denials e.g. proactively predicting denials and addressing root causes before they happen.
• Enabling a 360-degree view of the patient for clinicians and nurses at the patient bedside
• Advancing Precision Medicine and personalized treatment of patients, leveraging genomic data sets
• Improving supply chain management (SCM) efficiencies, including predicting stock outs and expired drugs
• Proactively identifying and mitigating cybersecurity risks, including medical fraud
• Identifying and classifying anomalies and imaging and incidental findings
• Proactively detecting fraud, waste and abuse pertaining to employee overtime and agency costs

2. Healthcare Providers need Analytics solutions that deliver granular insights which their EHRs do not deliver.

Healthcare providers have made $ BNs in investments in deploying their electronic health records (EHRs) which have delivered significant value (moving clinical records and data from paper to electronic) and ROI on their investments. However, most EMR platforms have not delivered on their promise of delivering granular analytics needed for executive decision making in areas like revenue cycle management (RCM), supply chain management (SCM), value-based care and population health management. (PHM). This has led to the proliferation of visual analytics and ETL platforms like Tableau, Power BI and Alteryx, as well as robust analytics solutions like MedeAnalytics which integrate with and ingest data from these EHRs to address the granular analytics needs of healthcare payers and providers for these processes.

Real-World Success Story: Wise Health System

Wise Health System, a network of hospitals and clinics based in Decatur, Texas, enabled a holistic approach to revenue cycle management (RCM) and bridged both clinical and financial processes and outcomes with MedeAnalytics, and their AllScripts Sunrise EMR.

With the portfolio of RCM solutions, Wise Health System saw unspecified code usage drop by 19%, improved their appeal success rates by 36.6%, their Case Mix Index (CMI) by 34.7% and their CC/MCC capture rates by 129.2%.

They also bridged their financial and clinical processes to improve their congestive heart failure and diabetes-related admissions. They saw 83.3% reduction in readmission rates for congestive heart failures and a decrease of 24.2% in average A1C for prediabetic and diabetic patients on a year-over-year (YoY) basis, with an 11% improvement in Patient Satisfaction. Further, they also reduced their Emergency Department (ED) Utilization by 11% as well as a 5% drop in re-admissions for their highest risk (top 5%) patients.

Please read the entire case study here.

3. Given loss of Elective Revenues from the pandemic, Analytics and AI to accelerate A/R, reduce denials and drive-up RCM staff productivity is becoming an imperative.

Loss of Elective Revenues has impacted provider revenues 10-30% and has reduced net margins below 2% in the wake of the Pandemic, jeopardizing financial stability in the wake of the Pandemic!

Given loss of elective revenues from the pandemic, RCM executives are challenges by their lack of visibility into A/R aging, denials, cost-to-collect, as well as RCM staff productivity, loss of revenues due to increasing self-pay accounts, revenue leakage in the mid-revenue cycle even with CDI programs, healthcare organizations need RCM analytics solutions that deliver this level of granularity not offered by their EHRs.

MedeAnalytics helps healthcare providers improve revenue realization by enabling actionable insights into their revenue cycle operations, enhancing employee productivity, and improving quality and outcomes.

Leveraging root cause analysis, trending, anomaly detection and predictive capabilities, organizations gain immediate visibility into revenue cycle opportunities so they can take corrective action to positively impact revenue. Providers assess documentation and coding performance in the mid-cycle to optimize claims reimbursement. RCM organizations have a consolidated view into accounts receivable, denials, bad debt and payer performance to improve cash flow and collections.

Healthcare providers using RCM Analytics solutions like MedeAnalytics with their EHRs have improved revenue realization in terms of reduced A/R days by 25%, reduced denials by 30%, enhanced staff productivity by 34% and increased CC/MCC capture by 31%.

Real-World Success Stories: Nebraska Methodist Health System

Nebraska Methodist Health System, a not-for-profit health system with 4 hospitals, adopted MedeAnalytics with Cerner to address its challenges (Re: increasing A/R and denials and little visibillity into its RCM staff productivity).

With the MedeAnalytics RCM solution, Nebraska Methodist Health System saw an 11% reduction in denials from 2016-19 resulting in a gross revenue equivalent of $12.9M in 2019. 

Please read the entire case study here.

 4.  Value based care and population health management is driving the need for greater transparency and shared analytics and insights between Providers and Payers.

COVID-19 has disproportionately impacted the economically dis-advantaged who have not only been debilitated by the Pandemic, but have also lost their livelihood, homes and family members and relatives. The key challenge confronting both Healthcare Providers and Payers is to figure out how they can deploy advanced analytics to segment their (providers) attributed patient population, risk stratify them to proactively identify the most vulnerable at-risk and rising risk patients to assure the best possible outcomes, leveraging not only clinical data but also social determinants of health data etc.

Healthcare organizations need a robust analytics solution that will enable users to understand patient medical and pharmacy compliance, analyze population health data by stratifying high-risk patients, assess the impact of social determinants of health for care management opportunities, and examine risk of patients with long-term conditions over time. 

Solutions from vendors like MedeAnalytics enables Healthcare Payers and Providers to aggregate disparate sources of data including SDOH to stratify patients based on risk, and deliver appropriate treatment protocols and services to ensure the best possible care at the lowest cost, assuring superior patient outcomes. This enables payers and providers lower treatment costs, increase revenue and improve the identification of at-risk members, culminating in measurable value as exemplified by Concerto Care below.

Real-World Success Story: Concerto Care

ConcertoCare, a risk-bearing Health Plan for Medicare and Medicaid Patients, leveraged predictive analytics to stratify their patient population based on risk (age, sex, co-morbidities) and assess their cost and utilization patterns to proactively address the needs of their most at-risk and rising-risk patients.

ConcertoCare lowered ER visits by 16%, admissions by 47%, and re-admissions by 40% for their patient population, below national averages with their Population Health Analytics solution.

Please read the entire case study here.

In Conclusion

As we emerge from the ravages of the COVID-19 Pandemic, 2022 presents enormous opportunities for healthcare organizations given the “renaissance in healthcare’ underway, thanks to the digital transformation in healthcare triggered by innovation in tele-health, remote patient monitoring, robotics, artificial intelligence (AI) and analytics. All these technologies offer tremendous promise in terms of higher quality of care delivery at a lower cost with superior patient outcomes for healthcare organizations.

I hope that the trends and the four (4) predictions for analytics and AI (which are by no means exhaustive) instantiated with real-world case studies articulating measurable value will inform the analytics and AI innovation blueprints and roadmaps of healthcare innovation leaders in 2022-23.

As always, I welcome your comments and feedback here on this blogpost, and on Twitter at @HITstrategy. 

Disclaimer: The perspective and views expressed in this Blog post are my own and do not represent those of my current or previous employers.

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