Digital privacy in the marketplace : perspectives on the information exchange

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This approach, although effective at the local level, creates a process that is out of alignment with national interoperability initiatives. The creation of local HIE patient matching architectures has generally not been successful in the United States because of the contention over the use of a universal patient identifier. Increasing the data elements utilized and incorporating standard data definitions into technical requirements for person capture provides a solid foundation regardless of the algorithm. Instituting a standard format and accepted definitions for data element capture minimizes the burden on staffing in routine business operations, providing long term financial relief.

Standardizing data element capture across the market will affect vendors financially and result in some time constraints in EHR architecture building. However, the positive results in accurate patient matching and successful interoperable HIE are of greater consideration. Embracing standardized data attributes, requiring minimal primary data capture, and increasing the use of secondary data elements will provide a solid foundation for interoperability with patient linking.

Figure 1 highlights recommended primary and secondary data attributes that will facilitate accurate patient matching. A fundamental and critical success factor for HIE is the ability to accurately link multiple records for the same patient across the disparate systems of the participating organizations. Algorithms can support many of the patient matching functions envisioned in HIE.

In this approach, mathematical calculations and predefined rules are applied to pairs of patient records to facilitate matching of patient identifiers. Basic algorithms that compare selected data elements, such as name, date of birth, and gender, are the simplest technique for matching records. Intermediate algorithms use more advanced techniques to compare and match records by assigning subjective weights to demographic elements for use in a scoring system to determine the probability of matching patient records.

Advanced algorithms contain the most sophisticated set of tools for matching records and rely on mathematical theory and statistical models to determine the likelihood of a match. Deterministic record matching programs compare values in various fields to determine whether the values are an exact match or a partial match to the value of that field in another record. The primary challenge with this type of algorithm is that data elements must be exact for a match to be recognized, and any variation in elements is considered nonmatching, resulting in many false negatives and duplicate patient records.

Thousands of different algorithms use statistical and mathematical constructs for patient record matching, and advanced algorithms often utilize a combination of many different algorithms. Policies that are designed to support capturing demographics in a standardized format can also facilitate patient matching. The process of capturing data is an operational consideration that cannot be taken lightly. See Appendix B for a sample naming convention policy that provides structure for data entry where free text is required.

Although patient matching algorithms have been widely adopted, methods of matching patient records within and across organizations have not been adopted uniformly across the industry. No consensus exists regarding patient matching accuracy thresholds, and each organization employs its own matching algorithm and patient matching methods, resulting in inconsistent results across the industry.

Standards development organizations have developed integration profiles to resolve several algorithm issues related to patient matching. Without accurate patient matching, providers may have incomplete information on their patients or may be presented with inaccurate information. A nationwide patient identification standard will facilitate patient matching and provide the foundation for interoperable HIE. This goal can be accomplished with the standardization of the following:.

A common set of standardized data elements to be used across multiple interoperability standards is ideal to support accurate patient matching. While the organizational impact of increased data entry is a consideration, the capture of additional data elements enables significant improvement of patient linking accuracy until a unique patient identifier becomes available or biometric technology improves, providing a more cost-effective matching method. Secondary data recommendations increase matching probability in the pediatric population and also serve as an additional level for data triangulation in the adult population.

Data integrity improves with the elimination of free text and the utilization of national data standards. Free-text entry is necessary for patient names, but capture of the complete legal name in discrete fields minimizes data entry errors. Common data capture of demographic elements through uniform policies that are widely shared will help to overcome the policy variations across organizations and appropriately manage the free-text component of data entry for names.

Continued use and adoption of existing technical profiles supports varying query and retrieval approaches for patient demographic data by providing flexibility to allow the use of various combinations where they are most feasible and applicable. Standardizing data capture through the use of existing national standards, increasing the number of primary data elements, and incorporating secondary data elements will provide a means to accurately identify participants in HIE.

