Today I spoke in a webinar entitled “Using Core Measures to Jump-Start Enterprise Analytics”. During this presentation I covered a number of topics around business intelligence in healthcare and specifically around an approach called targeted analytics. I reviewed some of the options available today to healthcare organizations and provided an example of building an enterprise BI platform using core measures analytics as the foundational application.

You can view the slides below. You can also view a recast of the webinar here: http://www.perficient.com/webinars/

Let me know what you think!

See this slideshow on SlideShare.

Business Intelligence for healthcare is a hot topic right now. Just about every list of top priorities for healthcare organizations includes business intelligence or analytics. This was evident during the recent HIMSS Conference, where the number of options presented by vendors was impressive.

So this begs the question: “What is the best approach for implementing Healthcare BI at your organization?”

FACTORS INFLUENCING YOUR BUSINESS INTELLIGENCE APPROACH

Fortunately or unfortunately, there isn’t one best answer to this question. There are a number of factors that would influence the approach to be used including, but not necessarily limited to:

• Is this the initial journey into business intelligence for your organization?
• Is there enterprise support for business intelligence (i.e. is it one of the stated business goals for the year?)
• Do you have an overall business intelligence strategy?
• Are the critical business issues for which business intelligence could provide immediate benefits?
• Is your organization prepared for business intelligence? Do you have the right skill sets, governance and processes to support a BI initiative?
• Do you currently have business intelligence technology in-house that will support your objectives?

The answers to these questions will drive the best approach to business intelligence for your organization.

HEALTHCARE BUSINESS INTELLIGENCE OPTION

There are many options to business intelligence for healthcare organizations. The diagram below highlights several of these options:

WHICH OPTION IS RIGHT FOR YOUR ORGANIZATION?

Each of the options above has strengths and weaknesses. For example, a package application might work well for your organization if it offers the majority of the analytical capabilities you need. However, if you are looking for something that is highly customizable or that is unique to your organization, it might not be the best choice.

Additionally, the different options are not necessarily mutually exclusive. An enterprise healthcare business intelligence platform might take components from several options to provide the required capabilities. For example, the business intelligence solution provided by your clinical transaction system vendor might provide the clinical reporting and analytics capabilities you need, but might need to be augmented with other components to provide the remaining required capabilities (ex. Financial or operational analytics).

Even within each option, there are different approaches to consider. Many organizations take a prototype approach, especially if it is their first foray into business intelligence.

As you can see, options abound for healthcare business intelligence. Choosing the right approach and option are critical first steps to success.

Do you have any questions about what business intelligence approach is best for your organization? Let us know, and we’d be happy to help. We would also like to invite you to attend our April 21st webcast: Jump Start Your Healthcare Enterprise Analytics with Core Measures. We will demonstrate how top healthcare organizations are realizing the benefits of data analytics in such core areas as core measures, clinical alerting, surgical analytics, service line profitability, diabetes management, revenue cycle management, claims management and utilization. Register Today

You can also see us today in Las Vegas at IBM Impact. We are in the Industry Zone at IZ-4 or check out our IBM Impact landing page.

Looking through the sessions at HIMSS 2011, one can see a wide range of topics related to business intelligence and analytics. From different uses for BI to different types of presentation vehicles to the potential of use predictive analytics, one will not be at a loss for finding something analytics related to sink their teeth into. It finally looks like organizations are truly realizing the power that leveraging their data can bring them.

However, in the rush to pursue analytics, organizations must realize that the value it can bring is directly related to the quality, timeliness, completeness and accuracy of the underlying data. Putting analytics on bad data is like putting lipstick on a pig. No matter how much you dress it up, it’s still a pig. In fact, putting analytics on inaccurate, incomplete or stale data can often be worse than not having analytics at all. Consider the situation in which clinicians are using near real-time analytics to help improve outcomes. Bad data will have a negative effect on the analytics presented, but, more importantly, it can have a negative effect on patient safety.

