Biomedical subjects

Daniel Lorence

Publications and source records attributed to Daniel Lorence.

5 recordsLinked to original sources

PubMed2006

Web-based consumer health information: public access, digital division, and remainders.

Public access Internet portals and decreasing costs of personal computers have created a growing consensus that unequal access to information, or a "digital divide," has largely disappeared for US consumers. A series of technology initiatives in the late 1990s were believed to have largely eliminated the divide. For healthcare patients, access to information is an essential part of the consumer-centric framework outlined in the recently proposed national health information initiative. Data from a recent study of health information-seeking behaviors on the Internet suggest that a "digitally underserved group" persists, effectively limiting the planned national health information infrastructure to wealthier Americans.

Access to Information↗

PubMed2006

Comparative analysis of medical web search using generalized vs. niche technologies.

One increasingly popular solution to the problem of information overload is the niche search engine, designed as a customized knowledge management tool to meet the needs of information seekers with similar interests. By limiting web crawling to a specific subject area, the niche engine is able to crawl deeper and more discreetly than commercial counterparts. This exploratory technology assessment study sought to examine differences in information search and retrieval patterns between commercial and niche search engines in areas of debated or uncertain healthcarer treatment. Findings suggest that while information found within the niche search is generally more trustworthy, niche searches leave out many reliable sources which are retrievable through commercial search engines. Also, consumer-friendly (non-technical) resources were found to be more prevalent using commercial search engines, suggesting greater relevance for the layperson within this domain.

Algorithms↗

PubMed2006

Assessing domains of uncertainty in critical Web-based healthcare communities.

Search engines and Web-based directories play a central role in facilitating access to online health information. In this environment consumers often find and act upon health information of variable quality, with little input from health professionals. As an added concern, when consumers access health information on the Web via a search engine they often fail to discuss the information with a healthcare provider, especially in areas of perceived medical uncertainty. For many health consumers, the Internet may be the primary (or even sole) source of health information, especially where consumers lack access to, or trust in, trained providers. To date the corresponding role of search engine technology use and efficacy has received relatively little attention, however. This study serves as an exploratory technology assessment that explains the application of keyword effectiveness indexing (KEI) analysis in estimating the ability of commercial search engines to return relevant results for healthcare consumers. Findings suggest that KEI can serve as a useful health search profiling tool, though its applicability may vary across domains.

Community Health Services↗

PubMed2003

Regional variation in medical classification agreement: benchmarking the coding gap.

The growing use of classification and coding of patient data in medical information systems has resulted in increased dependence on the accuracy of coding practices. Information maintained on systems must be trusted by both providers and managers in order to serve as a viable tool for the delivery of healthcare in an evidence-based environment. A national survey of health information managers was employed here to assess observed levels of coder agreement with physician code selections used in classifying patient data. Findings from this survey suggest that, on a national level, the quality of coded data may suffer as a result of disagreement or inconsistent coding within healthcare provider organizations, in an era where physicians are increasingly called upon to enter and classify patient data via computerized medical records. Nineteen percent of respondents report that coder-physician classification disagreement occurred on more than 5% of all patient encounters. In some cases disagreement occurs in 20% or more instances of code selection. This phenomenon occurred to varying degrees across regions and market areas, suggesting a confounding influence when coded data is aggregated for comparative purposes. In an evidence-based healthcare environment, coded data often serves as a representation of clinical performance. Given the increasing complexity of medical information classification systems, reliance on such data may pose a risk for both practitioners and managers without consistent agreement on coding practices and procedures.

Attitude of Health Personnel↗

PubMed2003

Measuring disparities in information capture timeliness across healthcare settings: effects on data quality.

The emergence of evidence-based medicine in the United States has created an industry-wide environment where the quality of data maintained by healthcare organizations is becoming a critical factor in the delivery of medical care. Such a transition necessitates a corresponding need for consistent data collection and maintenance methods. In this study results of a national survey of health information managers were used to assess prevalence of a standard data quality practice, the adoption of policies related to timeliness of data capture. Findings from this survey show that, on a national level, only a slight majority of respondents indicated adoption of timeliness policies. About 61% of respondents indicate they have policies and procedures addressing data timeliness, although persistent patterns of nonadoption were found. We examine how the timeliness of data collection might serve as part of an overall data collection strategy that managers can employ to improve the quality of their information.

Data Collection↗