Data and Measures

Setting and Data

The empirical opportunity to examine different mechanisms of network closure is provided by data that we collected on relations of patient transfer among members of a community of ninety-one hospital organizations located in Lazio, a large geographic region in central Italy with roughly 5.3 million inhabitants. In our analysis, we concentrate specifically on the transfer of in-patients. In-patients are individuals who have already acquired the status of “admitted patient” and, therefore, who have consented to follow the clinical and therapeutic paths proposed by professional medical staff who are clinically responsible and legally liable for their conditions. This is an important qualification because individual network ties induced by in-patient transfers are the outcome of

Network structure of interhospital patient mobility

Figure 15.2. Network structure of interhospital patient mobility.

organizational decisions over which patients have conceded control at admission. Of course, patients retain the right to refuse transfer in the same way as they retain the right to refuse treatment. However, they cannot choose where they will be transferred - a decision that remains a prerogative of the doctor in charge of the patient. Hence, the network structure of in-patient (henceforth, simply “patient”) transfer between hospitals in our sample can be legitimately seen - and modeled - as the outcome of a complex system of interrelated organizational decisions.

Using public data on transferred patients during the year 2003, we constructed a matrix of size 91 x 91. The matrix contains in each row/column, the hospital sending/receiving patients, and in the intersection cells, the number of patients transferred from the row to the column hospital (with zeroes down the diagonal). The overall number of patients transferred between hospitals is 13,178. The volume of transferred patients within dyads ranges from 0 to 525 patients, with an average of 1.6. The matrix of patient transfer relations is asymmetric because, for any hospital in the sample, the number of patients sent typically differs from the number of patients received; in other words, this is a directed network. We dichotomized the matrix by using the overall mean number of transferred patients as a cut-off value. Figure 15.2 illustrates the dichotomized version of the network induced by patient transfer relations between the hospitals in the sample. More detailed information on the sample and the institutional setting of the study is found in Lomi and Pallotti (2012).

< Prev   CONTENTS   Source   Next >