Evaluating a program to build data capacity for core public health functions in local maternal child and adolescent health programs in california.

Family Health Outcomes Project, University of California San Francisco, 3333 California Street, Suite 365, San Francisco, CA, 94118, USA. Olivag@fcm.ucsf.edu

OBJECTIVES: To improve local Maternal and Child Health programs' capacity to collect and analyze data to support core public health functions, the California Maternal and Child Health Branch (CAMCHB) and the University of California San Francisco Family Health Outcomes project (FHOP) entered into a cooperative agreement. FHOP utilizes a 6-pronged strategy: face-to-face training, telephone technical assistance, on-site consultation, development of automated analytic tools, development of written guidelines, and web dissemination of data and materials. We evaluated the acceptability and effectiveness of these approaches. METHODS: Local Health Jurisdiction (LHJ) staff completed a self-administered questionnaire on use of and satisfaction with FHOP's services. A 34-item assessment tool was used to independently evaluate each 5-year community assessment plan submitted by LHJs to the CAMCHB. Administrative data on the use of FHOP's service was also considered. Correlational analyses were done to determine if use of FHOP services and materials was related to more adequate plans. RESULTS: LHJs with higher overall adequacy scores on their plans had an overall higher level of use of FHOP's products and services. LHJs with higher adequacy scores reported calling FHOP for technical assistance more frequently, using FHOP's book - "Developing an Effective Planning Process: A Guide for Local MCH Programs," and using FHOP's automated tools including EpiBC, an EpiINFO based program for birth certificate analysis, and Microsoft Excel data analysis templates. CONCLUSION: This 6-pronged strategy is well utilized and accepted by local MCH staff and appears to have some degree of association with better quality of local MCH plan documents.

PMID: 17006772 [PubMed - indexed for MEDLINE]