Ad. Kaluzny et al., PREDICTING THE PERFORMANCE OF A STRATEGIC ALLIANCE - AN ANALYSIS OF THE COMMUNITY CLINICAL ONCOLOGY PROGRAM, Health services research, 28(2), 1993, pp. 159-182
Objective. This study is designed to examine the effects of environmen
t and structure of the Community Clinical Oncology Program (CCOP) on p
erformance as measured by patient accrual to National Cancer Institute
(NCI)-approved treatment protocols. Data Sources/Study Setting. Data
and analysis are part of a larger evaluation of the NCI Community Clin
ical Oncology Program during its second funding cycle, June 1987-May 1
990. Data, taken from primary and secondary sources, included a survey
of selected informants in CCOPs and research bases, CCOP grant applic
ations, CCOP annual progress reports, and site visits to a subsample o
f CCOPs (N = 20) and research bases (N = 5). Accrual data were obtaine
d from NCI records. Study Design. Analysis involved three complementar
y sets of factors: the local health care resources environment availab
le to the CCOP, the larger policy environment as reflected by the rela
tionship of the CCOP to selected research bases and the NCI, and the o
perational structure of the CCOP itself. A hierarchical model examined
the separate and cumulative effects of local and policy environment a
nd structure on performance. Principal Findings. Other things equal, t
he primary predictors of treatment accrual were (1) the larger policy
environment, as measured by the attendance of nurses at research base
meetings; and (2) operational structure, as measured by the number and
character of components within participating CCOPs and the number of
hours per week worked by data managers. These factors explained 73 per
cent of the total variance in accrual performance. Conclusions. Findin
gs suggest criteria for selecting the types of organizations to partic
ipate in the alliance, as well as for establishing guidelines for mana
ging such alliances. A future challenge is to determine the extent to
which factors predicting accrual to cancer treatment clinical trials a
re equally important as predictors of accrual to cancer prevention and
control trials.