The glossary of recommended primary and secondary data elements in Appendix A and the sample patient naming policy in Appendix B can be used to ensure consistency of data elements and provide structure for data entry where free text is required. Katherine G. Bipartisan Policy Center. June Dimitropoulos, Linda. January September Moehrke, John. Fears about online privacy stem from the technology's ability to monitor and record almost every aspect of Internet users' behavior, and are further fueled by media reports of Web sites that have violated their own privacy agreements by distributing customer information without permission Stout, ; Tweney, Recent opinion polls of Internet users reflect the magnitude of the public's concern over online privacy.

Some of the most frequently cited concerns include unfamiliar parties obtaining personal information and hackers stealing credit card information during business transactions taking place on the Web. The public's fears appear to be well-founded. And the problem appears to be worsening each year.

The National Consumer League's annual Internet fraud statistics show consistent increases in the number of complaints annually since National Fraud Information Center, At the same time, many commercial Web sites do not entitle Internet users to much privacy.


Exacerbating the problem, many Web sites do not alert users that they collect these data, nor do they offer a purpose for collecting it Culnan, ; FTC, Consequently, it is not surprising that some Internet users are reluctant to disclose personal information online. Hoffman et al. These data raise important questions regarding how businesses engaged in e-commerce can improve communication with customers. The factors that influence consumers to disclose information knowingly in the online environment is an open issue. Several variables are suggested by research in communication, marketing, and psychology.

For example, trust, regard for the company, perceived privacy protection, general privacy concern, and past Internet experience have been shown to be important factors in both commercial and online exchange e. Using prior theory and research, this study proposes and tests a model of how these variables affect information disclosure on the Internet see Figure 1. This model focuses on the role of trust and past online behavior in information disclosure, while exploring the concurrent influences of users' privacy perceptions and attitudes toward the Web site sponsor. In addition, this study also explores the quality of information disclosure on the Internet.

Trust is perhaps the most important influence on information disclosure Hoffman et al. Social exchange theory asserts that individuals weigh the costs and rewards in deciding whether to engage in social transactions. If the rewards are determined to outweigh the costs, then the individual is likely to enter into an exchange relationship. Trust is critical to this process because it is believed to reduce the perceived costs of such transactions.

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Indeed, several studies of interpersonal exchange situations have confirmed that trust is a precondition for self-disclosure because it reduces the perceived risks involved in revealing private information e. Culnan and Armstrong point out that although most research has focused on trust and self-disclosure in interpersonal contexts, similar balancing dynamics are used in electronic environments. That is, the risks of disclosing personal information are weighed against the benefits when deciding to provide information to a Web site, and so trust is the key to disclosure in both interpersonal and online relationships.

Research reported by Hoffman et al. These risks include theft of financial or identity information. For example, Jarvenpaa and Tractinsky found that trust increases confidence in a company, which lowers the perceived risk of electronic exchange with that company and, therefore, increases the likelihood of consumers engaging in electronic transactions.

Similarly, Swaminathan et al.

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The role of trust in facilitating disclosure may be particularly important in online exchanges where computer-mediated communication replaces physical contact. In an environment of reduced social cues, trust may be more difficult, yet more important, to establish than in interpersonal contexts Boyd, In sum, it is reasonable to suggest that trust of a commercial Web site will influence disclosure of personal information to that site.

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If trust is particularly significant to the process of online exchange, then it is important to ask what fosters trust of a commercial Web site, especially during initial encounters with the site. Consumers' overall regard for a company, defined as their affective evaluation of that company, is likely to influence perceptions of trust.

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Affective evaluations are made on the basis of many things, for example, firm reputation or personal experience with a company, both of which have been linked to trust in past research see Jarvenpaa et al. Support for the notion that regard for the company impacts trust comes from research on social influence, as well as studies of trust in ecommerce environments specifically.

For example, evidence that liking for a communicator positively influences judgments of trustworthiness is found across a number of studies examining communicator credibility see O'Keefe, for a review of this literature. Extending the credibility literature to the Web, Fogg found that Web sites of respected organizations that were visually pleasing were rated high in trustworthiness and expertise see also Sultan et al.

