The Meaningful Use of Cloud Computing in Healthcare

This dissertation focuses on the meaning of cloud computing for healthcare and its meaningful use in the healthcare industry. If used in a meaningful way, cloud computing is argued to be able to provide major benefits to the healthcare industry. Surprisingly, the benefits promised by using cloud computing often do not hold in practice, and the deployment of cloud computing services in healthcare organizations could lead to countereffects for healthcare. Although existing research studies cover a wide range of domains in healthcare, they often do not explain the way in which cloud computing could support healthcare in a systematic manner. In reply to that insufficiency in the research, this dissertation aims to investigate the phenomenon of cloud computing in healthcare organizations and to answer the following overarching research question: How can cloud computing support healthcare organizations in a meaningful way (i.e., meaningful use)? This dissertation conducted four research studies by employing established explorative research methods. The dissertation begins with a study (study 1) that investigates the basic properties of cloud computing services and their specific meanings for the healthcare industry, and suggests concrete directions for studies related to the meaningful use of cloud computing in healthcare. Study 2 focuses on the identification of industry-specific factors for the adoption of cloud computing services in healthcare, and studies 3 and 4 on an investigation of the way in which cloud computing supports collaborative activities in healthcare, respectively. Both focuses belong to research directions suggested by study 1. By addressing the overarching research question, this dissertation could deepen our understanding of the use of information technology (IT) artefacts that advances information systems theories, not only regarding cloud computing itself but also in terms of more general health IT levels

Assessment Instrument for Privacy Policy Content: Design and Evaluation of PPC

Privacy policies are notices posted by providers and intended to inform users about privacy practices. However, extant research shows that privacy policies are often of poor quality and do not address users’ concerns. In this paper, we design and develop PPC – a privacy policy content assessment instrument to support assessments of whether offered privacy policy content provides comprehensive information addressing users’ privacy concerns. PPC is developed based on extant research, standards, and guidelines. Application of PPC to 62 privacy policies of mHealth apps available in iOS and Android demonstrates utility of PPC and suitability of PPC as assessment instrument for privacy policy content. Contributions of our research are twofold: For research, we conduct improvement design science research contributing to design theory on assessment of privacy policy content. For practice, potential applications of PPC are support in privacy policy development and identification of deficiencies in offered privacy policies. In addition, through evaluation of PPC, we reveal an insufficient current state of mHealth app privacy policy content

Rethinking the Meaning of Cloud Computing for Healthcare: A Taxonomic Perspective and Future Research Directions

Background: Cloud computing is an innovative paradigm that provides users with on-demand access to a shared pool of configurable computing resources such as servers, storage, and applications. Researchers claim that information technology (IT) services delivered via the cloud computing paradigm (ie, cloud computing services) provide major benefits for health care. However, due to a mismatch between our conceptual understanding of cloud computing for health care and the actual phenomenon in practice, the meaningful use of it for the health care industry cannot always be ensured. Although some studies have tried to conceptualize cloud computing or interpret this phenomenon for health care settings, they have mainly relied on its interpretation in a common context or have been heavily based on a general understanding of traditional health IT artifacts, leading to an insufficient or unspecific conceptual understanding of cloud computing for health care. Objective: We aim to generate insights into the concept of cloud computing for health IT research. We propose a taxonomy that can serve as a fundamental mechanism for organizing knowledge about cloud computing services in health care organizations to gain a deepened, specific understanding of cloud computing in health care. With the taxonomy, we focus on conceptualizing the relevant properties of cloud computing for service delivery to health care organizations and highlighting their specific meanings for health care. Methods: We employed a 2-stage approach in developing a taxonomy of cloud computing services for health care organizations. We conducted a structured literature review and 24 semistructured expert interviews in stage 1, drawing on data from theory and practice. In stage 2, we applied a systematic approach and relied on data from stage 1 to develop and evaluate the taxonomy using 14 iterations. Results: Our taxonomy is composed of 8 dimensions and 28 characteristics that are relevant for cloud computing services in health care organizations. By applying the taxonomy to classify existing cloud computing services identified from the literature and expert interviews, which also serves as a part of the taxonomy, we identified 7 specificities of cloud computing in health care. These specificities challenge what we have learned about cloud computing in general contexts or in traditional health IT from the previous literature. The summarized specificities suggest research opportunities and exemplary research questions for future health IT research on cloud computing. Conclusions: By relying on perspectives from a taxonomy for cloud computing services for health care organizations, this study provides a solid conceptual cornerstone for cloud computing in health care. Moreover, the identified specificities of cloud computing and the related future research opportunities will serve as a valuable roadmap to facilitate more research into cloud computing in health care

Rethinking the Meaning of Cloud Computing for Healthcare: A Taxonomic Perspective and Future Research Directions

