2019 is the Year Healthcare Executives Need to get Strategic on Leveraging Data

Fri, 12/07/2018

A recent McKinsey article on rebooting the chief analytics officer role mentions that only eight percent of companies are reporting they are leveraging data at scale across the enterprise. Since healthcare lags behind general technology adoption we can assume that this number is high for the industry. Additionally, they found a number of key roles chief analytics officers must play as catalysts for change:

Convening a coalition of equals: McKinsey talks about the role catalysts play in leading the process by bringing stakeholders together through consistent communication. Some of the key elements of success include:

  • People and processes are more critical then technology
  • Putting the business value front and center
  • Communicate. Communicate. And then communicate some more
  • Keep an eye ahead

Making analytics an enterprise thing: Catalysts lead the centralized team… Read More »

The Importance of Data Management in Healthcare

Wed, 11/28/2018

According to hitconsultant.net, "…the use of data analytics could help save more than $300 billion in U.S. healthcare, apart from making information flow transparent and creating a value chain in healthcare." [1]

Sounds positive, right?

No matter how useful data analytics are, it’s important to realize that they don’t just pop up from your existing healthcare data. Your analytics are only as good as the data that goes into them. And your data is located everywhere: clinical and claims systems, HR and financial applications, and third-party sources. Healthcare organizations that struggle with disparate information assets and siloed processes must find a way to make data “fit for purpose” through aggregation, standardization, and enrichment.

Once information is collected and aggregated from various sources, healthcare organizations must ensure its accuracy, completeness, and consistency. They need a plan and supporting solutions that promote sound data management. A unified… Read More »

OmniHealthData.com Wins Gold for Best Healthcare Content

Mon, 11/19/2018

I have some great news to announce!

Recently, at the 22nd Annual Healthcare Internet Conference in Scottsdale Arizona, the Omni-HealthData website won the gold for “Best Healthcare Content” of the 2018 eHealthcare Leadership Awards program. Even more impressive, there were over 1000 entries submitted for these awards.

Earlier this year, when we launched this website, we wanted to enable healthcare organizations with powerful software to achieve effective data management. Providing informative content, including use cases and best practices, helps awareness of our product, and shows the value in purchasing a complete solution that will take data from anywhere, and turn it into actionable insights.

If you haven’t already, Read More »

The Importance of Provider Mastering

Wed, 11/07/2018

While many healthcare systems have implemented Enterprise Master Patient Indexes (EMPIs) for patients, few have embarked upon the daunting challenge of mastering providers. But there is a growing list of reasons why mastering providers is of equal financial importance. Healthcare organizations implement EMPIs to maintain up-to-date and accurate information about every patient. And for good reason: Inaccurate patient identification or information results in 33% claims denial and costs the US healthcare system over $6 billion annually.


Unfortunately, mastering a provider is so much more difficult then a mastering a patient. There are many reasons why.  A provider is not just a doctor, that term can extend to nurse practitioners, physician assistants, and more.  Layer in the dimension of a provider being employed, affiliated, and/or independent and the challenge is further exacerbated.  A sophisticated system will be able to facilitate a provider that is not currently in your system yet is a valid provider.  EMRs struggle with the existence of someone that does not exist in their system.  With their inability to incorporate HR data, a provider does not exist until they are seen by a patient in a… Read More »

Cutting Through the Hype, Part 4 of 5 – Leveraging Governance to Prioritize Clinical and Business Objectives

Thu, 11/01/2018

In the Marine Corps, one of the first things I learned about how to prioritize and follow various orders I received was the phrase “Stars over Bars”. “Stars” refers to the rank of generals and “bars” indicates the silver or gold bars that makeup the insignia for captains and lieutenants. In the corporate world, we might refer to this as “C’s over VPs”. Clear chain of command is vitally important in the life and death operations of both the military as well as healthcare organizations, but it may not be the most efficient way to order the priorities of an enterprise analytics program. 

In this blog, I will discuss an immediate, short term approach to managing analytic requests that most organizations can easily implement and harnesses your data governance program (from the last blog post). I will also provide a long term approach that optimizes the efficiency of your executive leadership, analytics staff, and performance improvement groups across the enterprise.

