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Interoperability: Is Your Aging Healthcare Integration Engine the Problem?

Posted on September 18, 2017 I Written By

The following is a guest blog post by Gary Palgon, VP Healthcare and Life Sciences Solutions at Liaison Technologies.
There is no shortage of data collected by healthcare organizations that can be used to improve clinical as well as business decisions. Announcements of new technology that collects patient information, clinical outcome data and operational metrics that will make a physician or hospital provide better, more cost-effective care bombard us on a regular basis.

The problem today is not the amount of data available to help us make better decisions; the problem is the inaccessibility of the data. When different users – physicians, allied health professionals, administrators and financial managers – turn to data for decision support, they find themselves limited to their own silos of information. The inability to access and share data across different disciplines within the healthcare organization prevents the user from making a decision based on a holistic view of the patient or operational process.

In a recent article, Alan Portela points out that precision medicine, which requires “the ability to collect real-time data from medical devices at the moment of care,” cannot happen easily without interoperability – the ability to access data across disparate systems and applications. He also points out that interoperability does not exist yet in healthcare.

Why are healthcare IT departments struggling to achieve interoperability?

Although new and improved applications are adopted on a regular basis, healthcare organizations are just now realizing that their integration middleware is no longer able to handle new types of data such as social media, the volume of data and the increasing number of methods to connect on a real-time basis. Their integration platforms also cannot handle the exchange of information from disparate data systems and applications beyond the four walls of hospitals. In fact, hospitals of 500 beds or more average 25 unique data sources with six electronic medical records systems in use. Those numbers will only move up over time, not down.

Integration engines in place throughout healthcare today were designed well before the explosion of the data-collection tools and digital information that exist today. Although updates and additions to integration platforms have enabled some interoperability, the need for complete interoperability is creating a movement to replace integration middleware with cloud-based managed services.

A study by the Aberdeen Group reveals that 76 percent of organizations will be replacing their integration middleware, and 70 percent of those organizations will adopt cloud-based integration solutions in the next three years.

The report also points out that as healthcare organizations move from an on-premises solution to a cloud-based platform, business leaders see migration to the cloud and managed services as a way to better manage operational expenses on a monthly basis versus large, up-front capital investments. An additional benefit is better use of in-house IT staff members who are tasked with mission critical, day-to-day responsibilities and may not be able to focus on continuous improvements to the platform to ensure its ability to handle future needs.

Healthcare has come a long way in the adoption of technology that can collect essential information and put it in the hands of clinical and operational decision makers. Taking that next step to effective, meaningful interoperability is critical.

As a leading provider of healthcare interoperability solutions, Liaison is a proud sponsor of Healthcare Scene. It is only through discussions and information-sharing among Health IT professionals that healthcare will achieve the organizational support for the steps required for interoperability.

Join John Lynn and Liaison for an insightful webinar on October 5, titled: The Future of Interoperability & Integration in Healthcare: How can your organization prepare?

About Gary Palgon
Gary Palgon is vice president of healthcare and life sciences solutions at Liaison Technologies. In this role, Gary leverages more than two decades of product management, sales, and marketing experience to develop and expand Liaison’s data-inspired solutions for the healthcare and life sciences verticals. Gary’s unique blend of expertise bridges the gap between the technical and business aspects of healthcare, data security, and electronic commerce. As a respected thought leader in the healthcare IT industry, Gary has had numerous articles published, is a frequent speaker at conferences, and often serves as a knowledgeable resource for analysts and journalists. Gary holds a Bachelor of Science degree in Computer and Information Sciences from the University of Florida.

ROI in the Business Office: Why HIM Should Keep a Watchful Eye – HIM Scene

Posted on August 16, 2017 I Written By

The following is a HIM Scene guest blog post by Lula Jensen, MBA, RHIA, CCS, Director of Product Management at MRO.  This is the second blog in a three-part sponsored blog post series focused on the relationship between HIM departments and third-party payers. Each month, a different MRO expert will share insights on how to reduce payer-provider abrasion, protect information privacy and streamline the medical record release process during health plan or third-party commercial payer audits and reviews.

According to most business office staff, pulling information and releasing medical record documentation to payers is a necessary evil to get claims paid and reduce accounts receivables. It is not their core competency.

Whether the request is unsolicited or solicited by the payer, time required to compile information and respond wreaks havoc on business office productivity. Also in efforts to meet payer deadlines and expedite claims, human mistakes can be made. Incorrect patient information might slip through the cracks.

Despite concerns, many business office directors prefer that payer disclosures be sent out by their own business staff—versus by the HIM department. If your organization follows that practice, this HIM Scene blog post is for you.

Two Types of Business Office Requests

There are two instances of business office Release of Information (ROI) to know: unsolicited and solicited requests. The unsolicited process takes place when medical documentation containing all the additional information pertinent to the service being billed is submitted proactively by the provider with the initial claim. The solicited process occurs when the original claim is sent without additional supporting medical record documentation and the payer subsequently (during the adjudication process) determines that additional information is needed. The payer then places a request for the additional documentation from the provider.

Unsolicited Releases During Claims Processing

The purpose of releasing information during claims processing is to expedite payment. In an effort to get the claim paid faster, medical records are sent proactively with the claim. This is especially true for high-dollar claims, payer policies, readmissions within 30 days and the published Office of Inspector General (OIG) Work Plan.

Sounds like a good intention with the organization’s best financial interests in mind. However, three concerns arise when business offices send medical record documentation to payers—versus having HIM professionals take charge.

  1. Business office staff may not know which parts of the medical record will be required to support the claim. Often, the entire chart is sent—a process that is not practical for high-dollar or long-length-of-stay cases.
  2. Sending the entire record is also not compliant with HIPAA’s Minimum Necessary Standard. By sending too much information, hospitals are at risk for HIPAA breach.
  3. Upon receipt of prepay documentation, the payer’s staff logs each record received, scans or otherwise digitizes the documents, and incorporates them into their own electronic systems. This creates a huge administrative burden on payers.

Similar challenges ensue with solicited payer medical record requests that occur during the adjudication process or retrospective reviews.

Business Office Disclosures for Payer Audits and Reviews

There has been significant uptick in payer audits and reviews, a topic that was covered by HIM Scene last month. This includes governmental and third-party commercial. According to one central business office director at an MRO client site, “The pull lists for payer audits and reviews keep getting longer and the piles of medical records to send keep getting higher.”

To reduce administrative burdens with payers, some organizations are allowing payers direct access to their EMRs and EHRs to obtain the required information during audits and reviews. While this process may lighten the load for billing personnel, it is laden with additional privacy risks.

