Applications of Electronic Health Information in Public Health: Uses, Opportunities
            and Barriers

Tomines, Alan; Readhead, Heather; Readhead, Adam; Teutsch, Steven M.

doi:10.13063/2327-9214.1019

Cited by 40 publications

(38 citation statements)

References 35 publications

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“…When HCPs do report, the CDR forms submitted to PHAs are frequently incomplete, error-prone, and delayed [5,8]. And despite efforts to improve HCP reporting [9,10], most PHA case management, investigation and resolution, contact tracing, and cluster identification activities traditionally depend on manual, HCP-initiated reporting [11-13]. …”

Section: Introductionmentioning

confidence: 99%

Leveraging public health's participation in a Health Information Exchange to improve communicable disease reporting

Painter

Revere

Gibson³

et al. 2017

OJPHI

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BackgroundInfectious diseases can appear and spread rapidly. Timely information about disease patterns and trends allows public health agencies to quickly investigate and efficiently contain those diseases. But disease case reporting to public health has traditionally been paper-based, resulting in somewhat slow, burdensome processes. Fortunately, the expanding use of electronic health records and health information exchanges has created opportunities for more rapid, complete, and easily managed case reporting and investigation. To assess how this new service might impact the efficiency and quality of a public health agency's case investigations, we compared the timeliness of usual case investigation to that of case investigations based on case report forms that were partially pre-populated with electronic data.InterventionBetween September 2013-March 2014, chlamydia disease report forms for certain clinics in Indianapolis were electronically pre-populated with clinical, lab and patient data available through the Indiana Health Information Exchange, then provided to the patientâ€™s doctor. Doctors could then sign the form and deliver it to public health for investigation and population-level disease tracking. Methods: We utilized a novel matched case analysis of timeliness changes in receipt and processing of communicable disease report forms. Each Chlamydia cases reported with the pre-populated form were matched to cases reported in usual ways. We assessed the time from receipt of the case at the public health agency: 1) inclusion of the case into the public health surveillance system and 2) to close to case. A hierarchical random effects model was used to compare mean difference in each outcome between the target cases and the matched cases, with random intercepts for case.ResultsTwenty-one Chlamydia cases were reported to the public health agency using the pre-populated form. Sixteen of these pre-populated form cases were matched to at least one other case, with a mean of 23 matches per case. The mean Reporting Lag for the pre-populated form cases was 2.5 days, which was 2.7 days shorter than the mean Reporting Lag for the matched controls (p = <0.001). The mean time to close a pre-populated form case was 4.7 days, which was 0.2 days shorter than time to close for the matched controls (p = 0.792).ConclusionsUse of pre-populated forms significantly decreased the time it took for the local public health agency to begin documenting and closing chlamydia case investigations. Thoughtful use of electronic health data for case reporting may decrease the per-case workload of public health agencies, and improve the timeliness of information about the pattern and spread of disease.

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Section: Introductionmentioning

confidence: 99%

Leveraging public health's participation in a Health Information Exchange to improve communicable disease reporting

Painter

Revere

Gibson³

et al. 2017

OJPHI

View full text Add to dashboard Cite

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“…Big Data research is a good match with public health, as the scope of analysis encompasses the whole population [36]. For example, infectious disease surveillance, which is an important area of public health, was limited in the past by passive methods of collecting data, such as notifiable cases of disease reported by physicians or laboratories [37]. In particular, in the case of influenza, it is likely that the passive reporting approach would have resulted in a significant number of missing cases, due to false negative diagnoses or to the recovery or death of people who had become infected but who had not undergone any medical consultation.…”

Section: The Use Of Big Data From Disaster Preparedness To Public mentioning

confidence: 99%

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

Wong

Chiang

Choi

et al. 2016

IJERPH

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The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term “Big Data”, which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.

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“…The term e-Health is meant for communication, sharing and removal of health information.Some papers discuss how electronic health records indirectly influence HIT's, which stands for Healthcare Information Technology [1].…”

Section: Introductionmentioning

confidence: 99%

Research on E-healthcare Security Evaluation in Cloud-Based System

2019

IJRTE

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As healthcare adopts electronic methods of storing patient health records, cloud technology allows mining and analyzing this data and accessing the general public health information. Patient’s privacy and security of personal information is crucial when considering using electronic health records in the healthcare industry (E-Healthcare). The need of the hour is to be able to store and recover patient’s data efficiently. However, moving patient’s medical information to the Cloud involves major security risks and destructs robust data privacy of health records. The threat of data breaches and the need to manage huge amounts of data are issues that have affected the healthcare industry for years. The privacy issues and threats faced by E-healthcare systems include network attacks and threats to hosts and unsanctioned access to EHR records. The major EHR system functions such as appointment scheduling, dietary planning, admission and discharge, transfer radiology/lab orders and prescription order entry are vulnerable to security threats. Security issues need to be assessed thoroughly in order for hospitals and other such medical institutions to shift to electronic standards of maintaining patient's data. Before moving to a cloud-based architecture, health organizations should perform a risk assessment. This will help to identify the security measures required to mitigate these risks. This approach provides a valid assessment of the security risk management procedure approved by field experts. It not only identifies threats to E-healthcare but also allows for a structured flow in risk management. The risk management process is documented and reported in an efficient and easy way for concerned stakeholders of the E-healthcare to understand. It will compare existing solutions on how to protect the confidentiality of patient information. Some of these methods include implementation of a Role-Based Access Control (RBAC) model, digital encryption and signature for cloud security and EHR service continuity management. Moreover, it will consider security matters that CSP’s should look into while storing patient’s record. Ultimately, it will come up with the most suitable solution to make E-Healthcare systems more secure. In this paper, the focus will be on identifying security encounters that E-health systems face by discussing means in which these systems are susceptible to attacks.

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Applications of Electronic Health Information in Public Health: Uses, Opportunities and Barriers

Cited by 40 publications

References 35 publications

Leveraging public health's participation in a Health Information Exchange to improve communicable disease reporting

Leveraging public health's participation in a Health Information Exchange to improve communicable disease reporting

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

Research on E-healthcare Security Evaluation in Cloud-Based System

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