So does this mean that organizations should be hesitant to pursue analytics? Not at all. The benefits to be derived in a competitive healthcare landscape are far too great not to be using analytics to its fullest potential. What it does mean is that just as much care should be taken to put in place a framework to insure the accuracy and completeness of the data. To this end, organizations should consider the following critical aspects of healthcare business intelligence in addition to the reporting and analytics capabilities.

Governance

This is a term that often receives bad press. Many organizations have tried to implement enterprise governance and failed, while others don’t know how to get started. To understand how critical this is, find someone at HIMSS 2011 who works for an organization that has successfully implemented this. I suspect they will tell you the effort was well worth it. Governance provides the enterprise view necessary to truly implement work class analytics.

Master Data

This is another area in which many organizations have either neglected putting the effort into or have done so with a very narrow focus. Master data is the glue that binds organizational data. From common definition for core functional domains (ex. Patient, Physician, etc.) to enterprise hierarchies (roll-up or aggregations of data) to standard reference data (Ex. diagnosis codes, procedure codes, etc), having enterprise master data drives improved analytics.

Data Integration Framework

Having high-quality, timely and accurate data is the foundation for analytics. Data is being derived from more sources today than ever before. From internal clinical, financial and administrative systems to industry organizations to HL-7 messages to manual data, the integration of data in healthcare can be a daunting task. Many organizations are feeling the effects of building so many point solutions in the past. However, the integration of data does not have to be as complex as some make it out to be. Having a strategy in place that clearly defines an integration roadmap and implementation framework, doing the proper analysis and quality checking and taking an incremental approach to implementation reduces the effort and risk.

Phased Roadmap

In the rush to implement analytics, many organizations bite off more than they should. The big-bang approach doesn’t work. It is a much better approach to create a strategy and roadmap that allows for a phased implementation of analytics based on business priorities. This not only allows for the faster realization of critical analytics capabilities, but also provides the flexibility to react to changing priorities and business conditions.

Analytics are an essential component to any world class healthcare organization. However, care should be taken to ensure the proper foundation is put in place to ensure you realize the full benefits.

As I look over the various sessions and presentations for the 2011 HIMSS conference, I’m excited to see an increased focus on data governance as a topic. At the same time, I ask myself “is it enough?”

Data governance in healthcare (especially in the provider space), has often been a neglected and forgotten critical component for success. Organizations are either too silo’d, have distributed operational authority, or have resources spread so thin to effectively address governance. Unfortunately, not implementing governance is just perpetuating operational inefficiencies, driving up costs and maxing out resources.

So why are healthcare providers in this situation? Taking a look to the past offers a glimpse into their current situation.

Growing Through Mergers and Acquisitions

Often, providers have grown through acquisitions of or mergers with other facilities and organizations. While this provides increased economies of scale, broader/deeper clinical expertise and increased presence/prestige locally, geographically and nationally, it has also created some of the most common challenges providers are experiencing today. Care has not always been given to ensure that all aspects of integrating the acquired/merged organization are addressed. Often, the acquired/merged organization continues to largely operate as an independent entity from an operational, administrative and/or technology perspective. While this offers tremendous benefits in some areas, it does create challenges in others. Duplication of effort, data and applications create operational inefficiencies, drive up costs and even can lead to decreased patient satisfaction.

Narrow Focus of Application Selection and Implementation

As provider organizations have selected and implemented applications, care has not always been taken to ensure that they have an enterprise view and integrate well with other parts of the organization. Even with something as critical as an EMR, it has often focused with only the clinical side of the house in mind (and sometimes with a too narrow focus even within the clinical world). Not addressing the enterprise aspect of applications leads to the same challenged noted above.

Best of Breed Application Strategy

Many organizations have pursued a “best of breed” application strategy in the past vs. an enterprise platform. There are pro’s and con’s to each approach. However, when pursuing a best of breed application strategy, the necessary steps have not always been taken to ensure proper integration and interaction between applications. This has often led to point solution integration, increased manual effort to report and analyze data across systems, redundant processes and increased support costs.