The degree to which Internet users feel that a Web site protects their privacy may also have an impact on their trust of the site. Although perceptions of privacy protection likely differ depending on the user, culture, and other factors, Web site design and content elements can communicate information about privacy protection Palmer et al. With regard to design, site complexity and layout e. Web site content also influences perceptions of a site's privacy protection through such elements as privacy statements and seals, for example, TRUSTe or BBBonline Culnan, ; Hansen, ; Palmer et al.

Research suggests that enhancing perceptions of Web site privacy protection via features such as privacy statements and seals may increase regard for the company and trust. For example, Fombrun shows that demonstrating goodwill and respect for customer needs is an important component of improving customer relations and firm reputation, which he defines as the consumer's overall affective evaluation of a company.

Digital Privacy and Your Personal Data Documentary

With regard to trust specifically, Culnan and Armstrong find that revealing information collection procedures increases consumers' feelings of security and organizational trust. Similarly, Sultan et al. Together, these findings suggest that the degree to which Internet users believe a commercial Web site protects their privacy will positively influence their overall regard for the company and trust of the company's Web site. Berscheid argues that individuals differ in the degree to which they desire and value personal control over information about themselves. Further, Jarvenpaa and Tractinsky argue that one's general trusting stance can generalize to trust of Internet-based companies.

Based on the truism that the best predictor of future behavior is past behavior, prior disclosure of personal information is likely to affect later disclosure. Chelune explains that past experiences with interpersonal exchanges affect the value placed on such exchanges and influence expectations regarding future interactions, which then guide future exchange behaviors. Accordingly, studies of disclosure in interpersonal contexts find that past disclosure positively affects future willingness to disclose when the initial disclosure is rewarded, because the perceived risks associated with self-disclosure are reduced Gilbert, This logic applies to other contexts as well.

For example, Culnan and Armstrong found that people's willingness to be profiled, that is, to give up personal information for marketing purposes, was a function of their past experience with revealing information to marketers. They suggest that people who have had prior experience with direct or targeted marketing are more likely to understand the benefits of consumer profiling. Furthermore, due to efficient data storage and transfer capacities of computer-based technologies, consumers may believe that after they disclose personal information online once, the damage has already been done and so they may feel less inhibited about revealing that information online again.

In this way, future disclosure is not necessarily associated with higher perceived risk in the Internet environment. For these reasons, past disclosure of personal information online is likely to predict future disclosure of personal information to a commercial Web site. But what leads a person to disclose information online initially?

Unfortunately, there is little data to answer this question. Two interesting possibilities are Internet experience and concern for privacy. Concern for online privacy may also predict whether people have ever disclosed personal information on the Internet.

Patient Matching in Health Information Exchanges

The research described earlier in which Internet users cite privacy fears as a barrier to engaging in Web-based business transactions supports this idea in the online environment e. The preceding theory and research on trust and disclosure in both interpersonal and computer-mediated communication contexts suggest the following hypotheses, which are illustrated by the paths depicted in the model shown in Figure 1. H1: The degree to which Internet users' believe a company's Web site protects their privacy positively influences their regard for the company.

H3: Internet users' concern for privacy online negatively influences their trust of a commercial Web site.

H4: Internet users' concern for privacy online negatively influences their past online information disclosure.

Digital privacy in the marketplace : perspectives on the information exchange Digital privacy in the marketplace : perspectives on the information exchange
Digital privacy in the marketplace : perspectives on the information exchange Digital privacy in the marketplace : perspectives on the information exchange
Digital privacy in the marketplace : perspectives on the information exchange Digital privacy in the marketplace : perspectives on the information exchange
Digital privacy in the marketplace : perspectives on the information exchange Digital privacy in the marketplace : perspectives on the information exchange
Digital privacy in the marketplace : perspectives on the information exchange Digital privacy in the marketplace : perspectives on the information exchange

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