Low back pain is virtually an epidemic in the United States. In many surveys, it is listed in the top 3 most frequent patient complaints resulting in a visit to a physician. It also appears to be more prevalent in the United States than in other industrialized societies, with only a muddle of theories available explain this costly difference. For this reason, a systematic methodology of evaluating the patient with back pain is clearly important. This would help the primary care physician, usually the first evaluate the patient, who is quietly worried that she or he might miss an ominous but uncommon etiology such as metastatic cancer. Also from the public health perspective, this methodology would help prevent multiple, unnecessary and costly imaging studies. And, in fact, many detailed evidence-based recommendations have been published over the years, going as far back as 1994.

While the availability of many evidence-based practice guidelines is of great benefit, the multiplicity also becomes a burden for the practicing physician who needs a quick and handy way to answer the question of what to do for a particular patient. Thus, the birth of a category of desktop and mobile applications named clinical decision support systems (CDSS). This growing and important sector bridges the gap between evidence based guidelines and clinical computer applications. Some of the larger players in this sector, such as Zynx Health, aim to integrate directly into the electronic health records (EHRs) used at hospitals. Others have opted for convenient, free-standing applications quickly available to the physician. The iPhone app Low Back Pain Clinical Management Guidelines is an example of the latter.

This app presents an algorithm using established guidelines for evaluating the patient with low back pain based on the patient’s history and a focused physical exam. [Editor’s Note: This app is based on 2007 guidelines from the American College of Physicians] It suggests when further imaging studies are necessary as well as providing broad criteria for detecting when the more unusual causes of lower back pain should be suspected, such as ankylosing spondylitis and metastatic cancer.

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While the very availability of such an application is quite welcome, its usability is clearly the largest factor in its success or failure, especially since it does not have the store-window advantage of being embedded in a larger clinical application. Here, unfortunately, the application design could have been improved. In particular, the organization of the screens was sometimes confusing and some of the more interesting information was difficult to find.

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What I liked:
  • addresses an important need
  • references important articles, explains statistics
  • quick reference to basic guidelines
What I didn’t like and What I’d like to see in future updates:
  • sometimes difficult to navigate in and out of the algorithm (screen flips and changes do not always make sense)
  • would be nice to have a couple of alternative navigation styles to find specific information (e.g. table or search)
  • embedded PDFs of some of the key articles in the literature
Conclusion:

Low Back Pain Clinical Management Guidelines puts some of the oldest and best developed evidence based clinical guidelines on the iPhone. One can imagine a clinician occasionally using this app to remind themselves of what to look for when a patient arrives with somewhat unusual back pain. Hopefully future versions will have an even more efficient navigation interface so that useful clinical information will be more quickly presented to a busy doctor.

 

iTunes: link

website: Clinically Relevant Technologies