For the dissimilarity metric I would suggest manhattan, as provided by dist (base package), daisy, agnes (both cluster package), for in your case a common "0" is meaningful - means that both pysicians didn't see the patient.

 

When using complete linkage you can see exactly how many patients (seen or not seen) the pysicians in one cluster have at least in common. If the height goes up too fast so that you would have to extract to many clusters you can use average linkage.

 

For the clustering you can use hclust from the base package, agnes from the cluster package, or, when hclust or agnes run out of memory, clara (see thread  [R] cluster analysis for 80000 observations)

 

sincerely, Markus

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Markus Preisetanz

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