Don’t Let Incremental Overtime Plague Your Healthcare Organization!

Get to the Root Cause: Increase Productivity and Patient Care While Reducing Labor Costs

The Causes and Consequences of Incremental Overtime

Incremental overtime may be costing your healthcare organization thousands of dollars unnecessarily and result in decreased employee morale and poor productivity, so it’s important to understand its root causes by gaining the ability to track overtime. A Labor Productivity/Labor Management solution that delivers key analytics provides specific answers to the root causes of incremental overtime.  Common causes include:

  • Early clock-in/late clock-out
  • Inability to complete required tasks by end of shift
  • Shift transition conflicts (i.e. last minute attending to patient needs or handoff not yet completed)

The Solution and its Benefits

A Labor Productivity solution provides data for labor hours so that ratios can be derived based on each organization’s definition of incremental overtime, and this leads to a clear understanding of the root causes of incremental overtime so that corrective action can be taken, including:

  • Ensure management visibility at change of shifts
  • Employee coaching/staff meetings to aid time management skills
  • Provide daily reports/analysis to managers to establish protocol for handling incremental overtime risks
  • Designate a synchronized clock that employees should rely on (i.e. department wall clock)
  • Educate employees on OT authorizations – cite repeated behavior in performance evaluations

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By addressing the causes of incremental overtime using data provided by a Labor Productivity solution, providers can deliver great patient care while decreasing labor costs by thousands of dollars and increasing productivity.

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Standardization of Comparative Analytics in Healthcare

A Comprehensive Solution for Value-Based Care

As healthcare providers are quickly consolidating and purchasing smaller health systems, standardization is paramount to enable comparative reporting across organizations or sites that facilitates changing attitudes, decreased costs, and better, more cost effective care. Provider systems need to operate independently using a standardized enterprise system process to effectively make decisions around costs, health outcomes, and patient satisfaction.  Without standardization, the analysis of metrics can require considerable work and time and create issues when comparing like sites since appropriate metrics can mean totally different things at the underlying base member calculation.

A standardized solution is simple – an enterprise-based model that allows data to be shared across systems and applications to facilitate comparative analytics with data integrity:

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Such a solution offers the ability to compare productivity indices across departments against national standards using a standard calculation approach with federated master data across all toolsets, resulting in comparative analytics to drive efficiencies and value-based care:

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Upgrading Oracle Business Intelligence to 12c

Ranzal was recently invited to participate in a number of chalk talks for the Healthcare Industry User Group (HIUG) in San Antonio, TX. One of these chalk talks covered how an organization should prepare for and execute an upgrade to Oracle Business Intelligence (OBI) 12c.  Since the technical steps are already covered in numerous blog posts as well as Oracle documentation, our conversation focused on a strategic approach to the upgrade.  Our conversation essentially came down to four topics:

  1. An overview of the simplicity of the upgrade from 11g to 12c
  2. Organizational mindset while preparing for the upgrade
  3. The new technical infrastructure and the implications for the organization
  4. How to introduce users to the new features and how this might impact governance

We wanted to formally document this lively and fast-paced discussion to help other organizations as well as the HIUG chalk talk participants who were furiously scribbling notes and may not have had the opportunity to take it all in.

We started our discussion with how relatively easy Oracle has made this upgrade. For those of you who experienced the difficult and buggy process of upgrading from OBI 10g to 11g and may be dreading the upgrade to 12c, we have some advice:  relax.  First, the upgrade to 12c is an “in place upgrade” which means your 11g environment remains intact while the metadata and configuration gets “lifted and shifted” into 12c.  Speaking of “lift and shift,” 12c comes with a tool that extracts the metadata and much of the configuration from 11g into one tidy package that is then pushed into 12c.  There is a small amount of manual configuration that has to occur; however, this will only slow down customers with highly customized environments.  Once this lift and shift has occurred, an Oracle validation tool checks that your Dashboards and Analysis are working and alerts you to potential issues.  While there are bugs with 12c (what new or old software does not have bugs?), we have not found any major issues that will cause a full stop for an organization.

So how does an organization prepare for this upgrade? First, we encourage clients to view this upgrade as an opportunity to “clean house,” especially for customers that have been building OBI assets for years.  Used properly, analytic tools lend themselves to experimentation and evolution.  Experimentation can result in partially formed or broken logical objects such as presentation columns and facts, Analysis, or entire Dashboards.  The developers of these objects have the best intention of coming back to either fix or complete development on these objects or, at the very least, delete them.  Developers are busy people though, and eventually the existence of these objects is forgotten.  Evolution of both the tool and the focus on analytics results in objects becoming stale and/or obsolete.  Take this opportunity to clean house on your OBI environment.  Run the consistency check in the BI Administration tool and resolve those lingering issues.  Evaluate your usage statistics and determine if unused Analysis and Dashboards are still needed.  Fix or discard broken Analysis and Dashboards.  As with any technology tool, have a process in place to document, communicate, archive, backup, and restore, if necessary.