Business office personnel complain about the travails of responding to all the various requests for records. However, a significant number of business office directors still insist on owning the ROI process for payer audits and reviews. When this is the case, there are several important steps for HIM directors to consider.

Three Steps for HIM: Educate, Track and Talk

For both types of business office disclosures, it is important to educate billing staff about the implications of a HIPAA breach and privacy risks listed above. Establish an organization-wide standard for ROI to keep PHI safe during all types of business office disclosures. Educating all personnel involved in business office ROI (whether for claims processing, audits or reviews) helps relieve frustration with the record release process.

Billers should also track which specific records, and what sections of each, were sent. By documenting and then reviewing this information, organizations gain valuable knowledge about payer trends—insights that can be used to prevent denials and negotiate more favorable terms for payer contracts.

Collaborate with privacy and the business office to determine which release information to track. Then establish a common database or software application to document each release to payers. Here are four ways to make the most of business office ROI tracking data:

  • Look for patterns in what payers are requesting. Any trends in payer request activity could offer opportunities for provider improvement.
  • Identify risk. Analytics can help business offices detect weaknesses in the revenue cycle, involving coding, documentation or other internal processes.
  • Educate coders, biller, collectors, physicians, etc. on payer trends and how collaboration can promote accurate, complete billing for services rendered and support a claim via medical record documentation.
  • Use data analysis. When payer contract negotiations arise, use payer trend statistics to your advantage in the next round of negotiations.

Talk with local payers and stay updated on policy changes related to claims processing, audits and retrospective reviews. Open communication with each payer is recommended to ensure records are sent in the most secure way possible. Communication with payers also reduces phone tag and minimizes payer-provider abrasion.

Finally, due to the importance of collecting medical record documentation, health plans are willing to pay for records. Business offices and HIM departments fulfilling these requests are encouraged to discuss and pursue reimbursement from payers.

About Lula Jensen

In her role as Director of Product Management for MRO, Jensen drives product enhancements and new product initiatives to ensure MRO’s suite of solutions enable the highest levels of client success and end-user satisfaction. She has more than 15 years of experience in healthcare, focusing on Health Information Management (HIM), Revenue Cycle Management, analytics, software development and consulting. In addition to holding product management roles at McKesson Health Solutions and CIOX Health, she also served as Revenue Cycle Manager at Fox Chase Cancer Center and taught a course on ICD-9 CM Coding and Reimbursement at Bucks County Community College. Jensen is an active member of the Healthcare Financial Management Association (HFMA), American Health Information Management Association (AHIMA) and Pennsylvania Health Information Management Association (PHIMA); she is a 2005 PHIMA Scholar Award recipient. Jensen holds a B.S. in HIM from Temple University and an M.B.A. in Health Care Administration from Holy Family University.

If you’d like to receive future HIM posts in your inbox, you can subscribe to future HIM Scene posts here.

Achieve MU3: Measure 3 with these 5 MEDITECH Clinical Decision Support Interventions (CDSi)

Posted on August 11, 2017 I Written By

The following is a guest blog post by Kelly Del Gaudio, Principal Consultant at Galen Healthcare Solutions.

Over the past several years, there has been significant investment and effort to attest to the various stages of meaningful use, with the goal of achieving better clinical outcomes. One area of MU3 that directly contributes to improved clinical outcomes is implementation of Clinical Decision Support Interventions (CDSi). Medicaid hospitals must implement 5 CDSi and enable drug-drug and/or drug-allergy checking.

From looking at this measure it seems like a walk in the park, but how does your organization fair when it comes to CDS?

Thanks to First Databank, users of EMR’s have been accomplishing drug to drug and drug to allergy checking for over a decade, but what about the edge cases you think will be covered but aren’t? Take a patient that is allergic to contrast for example. Since imaging studies requiring contrast are not drugs, what happens when they are ordered? Are they checking for allergies? In most cases, additional configuration is required to get that flag to pop. This is usually where we come in.

Let’s take a look at a simple CDSi definition provided by CMS.gov

“CDS intervention interaction. Interventions provided to a user must occur when a user is interacting with technology. These interventions should be based on the following data:  Problem list; Medication list; Medication allergy list; Laboratory tests; and Vital signs. “

Without a decent rule writer on staff, there are limitations within MEDITECH for accomplishing full CDSi. The primary reason we started recording these discrete data elements in the first place is the glimmer of hope that they would someday prove themselves useful. That day is here, friends. (If you don’t believe me, check out IBM’s Watson diagnosing cancer on YouTube. . .you might want to block off your schedule.)

In collaboration with 9 hospitals as part of a MEDITECH Rules focus group – Project Claire[IT] – we researched and designed intuitive tools to address Clinical Quality Measures (eCQM’s) and incorporated them into a content package. If your organization is struggling to meet these measures or you are interested in improving the patient and provider experience, but don’t have the resources to dedicate to months of research and development, Project Claire[IT]’s accelerated deployment schedule (less than 1 month) can help you meet that mark. Below are just some examples of the eCQM’s and CDS delivered by Project Claire[IT].

CMS131v5     Diabetes Eye Exam
CMS123v5     Diabetes: Foot Exam
CMS22v5       Screening for High Blood Pressure and Follow-Up Documented

Synopsis: The chronic disease management template will only display questions relevant to the Problem List (or other documented confirmed problems since we know not everyone uses the problem list). Popup suggestions trigger orders reminding the provider to complete these chronic condition follow-up items before letting the patient out of their sights. Our goal was to save providers time by ordering all orders in 1 click.

CMS71v7     Anticoagulation Therapy for Atrial Fibrillation/Flutter
CMS102v6   Assessed for Rehabilitation

“The Framingham Heart Study noted a dramatic increase in stroke risk associated with atrial fibrillation with advancing age, from 1.5% for those 50 to 59 years of age to 23.5% for those 80 to 89 years of age. Furthermore, a prior stroke or transient ischemic attack (TIA) are among a limited number of predictors of high stroke risk within the population of patients with atrial fibrillation. Therefore, much emphasis has been placed on identifying methods for preventing recurrent ischemic stroke as well as preventing first stroke. Prevention strategies focus on the modifiable risk factors such as hypertension, smoking, and atrial fibrillation.” – CMS71v7

The above quote is taken directly from this measure indicating the use of the Framingham Heart Study we used to identify and risk stratify stroke. Claire[IT] content comes complete with three Framingham Scoring tools:

                Framingham Risk for Stroke
                Framingham Risk for Cardiovascular Disease
                Framingham Risk for Heart Attack

These calculators use all the aforementioned data elements to drive the score, interpretation and recommendations and the best part is they only require one click.

*User adds BP. BP mean auto calculates. Diabetes and Smoking Status update from the Problem List. Total Cholesterol and HDL update from last lab values.
Ten year and comparative risk by age auto calculates.