In one organization I belonged to, we called the “C’s over VPs” situation the “wild west” method.  Sometimes requests came through a… Read More »

Reference Data Management in a Sea of Codes

Wed, 10/24/2018

Many health practitioners seem to think that interoperability among health systems is the most important issue they face. And that’s almost true. Interoperability is key to keeping real-time operations flowing.


But achieving interoperability doesn’t eliminate a more serious problem: the fact that these systems describe the same situations in completely different ways.


The codes inside our systems are a kind of language that we use to describe, track, and communicate what’s happening in our healthcare organizations. When we try to analyze and understand what’s happening in our organizations, we need to get information from all of our systems and make a coherent picture from it.


Suppose an analyst needs to study a cohort of diabetic men over age 45 who are on blood pressure medications. How would you navigate your systems and the variety of code sets they use to get a list of diabetic patients for her?


Could you further refine your list to include a comorbidity of hypertension?


Consider the following… Read More »

Population Health Management, Defined

Fri, 10/12/2018

Population Health Management refers primarily to the identification of groups that need healthcare support, and the coordination of care for improving their outcomes.

When healthcare organizations have a data driven technology plan, they are more easily able to exchange information, identify opportunities in care, and provide timely interventions. This makes for healthier patients as well as a better overall patient experience.

To implement a data driven technology plan, you may want to use software that enables cohort analysis, which finds groups in a population that share similar characteristics. You also may need help with population metrics by using performance scorecards to highlight areas to focus on for immediate attention.

Leveraging all your data resources in order to achieve optimal population health management is not as hard as you think. For more information on how to succeed with population health management, read our trending topics page.

Employer innovations transforming health care delivery

Thu, 10/04/2018

Rising healthcare costs are increasing the financial burden on employer groups, especially small employer groups who provide health benefit coverage to their employees. According to data released by Peterson-Kaiser Health System Tracker, health plan cost sharing and deductible spending have outpaced employee wage growth in the past ten years. Employees’ total financial responsibility increased by 54 percent from 2006 to 2016 while wages only increased by 29 percent during the same amount of time. As more and more health plans shift the cost of healthcare services to their beneficiaries, employers are looking at innovative ways to reduce the financial burden of their employees.

Frustrated with the pace at which the healthcare industry is driving change, some employers are taking a more proactive role and driving changes in the healthcare delivery system. They gear these changes towards innovative ways of healthcare delivery that emphasize on the components of value-based care.

ACOs and HPNs

Employers are contracting directly with Accountable Care Organizations (ACOs) or high-performance networks (HPNs) when these organizations offer the highest quality and/or most cost-effective providers. Under many high performance networks such as ACOs or narrow network plans, employers typically leverage… Read More »

Industry Stalwarts Focus on Interoperability's Need for an Architecture

Mon, 09/24/2018

Interoperability in healthcare was the focus this week both from HIMSS and on Capitol Hill. In both cases, missing was the clarion call for healthcare organizations to take charge of their data with an enterprise approach to data management.

First up, Healthcare IT News sat down with HIMSS Chief Technology and Innovation Officer Steve Wretling to discuss interoperability. Wretling focused on the need for an architecture to drive interoperability beyond the use of APIs, which has increased in the last several years. He emphasized, “We’re in a data revolution time period where digital information and technology is opening many avenues to innovation on data that have not been there before."

So, let's examine the outburst of data over the last several years with more to come:

  • Electronic health records have exploded since Meaningful Use Incentive Program was launched with the passage of ARRA (American Recovery and Reinvestment Act) in 2009
  • Changing payment models… Read More »

Know Your Patient: Bringing consumer product marketing techniques to healthcare

Wed, 09/05/2018

Let me start by making sure that you, the reader, know that the purpose of this blog post is NOT to debate the concepts of patient versus customer, and the perils of confusing the two. However one feels about the encroachment of consumerism in healthcare, it doesn’t mean that healthcare is so different that we cannot learn and exploit known marketing outreach techniques often targeted at the ”customer” in other industries.  And just like Know Your Customer (KYC) in finance, Know Your Patient (KYP?) depends heavily on knowing every single fact at your disposal that could be relevant to the end goal you are trying to achieve. The optimal use of these facts is highly dependent on the data you collect and your ability to organize it into a coherent representation of everything you know. 

