PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 15360901

Generic computer-based questionnaires: an extension to OpenSDE.

Astrid M van Ginneken·Marcel de Wilde·C Blok
View original source ↗Export metadata ↓

Abstract

Development of computer-based questionnaires (CQs) has been an ongoing challenge since the 1960s. The added value of such CQs for data collection and the acceptance by patients have been well documented. Many questionnaire projects, however, were temporary due to dedicated software, limited funding, and lack of integration with medical information systems. Also, the use of a fixed dedicated database makes integration cumbersome, as change in content requires change to the data model. Since much of the functional requirement of CQs is not dependent on content, the challenge is to both separate functionality and database structure from content. Following these principles, we extended OpenSDE, a generic application for structured data entry, with a tool to construct and run CQs as an alternative way of data input. We propose the combination of a generic building tool and a content-independent data model as an effective strategy to tackle the above-mentioned problems in CQ development.

Explore related subjects

Data CollectionInformation Storage and RetrievalMedical Records Systems, ComputerizedSoftwareSurveys and QuestionnairesUser-Computer InterfaceJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Astrid M van Ginneken, Marcel de Wilde, C Blok. 2004. Generic computer-based questionnaires: an extension to OpenSDE.. https://pubmed.ncbi.nlm.nih.gov/15360901/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2006

Comparison of universal newborn hearing screening programs in Illinois hospitals.

UNLABELLED: SUMMARY/OBJECTIVES: In accordance with the Joint Committee on Infant Hearing's (JCIH, 2000) position statement regarding Universal Newborn Hearing Screenings (UNHS), the state of Illinois enacted legislation requiring all birthing hospitals to conduct UNHS by 31 December 2002. Currently 100% of birthing facilities in the state of Illinois perform newborn infant hearing screenings using otoacoustic emissions (OAEs) and/or automated auditory brainstem response (AABR) measures. This study is an attempt to document current practices in hospital-based UNHS programs, as reported by program personnel, in the state of Illinois. The goal is to compare these reported practices to the recommended standards and identify factors that could lead to further refinement of the process. METHODS: A modified version of the Newborn Hearing Screening Survey from the Marion Downs National Center for Infant Hearing was used to gather practice- and protocol-related data for the 2004 calendar year via the World Wide Web. Data presented here are extracted from the online survey as reported by hospital staff presumably associated with the UNHS program. RESULTS: Fifty-nine of the 140 hospitals with UNHS programs responded to the Web-based survey. Nursing staff, followed by technicians, were most commonly reported to perform initial hearing screenings in both the well-baby nursery (WBN) and the neonatal intensive care unit (NICU). Audiologists appeared to participate in re-screenings at a greater number of the facilities. Automated ABR was the most common screening tool (80%) followed by Distortion Product OAEs (32%) and Transient Evoked OAEs (5%). Eighty-six percent reported referral rates that were less than 5%, with 32% reporting a referral rate less than 1%. CONCLUSIONS: At the beginning of 2004, 99% of all infants born in Illinois were being screened for hearing loss. Personnel involvement and screening measures employed were comparable to the few reports available from other states. The audiologist's role was found to be fairly limited in screening, re-screening, or managing UNHS programs. Referral rates were consistent with national standards ( approximately 1%). Management of UNHS programs in small, rural facilities, tracking/monitoring high-risk infants, and other services provided to families emerged as areas with room for improvement.

Data Collection↗
PubMed2006

Validation of a self-administered, computerized tool for collecting and displaying the family history of cancer.

PURPOSE: A detailed family history is important for cancer risk assessment, but obtaining it is time consuming and infrequently accomplished in practice. The Genetic Risk Easy Assessment Tool (GREAT) conducts a computer-administered family history interview and immediately generates a pedigree diagram in digital form. The purpose of this study was to validate family cancer histories produced by patients using the computer tool in comparison with pedigrees made by genetic counselors. METHODS: Patients scheduled for genetics consultation recorded their family histories using the GREAT, separate from their genetic counseling session. The presence of each relative; presence, type, and age at diagnosis of cancers; and cancer geneticist's risk assessment were compared for 120 pairs of pedigrees produced by counselors versus computer tool. RESULTS: The automated telephone interview took a mean of 33.5 minutes and was highly acceptable to respondents. Ninety-four percent of first-degree relatives, 67% of second-degree relatives, and 38% of third-degree relatives were identical on paired pedigrees; computer-generated pedigrees included additional relatives. Sixty-three percent of all cancers were identified by both family histories, with 90% agreement on the type of cancer. There was very good agreement (kappa = 0.70; correlation = 0.77) between the geneticist's breast cancer risk assessments based on computer versus counselors' pedigrees. In a subsample of 61 users, test-retest reliability for the computer-administered questionnaire was high (phi = 0.94 for cancers in first-degree and phi = 0.91 in second-degree relatives). CONCLUSION: The GREAT computer-administered questionnaire provides an acceptable, reliable, and valid way of collecting an unverified but extensive family history of cancer and displaying it as a pedigree, in an entirely automated process.

Data Collection↗
PubMed2006

Unified medical language system coverage of emergency-medicine chief complaints.

BACKGROUND: Emergency department (ED) chief-complaint (CC) data increasingly are important for clinical-care and secondary uses such as syndromic surveillance. There is no widely used ED CC vocabulary, but experts have suggested evaluation of existing health-care vocabularies for ED CC. OBJECTIVES: To evaluate the ED CC coverage in existing biomedical vocabularies from the Unified Medical Language System (UMLS). METHODS: The study sample included all CC entries for all visits to three EDs over one year. The authors used a special-purpose text processor to clean CC entries, which then were mapped to UMLS concepts. The UMLS match rates then were calculated and analyzed for matching concepts and nonmatching entries. RESULTS: A total of 203,509 ED visits was included. After cleaning with the text processor, 82% of the CCs matched a UMLS concept. The authors identified 5,617 unique UMLS concepts in the ED CC data, but many were used for only one or two visits. One thousand one hundred thirty-six CC concepts were used more than ten times and covered 99% of all the ED visits. The largest biomedical vocabulary in the UMLS is the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), which included concepts for 79% of all ED CC entries. However, some common CCs were not found in SNOMED CT. CONCLUSIONS: The authors found that ED CC concepts are well covered by the UMLS and that the best source of vocabulary coverage is from SNOMED CT. There are some gaps in UMLS and SNOMED CT coverage of ED CCs. Future work on vocabulary control for ED CCs should build upon existing vocabularies.

Data Collection↗