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ADOPTION OF ELECTRONIC HEALTH RECORDS IN THE PRESENCE OF PRIVACY CONCERNS: THE ELABORATION

LIKELIHOOD MODEL AND INDIVIDUAL PERSUASION

Angst and Agarwal, 2009

The main purpose of this study is to empirically investigate whether or not it is possible to persuade individuals to adopt Electronic Health Records system, even in the presence of significant levels of privacy concerns. In other words to test whether providing people with positively framed messages about the value of EHRs, persuade them to allow their medical information to be digitized.

By integrating the Elaboration Likelihood Model (ELM) from psychology with Concern for Information Privacy (CFIP), the authors have tried to examine the effects of privacy concerns on the modification of attitudes. Explaining the ELM theoretical basis, the authors clarify that in this study they focus on the characteristics of message (conceptualized as argument framing) as well as characteristics of the recipient (conceptualized as issue involvement) to study how manipulation of these factors influence on individuals’ attitudes.

In terms of predicting attitude toward EHR use, based on the ELM theory, it is hypothesized that the amount of persuasion occurred in an individual (i.e. post-manipulation attitude) is driven by the argument framing as well as issue involvement. Also it is hypothesized that the effect of message framing on post-manipulation attitude is moderated by the individuals’ issue involvement as well as CFIP. Moreover, the relation between AF x II interaction term is hypothesized to be moderated by the concern for Information Privacy. Also in terms of predicting the likelihood of EHR adoption by individuals, post-manipulation attitude as well as CFIP are hypothesized to be the main drivers of likelihood of adoption (i.e. opt-in intention).

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The proposed model is then tested using an experimental approach and by randomly assigning the subjects to a single treatment with two conditions (i.e. positive and neutral argument framing). A structural equation modeling analysis (using a robust maximum likelihood estimation strategy for handling categorical data) is conducted on data collected from 366 subjects and the results provide support for all but one hypothesis (i.e. II moderates the relationship between AF and post-manipulation attitude). At the end, a series of post-hoc analyses are also conducted to investigate the interactions among variables.

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Privacy Protection and Technology Diffusion:The Case of Electronic Medical Records

Miller and Tucker, 2009

The main goal of this paper is to quantitatively examine the role of state-level privacy

protection legislations on the adoption of Electronic Medical Records (EMRs) by hospitals.

At the first stage, the authors argue that network effects (i.e. the economic externality

produced from one hospital’s adoption decision on the profitability of EMR adoption for

other hospitals) may shape the adoption of EMRs. They maintain that whereas ‘privacy

protection’ can increase the network benefits to hospitals of exchanging information

electronically, at the same time it more expensive infrastructure and thereby can reduce

network benefits. They model the ‘net gain’ of adoption and discuss that it involves two

components: ‘network benefits’ and ‘stand-alone benefits’.

After describing the data set used in the study (the HADB as well as AHA survey), it is

used to study how network effects shape the adoption of EMRs, and how these effects differ

for states with and without legislations. A linear probability model is used to examine this

issue. The results from both panel and cross-sectional data sets provide evidence of the

presence of network benefits from EMRs that are diminished by privacy laws. In states

without hospital privacy protection it is shown that one hospital’s adoption increases the

propensity of other hospitals in the local area to adopt, while no such effect has been

observed in states with privacy protection.

The next section deals with examining the effect of passing privacy protection legislation

on adopting EMRs, without studying its effect on the network benefits of adoption. A

negative relationship between privacy legislations and EMR adoption is reported.

In short, the study indicates that although there may be many reasons for states to

restrict medical providers’ ability to disclose information, these restrictions do lead to

lower adoptions of EMRs.

Behrooz

The impact of personal dispositions on information sensitivity, privacy concern and Trust in disclosing health information

online

Bansal et al., 2010

The main goal of this article is to explore the role of personal dispositions (i.e. personality traits, health status, information sensitivity, and other personal circumstances) as an intrinsic factor on individuals’ online trust and privacy concerns with respect to their decision to disclose their health information online based on Utility Theory and its application to choice theory in which consumer preferences depend on personal characteristics.

The authors first argue that disclosing personal health information online is associated with some potential undesirable outcomes (disutility) as well as some potential desirable outcomes (utility) and that individuals need to balance these utilities and disutilities. To investigate this decision, they have used Utility Theory. Actually they hold that the individuals’ decision (disclose vs. not disclose) is a function (unique to each individual) of the benefits and concerns about this decision. Moreover they mention that these benefits and concerns, themselves are functions of individuals’ personal dispositions.

They continue by focusing the ‘disutility’ part of the mentioned decision function and argue that ‘privacy concern’ and ‘trust’ can be considered as the main ‘disutility enhancer’ and ‘disutility reducer’ factors (respectively) in this context. Afterwards in the form of a conceptual model, they propose that personal dispositions influence privacy concern (through perceived sensitivity of information), which in turn is countered by trust, both affecting intentions to disclose personal health information.

The proposed model is then tested with a cross-sectional survey of 367 participants using SEM analysis (mean-adjusted maximum likelihood criterion). The results provide

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support for most of the hypothesized relationships; however the mediated influence of privacy concern on intention (through trust) is not supported. Moreover, while personality traits were hypothesized as a main antecedent of privacy concern (through perceived sensitivity of information), the results indicate that only ‘Emotional Instability’ has a significant effect on the perceived sensitivity of information and the effect of four other personality traits are non-significant. I think this issue undermines the main contribution of the paper (as contended by authors) because ‘personality’ is considered as one of the main components of ‘personal dispositions’ in the model.

Behrooz

Protecting Medical Privacy: Challenges in the Age of Genetic Information

Alpert, 2003

The main purpose of this paper is to explore some of the privacy issues with respect to groups’ genetic information and to propose some courses of action to deal with these issues in the future.

The paper begins by explaining the concept of informational privacy (i.e. how much personal information is available from sources other than the individual to whom it pertains) and the consequences of loss of it as according to the authors in medical privacy issues, ‘informational privacy’ is most often the interest at stake. Particularly they argue that in the context of genetic information, the loss of informational privacy can lead to intrusion on group or collectivity (defined as a collective of individuals who are culturally and ethnically related, where shared characteristics are either likely of possible) privacy interests. This discussion is then narrowed down to the specific context of medical information privacy.

In the next section, the use of computers to record, store, and analysis of medical information is discussed and both benefits and risks are mentioned. Following that they argue that in United States, one of the complicating factors in computerizing medical information is the current federal Law as it only protects a small proportion of patient information (i.e. substance abuse and mental health) and they mention that only a few states have adopted meaningful laws to protect a wider variety of information.

The discussion from the next section is shifted towards the specific context of Genetic information. First the probabilistic nature of genetic information is discussed and it is added that new computer chips are able to analyze human biological samples. Following that the privacy interests of ‘groups’ due to genetic analysis and computerized genetic records are addressed (e.g. the case of Ashkenazi Jews as an interesting group for biological studies and their consequent concerns about their group privacy). The authors argue that overgeneralizations in a genetic context may cause group members feel violated. It is also the case for Family Genetic Information where some similar privacy issues may arise by conducting genetic tests.

At the end, a number of recommendations are made to help practitioners as well as policymakers address the genetic information privacy issues in the future.