Take for example, the siting of specialized facilities that your network is looking to invest for the future.  One could take an educated guess and surmise that because there are other health related facilities in an area, yours would do well being nearby. But is that what a consumer focused company would do?  No. They would first examine how many of their profile customers live in or around the area in question using market data. Then they would layer the demographics of people who currently travel past the location to determine the level of traffic they could potentially see and compare this to other… Read More »

Cutting through the Hype, Part 3 of 5 – Data Governance; How to Start, Organize and Build to Sustain

Thu, 08/23/2018

In Part 2 of the “Cutting through the Hype” series, we discussed the importance, especially in healthcare, of getting the data matched, merged, cleansed, mastered and enriched/tagged with the proper HLI code sets and clinical ontologies.  This is the work represented in the first 4 columns (Connect, Move, Fix, and Relate) of the “Data Value Chain” diagram below:

Data Value Chain

Following “Relate” is “Govern”.  For healthcare organizations, data governance is regularly discussed, rarely understood, and hardly attempted.  In my experience working for and collaborating with some of the top analytics groups in the country, data governance failures (or non-starts) are the result of two primary causes:

  1. The columns to the left of “Govern” are not being done with automated, scalable technology
  2. Lack of clarity – what is data governance, what is its purpose, why is it needed?

We’ve reviewed item one with sufficient detail in… Read More »

Thinking beyond the EHR

Tue, 08/14/2018

Last week, I went to see a presentation on the importance of an enterprise data foundation to drive analytical change in healthcare. It made me think about two articles I read recently:

The first article covered Dr. Frank Opekla's testimony in front of congress on behalf of The American College of Surgeons and American Medical Association.  He discussed the possibility of shifting from merit-based incentive payments for EHR use to encouraging a broader use of sources that extend beyond the EHR. His key point was that the focus on EHRs alone is too narrow when in advancing care information there are many more sources to consider.

In addition, the EHR should be a key data source and a consumer of analytics, but not serve as the enterprise data and analytics foundation. Dr. Opekla concluded with “There is so much more we can do for quality and for lowering costs by leveraging digital information. “We have to stop thinking of EHRs and think beyond them.”

The second article was based on the results of a Quest Diagnostics survey on value-based care. The… Read More »

Payer investments in community leading to healthier outcomes

Thu, 08/02/2018

According to the World Economic Forum, social and environmental risk factors account for 20% of health outcomes. Social determinants of health include the conditions of the places where people live, learn, work, and play. These conditions can affect a variety of health risks and outcomes. Unstable housing, low income, unsafe neighborhoods, and substandard education are some of the major factors that can influence patient health.

Factors Influencing Health Outcomes

Social risk factors increase the danger of a future disease burden, particularly in the lower income populations. Incorporating these social determinants into patient EHRs, and having them become part of the workflow may improve individual and population health. Once these social determinants are mapped, they provide the key to developing personalized care.

Collection will be exacerbated if there are limitations on data sources and challenges to the workflow. Collecting social determinants of health is a challenge to begin with, considering they are not commonly found in claims or medical records. Mostly, this information is found in coded and unstructured… Read More »

The struggle for healthcare in breaking down silos and moving to enterprise data usage

Thu, 07/26/2018

Rather than think about how we tackle data issues for population health, value based care, AI, and predictive analytics, healthcare organizations need to think about what their data strategy is and what platform should be used across the entire enterprise.

Organizations need to take into account data sources, volume, and usage that will be growing year after year. Due to the increased volume, data analysts, who want to use data for impactful change, are really data jockeys, spending more than 80% of their time preparing data for projects.

For data to be most helpful, it must be integrated quickly and at scale from a diverse set of sources, such as: legacy applications, machine data, spreadsheets, web services, user generated data, and more. This data then must be mastered, cleansed, harmonized, and prepared for analytical use. This process seems straightforward, but it not happening enough.

