How Does the Clinical Tool 'What's Going Around' Affect Clinical Practice

The epidemiological context of a patient's presentation can provide important information for clinicians to aid in diagnosis and treatment. The investigators previously developed and validated a syndromic surveillance tool for detecting influenza-like illness (ILI) encounters. The investigators then evaluated 40,642 outpatient ILI episodes during 'flu seasons' over 6 years. The investigators found that even after controlling for patient presentation and physician factors, the context in which a patient presented was strongly associated with the likelihood that an antimicrobial agent would be prescribed. Specifically, patients were less likely to be prescribed an antibiotic if they presented with ILI during the pandemic influenza period (when awareness of 'flu season' was very high), or after their physician had personally seen many patients with ILI in the prior week.

Currently, most clinicians have only limited access to data regarding the 'context' in which a patient presents. Under such circumstances, physicians are often unaware of local epidemiological information that could help them make optimal treatment decisions. In centers with advanced use of electronic health records (EHRs), it is increasingly possible to perform syndromic surveillance that is local (e.g. specific to a neighborhood or school district), current (e.g. updated daily), and specific to a patient's characteristics (e.g. age, chief complaint).

To that end, the investigators have developed algorithms for syndromic surveillance for a number of syndromes including Asthma, ILI, Pertussis, Group A Streptococcus Pharyngitis, and Gastroenteritis. These algorithms may provide contextual information that might be of use to clinicians.

The purpose of this study is to determine the effect of how a point-of-care clinical decision tool in the form of syndromic surveillance algorithms affect clinical decision making amongst outpatient health care providers and also patient outcomes. We will be using a 2 year look back prior to tool roll out as a comparison.

Specific Aims:

To determine the effect this point-of-care clinical decision tool has on clinical decision making amongst primary care providers.

To determine the clinical outcomes of patients whose physicians had access to these tools

To understand how these point-of-care clinical decision tools are used among healthcare providers in day to day practice

Inclusion criteria

All patients seen in a Northshore University HealthSystem outpatient clinic (Family Medicine, Internal Medicine or Pediatric) between the Nov 1 2013 to Oct 31 2014

Exclusion criteria

None