Computer-assisted test interpretation: considerations in patient care

Sirenomelia and cyclopia cluster in Cali, Colombia

Sirenomelia and cyclopia share etiologic and pathogenic characteristics. A cluster of these two patterns of malformation in the city of Cali, Colombia, is described. Four sirenomelia and four cyclopia cases were born within a 165 days period in one hospital in Cali. The lapse between conception dates of first and last cases was shorter for sirenomelia (53 days) than for cyclopia (231 days). Based on ECLAMC (Latin American Collaborative Study of Congenital Malformations) published data, the observed/expected ratio (5.7) for both defects is statistically significant (P < 0.001). Mother's residence during the first trimester of pregnancy is concentrated in a same city quarter for four of the eight cases, close to a know polluting active landfill, and the other four cases, along the Cauca river, downstream from this landfill. Birth prevalence rates for two sentinel anomalies, that is, anal and esophageal atresia for sirenomelia and oral clefts for DeMyer holoprosencephaly spectra, were not higher in Cali than in the rest of ECLAMC material. The Computer Assisted Telephone Interviewing was applied to mothers of the 8 patients, and 32 matched controls. Seven of 295 variables were associated with sirenomelia, 3 of them related to house tap water, one to exposure to street drugs, one to physical injury, and 2 secondary to abnormal pregnancy outcome. None was associated with cyclopia. Results from hair dosage of heavy metals in the 8 patient's mothers were inconsistent. The time-space cluster is nonrandom for sirenomelia, and possibly random for cyclopia. The polluting landfill remains as a possible etiological factor.

Voting and priorities in health care decision making, portrayed through a group decision support system, using analytic hierarchy process

Within the health care industry many decision making approaches and tools are used. This paper explores a new tool, the Analytic Hierarchy Process (AHP), which permits both subjective and objective information to be considered in a decision. AHP has tremendous potential to solve both traditional and non-traditional health care problems. Its strength as a decision-making tool is its ability to combine both subjective and objective data. Application of AHP is discussed within the context of a Group Decision Support System (GDSS) model developed by Hatcher. The model is reviewed in limited detail, and readers are referred to the original article that defined and discussed the uniqueness and level of sophistication of GDSS applications in the health care industry. Health and medical delivery problems are discussed to highlight AHP requirements and the complexity of AHP applications. Health care applications are unique in that they lend themselves ideally to the use of computer data, image, voice, text, and multimedia concepts.