Qualitative and Quantitative Analysis

Prior to embarking on a process improvement project around diabetic foot infections (DFIs) at your institution, it is imperative to understand the epidemiology and characteristics of the local population. Unlike other at-risk populations, administrative coding for diabetics with soft-tissue disorders may be poorly defined. For example, a first step in QI/process improvement includes defining the target population. In the case of congestive heart failure, pneumonia, or myocardial infarction, administrative databases and coding programs posses discrete identifiers that are conducive to establishing a denominator. In the case of DFIs, there is no discrete ICD-9 code or MS-DRG that can be queried. The DFI patient may be hidden in administrative databases under the following codes or combinations of codes.

Once the patient population is identified in the administrative database, drilling down to establish baseline characteristics of the population becomes much less labor intensive. Understanding who is providing the care to the population and how “well” they provide that care allows the team to make targeted interventions and garner resources from administration. This helps the team make the case for a quality improvement project budget.

The following table illustrates one way to present demographic and administrative data to stakeholders:

434 DM Foot Infections Froedtert Memorial Lutheran Hospital 2006–2007 (submitted by Michael Radzienda, MD)

Depending on the institution, baseline data might also include the following measures: mortality, ICU days, readmission rates, ADEs, transfusion requirements, antibiograms, radiology utilization, angiography utilization, and so forth.