*User adds BP. BP mean auto calculates. Diabetes, Smoking Status, CVD, Afib and LVH update from the Problem List. On Hypertension meds looks to Ambulatory Orders.
Ten year risk auto calculates.

*User adds BP. BP mean auto calculates. Diabetes and Smoking Status update from the Problem List. Hypertension meds looks to Ambulatory Orders. Total Cholesterol and HDL update from lab values.
Ten year risk auto calculates.

CMS149v5      Dementia: Cognitive Assessment

Synopsis: Not only is this tool built specifically as a conversational assessment, it screens for 4 tiers of mental status within one tool (Mental Status, Education, Cognitive Function and Dementia). The utilization of popup messages allows us to overcome the barrier of character limits and makes for a really smooth display on a tablet or hybrid. Our popups are driven by the primary language field in registration and our content currently consists of English and Spanish translations.

CMS108v6     VTE Prophylaxis
CMS190v6     VTE Prophylaxis is the ICU

Synopsis: Patients that have an acute or suspected VTE problem with no orders placed for coumadin (acute/ambulatory or both) receive clinical decision support flags. Clicking the acknowledge tracks the user mnemonic and date/time stamp in an audit trail. Hard stops are also in place if NONE is chosen as a contraindication. The discharge order cannot be filed unless coumadin is ordered or a contraindication is defined. These rules evaluate the problem list and compare it to the medication list to present the provider with the right message.

Learn more about the work of our focus group and Project Claire[IT] by viewing our MEDITECH Clinical Optimization Toolkit.

VIEW THE TOOLKIT TO ACCESS:

  • Deliverable Package of Complex Rules, Assessments, CDS’s and Workflows
    • Problem List Evaluation
    • Total Parenteral Nutrition
    • Manage Transfer Guidance
  • Surveillance Dashboard Setup Guide
    • Dictionary Setup & Validation
  • 6.x Rules Setup Guide
    • Basic Rules for Assessments, Documents & Orders
  • IV Charge Capture Setup Guide

About Kelly Del Gaudio
Kelly is Principal Consultant at Galen Healthcare Solutions, and has been optimizing MEDITECH systems for over 10 years. She worked for MEDITECH on an elite 4-person team (the MEDITECH SWAT Team), whose sole concentration was clinical optimization, ROI analysis, MU certification, and achievement of HIMSS EMRAM Stage 6/7. Kelly currently leads Galen’s MEDITECH practice, and championed a focus group, which led to the delivery of Project Claire[IT], a MEDITECH content package of complex rules, assessments, CDS’s, and workflows that evaluate, suggest, and support documentation of chronic and acute problems. Learn more about Kelly in the #IAmGalen series.

About Galen Healthcare Solutions

Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the EMR Clinical Optimization Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

EMR Clinical Optimization CIO Perspectives – EMR Clinical Optimization Series

Posted on July 26, 2017 I Written By

The following is a guest blog post by Julie Champagne, Strategist at Galen Healthcare Solutions.

Most HDOs today face a decision: start over with a new EMR or optimize what you have. A poorly executed implementation, coupled with substandard vendor support, makes EMR replacement an attractive and necessary measure. Further, the increase in mergers and acquisitions is driving system consolidation and consequently increasing the number of HDOs seeking EMR replacement to address usability and productivity concerns.

Galen Healthcare Solutions spoke with two prominent health information technology leaders, who have quite a bit of experience in the optimization field to hear their views on the topic. Sue Schade, MBA, LCHIME, FCHIME, FHIMSS, is a nationally recognized health IT leader and Principal at StarBridge Advisors, providing consulting, coaching and interim management services. Jim Boyle, MPH, CGEIT is Vice President of Information Services of St. Joseph Heritage Healthcare (Anaheim, Calif.). In his current role, Jim oversees the delivery of applications and technology and is a member of the executive leadership team. Below are their perspectives

Opportunities for EMR optimization generally fall into three categories:

  • Usability & efficiency: Improve end-user satisfaction and make providers more efficient and productive
  • Cost Avoidance: Improve workflows to increase utilization and decrease variability
  • Increase Revenue: Implement analytics to transition from volume to value


Recently, three prominent Boston-area physicians contributed an opinion piece to WBUR, “Death By A Thousand Clicks”. They postured that when doctors and nurses turn their backs on patients in order to pay attention to a computer screen, it pulls their focus from the “time and undivided attention” required to provide the right care. Multiple prompts and clicks in an EMR system impact patients and contribute to physician burnout.

HDOs should then limit their intake to what can be accomplished within one quarter, referred to as a sprint. Accountability should be assigned, and visual controls or Kanban should be leveraged.


 
For HDOs that experienced failed EMR implementations, making corrections and reengineering is a necessary first measure. Typically, a deficiency in the additional support for the system implementation is to blame, and employing qualified application support staff will help to address and resolve end user dissatisfaction.
 
 
 
To realize lasting impact from the EMR, extensive post go-live enhancement and optimization is needed. Leveraging the operational data in the EMR system can support many initiatives to improve workflows, as well as clinical and financial performance. Prioritization of the levers that can be adjusted depends on the HDO’s implementation baseline and strategic goals.

 
The most important deciding success factor for an optimization project is focusing effort and ensuring the scope is not too large. Further, it is of critical importance to set measurable and attainable metrics and KPIs to gauge the success and ROI of the initiative. Quantification of staff effort and IT investment is also important.

Gain perspectives from HDO leaders who have successfully navigated EMR clinical optimization and refine your EMR strategy to transform it from a short-term clinical documentation data repository to a long-term asset by downloading our EMR Optimization Whitepaper.

About Sue Schade
Sue Schade, MBA, LCHIME, FCHIME, FHIMSS, is a nationally recognized health IT leader and Principal at StarBridge Advisors providing consulting, coaching and interim management services. Sue is currently serving as the interim Chief Information Offi cer (CIO) at Stony Brook Medicine in New York. She was a founding advisor at Next Wave Health Advisors and in 2016 served as the interim CIO at University Hospitals in Cleveland, Ohio. Sue previously served as the CIO for the University of Michigan Hospitals and Health Centers and prior to that as CIO for Brigham and Women’s Hospital in Boston. Previous experience includes leadership roles at Advocate Health Care in Chicago, Ernst and Young, and a software/outsourcing vendor. Sue can be found on Twitter at @sgschade and writes a weekly blog called “Health IT Connect” – http://sueschade.com/

About Jim Boyle
Jim Boyle, MPH, CGEIT is a Vice President of Information Services of St. Joseph Heritage Healthcare (Anaheim, Calif.). Jim Boyle is nationally recognized as part of a new generation of health care informatics professionals who understand IT’s full potential to greatly improve peoples’ lives. In his current role Jim oversees the delivery of applications and technology and is a member of the executive leadership team for St. Joseph Heritage Healthcare, which comprises over 860 medical group providers and 1300 affiliated physicians across California. Since joining St. Joseph Health 12 years ago, he has held eight different positions, including project manager, application analyst and IT director at Fullerton, Calif.-based St. Jude Medical Center. Jim can be found on Twitter at @JBHealthIT and LinkedIn.

