IT 101

It's rather interesting what passes for IT these days. "Healthcare IT" seems to refer to Microsoft Azyxxi, EMR's, health information exchange certifications, and telemonitoring from patients' homes all in the same breath.

So far, I think people think "healthcare IT" means a "monolithic on-premises application, derived most likely from MUMPS, that's HL7 compliant and too expensive to port to physicians' offices unless it's Vista in which case it's probably free but has shall-we-say a learning curve." Somewhat like the situation not too long ago with products and vendors such as SAP for ERP in the manufacturing field.

In manufacturing, market forces and the steady progression of real IT shaped the acceptance and use of a wide variety of products and systems to manage business processes. And still the major players came out ahead -- primarily because they were agile and because the business of IT supporting business is serious business.

Insofar as healthcare IT is at a crossroads today similar to that when mainframes went client/server, and again when client/server went web (and now that portals are going Web 2.0), it's probably a good idea to review the basics -- IT 101, as it were -- of what constitutes information technology, its adoption, and its evolution for a particular industry. For now, we see, the business of IT supporting the business of healthcare is serious, serious business.

Here's my hierarchy of information technology support levels for an organization:

• Infrastructure
• Applications
• Processes
• Technology
• Customer Service

Infrastructure support provides the "basal metabolism," as it were, for IT functions that are pretty much common across all industries.

Support for Applications addresses the differentiators that are important to healthcare to serve functions for service delivery (electronic medical record, imaging systems, patient bedside monitoring, CPOE, the standard stuff).

Support for Processes refers to the true purpose of IT implementation -- namely, effective use of technology and evolution of that effectiveness to help ensure that business processes succeed in their intended goals. (What is the business of a provider organization? What processes serve the business? What IT applications, and sequencing of those applications, ensure the success of those porcesses in serving the business?)

Technology support paves the way for agile, innovative "invocations" of the organization's fundamental business processes. As the technology grows and matures, so do the processes and their results improve. (What's the measure of improvement? Cost? Quality? Profitability?)

And finally, Customer Service rests at the pinnacle -- that is the true business of healthcare, is it not? and the true target of IT support for healthcare business processes.

There's a particular reason I find this hierarchy really helpful: when you look at IT this way, you can start to identify separate metrics for the different levels that let you assess the performance of your IT implementation choices based on the business performance they target. For example, try these measures for analyzing your IT systems, and for analyzing how they associate with measures of your business systems' performance:

• Infrastructure: Reliability, Efficiency
• Applications: Cost, ROI, Availability
• Processes: Effectiveness, Efficiency
• Technology: Cost-of-Conversion, Earned Value
• Customer Service: Responsiveness, Quality-of-Service

This way you can begin to understand the components of your IT installations, and begin to compare accurately the value and effectiveness of different implementations (systems, technologies, processes) that the IT organization serves. Now there's a way to measure business performance...

Patient Flow - OR in Healthcare

OR/MS Today recently published a good overview of an important Operations Research application in healthcare: Patient Flow: The new queueing theory for healthcare. The author, Randolph Hall, leads a progressive systems engineering group at USC, with research in queueing theory focusing on modeling, simulation, analysis, and optimization. Here is a general assessment from the article of how useful those techniques can be in a healthcare setting (large urban county hospital):

Healthcare systems can be changed for the better through a strategy that combines participation and creativity. But change cannot be sustained without vigilance and without analysis based on data. Herein lies the opportunity for the O.R. community. For instance, the O.R. community can work with hospital clinicians and administrators in these areas:

• Process modeling to ascertain how patients are currently served, to determine where inefficiencies exist and to prioritize future changes. Process modeling can reveal unnecessary repetition, miscommunication, and inconsistency in methods.
  
• Simulation modeling both to evaluate new processes and to understand and demonstrate the current causes of delay. For instance: simulating delays before and after, implementing a new appointment system, changing the methodology for assigning patients to beds, or implementing an electronic patient record system.
  
• Optimization can be used in many aspects of system design, such as scheduling nurses, scheduling operating rooms or facility layout.
  
• Queue analysis is invaluable when executed on a real-time basis to highlight the delays currently experienced throughout a hospital, and to make this information available to all key decision-makers, so that they can better understand delays both upstream and downstream, and act on these delays through reallocation of resources and appropriate prioritization of patients.

Queue analysis in this context is a springboard to other "downstream" optimization methods based on simulation, such as finite-horizon integer programming methods mentioned in the article for analyzing effects of surgery demand on hospital length-of-stay, or capacity analysis / revenue management methods and how these are specialized in the healthcare setting. The point is that these methods are now mainstream in a lot of service areas, and should be made so in healthcare analystics as well.