Some of the reasons why healthcare organizations aren’t tackling data as an enterprise issue are:

  1. They all want to continue to use their existing EHR systems, in which they have invested millions of dollars. They hope the EHR will figure out the data and analytics issues on their own.
  2. The landscape is filled with HIE and… Read More »

Healthcare Analytics and the Challenge of Imagination

Fri, 07/20/2018

The strategic importance of becoming a data driven organization in healthcare cannot be overemphasized.  Making the transition from opportunistic and transactional information sharing to a proactive data centric business can present challenges for most health systems. It surely is not from lack of motivation, as there is a level of excitement around data in healthcare that couldn’t be more pronounced and it is felt at every level of the organization.  So why when we have the desire, the motivation, the mandate, and the tools to make this transition are we having trouble taking meaningful steps to change?

One big reason that is somewhat unique to healthcare is that this change has to take place while the responsibilities of every day work remain unchanged, especially when working with data is not your primary day job.  Current reporting and analytic strategies often represent past hard-fought battles for data acquisition, hours with Excel getting the data right, and then fighting for the results to be accepted as fact by the business.  Couple those feelings with the sheer habit of my current report and analytic generation process (and yes I know exactly how much of my time it will take to get it done this month!) and you get a recipe for stasis. 

As the barriers to… Read More »

Cutting Through the Hype, Part 2 of 5 – Real Life Illustrations That Help Define Healthcare’s Unique Data Challenges

Thu, 07/12/2018

In my previous blog post, it was determined that data silos in healthcare require utilization of technology with capabilities in three core competencies: Integration, Integrity (Data Quality), and Intelligence.  Since these are not core competencies of the EHR, we should define the problem in more detail before considering further options. 

In this post, you will see three simple data illustrations to help increase our understanding of the issues.  

First, let’s look at some quality, cost, and operations information for patients or members using data from different systems. We’ll include EHRs, materials management, HR/Staffing, and shift/timekeeping systems.  Let’s group the information by gender, which is stored in each of these four systems as follows:

Patient Gender (22)

However, we only really want to group by the following six types:

Read More »

The Importance of Mastering Provider Information

Fri, 06/22/2018

A lot of effort has been put forth in mastering the patient/member and rightfully so.  When effective, patient duplicates drop, the chances of administering the incorrect drugs decline, claims processing improves, the patient member experience enhances and so on.  Now the challenge becomes provider or physician mastering.  On the surface, that would seem to be a relatively easy task, but the devil is always in the details.

Providers wear many hats.  They can be a solo practitioner, a physician as a part of a practice, a hospitalist, credentialed at many hospitals, and even the possibility of a single physician having two different National Provider Indexes (NPI’s).  Some specialists, even within the same practice, will serve patients at different locations.  To compound it further, information about a physician (e.g. – fax number) is spread across the 20+ systems that may be housed even within a single hospital system.

The impacts affect many different areas.  Incorrect physician information could inhibit or delay notification when a patient has been discharged from either Emergency Department (ED) or inpatient services.  When the patient presents for follow up, physicians are commonly surprised to learn they even went to a hospital.  If the patient presented at both ED and subsequently Inpatient, one or both of the encounters may not be communicated to the PCP due to erroneous contact… Read More »

Predictive Algorithms: The importance of reliable data

Mon, 06/18/2018

There is little doubt that one of the hottest trends in healthcare information management is predictive analytics. Some of the most common research topics are predicting the likelihood of sepsis in a hospital patient, understanding who is most likely to readmit and getting insight into co-morbidities and their likely progression for certain chronic conditions. These advanced informational algorithms get our attention because they can have such a direct impact on patient wellness and our ability to deliver cost effective quality care. But if we believe that (and I am sure of us most do), why aren’t we doing it already. 

In order to be able to effectively predict the future we need to have a firm understanding of the present and the past. The nature of healthcare data and its tendency to be voluminous while often living in segregated siloed systems often doesn’t allow us to have a firm understanding on what is actually going on. Sure, I can tell you everything we did while the patient was in the hospital, every test we ordered, the results and other observations, what we instructed the patient when they left and what meds we prescribed. But I don’t necessarily know if they filled their prescription, whether they reliably took their medicine or followed any of the instructions. We do… Read More »

Cutting Through the Hype, part 1 of 5 – Analytics Beyond the EHR

Tue, 06/12/2018

In my introductory blog, I spoke of the importance of getting the foundational aspects of data correct before moving into more technologically advanced areas.  Getting our “data house in order” is the first step to avoiding a lot of rework, which reminds me of a cautionary cartoon a co-worker had pinned in his cube when I first started as a software developer; “Don’t worry about the mule going blind, just load the cart.” 