About Galen Healthcare Solutions
Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the EMR Clinical Optimization Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

 

Finding Civility in Payer Relationships: Audits, Reviews and HIM – HIM Scene

Posted on July 19, 2017 I Written By

The following is a HIM Scene guest blog post by Greg Ford, Director, Requester Relations and Receivables Administration at MRO.  This is the first blog in a three-part sponsored blog post series focused on the relationship between HIM departments and third-party payers. Each month, a different MRO expert will share insights on how to reduce payer-provider abrasion, protect information privacy and streamline the medical record release process during health plan or third-party commercial payer audits and reviews.

Civility is defined by Webster’s as courtesy and politeness. It is a mannerly act or expression between two parties. While civility in politics has waned, it appears to be on the rise in healthcare.

New opportunities for civility between payers and providers have emerged with the shift from fee-for-service to value-based reimbursement. Population health, quality payment programs and other alternative payment models (APMs) are opening the door to better collaboration and communications with payers. Optimal patient care is a mutual goal between payers and providers.

HIM professionals can also contribute to stronger payer-provider relationships. Our best opportunity to build civility with health plans and payers is during audits and reviews. HIM professionals who take the time to understand the differences will make notable strides toward a more polite and respectful healthcare experience.

Payer Audits vs. Payer Reviews: What’s the Difference?

It’s no secret to most HIM professionals that the volume of health plan medical record requests continues to increase significantly. In fact, between 2013 and 2016 the number of requests for HEDIS and Risk Adjustment reviews increased from one percent to 11 percent of the total Release of Information requests received by MRO.

The main difference between audits and reviews is the potential negative financial impact to providers. Payer audits include risk for revenue recoupment while payer reviews do not.

For example, audits conducted by third-party payers are intended to recoup funds on overpaid claims. The most common reason for a post-payment payer audit is to confirm correct coding and sequencing as billed on the claim to determine if payment was made to the provider correctly. In audits, the health plan’s intention is to recoup funds on overpaid claims.

Payer reviews do not carry financial risk to the provider. Instead, payer reviews deliver valuable insights providers can use to improve their relationships with health plans and patient populations.

The Upside of Payer Reviews

HEDIS and Risk Adjustment reviews are the most common types of payer reviews. Payer data submissions for HEDIS are due to the National Committee for Quality Assurance (NCQA) by June of every year. Medicare Risk Adjustment results are due in January and Commercial in May.

Since these payer reviews both overlap and occur simultaneously, HIM departments are deluged with medical record requests. Understanding the importance of these reviews improves communication between HIM, Release of Information staff and health plan requesters.

HEDIS Reviews

HEDIS reviews can benefit providers during contract negotiations because the HEDIS performance rankings can be used to gauge the quality and effectiveness of different health plans for potential participation with the facility.

Risk Adjustment Reviews

With these reviews, health plans are required to prove the needs of the population to CMS so they can continue to provide services for higher risk patients and pay providers for the care of this population.

In both cases, medical records are needed to provide the analysis, so HIM is involved.

HIM’s Role: Reimbursable Release of Information

In 2015, 85 percent of MRO’s audit and review requests came from third-party vendors representing health plans. Both post-payment audit and review requests are typically chargeable to the requesting party. Due to the importance of collecting medical record documentation, health plans and payers are willing to pay for records.

HIM professionals are encouraged to pursue reimbursement for payer requests. This is especially true if your HIM department is working diligently to accommodate the payer deadline for record receipt.

A provider’s Release of Information staff should be able to work directly with these requesters to ensure payment for the timely delivery of records. HIM professionals can reduce payer-provider abrasion and ultimately strengthen relationships to improve compliance. It’s the first step to increasing civility in healthcare.

Watch for our August HIM Scene post to learn more about how to secure patient privacy when sending records to payers and health plans.

About Greg Ford
In his role as Director of Requester Relations and Receivables Administration for MRO, Ford serves as a liaison between MRO’s healthcare provider clients and payers requesting large volumes of medical records for purposes of post-payment audits, as well as HEDIS and risk adjustment reviews. He oversees payer audit and review projects end-to-end, from educating and supporting clients on proper billing practices and procedural obligations, to streamlining processes that ensure timely delivery of medical documentation to the requesting payers. Prior to joining MRO, Ford worked as Director of Operations and Sales at ARC Document Solutions for 15 years. He received his B.A. from Delaware Valley University.

If you’d like to receive future HIM posts in your inbox, you can subscribe to future HIM Scene posts here.

EMR Clinical Optimization Infographic – EMR Clinical Optimization Series

Posted on July 12, 2017 I Written By

The following is a guest blog post by Justin Campbell, Vice President, Strategy, at Galen Healthcare Solutions.


(See Full EMR Optimization Infographic)

In this infographic, Galen Healthcare Solutions provides critical information and statistics pertaining to EMR optimization including:

  • EMR Market Maturation
  • EMR Capital Investment Priorities
  • EMR as a Valuable Asset vs Required Repository
  • Clinical Optimization Goals & Benefits
  • Types of Clinical Optimization
  • Clinical Optimization Effort & ROI Matrix

EMR products get widely varying reviews. There is strong support and appreciation for EMRs in some HDOs, where the sentiment exists that the EMR is well-designed, saves time, and supports clinical workflows. That said, in other HDOs, providers using the same EMR complain that EMRs add work, decrease face time with patients and create usability issues and slowdowns. Multiple prompts and clicks in an EMR system impact patients and contribute to physician burnout. The resounding sentiment for these set of providers is that the EMRs are not designed for the way they think and work. Why then the varying response among providers to the same EMR products? Deficient implementations.

Under the pressure of moving ahead to meet the requirements of the Meaningful Use program, most EMRs were implemented using a Big Bang approach, and very rapidly. While this approach may have been the most effective to capture incentives, generic, rapid EMR implementation led to several unintended consequences, resulting in widespread user dissatisfaction. EMRs today serve more as a transactional system of record than a system of engagement. To be used to their full capacity, the different components and modules of the EMR should be evaluated against baseline metrics to harness additional capabilities including clinical decision support, analytics at the point of care, and efficiency of workflow. To realize lasting impact from the EMR, extensive post go-live enhancement and optimization is needed. Leveraging the operational data in the EMR system can support many initiatives to improve workflows, as well as clinical and financial performance. Prioritization of the levers that can be adjusted depends on the HDO’s implementation baseline and strategic goals.


