Tag: hospitals

Business Intelligence: Data Warehouse

A data warehouse is a central database, which contains a collection of decision-related internal and external sources of data for analysis that is used for the entire company (Ahlemeyer-Stubbe & Coleman, 2014). The authors state that there are four main features to data warehouse content:

  • Topic Orientation – data which affects the decisions of a company (i.e. customer, products, payments, ads, etc.)
  • Logical Integration – the integration of company common data structures and unstructured big data that is relevant (i.e. social media data, social networks, log files, etc.)
  • Presence of Reference Period – Time is an important part of the structural component to the data because there is a need in historical data, which should be maintained for a long time
  • Low Volatility – data shouldn’t change once it is stored. However, amendments are still possible. Therefore, data shouldn’t be overridden, because this gives us additional information about our data.

Given the type of data stored in a data warehouse, it is designed to help support data-driven decisions.  Making decisions from just a gut feeling can cost millions of dollars, and degrade your service.  For continuous service improvements, decisions must be driven by data.  Your non-profit can use this data warehouse to drive priorities, to improve services that would yield short-term wins as well as long-term wins.  The question you need to be asking is “How should we be liberating key data from the esoteric systems and allowing them to help us?”

To do that you need to build a BI program.  One where key stakeholders in each of the business levels agree on the logical integration of data, common data structures, is transparent in the metrics they would like to see, who will support the data, etc.  We are looking for key stakeholders on the business level, process level and data level (Topaloglou & Barone, 2015).  The reason why, is because we need to truly understand the business and its needs, from there we can understand the current data you have, and the data you will need to start collecting.  Once the data is collected, we will prepare it before we enter it into the data warehouse, to ensure low volatility in the data, so that data modeling can be conducted reliable to enable your evaluation and data-driven decisions on how best to move forward (Padhy, Mishra, & Panigrahi,, 2012).

Another non-profit service organization that implemented a successful BI program through the creation of a data warehouse can be found by Topaloglou and Barone (2015).  This hospital experienced positive effects towards implementing their BI program:  end users can make strategic data based decisions and act on them, a shift in attitudes towards the use and usefulness of information, perception of data scientist from developers to problem solvers, data is an immediate action, continuous improvement is a byproduct of the BI system, real-time views with data details drill down features enabling more data-driven decisions and actions, the development of meaningful dashboards that support business queries, etc. (Topaloglou & Barone, 2015).

However, Topaloglou and Barone (2015) stressed multiple times in the study, which a common data structure and definition needs to be established, with defined stakeholders and accountable people to support the company’s goal based on of how the current processes are doing is key to realizing these benefits.  This key to realizing these benefits exists with a data warehouse, your centralized location of external and internal data, which will give you insights to make data-driven decisions to support your company’s goal.

Resources

Business Intelligence: Effectiveness

Non-profit Hospitals are in a constant state of trying to improve their services and drive down costs. Thus, one of the ways they do this is by turning to Lean Six Sigma techniques and IT to identify opportunities to save money and improve the overall patient experience. Six Sigma relies on data/measurements to determine opportunities for continuous improvements, thus aiding in the hospitals goals, a Business Intelligence (BI) program was developed (Topaloglou & Barone, 2015).

Key Components of the structure

For an effective BI program the responsible people/stakeholders (Actors) are identified, so we define who is responsible for setting the business strategies (Goals).  The strategy must be supported by the right business processes (Objects), and the right people must be assigned as accountable for that process.  Each of these processes has to be measured (Indicators) to inform the right people/stakeholders on how the business strategy is doing.  All of this is a document in a key document (called AGIO), which is essentially a data definition dictionary that happens to be a common core solution (Topaloglou & Barone, 2015).  This means that there is one set of variables names and definitions.

Implementation of the above structure has to take into account the multi-level business and their needs.  Once the implementation is completed and buy off from all other stakeholders has occurred, that is when the business can experience its benefits.  Benefits are: end users can make strategic data based decisions and act on them, a shift in attitudes towards the use and usefulness of information, perception of data scientist from developers to problem solvers, data is an immediate action, continuous improvement is a byproduct of the BI system, real-time views with data details drill down features enabling more data-driven decisions and actions, the development of meaningful dashboards that support business queries, etc. (Topaloglou & Barone, 2015).

Knowledge management systems fit into the structure

“Healthcare delivery is a distributed process,” where patients can receive care from family doctors, clinicians, ER staff,  specialists, acute care, etc. (Topaloglou & Barone, 2015).  Each of these people involved in healthcare delivery have vital knowledge about the patient that needs to be captured and transferred correctly; thus hospital reports help capture that knowledge.  Knowledge also lies with how the patient flows in and out of sections in the hospital, and executives need to see metrics on how all of these systems work together.  Generating a knowledge management distributed database system (KMDBS), aids in tying all this data together from all these different sources to provide the best care for patients, identify areas for continual improvements, and provides this in a neat little portal (and dashboards) for ease of use and ease of knowledge extraction (Topaloglou & Barone, 2015).  The goal is to unify all the knowledge from multiple sources into one system, coming up with a common core set of definitions, variables, and metrics.  The common core set of definitions, variables, and metrics are done so that everyone can understand the data in the KMDBS, and look up information if there are any questions.  The development team took this into account and after meeting with different business levels, the solution that was developed in-house provided all staff a system which used their collective knowledge to draw out key metrics that would aid them in data-driven decisions for continuous improvement on the services they provide to their patients.

1 example

Topaloglou & Barone, (2015) present the following example below:

  • Actor: Emergency Department Manger
  • Goal: Reduce the percentage of patients leaving without being seen
  • Indicator: Percentage of patients left without being seen
  • Object: Physician initial assessment process

 

Resources