It is important to think of data as the valued assets that they are, and when it comes to treating data as an asset, we need a new, modernized way of thinking, especially in healthcare.  If data are inaccurate in retail, finance and manufacturing, it can cause logistical issues or cost money.  If they are wrong in healthcare, people get hurt, clinical outcomes suffer and population health declines.  However, if Integration and Integrity (quality) are done correctly, there is a massive increase in speed to value for achieving Intelligence/Analytics with a significant reduction in long-term FTE overhead.  Thereafter, all staff and leadership involved in the effort to solve Data Rich and Information Poor are… Read More »

Apple has the Healthcare IT community FHIRed up!

Fri, 06/01/2018

Earlier this year, tech behemoth Apple announced it is launching a personal health record (PHR) feature with iOS 11.3. “App”tly named Health Records, the feature will aggregate existing patient-generated data in the Health app with data from a user's electronic medical record at a participating hospital. At launch, Apple is working with 12 hospitals across the country, including Penn Medicine, Cedars-Sinai in Los Angeles, Johns Hopkins, and Geisinger Health System.

The feature will use HL7's FHIR (Fast Healthcare Interoperability Resources) specification. Users will be able to see things like allergies, medications, conditions, immunizations and lab results, as well as the sort of things that can be usually pulled in a patient chart in an EMR. They can be notified when the hospital updates their data. The data will be encrypted and users will need to enter a password to view it.

What is FHIR?

The Fast Healthcare Interoperability Resource is an interoperability standard that has emerged from the non-profit HL7 organization, and functions as a universal… Read More »

Achieving Data Liquidity in Healthcare

Fri, 05/18/2018

By harnessing the true power of data, healthcare providers can make both clinical and business improvements that transform the way they operate.

But data liquidity, when the right information is delivered to the right people at the right time, is not easy to achieve. Healthcare processes may be fragmented, and as a result, the data generated during the course of healthcare transactions is fragmented as well.  It resides in siloed EHRs, claims processing applications, pharmacy systems, and more. Compounding the problem are new, but important sources of health information such as genetic data and patient-generated data. 

Clinicians and other stakeholders rarely have access to the comprehensive, timely, accurate information they need. This lack of data liquidity makes it difficult to apply data for specific uses, such as managing quality indicators, and nearly impossible to leverage in support of “on the fly” questions and information needs as they arise. 

Providers need to address the entire data value chain – collecting it from various sources, integrating and standardizing it, preparing it for analysis, and offering different tools for interacting with it in different ways – in order to reach full data liquidity. The right… Read More »

Cut Through the Hype – Healthcare Data Governance and Enabling Technology

Thu, 05/10/2018

When it comes to Business Intelligence and Analytics, people tend to think about big data, artificial intelligence, and data mining. This “silver bullet thinking” tends to be driven by much of the hype out there. The challenge is that none of it works without two key requirements:

  1. The data are accurate, reliable, complete and consistent with the proper relationships.
  2. The definitions for the data types, groups, cohorts, metrics, and benchmarks are clear and easily available throughout the organization – ideally in context of the associated dashboards, scorecards and reports.

PwC, in their “Top health industry issues of 2018” report, calls out that “An AI tool is only as good as the data it uses for decision-making. Companies should invest in finding, acquiring and creating good data, standardizing it and checking it for errors.”

Many healthcare organizations have a master patient/member index.  However, most do not have a practitioner master file or a single source or list of all of their physicians. Many a brave soul has had the experience of showing attributed data to a physician only to have it quickly picked apart. … Read More »

AI, Data Warehousing, and How to Handle the Hype

Thu, 05/03/2018

Recently, I read some articles showcasing technology hype versus what organizations really need. While all sectors suffer from an overload of hype, healthcare’s complexity means it gets hit particularly hard.

For example, there’s a crescendo of noise surrounding Artificial Intelligence (AI) right now. One thing that often gets left out is an age-old maxim: garbage in, garbage out. If you want good results from AI, you need a solid data strategy and enterprise data layer. The more data – good data – that we can feed into the AI algorithms, the more useful they will become. That means we need accurate, harmonized data from all data sources across the continuum of care, including EHR data, machine data, and user-generated data.