Background: Cloud computing is an innovative paradigm that provides users with on-demand access to a shared pool of configurable computing resources such as servers, storage, and applications. Researchers claim that information technology (IT) services delivered via the cloud computing paradigm (ie, cloud computing services) provide major benefits for health care. However, due to a mismatch between our conceptual understanding of cloud computing for health care and the actual phenomenon in practice, the meaningful use of it for the health care industry cannot always be ensured. Although some studies have tried to conceptualize cloud computing or interpret this phenomenon for health care settings, they have mainly relied on its interpretation in a common context or have been heavily based on a general understanding of traditional health IT artifacts, leading to an insufficient or unspecific conceptual understanding of cloud computing for health care. Objective: We aim to generate insights into the concept of cloud computing for health IT research. We propose a taxonomy that can serve as a fundamental mechanism for organizing knowledge about cloud computing services in health care organizations to gain a deepened, specific understanding of cloud computing in health care. With the taxonomy, we focus on conceptualizing the relevant properties of cloud computing for service delivery to health care organizations and highlighting their specific meanings for health care. Methods: We employed a 2-stage approach in developing a taxonomy of cloud computing services for health care organizations. We conducted a structured literature review and 24 semistructured expert interviews in stage 1, drawing on data from theory and practice. In stage 2, we applied a systematic approach and relied on data from stage 1 to develop and evaluate the taxonomy using 14 iterations. Results: Our taxonomy is composed of 8 dimensions and 28 characteristics that are relevant for cloud computing services in health care organizations. By applying the taxonomy to classify existing cloud computing services identified from the literature and expert interviews, which also serves as a part of the taxonomy, we identified 7 specificities of cloud computing in health care. These specificities challenge what we have learned about cloud computing in general contexts or in traditional health IT from the previous literature. The summarized specificities suggest research opportunities and exemplary research questions for future health IT research on cloud computing. Conclusions: By relying on perspectives from a taxonomy for cloud computing services for health care organizations, this study provides a solid conceptual cornerstone for cloud computing in health care. Moreover, the identified specificities of cloud computing and the related future research opportunities will serve as a valuable roadmap to facilitate more research into cloud computing in health care

Mediator Kinase Disruption in MED12-Mutant Uterine Fibroids From Hispanic Women of South Texas

Context: Mutations in the gene encoding Mediator complex subunit MED12 are dominant drivers of uterine fibroids (UFs) in women of diverse racial and ethnic origins. Previously, we showed that UF-linked mutations in MED12 disrupt its ability to activate cyclin C-CDK8/19 in Mediator. However, validation of Mediator kinase disruption in the clinically relevant setting of MED12-mutant UFs is currently lacking. Objective: The objective of this study was twofold. First, to extend the ethnic distribution profile of MED12 mutations by establishing their frequency in UFs from Hispanic women of South Texas. Second, to examine the impact of MED12 mutations on Mediator kinase activity in patient-derived UFs. Methods: We screened 219 UFs from 76 women, including 170 tumors from 57 Hispanic patients, for MED12 exon 2 mutations, and further examined CDK8/19 activity in Mediator complexes immunoprecipitated from MED12 mutation-negative and MED12 mutation-positive UFs. Results: MED12 exon 2 mutations in UFs from Hispanic women are somatic in nature, predominantly monoallelic, and occur at high frequency (54.1%). We identified a minimal cyclin C-CDK8 activation domain on MED12 spanning amino acids 15 through 80 that includes all recorded UF-linked mutations in MED12, suggesting that disruption of Mediator kinase activity is a principal biochemical defect arising from these pathogenic alterations. Analysis of Mediator complexes recovered from patient UFs confirmed this, revealing that Mediator kinase activity is selectively impaired in MED12-mutant UFs. Conclusions: MED12 mutations are important drivers of UF formation in Hispanic women of South Texas. MED12 mutations disrupt Mediator kinase activity, implicating altered CDK8/19 function in UF pathogenesis.Peer reviewe

Uterine Leiomyoma-Linked MED12 Mutations Disrupt Mediator-Associated CDK Activity

Peer reviewe

A Systematic Analysis on DNA Methylation and the Expression of Both mRNA and microRNA in Bladder Cancer

Background: DNA methylation aberration and microRNA (miRNA) deregulation have been observed in many types of cancers. A systematic study of methylome and transcriptome in bladder urothelial carcinoma has never been reported. Methodology/Principal Findings: The DNA methylation was profiled by modified methylation-specific digital karyotyping (MMSDK) and the expression of mRNAs and miRNAs was analyzed by digital gene expression (DGE) sequencing in tumors and matched normal adjacent tissues obtained from 9 bladder urothelial carcinoma patients. We found that a set of significantly enriched pathways disrupted in bladder urothelial carcinoma primarily related to "neurogenesis" and "cell differentiation" by integrated analysis of -omics data. Furthermore, we identified an intriguing collection of cancer-related genes that were deregulated at the levels of DNA methylation and mRNA expression, and we validated several of these genes (HIC1, SLIT2, RASAL1, and KRT17) by Bisulfite Sequencing PCR and Reverse Transcription qPCR in a panel of 33 bladder cancer samples. Conclusions/Significance: We characterized the profiles between methylome and transcriptome in bladder urothelial carcinoma, identified a set of significantly enriched key pathways, and screened four aberrantly methylated and expressed genes. Conclusively, our findings shed light on a new avenue for basic bladder cancer research

Context matters: A review of the determinant factors in the decision to adopt cloud computing in healthcare

Cloud computing is an IT service paradigm that can, if used meaningfully, enhance traditional health IT approaches and offer major benefits to the healthcare industry. However, its adoption by healthcare organizations has been accompanied by diverse challenges that could impede its meaningful use. Decisions about its adoption should be made after serious consideration of relevant industry-specific factors. Whereas the literature has focused on cloud computing adoption in general, the industrial specificities that influence the decision to adopt cloud computing in the healthcare context have yet to be systematically addressed. We reviewed empirical studies on both information systems and medical informatics to investigate the determinant factors of the cloud computing adoption decision in healthcare organizations and the industrial specificities of those factors. Based on the results of our review, we proposed a conceptual framework of cloud computing adoption studies in healthcare and made seven recommendations for related future research. Our research contributes to the theory by providing a comprehensive list of industry-specific factors that influence cloud computing adoption decisions in healthcare and explains their specificities for the healthcare industry. For practitioners, the identified factors serve as a checklist that informs healthcare organizations' decision making regarding cloud computing adoption