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Administrative Data Algorithms Can Describe Ambulatory Physician Utilization
Author(s) -
Shah Baiju R.,
Hux Janet E.,
Laupacis Andreas,
Zinman Bernard,
CauchDudek Karen,
Booth Gillian L.
Publication year - 2007
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/j.1475-6773.2006.00681.x
Subject(s) - medicine , concordance , ambulatory , ambulatory care , pharmacy , family medicine , medline , algorithm , primary care , health care , computer science , political science , law , economics , economic growth
Objective. To validate algorithms using administrative data that characterize ambulatory physician care for patients with a chronic disease. Data Sources. Seven‐hundred and eighty‐one people with diabetes were recruited mostly from community pharmacies to complete a written questionnaire about their physician utilization in 2002. These data were linked with administrative databases detailing health service utilization. Study Design. An administrative data algorithm was defined that identified whether or not patients received specialist care, and it was tested for agreement with self‐report. Other algorithms, which assigned each patient to a primary care and specialist physician, were tested for concordance with self‐reported regular providers of care. Principal Findings. The algorithm to identify whether participants received specialist care had 80.4 percent agreement with questionnaire responses ( κ =0.59). Compared with self‐report, administrative data had a sensitivity of 68.9 percent and specificity 88.3 percent for identifying specialist care. The best administrative data algorithm to assign each participant's regular primary care and specialist providers was concordant with self‐report in 82.6 and 78.2 percent of cases, respectively. Conclusions. Administrative data algorithms can accurately match self‐reported ambulatory physician utilization.

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