Getting More “Bang” for Your Performance Measures “Buck”

Datos Bibliográficos

ID12470581
AutoresMary Ann Scheirer (Evaluation & Performance Measures Consultant, 4616 Hillbrook Drive, Annandale VA 22003, autor de correspondencia)
Año2000
Volumen21
Número2
Páginas139-149
Fecha de publicación2000-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaAmerican Journal of Evaluation (JOURNAL)
Identificadores de la revistaISSN: 1098-2140 • E-ISSN: 1557-0878
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1177/109821400002100202
OpenAlexW4248330185
IdiomaEN
Citas recibidas3
Referencias citadas12

Funders of intervention programs and services at the federal, state, and local levels are requiring greater accountability via the use of performance measures. Data from these measures are usually reported descriptively for the entire program. It is suggested here that performance measure data that are already being collected could become much more useful, at low additional cost, by further analyzing the relationships among the measures, especially across time. By using logic models to show expected relationships among several types of measures, and then analyzing variability among program delivery units for those measures, evaluators could provide evidence for the hypothesized connections among program delivery, outputs, and desired outcomes. Such analyses also would help to link two major purposes for performance measurement—program improvement and accountability to the public—which are often viewed as contrasting or even incompatible uses

Accountability · Business · Data mining · Intervention (counseling · Logic model · Measure (data warehouse · Performance measurement · Political science · Process management · Program evaluation · Computer Science · Evaluation and Performance Assessment · Health Policy Implementation Science · Primary Care and Health Outcomes · Psychology · Public Administration · Marketing