(Click to see larger version of graphic)

A robust EMR optimization strategy can help HDOs realize the promised value from implementation of an EMR. EMR optimization is the driver of strategic value, and can become a sustainable competitive advantage through leadership, innovation and measurement. Success requires a disciplined, data-driven, outcomes-based approach to meet a defined set of objectives.

Gain perspectives from HDO leaders who have successfully navigated EMR clinical optimization and refine your EMR strategy to transform it from a short-term clinical documentation data repository to a long-term asset by downloading our EMR Optimization Whitepaper.

About Justin Campbell
Justin is Vice President, Strategy, at Galen Healthcare Solutions. He is responsible for market intelligence, segmentation, business and market development and competitive strategy. Justin has been consulting in Health IT for over 10 years, guiding clients in the implementation, integration and optimization of clinical systems. He has been on the front lines of system replacement and data migration, and is passionate about advancing interoperability in healthcare and harnessing analytical insights to realize improvements in patient care. Justin can be found on Twitter at @TJustinCampbell and LinkedIn.

About Galen Healthcare Solutions
Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the EMR Clinical Optimization Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

Deriving ROI from Data-driven EMR Clinical Optimization

Posted on June 28, 2017 I Written By

The following is a guest blog post by Justin Campbell Vice President, Strategy, at Galen Healthcare Solutions.  Learn more about their work by downloading their EHR Clinical Optimization Whitepaper.

Resistance to change is natural. People are uncomfortable with it. Organizations are frightened by it. Acceptance of healthcare information technology took a long time and even in these first two decades of a new century, despite incentives such as the Meaningful Use program, and promises of increased efficiency, implementation of Electronic Medical Records has been a bumpy ride.

Between 2008 and 2016, healthcare organizations spent more than 20 billion dollars adopting electronic health record systems. Many different approaches were applied. Many HCOs decided to act quickly, using what we now call a “Big Bang” fix. Installations of generic systems were in place but users of the new systems were unhappy. In 2013, with the process well underway throughout the nation, two thirds of doctors polled said they used EMR systems unwillingly, with 87% of these aggravated physicians complaining about usability and 92% of physician practices complaining that their EMRs were “clunky” and/or too difficult. Specifically, only 35% reported that it had become easier to respond to patient issues, one third said they could not more effectively manage patient treatment plans, and despite the belief that technology would permit caregivers to spend more time with their patients, only 10% said this was occurring.

The medical side was not alone in expressing dissatisfaction. Hospital executive and IT employees who had replaced their Electronic Health Record systems reported higher than expected costs, layoffs, declining revenues, disenfranchised clinicians and serious misgivings about the benefits gained:

  • 14% of all hospitals that replaced their original EMR since 2011 were losing inpatient revenue at a pace that would not support the total cost of their replacement EMR
  • 87% of hospitals facing financial challenges now regret the decision to change systems
  • 63% of executive-level respondents admitted they feared losing their jobs as a result of the EMR replacement process
  • 66% of the system users believe that interoperability and patient data exchange functionality have declined.


Not all reviews are negative. There is strong support and appreciation for EMRs in some Healthcare Delivery Organizations (HDOs) who believe well-designed EMRs save time and support clinical workflows. But, there is no escaping the majority sentiment: EMRs are not designed for the way providers think and work.

Today, most HDOs are at a crossroads. They can start over with a new EMR or optimize the one they have. The case for a do-over is supported by sub-standard vendor support for their existing systems and the increase in mergers and acquisitions, which drive system consolidation. One fifth of large practices and clinics report they intend to replace their EMRs and studies show that the EMR replacement markets will likely grow at an annual rate of 7%-8% over the next five years. The case for the status quo is made primarily by the HCOs that do not have the financial resources to undertake EMR replacement.

All options face the same key inter-related questions: how to generate additional margin? How to maximize return on technology investments? Which path will best serve the HCO, caregivers and patients?

This is a bit of vicious circle. HCOs are cash-strapped and the transition from fee for service to value-based care exerts downward cost pressures, exacerbating the problem. But patchwork fixes have not resolved that problem. Alternatively, some attempted to do too much too quickly and became frustrated because they lacked the depth of experience and knowledge to perform remediation. And, as KPMG concluded after studying the problem, “The length of time to resolve the issues increased and frustrations mounted as clinical, senior management, IT and human resources staff found themselves spinning their wheels.”

Like a patient being pressured to swallow medicine, HDOs are beginning to accept their situation. According to a recent survey conducted by KPMG in collaboration with CHIME, 38% of 112 respondents ranked EMR/EMR optimization as their top choice for the majority of their capital investments for the next three years.

EMR adoption is already approaching maximum levels. Consequently, healthcare delivery organizations have begun to shift their EMR strategies from short-term clinical documentation data repositories to long-term assets with substantial functionality in support of clinical decisions, health maintenance planning and quality reporting. They are coming to see their IT investments as platforms rather than limited systems of record or glorified data banks. In short, they now understand that the capture of information is only the most basic attribute of an EMR, and that instead, the EMR in which they invest can be flexible and extensible, capable of adopting emerging technologies that are driving insights to the point of care.

Assess opportunity, formulate strategy, improve usability & derive additional ROI & by downloading our EHR Clinical Optimization Whitepaper.

About Justin Campbell
Justin is Vice President, Strategy, at Galen Healthcare Solutions. He is responsible for market intelligence, segmentation, business and market development and competitive strategy. Justin has been consulting in Health IT for over 10 years, guiding clients in the implementation, integration and optimization of clinical systems. He has been on the front lines of system replacement and data migration and is passionate about advancing interoperability in healthcare and harnessing analytical insights to realize improvements in patient care. Justin can be found on Twitter at @TJustinCampbell and LinkedIn.

About Galen Healthcare Solutions

Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the Tackling EHR & EMR Transition Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

Promoting Internal Innovation to Drive Healthcare Efficiency

Posted on June 1, 2017 I Written By

The following is a guest blog post by Peyman S. Zand, Partner, Pivot Point Consulting, a Vaco Company.

Technical innovation in healthcare has historically been viewed through the lens of disruption. As tech adoption in the industry matures, perceptions on the origin of innovation are evolving as well. Healthcare leadership teams are increasingly leaning on feedback from the front lines of care delivery to identify ways to eliminate waste and drive greater efficiency. Rather than leaving innovation up to third parties, many health organizations are formalizing programs to advance innovation within their own facilities.

