1:20 - 2:20 pmSaturday, September 6
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Developing a computer kiosk module for managing acute cough Illness at the VA Palo Alto Healthcare Systems - a pilot study
Lower Lobby
Developing a computer kiosk module for managing acute cough Illness at the VA Palo Alto Healthcare Systems - a pilot study
MD, VAPAHCS/Stanford
Microbial antibiotic resistance is linked to delays in appropriate care, increased costs of inpatient care, and excess mortality.  A root cause of this public health problem is non-selective use of antibiotics. ... Read more

Description

Microbial antibiotic resistance is linked to delays in appropriate care, increased costs of inpatient care, and excess mortality.  A root cause of this public health problem is non-selective use of antibiotics.  One way to address this problem is to incorporate a real-time decision support system to improve health care provider prescribing patterns for cough related illnesses. A novel interactive, self-service kiosk would allow patients to input information about their illness at the point of care.  Utilizing patient provided data, a decision support algorithm then generates tailored recommendations for health care providers. As a preliminary step, such patient information validation is assessed.

 

Program Objectives:

  1. Develop and deploy a prototype, and refine a patient and clinician driven decision support enhancement to aid in the proper treatment of specific patient clinical syndromes.
  2. Provide clinical decision support related to viral (influenza) treatment as one strategy for reducing antibiotic use.
  3. Assess the safety of a clinical decision support algorithm in practice. 

 

Methods:

Setting:  VA Palo Alto Healthcare Systems

Patients with chief complaints of “cough”, “cold” or “flu” symptoms were eligible to participate. Using an interactive touch screen computer kiosk, patients gave informed consent and completed health questionnaires regarding their symptoms and co-morbidities. A summary of the patients’ responses along with an evidence-based recommendation (based on CDC practice guidelines) was printed and given to the providers prior to seeing the patients. The ultimate decision to prescribe or not prescribe anti-influenza treatment and/or antibiotics was made by the health care provider.

 

Results:

  • A total of 42 patients have been enrolled in the study thus far.  The median age was 60 years old.
  • 32% of the patients who used the kiosk reported flu-like symptoms.  Of these patients, 7.7% were diagnosed with influenza. 14% of the patients reported risk factors for complicated influenza infection or spread to persons at high risk for influenza complications, for whom anti-influenza therapy is recommended by CDC. 46% of patients reporting flu-like symptoms were treated with antibiotics compared with 54% of patients who did not have flu-like symptoms. 

 

Conclusion:

The results provide a basic step towards validating the algorithm and subsequent levels of refinement would enhance kiosk efficacy. Such a novel, interactive device could assist patients in achieving more appropriate clinical management and encourage a greater acceptance of technologically-based clinical support interfaces.

 

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