This article synopsizes a recent ONC Report on the impact AI will have on healthcare. While recognizing some early AI successes, it also explores future challenges faced by organizations that want to realize its benefits. One significant danger: Putting AI projects in silos rather than looking at multiple AI projects holistically. (We’ve seen this happen before with population health and care management.) In an environment with multiple vendors,… Read More »

Trusted Data and Actionable Analytics in Healthcare

Thu, 04/26/2018

Did you know that real-time feedback about clinical, financial, and administrative metrics can provide extra visibility into the information that is most critical for your organization? And once you have that visibility, then your firm can maximize their productivity and effectiveness.

We have recently developed this cool asset that you may find interesting. It’s an eBook, and the topic is Success in Healthcare. The information in this eBook can be applied to almost any type of company that works with payers, providers, or clients.

Read this eBook and see great examples of what advanced technologies can be used to achieve a successful organizational strategy. Some of the real-world case studies should how to reduce costs, visualize performance metrics, and boost performance.

Download it here and let us know what you think.

Preparing for the next wave of Medicare Advantage enrollees

Thu, 04/19/2018

Created in 1965, Medicare is the federal health insurance program for people ages 65 and over, regardless of income, medical history, or health status. The program was expanded in 1972 to cover people under age 65 with permanent disabilities. The program helps to pay for many medical care services, including hospitalizations, physician visits, and prescription drugs, along with post-acute care, skilled nursing facility care, home health care, hospice care, and preventive services. The Medicare Advantage (Part C) refers to the Medicare program where beneficiaries can enroll in a private health plan, such as a health maintenance organization (HMO) or preferred provider organization (PPO), and receive all Medicare-covered Part A and Part B benefits and typically Part D benefits. Medicare spending accounted for 15% of total federal spending in 2016 and 20% of total national health spending in 2015.

Medicare enrollment is on the rise. According to CMS’s recent media release:

  • Medicare Advantage enrollment is expected to increase to 20.4 million in 2018, a nine percent increase compared to 2017… Read More »

A New Perspective on your Healthcare Data

Thu, 04/12/2018

Not a day goes by when I don’t receive an email or see an article about the importance of good data at the point of care. As a proponent of maximizing the value of data this is a hard point to argue against. While this represents a trend in terms of thinking about healthcare data, it isn’t clear if there is a payoff for most practitioners, even if it were more than just an idea or goal.  Why?

Since we recently opened the 2018 MLB regular season, now seems to be the perfect time to include a baseball analogy. It would be hard to argue against the concept that the seasoned baseball announcer represents the pinnacle of “knowledge at your fingertips” and its impact on the craft of calling a game in real time. The traditions of the game dictate that especially on the radio, there are a myriad of statistics on the players, the teams, the opponents, and the ballpark itself that shape the perspective of every moment of every game. The announcer is perched in the announcers booth next to the press box with his/her cheat sheet, books, notes, a computer, and a co-announcer (with the same tools available), ready to react with the ‘perfect’ commentary based on what unfolds on the field.

But is this really the scenario we want played out in the precious moments… Read More »

Information Builders Drives Healthcare Transformation at #HIMSS18

Thu, 03/01/2018

Every year at HIMSS, attendees are given a tremendous opportunity to learn from healthcare’s top experts. This year will prove no different as clinicians, executives, vendors, and IT professionals come together this March to explore the potential of the healthcare industry in 2018. Once again, you’ll find Information Builders talking about Omni-HealthData on the exhibition hall floor at booth #4069, eager to meet and discuss how the ways data can transform healthcare!

Information Builders Drives Healthcare Transformation at #HIMSS18

With the move to value-based and patient-centered care, now more than ever before, healthcare payers and providers need effective BI, analytics, and data management technologies. Only when information from across the healthcare ecosystem is integrated and validated to create a single view of the patient, can payers and providers make clear and data-driven decisions about operations and patient care. With this in mind, Information Builders launched Omni-HealthData in partnership with St. Luke's University Health Network at HIMSS last year.

We’re excited to continue down this path with St. Luke’s and even more thrilled to announce a new solution for healthcare payers… Read More »