There are two schools of thought on healthcare innovation. Some argue that the market’s unique challenges can only be understood by those in the field, leaving outside influencers destined to fail. Others view innovation success in outside markets as an opportunity for healthcare stakeholders to learn from the wins and losses of more technically progressive industries. By mimicking other industries’ approach to promoting innovation (as opposed to their byproducts) in our hospitals and health systems, healthcare can draw from the best of both worlds. What we know is that the process in which innovation is adopted is very similar in all industries. However, the types of innovations and specific models can and should be tailored to the healthcare industry.

Innovation in Healthcare: Three Examples at a  Glance

There are several examples of health organizations successfully forging a path to institutionalized innovation. University of Pittsburg Medical Center (UPMC), Intermountain Healthcare and Mayo Clinic have pioneered innovation programs that merge internal clinical expertise with technical innovators from vertical markets in and outside healthcare. This article highlights some of the ways these progressive organizations have achieved success.

Innovation at UPMC

UPMC Enterprises boasts a 200-person staff managed by top provider and payer executives at UPMC. The innovation team is presently engaged in more than a dozen commercial partnerships, including support for Vivify Health’s chronic care telehealth solutions, medCPU’s real-time decision support solutions and Health Catalyst’s data warehousing and analytics solutions. Each project is focused on the goal of improving patient outcomes. The innovation group was recently rumored to be partnering with Microsoft on machine learning initiatives and the results may have a profound impact on how we use technology in care delivery.

UPMC Enterprises supports entrepreneurs—both internal individuals and established companies—with capital, technical resources, partner networks, recruiting and marketing assistance to support innovation. Dedicated focus in the following areas lends structure to the innovation program:

  • Translational science
  • Improving outcomes
  • Infrastructure and efficiency
  • Consumer engagement

All profits generated from investments are reinvested to support further research and innovation.

Innovation at Intermountain Healthcare

Like UPMC, Intermountain’s Healthcare Transformation Lab supports innovation in the areas of telehealth and natural language processing (NLP), among others. Like most providers, one of Intermountain’s primary goals is controlling costs. The group’s self-developed NLP program is designed to help identify high-risk patients ahead of catastrophic events using data stored in free-text documents. Telehealth innovations let patients self-triage to the right level of care to incentivize use of the least expensive form of care available. Intermountain’s ProComp solution offers its providers on-the-spot transparency about the cost of instruments, drugs and devices they use. That innovation alone net the health system roughly $80 million in reduced costs between 2013 and 2015.

Most of Intermountain’s innovation initiatives are physician led or co-led. The program strives for small innovations in day-to-day work, supported by a suite of innovation support services and resource centers. Selected innovations from outside startups are supported by the company’s Healthbox Accelerator program involvement, while internal innovations are managed by the Intermountain Foundry. Intermountain offers online innovation idea submissions to promote easy participation. The health organization’s $35 million Innovation Fund supports innovations through formalized investment criteria and trustee governance resources. It is important to note that Intermountain Healthcare is interested in all aspects of innovation including supply chain and other non-clinical related projects.

Innovation at Mayo Clinic

Mayo Clinic’s Center for Innovation (CFI) brings in innovation best practices from both healthcare and non-healthcare backgrounds to drive new ideas. The innovation team’s external advisory council is comprised of both designers and physicians to drive innovation and efficiency in care delivery. The CFI features a Multidisciplinary Design Clinic that invites patients into the innovation process as well.

CFI staff found it was essential to show physicians data that demonstrated known problems and how proposed innovations could make a difference to their patients. They emphasize temporary changes, or “rapid prototyping,” to garner physician buy-in. Mayo’s CFI promotes employee involvement in innovative design through its Culture & Competency of Innovation platform, which features weekly meetings, institution-wide classes, lunch discussion groups and an annual symposium. Mayo’s innovation efforts include these additional physician-led platforms:

  • Mayo Clinic Connection—supporting shared physician experience
  • Prediction and Prevention
  • Wellness—promoting patient education
  • Destination Mayo Clinic—focused on improving patient experience

While these innovation examples represent large healthcare organizations, fostering innovation does not require a big budget. Mayo Clinic’s “think big, start small, move fast” approach to innovation illustrates a common thread among successful innovation programs. Here are practical strategies to advance innovation in healthcare, regardless of organizational size or budget.

Four Steps to Implementing an Innovation Program in Your Organization

Innovation doesn’t have to be grandiose or expensive. Organizations can start small. Begin by opening a companywide dialogue on innovation and launching a simple, online idea submission process to engage personnel in your organization. The most important part of this process is educating your teams to understand how to evaluate new innovations against a relatively pre-defined set of criteria.  For example, are you trying to improve patient safety, quality of care, reduce cost, increase patient or physician satisfaction, etc.

Another key element of successful innovation is encouraging collaboration and participation across a wide variety of stakeholders. Cross-functional teams bring multifaceted perspectives to the problem-solving process. Strive for incremental gains in facilitating opportunities for cross-department collaboration in your organization. This is particularly important for the implementation step.

Measure success using performance metrics where clinical efficiencies are concerned. Physician satisfaction, while difficult to quantify, can also pose big wins. You can expect some failures, but stack the odds by learning from other departments, organizations and industries to avoid making the same mistakes.

To work, innovation must happen often and organically. Dedicate funding, establish cross-department teams and build a formal process for vetting internal ideas. Consider offering staff incentives to drive engagement. Not all ideas will succeed. Identify metrics that will help determine ROI (not all ROIs are measured in dollars) on pilot programs so you can weed out initiatives that aren’t delivering early on to protect resources. Also, keep in mind that you can improve these innovations at each iteration.  Make the process iterative and roll out the initiatives quickly. If it fails, shut the process down quickly and move on. If it is successful, improve it for the next iteration and scale it quickly to maximize the benefits.

Whether you’re cross-pollinating internal teams to promote innovation, building partnerships with other organizations or leveraging technology to better connect providers and patients, healthcare’s ability to successfully collaborate is vital to advancing innovation in healthcare.

About Peyman S. Zand
Peyman S. Zand is a Partner at Pivot Point Consulting, a Vaco company, where he is responsible for strategic services solving healthcare clients’ complex challenges. Currently serving as interim regional CIO for Tenet Healthcare, Zand was previously a member of the University of North Carolina Healthcare System, leading Strategy, Governance, and Program/Project Management. He oversaw major initiatives including system-wide EHR implementation, regulatory programs, and physician practice rollouts. Prior to UNC, Zand formed the Applied Vision Group, a firm dedicated to assisting healthcare organizations with strategic planning, governance, and program and project management for key initiatives.

Zand holds a Bachelor’s of Science in Computational Mathematics and Engineering from Michigan State University, and a Master of Business Administration from the University of Michigan.

