Relationships Among Patient Age, Diagnosis, Hospital Type, and Clinical Laboratory Utilization

Abstract

OBJECTIVE: The aging population will likely have a major impact on laboratory utilization. Utilization data will be necessary for laboratory managers to make informed decisions concerning staffing patterns and services offered.

DESIGN: In a retrospective non-descriptive study, the relationships among age groups, hospital type, diagnosis, and the numbers and types of laboratory tests performed were investigated.

SETTING: Half of the participants were from a private hospital, Touro Infirmary, and half were from a large public hospital, The Medical Center of Louisiana at New Orleans. Both facilities are located in New Orleans, Louisiana.

PATIENTS: Laboratory records from a random sample of 250 inpatients age 21 to 64, a sample from 250 inpatients age 65 to 84, and a sample from 250 inpatients age 85 and over with at least one of five admission or discharge diagnoses were analyzed.

INTERVENTIONS: Twenty-five records from each of the five diagnostic categories for each of the three age groups and two hospital types were analyzed, yielding a total sample of 750 records.

MAIN OUTCOME MEASURES: Laboratory tests for each inpatient stay were counted and categorized for analysis. The one-way ANOVA was used to test the degree of concordance between age groups and numbers of tests ordered and between age groups and types of tests ordered across hospital types.

RESULTS: Data analysis showed statistically significant differences in the total number of laboratory tests ordered for the three age groups regardless of facility (p 0.008). The age group with the highest number of total laboratory tests ordered was the group aged 65 to 84 (48.64 mean tests per patient). Across the total sample, more tests were ordered at the public facility than the private facility (51.75 and 32.42 mean tests per patient, respectively). Statistically significant differences in orders between the two facilities were noted in chemistry, hematology, and toxicology (p <0.001). When analyzing numbers of tests by age group and facility, no statistically significant differences were noted in any laboratory category. Analysis of disease and laboratory test categories, regardless of facility, showed statistically significant differences in numbers of tests ordered in microbiology, cytology, histology (p <0.001), and blood bank (p0.001). When analyzing numbers of tests by disease category and facility, significant correlation was noted in toxicology (p 0.001).

CONCLUSION: This research allowed comparisons in laboratory utilization between a private and a public hospital among different age groups. Differences were noted in both volume and type of laboratory tests ordered on patients with specific diagnoses in the two facilities. Although comorbidity was not well controlled for, the study does suggest that clinical laboratories may undergo changes in utilization as our nation's population ages.

ABBREVIATION: ICD-9-CM = International Classification of Diseases, 9th revision, Clinical Modification.