And things aren’t getting any simpler. Healthcare organizations are experiencing change at a more rapid pace than ever. Things such as implementation of EMR’s, EMPI’s, Health Information Exchanges, government regulations, 4010/501 and ICD-9/ICD-10 migrations etc. are pushing organizations to the limit. They are starting to feel the effect of not taking an enterprise view of operations, applications and data in the past. Many organizations have realized the need for governance to drive the enterprise view and reaping the benefits in the form of more efficient operations, reduced costs, increased patient satisfaction and quicker application implementations. Unfortunately, others have not yet gone down this path. They continue to develop point solutions, fail to properly integrate acquired/merged operations and not give the proper focus on the enterprise view.

I’m hopeful that the increased focus at HIMSS 2011 will cause these organizations to see the tremendous benefits that governance can bring. I’m just concerned that the message might not be received. We would love to meet you and discuss Business Intelligence and Data Governance in Healthcare. If you are interested in learning more about how to become a more viable and world-class healthcare system, please visit us at our HIMSS Booth #3681.

An enterprise master patient index (EMPI) is the glue that holds together all things patient related. It provides the foundation for improved patient safety and outcomes, as well as a positive patient experience. The issue I’ve seen is that a lot of healthcare organizations don’t havea comprehensive, consistent, EMPI.

So why are organizations in this situation? There are a number of reasons, including:

Growth through Acquisition

Many healthcare organizations have grown through the mergers with, or acquisitions of, other healthcare facilities. However, in many cases, they haven’t fully integrated the clinical, administrative or operational transaction systems to a common platform. This often results in patients having different identifiers for different facilities of the same overall healthcare organization.

Silo’d Nature of Healthcare Organizations

I’m sure the following statement will cause some controversy. Many healthcare organizations are highly silo’d in nature and the silos often don’t collaborate well. Agreeing on a common, EMPI definition requires strong collaboration between all the major players across the organization. A strong governance function facilitates this, but most organizations don’t have such a group driving this type of enterprise view.

Best of Breed Application Strategy

Historically, a lot of healthcare organizations have purchased their core transaction systems taking a best of breed vs. an integrated platform approach. I’m not expressing an opinion that one approach is better than the other, but additional care needs to be taken to ensure system inter-operability when implementing applications from different vendors.

Lack of Priority or Resources to Implement an Enterprise Patient Identifier

In many cases, the implementation of an EMPI just hasn’t reached a higher enough priority level. Over the past several years, healthcare organizations havebeen under a number of competitive, regulatory and cost pressures that they perceive to require focus elsewhere. Ironically, an EMPI would benefit in each of these areas.

The impact of not having a common EMPI can be significant. As noted above, healthcare organizations are under pressure to reduce costs, attract patients and comply with new (and often ambiguous) government regulations. Not having an EMPI can make addressing these pressure much more complicated. The lack of an EMPI can potentially result in:

Reduced Patient Safety and Less Optimal Outcomes

Not having all the pertinent information on a patient (or even worse, having conflicting information) can result in inefficient treatment or even treatments that can result in negative consequences. Often patients are not in a position to fully inform the clinician of their medical backgrounds and the clinicians must rely on the information they have, which can be incomplete if all the patient information isn’t tied together.

Increases Administrative/Operational Costs

When patient information isn’t well integrated, it often takes significant time and effort to manually collect and organize the data into a usable form. This can result in significant cost for the resources to perform this activity.

Decreased Patient Satisfaction
When patients visit a healthcare facility, they are usually concerned with a specific health related issue that they are facing. Having to deal with providing personal information they have repeated given in the past or correcting information in the systems can be frustrating and stressful. The reduced patient satisfaction that can result may cause some patients to consider healthcare provider alternatives.

The good news is that most healthcare organizations have realized the criticality of having fully integrated patient information and the importance an EMPI plays in doing so. Some have either implemented an EMPI or are well on the way. However, there are still many that have not begun the journey or are stuck in the implementation. There are a number of things healthcare organizations can do to help ensure the success in implementing an EMPI:

Make Sure All the Key Players Are On-Board

The “E” in EMPI stands for Enterprise. While this might seem like a silly statement, organizations often still take a silo’d view when implementing an EMPI. Clinical, financial, administrative, operational and research groups all have a vested interest in ensuring the EMPI will meet their needs.

