Knowledge Item: CA-Quality of Life and Health-40
Trends in Quality of Life Over the Course of the Treatment Episode Part VI–More Complex Hierarchical Linear Models Showing Differential Change for Groups Formed by Needs and Vulnerabilities

This Knowledge Item is a direct follow-up to Knowledge Item CA-Quality of Life and Health-39 which presents the first analyses in this set. 

Hierarchical linear modeling (or HLM) methods are used to study change in quality of life over time. For each person, an individual trend is line fit to that patient's quality of life scores over time. The method uses all observations for individual patients and takes into account the fact that patients received the assessments at different times in their treatment histories. After fitting "individual" curves for each patient, overall trends in the "average curves" or "trajectories" are studied and related to other factors. HLM modeling can be considered the "definitive" method for studying change in the kinds of naturally-occurring treatment assessment data from these projects.

The hierarchical models show that on the average patients experience increasing quality of life over the course of their involvement with the programs represented here. This Knowledge Item studies the rate of change as a function of different service needs and vulnerabilities of the patient. A number of service needs-vulnerabilities are related to both the initial quality of life level of the patient at the time of enrollment into the program and to the rate of change throughout the program.

Furthermore, patients receiving services in projects with "wrap-around" psychosocial services (as represented by University-based Comprehensive Healthcare Programs and Psychosocial Community Based Organizations with linked medical services) improve more over time than patients in Managed Care Medical Programs which do not have strongly integrated psychosocial service components.

The degree of quality of life increase over time is related to certain patient need and vulnerability factors.

This test of the difference in rate of estimated change is statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is not statistically significant.

This test of the difference in rate of estimated change is not statistically significant.

This test of the difference in estimated level at enrollment is statistically significant.

Further analyses given in Knowledge Items: CA-Quality of Life and Health-37, -42, -43, -50, -51, and as well as Knowledge Items: CA-Medical Outcomes-11, -12, and -13 show additional analyses that confirm with alternate methods that the projects with wrap-around comprehensive psychosocial services, supplementing basic medical services, tend to maintain the patient at the same or an increased quality of life for a longer time, and with a greater ratio of improvement, than just medical services. The additional Knowledge Items use alternate statistical designs and models with different factors "controlled," but the different methods of assessing the relative effectiveness of these different types of service models in achieving improved quality of life for the patients all point out the importance of integrated psychosocial or "wrap-around" services. 

In interpreting this Knowledge Item, and all others in this section on Quality of Life and Health, remember that the ratings of quality of life, symptom impact, and healthcare utilization are based on patient self reports.

Knowledge Item Citation: Huba, G. J., Panter, A. T., Melchior, L. A., and the HRSA/HAB SPNS Cooperative Agreement Steering Committee (1998-2001). Knowledge Item: CA-Quality of Life and Health-40 from HRSA/HAB's SPNS Cooperative Agreements on Innovative Models of Care, The Measurement Group Knowledge Base on HIV/AIDS Care, Online at www.TheMeasurementGroup.com.