Implementing Rolling Forecasts in Healthcare: A Strategic Approach

As healthcare moves to a consumer-focused market and patients become increasingly aware of costs related to services, health systems are continuously trying to find ways to cut costs and react faster to data while still delivering quality care.  This is most evident in the Planning process; the number of clients moving beyond budgets to real-time Rolling Forecasts is on the rise because it allows organizations to think more strategically and quickly, and it enables them to better plan for future changes.

Moving from a budget to a forecast is a key decision that requires leadership to be aligned.  Three tenets to accomplish this are:

  • Leadership Alignment – how will the business get there?
  • Data Alignment – driver-based
  • Technology Alignment – can your system easily adapt from budget to forecast?

Leadership Alignment

Change is not easy to for any organization and trying to force change without leadership buy-in and alignment is nearly impossible.  Moving from a budget process to a rolling forecast can be very different for those involved in the process.  Effectively communicating the advantages and goals of the change is imperative for user adoption.  A solid communication plan and transition strategy is the first consideration and should focus on the following items:

  • Budgets generally outdated by the time submitted
  • Shift focus to key drivers to react quickly and limit user touch points
  • Modifications/updates made timelier instead of waiting until annual budget process
  • Being able to see immediate feedback to the forecast based on critical decisions allow organizations to be agile

Data Alignment

The real work comes in aligning data correctly to support a rolling forecast and is affected by how well a forecast is initiated while maintaining a rolling look of the data.  Clients often struggle with this because the “wall” approach of a budget offers a clear range on which to focus a view.

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A rolling forecast is always forward-looking based on relevant drivers and decisions.

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Another key decision is to outline how to ensure that accounts have clear alignment with drivers and/or processes as a rolling forecast progresses.  This can take time and should involve “superusers” to assist with adoption and training.  Below is a snippet of the tasks involved.

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Technology Alignment

Finally, the implemented solution should have the ability to operate in both worlds (budget & forecast) or easily transition from a budget to forecast when ready.  Oracle Enterprise Planning and Budgeting Cloud Service (EPBCS) is just that solution.

It is critical that systems be somewhat dynamic and provide the ability to use variables to prevent the need to manually maintain horizons.

EPBCS allows easy updates to the rolling forecast variables with just a few simple clicks.  The screenshots below illustrate how quickly updates to all variables can be made to support the next quarter.

Once completed, the forms show all the appropriate column updates using the necessary variables.

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If you are interested in understanding what it takes to move your organization beyond budgeting and leverage a rolling forecast concept, the Alithya team can guide you with a phased approach to help your business to think more strategically.

If you need more information or have questions about this topic, email us at infosolutions@alithya.com.  Subscribe to receive notifications about new posts.  Follow Alithya on social media for the latest information about EPM, ERP, and Analytics solutions to meet your business needs.

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Labor Budget Increases, Staffing Shortages Loom Large for Healthcare Execs in 2019; Set Expectations Now and Uncover Your Capabilities for an Enterprise-Based Labor Productivity Solution!

The two resounding topics on healthcare websites and in related blog posts:   (1) increased labor costs and (2) burnout or shortages of clinical staff.  The article published in “Healthcare Finance” Labor Budget Increases, Staffing Shortages Loom Large for Healthcare Executives in 2019 highlights this exact topic.

This isn’t surprising considering access to healthcare for all has increased; therefore, there are more patients to see which, in turn, requires more staff which results in increased labor costs…see where I’m going here? It’s easy to see how this can quickly become a major concern for providers to analyze and keep up with demand.

It becomes evident while working with numerous healthcare clients that not all healthcare companies are treated equally regarding their maturity scale when answering specific labor questions, providing/analyzing data, or even supporting a labor productivity solution. Edgewater Ranzal’s complimentary Healthcare Labor Productivity Assessment Workshop not only helps reset clients’ expectations, but also uncovers clients’ enterprise-based labor productivity solution capabilities.

Our solution utilizes Oracle Cloud or on-premise technology to help clients see an immediate return-on-investment just by analyzing contract agency usage statistics, providing detailed overtime analysis, and offering the ability to compare productivity across national standards that are loaded into the system. Additionally, we help clients align their labor productivity solutions with their planning/budgeting processes to improve budget detail and accuracy.  Comprehensive experience with data integration – often a challenging task for clients – allows us to work with staff to bring all the required data elements together to create a cohesive picture of labor productivity details.

Take a look at our webinar recording of The Key Ingredients to Understanding Labor & Productivity to learn more about our solution to uncover best practices in addressing labor productivity in your organization.  Then contact Edgewater Ranzal’s Healthcare experts to answer specific questions about implementing a solution to help cut labor costs and provide data-rich analytics to your organization.

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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When FDM Isn’t an Option…Using Essbase to Map Data

lots-of-arrowsThere are times when you do not have an option of using FDM to do large data mapping exercises prior to loading data into Essbase. There are many techniques for handling large amounts of data mappings in Essbase, I have used the technique oultined here several times for large mappings and it continues to exceed my expectations from a performance and repeatability perspective.

Typically, without FDM or some other ETL process, we would simply use an Essbase load rule to do a “mapping” or a replace. However, there are those times when you need to do a mapping based on multiple members. For example, if account = x and cost center = y then change account to z.

Let’s first start with the dimensionality that is in play based on the example below: Time, Scenario, Type, NOU, Account, Total Hospital, and Charge Code

Dimension Type Members in
Dimension
Members
Stored
Time Dense 395 380
Scenario Dense 13 6
Type Sparse 4 4
NOU Sparse 25 18
Account Sparse 888 454
Total Hospital Sparse 5523 2103
Charge Code Sparse 39385 39385

You then need to be able to identify the logic of where the mapping takes place.  I will want to keep the mapping data segregated from all other data so I will load this to a Mapping scenario (Act_Map).  I load a value of ‘1’ to the appropriate intersection, always level0.  Since the mapping applies to all Period detail I will load to a BegBalance member.  The client will then update this mapping file from a go forward basis based on new mapping combinations.

Here is a sample of what the mapping file looks like that gets loaded into Essbase:
NOU STATUS Revised DEPT ACCT # CDM Data
SLJ   IP            2CC      2         0012013         1
SLJ   IP            2CC      2         0012021         1
SLJ   IP            2CC      2         0012062         1

Here is what it looks like when you do a retrieve.  So for 4410CC->2600427->IP->67->SVM there is a value of 1 and for 4410CC->2600435->IP->67->SVM as well.

Essbase Mapping

The next step in the process is to load the actual data that ultimately needs to be mapped. I will load this data based on the detail and dimensionality I have, again at level0.  In my experience, the data is missing a level of detail (GL account for project based planning, Unit/Stat for charge master detail, etc.). So this data gets loaded to specific “No_Dimension” member via a load rule or a generic member. Again, I load this data to a separate scenario as well (Act_Load).

In the example below you will see I am loading Account detail (67 & 68 in the above screenshot) to the Stat_Load member. The data comes across missing the account detail.

essbase mapping

The final step is to calculate the Actuals scenario based on the two scenarios above. You will see that after we run the calculation, Current Yr Actuals is calculated correctly in that the data resides where it should reside.

essbase mapping

Keeping all the data segregated in different scenarios allows you to easily clear data should anything be wrong with one of the loads, thereby keeping the other datasets intact. This process runs on the entire year in less than 2 minutes and not only performs the calculation but also does an aggregation for the Current Yr Actuals.