Consider Implementing a Governance Function

When you bring together the diverse groups necessary to implement an effective EMPI, there are going to be conflicting opinions. A governance function can provide the structure, direction and decision making authority to help breakthrough roadblocks that arise. Any governance function created needs to have representation for the all impacted parties.

Have a Strategy (a.k.a. Do the Necessary Upfront Planning and Analysis)

Implementing an EMPI is not a task for the faint of heart. Years of silo’d applications, conflicting opinions of how the EMPI should be defined and dealing with poor data quality can lead to frustration and failure. Trying to go directly into implementation without doing the proper due diligence will significantly increase costs and the chances for less optimal results. Fully understanding the current environment, having a clear vision of the end game and creating a realistic and pragmatic roadmap will make the journey much easier.

Take a Phased Approach

Implementing an EMPI is not an overnight activity. It can take significant time and resources to do properly. Issues will arise, business priorities will change, resources will be pulled in multiple directions. Short implementation cycles with clear goals and deliverables will allow for the flexibility to deal with the challenges that arise.

An EMPI offers substantial benefits. Having the right approach and framework in place is critical to success. It’s not an easy journey, but the payoff will justify the trip.

The healthcare world is in the middle of a data revolution of sorts. Both providers and payors are starting to realize that their transactional systems contain a wealth of data that can be used for strategic advantage. Many organizations are spending considerable time and resources in standardizing, cleansing and remediating data issues in their transactional systems to be able to leverage this data to drive improvements in quality of care, financial efficiencies, operational effectiveness and innovative research. However, in many cases, organizations are potentially missing one of the most critical components: the integration of clinical and financial data.

Both provider and payor organizations individually realize the value of their data. However, even in the case of a provider with a health plan, both sides tend to view their data in isolation, thus missing the benefits of integrated data. Integrated clinical and financial data offer a wide range of benefits, including the ability to have a:

More Complete View of the Patient Experience
In today’s competitive healthcare landscape, the patient experience cannot be underestimated. Consumer’s have increasing choices of where to get their healthcare services (hospitals, private practitioners, community health centers, urgent care facilities, etc.). If there isn’t a significant difference in the cost and/or quality of care, consumers tend to go to where they feel comfortable.

Comprehensive Cost Picture vs. Outcomes
For years, healthcare organizations have been trying to understand the true cost of the services provided. The increased focus in areas such as surgical analytics, materials management, etc. are attempts to gain an understanding of the cost of treatment choices made vs. the outcomes derived. However, this focus only goes part way. A true comprehensive cost vs. outcome analysis requires including the health insurance side of the equation. By having this complete picture, organizations can drive costs down without impacting quality of care. In fact, in many cases, the costs go down while the quality care goes up. Consumers are savvier today than in the past. With the wealth of comparative information available today, consumers can make more informed decisions on where to get their healthcare services.

Complete Longitudinal Record of a Patient
Statistics show that people are receiving more healthcare services today than they have in the past. Additionally, there is a greater emphasis on preventive care as part of an individual’s healthcare plan. Understanding the complete lifecycle of a patient thus becomes critical in developing and evaluating a patient’s progress. While the clinical systems provide a great deal of the base information for a longitudinal view of a patient, health plan data can complete the picture and provide additional insights that might not be apparent with a clinical system only view.

So why haven’t more organizations pursued integrated clinical and financial data? There are a number of reasons I’ve heard over the past couple of years. For some organizations, the provider and payor worlds use different terminology and it’s difficult to create the link. For others, it’s the perceived cost vs. payback to integrate the data. While for others, it’s the lack of prioritization for such an initiative. Whatever the reason, the cost of not having the integrated view can result in significant adverse consequences. Examples include:

No Real Way to Tie Comprehensive Cost to Outcome
Without a comprehensive cost picture, informed decisions on equipment and materials usage, treatment protocols, etc. vs. outcomes cannot be truly and objectively be made. This can result in significantly higher treatment costs that do not result in improved outcomes.

