Incorporation of Socioeconomic Status Indicators into Policies for the Meaningful Use of Electronic Health Records

Chen, Candice; Weider, Katie; Konopka, Kristen; Danis, Marion

doi:10.1353/hpu.2014.0040

Cited by 25 publications

(19 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among the advantages of the voluntary health insurance as a source of the health care system financing we should mention the possibility of contract extension, the relationship between the payment volumes and the amount of the health services rendered (see the works of Farrah, 2013;Chen et al, 2014). When it comes to the disadvantages of this source of financing, special supervisory authorities should be established in order to ensure adequate control over the amount of deductions.…”

Section: Literature Reviewmentioning

confidence: 99%

Diagnosis of the socio-economic potential of health insurance

Borisova¹

2018

Insurance Markets and Companies

View full text Add to dashboard Cite

This study investigates the features of the development of the discriminant model of diagnostics of the socio-economic potential of health insurance, and the trends in the medical insurance system development in Ukraine. This study uses logistic, statistical and normative methods to assess of the socio-economic potential of health insurance in Ukraine from 2010 to 2017. The empirical result shows that the block assessment of the financial potential of health insurance gives the complete information on the dynamics of individual indicators and trends of the branch. The need for assessment of the socio-economic potential of health insurance in order to improve the efficiency of the public financial management of the health care finance system and the insurance market regulation has been justified.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Diagnosis of the socio-economic potential of health insurance

Borisova¹

2018

Insurance Markets and Companies

View full text Add to dashboard Cite

show abstract

“…Appropriate protocols to address data breaches or re-identification of de-identified data are also needed as even a robust de-identification process does not make re-identification impossible. 24 …”

Section: Findings and Recommendationsmentioning

confidence: 99%

“…We need to look beyond administrative, clinical, and physiological variables, and capture and incorporate social, behavioral, patient-reported, patient-monitored, genetic, public health, and environmental data into predictive models. 14 , 22 – 24 This could improve the accuracy and scope of predictive models.…”

Section: Findings and Recommendationsmentioning

confidence: 99%

Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges

Amarasingham¹,

Audet²,

Bates³

et al. 2016

eGEMs

View full text Add to dashboard Cite

Context:The recent explosion in available electronic health record (EHR) data is motivating a rapid expansion of electronic health care predictive analytic (e-HPA) applications, defined as the use of electronic algorithms that forecast clinical events in real time with the intent to improve patient outcomes and reduce costs. There is an urgent need for a systematic framework to guide the development and application of e-HPA to ensure that the field develops in a scientifically sound, ethical, and efficient manner.Objectives:Building upon earlier frameworks of model development and utilization, we identify the emerging opportunities and challenges of e-HPA, propose a framework that enables us to realize these opportunities, address these challenges, and motivate e-HPA stakeholders to both adopt and continuously refine the framework as the applications of e-HPA emerge.Methods:To achieve these objectives, 17 experts with diverse expertise including methodology, ethics, legal, regulation, and health care delivery systems were assembled to identify emerging opportunities and challenges of e-HPA and to propose a framework to guide the development and application of e-HPA.Findings:The framework proposed by the panel includes three key domains where e-HPA differs qualitatively from earlier generations of models and algorithms (Data Barriers, Transparency, and Ethics) and areas where current frameworks are insufficient to address the emerging opportunities and challenges of e-HPA (Regulation and Certification; and Education and Training). The following list of recommendations summarizes the key points of the framework: Data Barriers: Establish mechanisms within the scientific community to support data sharing for predictive model development and testing.Transparency: Set standards around e-HPA validation based on principles of scientific transparency and reproducibility.Ethics: Develop both individual-centered and society-centered risk-benefit approaches to evaluate e-HPA.Regulation and Certification: Construct a self-regulation and certification framework within e-HPA.Education and Training: Make significant changes to medical, nursing, and paraprofessional curricula by including training for understanding, evaluating, and utilizing predictive models.

show abstract

Section: Introductionmentioning

confidence: 99%

“…For instance, there is a wide body of literature that indicates that those individuals living with low socioeconomic status have more chronic illness, receive less preventative care, and die earlier than more advantaged income groups ( Chen, Weider, Konopka, & Danis, 2014 ). Recognizing that HIT may facilitate the collection of SDH information to improve practice and policy, Chen et al (2014) recommended routinely assessing and recording socioeconomic status into the electronic health record. Prioritizing a comprehensive approach to health care that includes routine screening and early identification of the entirety of an individual’s social context would enable the multidisciplinary team to incorporate tailored interventions into the CSCP, thereby synchronizing care and ideally improving overall individual and population-level health outcomes.…”

Section: Introductionmentioning

confidence: 99%

Integrating social context into comprehensive shared care plans: A scoping review

et al. 2017

View full text Add to dashboard Cite

BackgroundFailure to address social determinants of health (SDH) may contribute to the problem of readmissions in high-risk individuals. Comprehensive shared care plans (CSCP) may improve care continuity and health outcomes by communicating SDH risk factors across settings.PurposeThe purpose of this study to evaluate the state of knowledge for integrating SDH into a CSCP. Our scoping review of the literature considered 13,886 articles, of which seven met inclusion criteria.ResultsIdentified themes were: integrate health and social sectors; interoperability; standardizing ontologies and interventions; process implementation; professional tribalism; and patient centeredness.DiscussionThere is an emerging interest in bridging the gap between health and social service sectors. Standardized ontologies and theoretical definitions need to be developed to facilitate communication, indexing, and data retrieval.ConclusionsWe identified a gap in the literature that indicates that foundational work will be required to guide the development of a CSCP that includes SDH that can be shared across settings. The lack of studies published in the United States suggests that this is a critical area for future research and funding.

show abstract

Incorporation of Socioeconomic Status Indicators into Policies for the Meaningful Use of Electronic Health Records

Cited by 25 publications

References 33 publications

Diagnosis of the socio-economic potential of health insurance

Diagnosis of the socio-economic potential of health insurance

Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges

Integrating social context into comprehensive shared care plans: A scoping review

Contact Info

Product

Resources

About