The most substantial change to come with OBI 12c is the underlying technical architecture. Fusion Middleware and Enterprise Management has a new look and feel.  Additionally, some actions are no longer performed within these tools.  For instance, deploying the RPD is no longer done through Enterprise Manager (in fact, the RPD is now the BAR file).  The directory has significantly changed which is a bit unfortunate for those of us who like to go directly to the log files in the directory rather than relying on Enterprise Manager and Session Manager.  Finally, many of the RPD . . . that is . . . BAR functions, such as deploying and copying, are done through a new command line interface.  So, while most of your users will be able to log into 12c and quickly adapt to the new look and feel, your OBI support team will have some learning to do.  Again, the goal of this post is to provide an overarching upgrade strategy, so we will not delve any deeper into these changes.  There is plenty of quality content online regarding these changes and you should always review Oracle documentation before performing implementation or upgrades.

End users will initially feel that, with the exception of a new look and feel, nothing much has changed. However, with new graphing options, statistical analytics capabilities based on R, as well as Visual Analyzer, users have an opportunity to expand their analytical capacity.  The organizational challenge is to go back to the change management playbook that was used when OBI was initially introduced, re-evaluate, and update so that end users can get the most out of this upgrade.  Evaluate how to train users on where to properly use the new graphs and charts.  Determine (or re-determine) who your power users are who need or want the new statistical capabilities.  Review existing Dashboards and Analysis and make appropriate upgrades.

Potentially the biggest challenge will be evaluating and understanding the capabilities of the new Visual Analyzer tool which, among other features, allows you to perform data mashups. This new tool will require that your organization determines some use cases and user groups as well as some additional training.  While users uploading data into the OBI system and combining it with existing data models opens up entirely new possibilities for insight, it also creates a governance challenge.  How do you separate and maintain the organizational “one version of the truth” while encouraging and properly promoting new analytic insight?  How will security be handled and users trained to adhere to this model?  How will you handle the archiving and deletion of potentially huge numbers of Excel spreadsheets uploaded onto the OBI server?  While this all sounds intimidating, keep in mind that your organization has already been through these exercises once during the original OBI implementation.  Adapt your existing knowledge.

Thus far, Ranzal has had a positive experience with the 12c upgrade. The underlying technical architecture has resulted in some real gains in performance, especially when leveraging EPM as a data source.  The upgrade is well thought out and simple, especially if you go through a system checkup and resolve issues.  While your technical BI support team will have some homework and learning to do to continue to fill that role, your users will be able to jump right into using 12c.  Despite this ease of user adoption, be sure to have a change management plan in place and take advantage of the new features and capabilities of 12c.

If you are thinking of doing an upgrade and have questions, feel free to reach out to us. Also, keep an eye out for an upcoming webcast on upgrading to 12c with an interactive question and answer session.

Data Discovery In Healthcare — 1st Installment

Interested to understand how cutting edge healthcare providers are turning to data discovery solutions to unlock the insights in their medical records?  Check out this real-world demonstration of what a recent Ranzal customer is doing to unlock a 360 degree view of their clinical outcomes leveraging all of their EMR data — both the structured and unstructured information.

Take a look for yourself…

Data Discovery In Healthcare

A few days ago, QlikTech and Epic announced a technology partnership that will strengthen the integration between their software products as well as provide a forum for their joint customers to share best practices and innovative ways to use both technologies.

For a firm like Ranzal who is currently implementing several population health discovery applications, my first reaction was simply that this partnership made sense.  Both companies are leaders in their respective domains and are very well-regarded.  Beyond that, discovery technologies like Qlik, Tableau and Endeca are quickly establishing a foothold in the blossoming domain of healthcare analytics.  Unlike traditional BI technologies, data discovery tools are meant to quickly mashup disparate datasources and allow users to ask in-the-moment, unanticipated questions.  This alternative approach to analytics is allowing healthcare providers to build self-service discovery applications for broad audiences at speeds unimaginable in the world of the clinical data warehouse.  Since almost all healthcare analytics applications rely on data from the EMR, this partnership seemed natural, if not overdue.

My second reaction was that there was something missing.  In my experience, to get a holistic view of the health system, all of the relevant data must be tapped.  Data discovery on structured data, while powerful, can only tell party of the story.  With 60% of a health system’s data is tied up in unstructured medical notes, reports and journals, Qlik is not fully equipped to allow healthcare practitioners to gain a 360 degree view of their health system.

Endeca shines when structured and unstructured data are both required to paint a complete picture.  In healthcare, properly analyzing clinical data can mean drastically better outcomes at lower costs.  Understanding the “why” behind the “what” means properly tapping the narratives in the medical notes and tools like Endeca are best suited to unlock value when unstructured is prominent.

QlikView is a powerful tool and one cannot question its ease of use and numerous discovery features.  However, in industries rife with unstructured, products like Endeca that treat unstructured as a first class citizen (in the way it acquires, enriches, models, searches, and visualizes unstructured) are better suited to unlock the whole story.

So, I couldn’t help but think that a strong partnership could also be made between other EMR vendors with Oracle Endeca.  We spend a lot of time sizing up the relevant technologies in the data discovery space trying to understand differentiators.  For the types of discovery we’re seeing healthcare when unstructured is necessary to tell the whole story, our money remains on Endeca.