Inefficient Claims Processing
Without a common terminology between provider and payor, claims processing costs can be significantly higher than necessary. Double processing of claims, increased claims administration, etc. can drive up overall cost and reduce profits.
Increased administrative costs on both sides due to inconsistent interpretation of data
As an extension of above, inconsistent terminology can significantly increase administrative costs on both the provider and payor side. Investigation of differences, reconciliation of results, etc. can require significant person-hours to perform the necessary activities.

Decreased Patient Satisfaction
Most people at one time or another have probably dealt with the hassles with insurance claims. Something as simple as trying to tie an Explanation of Benefits statement to the services provided can be demanding. With the choices offered to consumers today, frustrating consumer experiences can drive patients to investigate alternative providers and insurance providers.
The good news is that the organizations are starting to realize the benefits of integrating clinical and financial data. This fact, coupled with increasing competitive and regulatory pressures, is driving organizations to act on initiatives to provide more coordination and integration of the clinical and financial data. Examples include:

4010/5010 – Expanded HIPAA codes shared between the two sides

ICD-9/ICD-10 – Expanded diagnosis codes shared between the two sides

Health Information Exchanges – Intra- and inter-provider/payor sharing of patient information

Outcome Based Medicine – Push to base compensation/reimbursements on outcomes or Pay for Performance

Advanced analytics on chronic disease management with new ICD-10 code granularity (more detail equals more sophisticated analysis)

The bottom line is that, although some organizations are starting to realize some of the benefits of having integrated clinical and health plan data, the leaders are exploiting this data for their strategic advantage. Organizations that are not actively pursuing this strategic approach will be at a competitive disadvantage. As the pressures increase to control administrative costs and spend more on clinical outcomes, integrated clinical and financial data will rise to the top of organizational priorities.

Analytics can offer a wide range of benefits to healthcare organizations. It can provide information to make better decisions on or impact quality of care, patient outcomes, cost containment, operational efficiency and regulatory compliance. At a theoretical level, healthcare organizations understand these benefits. In fact, implementing analytics is on the top ten list of many healthcare organizations today. Ironically, most aren’t pursuing it to the level they need. So what’s stopping them? I’ve heard a number of different reasons over years and found that many are based on assumptions that simply aren’t true:

“Analytics are expensive and I don’t have the budget”

It’s true that enterprise analytics can be expensive over the long haul. However, when done properly, they can (and should) offer payback far more than the investment. Additionally, getting started doesn’t always require a large investment. There are tools and technologies available that allow you to test out analytics at a relatively low cost. Using these tools also allow you to see what technologies will and will not work for what you want to do.

“Analytics are a major undertaking and we just don’t have the time to do it right now”

Getting started on analytics doesn’t have to be a huge undertaking. In fact, it’s often best to start out targeting a specific area in which there is immediate business value. This allows you realize the ROI of the analytics application, as well as work out any issues in a localized fashion.

“I can’t convince others it worth the time or money”

You can present all the figures, whitepapers, articles, etc. and some people will still not understand the benefits of analytics. However, if you show an application of analytics targeted at solving a current problem they are facing, they suddenly get interested. People react better to something actually demonstrates solving their problems vs. reading theoretical material.

“The last thing we need is another silo’d application”

Building an analytics application targeted at a specific business problem doesn’t have to mean that it’s an end point. With the right approach, targeted analytic applications can be built in such a way to be easily expandable to other subject areas or even to the enterprise.

You can see from above that many of the assumptions people have regarding analytics are simply not true. While is always nice to have an unlimited budget and timeline for a project, we all know that never happens. Check back for future blogs on what I call “Targeted Analytics with an Enterprise View”. In these posts, I will be discussing an approach that can be highly effective in getting started on analytics and driving excitement about it in an organization.