Real-Time Health Systems (RTHS) and Experiential Wayfinding

Posted on May 19, 2017 I Written By

The following is a guest blog post by Jody Shaffer from Jibestream.

You have probably heard about Real-Time Health Systems (RTHS). This is a game-changing trend among healthcare providers where the delivery of healthcare is transforming to a more aware and patient-centric system. Providers are leveraging technology to get pertinent information to decision makers as quickly as possible empowering them to make more informed decisions in real-time. Facilities that are amenable to change will remain strong in competitive markets, while those who are reluctant to adapt will fall behind.

As we entered this new era in healthcare, providers are faced with a series of challenges. Smart medical devices are transforming the healthcare dynamic as medical data and information is produced and multiplying at an exponential rate, yet it’s use has not been keeping pace. This data overload has created a significant obstacle for healthcare providers to overcome. There is also intense pressure to create a consumer and patient experience that is dynamic, accessible and engaging.

So the question is, how can healthcare providers quickly process and interpret copious amounts of data into a digestible format for immediate patient consumption while internalizing and translating the same data into operational intelligence?

The answer lies in evolving to a paradigm that is situationally aware and patient-centric in both operations and management. Not only is this pivotal in successfully achieving a RTHS, it ensures that healthcare providers connect, communicate and collaborate more effectively than they have in the past.

When looking to achieve a Real-Time Healthcare System, there are four primary phases that need to be addressed:

Phase 1 – Collecting data

Phase 2 – Processing data

Phase 3 – Translating data into intelligence

Phase 4 – Utilizing/sharing data

The final two phases are essential for healthcare providers to excel in this changing market dynamic and meet increasing patient expectations.

To yield valuable intelligence, data needs to be presented with situational context. Raw data is in itself useful for analytics, but can only be leveraged to create spatial awareness when augmented with location-based data.

Consumers have grown accustomed to the convenience of real-time access to information from mobile devices and apps, and healthcare is no exception. Through a combination of location-aware technologies, hospitals can eliminate some of patient’s biggest frustrations fostering a more positive patient experience across the continuum of care.

Mobile apps, digital maps and interactive kiosks leverage connected technologies to help create a more familiar and engaging environment promoting an effortless and seamless patient experience.

Experiential wayfinding, made available through these technologies, form the foundation for enhancing patient experience, which is paramount to the success of a healthcare organization. Experiential wayfinding reduces the complexity of indoor spaces by anticipating where people are going and what they are looking for. It can be used to direct visitors to a facility and identify parking availability nearest their desired location. Once there, it can be used to guide visitors to destination(s) within a facility using turn-by turn directions making it easy and less stressful to get where they need to go.

An integrated platform can also enable proactive interactions engaging patients before, during, and after hospital visits. The use of mobile messaging to deliver contextual content based on a patient’s location and profile help create a more pleasant and efficient patient experience. Prior to a visitor’s departure to a hospital, the facility’s mobile apps can share information such as appointment delays or traffic delays to take into account on the way there. Mobile messaging also enables facilities to communicate with visitors by sending appointment reminders, context-aware messages, preparation guidelines, post-care instructions, and more. Another application of this can save patients the frustration of intolerable wait-times when a hospital is stretched beyond capacity by sending notifications to offer a change of appointment or alternate appointment location.

Location awareness and spatial context benefit both patients and healthcare providers alike. For clinicians and healthcare teams, this translates to accelerated productivity facilitated through visibility, the streamlining of processes resulting in the elimination of inefficiencies, minimizing staff interruptions, and a balance between resources and demand.

When managed properly, a RTHS enables healthcare providers to improve patient satisfaction and outcomes by leveraging the vast amount of data made available through connected computers, technologies and medical equipment across hospitals, clinics, and patient homes.

By merging the location dimension into healthcare systems, providers are able to bring order to complex data. Through geoenrichment and data visualization, providers can improve patient experiences and outcomes, uncover previously unseen data patterns, realize workflow efficiencies through connected technologies and enrich business insights leading to better more actionable decisions.

Behind the Scenes: Preparing for a RTHS Transition

  • Digitization of Space (converting CAD/DWG map files to SVG)
    Before data can be presented in the context of a map, healthcare providers need to digitize their space. This provides a scalable platform for plotting data to support multiple use cases.
  • Connect core systems and data
    Leveraging technology that offers interoperability allows for seamless integration of core systems and data
  • Connect assets and people
    Create situational awareness by connecting to assets and people
  • Connect maps to data with Indoor Positioning Systems (IPS)
    Look for a solution that offer a technology agnostic architecture to calibrate maps Indoor Positioning
  • Implementation
    Make all this available by extending solution to patient and nonpatient hospital workflows

About Jody Shaffer
Jody Shaffer is an experienced marketer with more than 13 years in the software industry. Jody currently leads the marketing department at Jibestream, an award-winning company specializing in indoor mapping and location intelligence solutions. The company’s platform provides developers with the tools to build custom map-enabled applications unlocking the full potential of the Internet of Things (IoT). Jibestream’s platform can be found implemented in hospitals and health care facilities across north America.

Healthcare Analytics are the Problem. Applied AI is the Solution.

Posted on May 17, 2017 I Written By

The following is a guest blog post by Gurjeet Singh, Executive Chairman and Co-founder of Ayasdi.

The combination of electronic medical records, financial data, clinical data, and advanced analytics promised to revolutionize healthcare.

It hasn’t happened.

The common excuse is that healthcare wasn’t really prepared for the enormity and complexity of the data challenge and that, over time, with the next EMR implementation, that healthcare will be positioned to reap the benefits. Unfortunately, the next generation of EMR, or the one after that, isn’t going to solve the problem.

They problem is on the analytics side.

Healthcare analytics are still driven by a question-first approach. The start of our analytics journey still begins with the question.  The challenge is which question? The more data we have at our disposal, the more potential questions there are and the lower the likelihood that we will ask the one that generates new value for the patient, the provider, or the payer. Even when we are successful in asking the right question, we have engaged in a confirmatory process – we have confirmed something we already knew.

Some will suggest that predictive analytics solves the problem, but it too is hypothesis driven – just in a different way. With predictive analytics, the set of variables selected, the choice of algorithms are, in effect, guesses as to what will produce the best outcome.

Ultimately, both approaches are flawed.

We need a new approach that surfaces trends we humans haven’t even considered, and that delivers a host of meaningful insights to clinicians before they even ask any questions. We need technology solutions that combine the best qualities of human intelligence (artificial intelligence) with the best computing capabilities that exceed human ability (machine learning).  When these technologies are operationalized systematically across an enterprise, it’s called Applied AI.  Applied AI is here to replace healthcare analytics, and we all stand to benefit.

Five Keys to Applied AI

Applied AI has already begun driving care improvement, cost-reduction, and improved clinical and financial decision-making across the healthcare enterprise – and the entire healthcare continuum. Applied AI is not a concept, but a series of intelligent applications that target discrete healthcare problems from clinical variation to population health. These intelligent applications have a collection of capabilities that make them intelligent – of which all need to be present. Let’s look at those capabilities:

DiscoveryIntelligent applications need to support both unsupervised and semi-supervised discovery. These capabilities are quite rare but serve as the foundation for our efforts to move past hypothesis driven inquiry. In practical terms, this means that an intelligent application considers all the data and all the possibilities within that data to detect the patterns, groups or anomalies that elude traditional approaches. Using their own systems of records, including EMRs, financial data, patient-generated data, and socio-economic data, healthcare organizations can automatically discover groups of patients that share unique combinations of characteristics. These groups can then be used to tailor and personalize diagnostics and care paths, for example. Alternatively, healthcare organizations may also discover unique patterns or outliers within their claims data to aid in member retention or preventing fraud or waste. This type of holistic discovery is unique to AI and improves prediction and makes operational insights possible.

Predictions Intelligent applications must also be able to predict the future with high accuracy. Holistic discovery enables even better predictive models through the unbiased creation of groups or the identification of patterns. Superior prediction gives healthcare organizations foresight into the future needs, costs, disease burden, and risks of patients. For example, intelligent applications can determine the groups of patients projected to have the highest escalation of costs over time, as well as other outcomes such as the conditions likely to appear for each group, and an individual’s predicted change in utilization. Predictions can be made across multiple targets and are multi-faceted, considering all factors whether they’re health- or non-healthcare-related occurring outside of the healthcare system.

JustificationAn intelligent solution must justify its predictions, discoveries, and actions in a transparent way so human operators feel confident to act upon its recommendations. For example, a healthcare app may reveal differentiating characteristics of patient risk trajectories, what factors make them high or low-risk, and descriptions of individual factors that lead to variation in cost and quality. Justification is key because without a thorough understanding of the “why” behind predictions, organizations are unable to adopt AI into day-to-day decision-making.

Action An intelligent system that is not effectively operationalized will become less intelligent over time. Actionable information that guides and augments human decision-making is what makes AI a part of daily operations. For these systems to deliver optimal value they need humans in the loop providing feedback and governance. Whether it be a recommended care path or a detailed risk profile, intelligent applications allow organizations to collaborate on the best actions tailored for each patient population, or to physicians or organizations. Across the care continuum, within health systems and health plans, this allows them to better assess individuals and the best course of care, and more confidently prescribe care and programs for each individual.

LearningIntelligent applications “learn” to improve predictions over time. As more and more data is analyzed, the technology learns from these complex data points to improve predictions over time. Whether it be claims, medical records, or socio-economic data, AI taps into these data points to generate more accurate, personalized predictions that continuously improve. Further, intelligent apps learn the impact of actions over time to support and continuously improve decision making.

Applied AI in action

A large hospital system decided it wanted to reduce clinical variation across its enterprise to improve outcomes for all patients. It implemented machine intelligence, including unsupervised machine learning techniques that run algorithms using the system’s own data—not benchmarks—to uncover actionable insights. The technology correlates and analyzes electronic medical record and financial data including treatments prescribed, procedures performed, drugs administered, length of stay, and costs per patient. The goal was to discover and refine clinical pathways that are optimized to drive higher quality of care and lower costs.

The machine intelligence solution identified a group of orthopedic surgeons who consistently had better outcomes among their knee replacement patients. These patients had shorter hospital stays and shorter time to ambulation than other total knee surgery replacements across the system. The solution also told clinicians why:  these doctors prescribed a unique, not widely used medication at an earlier postsurgical time than their peers. The medication reduced patients’ pain so they could get out of bed and walk around sooner – improving their outcomes and reducing costs.

Clinicians hadn’t previously known to look for variation based on what medication was given post-operatively. But machine intelligence identified a pod of doctors with better outcomes that were statistically significant. By comparing very large numbers of data points, the solution quickly uncovered why.  Now the hospital system has operationalized these best practices throughout their hospitals, lowering costs for knee replacement by more than 5 percent, and reducing pain for patients.

The last piece of the puzzle – AI applications

As healthcare organizations increasingly see the value of Applied AI, they may worry that more robust technology means greatly increased technical headcount to manage this strategy. But an important component of a successful Applied AI strategy is that it leverages the unique capabilities of both machines and humans. Hiring a dozen data scientists won’t make the most of the human intelligence within your organization. That’s because these new data scientists likely would not have the subject matter expertise needed to recognize and deploy the meaningful insights that surface. Meanwhile, the people who are the best suited to learn from the data, domain experts, usually do not have an interface to read data themselves. Subject matter experts typically only interact with data using rudimentary applications like PowerPoint or Excel.

So, the last key to a successful Applied AI strategy is to wrap the results of machine learning and artificial intelligence into business-facing applications. These applications can be customized for the types of insights they uncover, such as the optimal way to perform surgical procedures. It’s critical that the results of machine learning and machine intelligence actually make it to clinicians, instead of ending up siloed somewhere in the IT department. The successor technology to healthcare analytics must not only be more powerful and more precise, it must also be more user-friendly.

What’s Next

Healthcare analytics simply aren’t living up to their promise. We can wring our hands, we can wait, we can soldier on with insights that only marginally move the needle to improve outcomes and lower costs. Or we can combine artificial intelligence with powerful machine learning to turn enormous datasets into business insights that really matter. Then we can deliver those insights, via easy-to-use business applications, to the best clinician minds, to operationalize this machine intelligence approach across the enterprise. That’s Applied AI, and it’s a bright future.

About Gurjeet Singh
Gurjeet Singh is Ayasdi’s Executive Chairman and co-founder. As the Executive Chairman, he leads a technology movement that emphasizes the importance of extracting insight from data, not just storing and organizing it.

Gurjeet developed key mathematical and machine learning algorithms for Topological Data Analysis (TDA) and their applications during his tenure as graduate student in Stanford’s Mathematics Department where he was advised by Ayasdi co-founder Prof. Gunnar Carlsson.

Gurjeet is the author of numerous patents and has published in a variety of top mathematics and computer science journals. Before starting Ayasdi, he worked at Google and Texas Instruments. Gurjeet was named by Silicon Valley Business Journal as one of their 40 Under 40 in 2015.

Gurjeet holds a B.Tech. from Delhi University, and a Ph.D. in Computational Mathematics from Stanford University. He lives in Palo Alto with his wife and two children, and develops multi-legged robots in his spare time.