Consent Mechanisms for Electronic Health Record Systems: A Simple Yet Unresolved Issue

Win, Khin Than; Fulcher, John

doi:10.1007/s10916-006-9030-3

Cited by 31 publications

(17 citation statements)

References 14 publications

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“…Shared electronic record programmes in Scotland (emergency care summary), Wales (individual health record), and France (dossier médical personnel) have to some extent squared this circle by combining "implied consent to upload" with "explicit consent to view" at the point of care, although this has not been without controversy. [29][30][31][32] Connecting for Health is reviewing the SCR consent model in the light of our findings.…”

Section: Consent Modelmentioning

confidence: 96%

Introduction of shared electronic records: multi-site case study using diffusion of innovation theory

Greenhalgh

Stramer

Bratan

et al. 2008

BMJ

196

162

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Objective To explore the introduction of a centrally stored, shared electronic patient record (the summary care record (SCR)) in England and draw wider lessons about the implementation of large scale information technology projects in health care. Design Multi-site, mixed method case study applying utilisation focused evaluation. Setting Four early adopter sites for the SCR in Englandthree in urban areas of relative socioeconomic deprivation and the fourth in a relatively affluent rural area. Data sources and analysis Data included 250 staff interviews, 1500 hours of ethnographic observation, interviews and focus groups with 170 patients and carers, 2500 pages of correspondence and documentary evidence, and incorporation of relevant surveys and statistics produced by others. These were analysed by using a thematic approach drawing on (and extending) a theoretical model of complex change developed in a previous systematic review. Main findings The mixed fortunes of the SCR programme in its first year were largely explained by eight interacting influences. The first was the SCR's material properties (especially technical immaturity and lack of interoperability) and attributes (especially the extent to which potential adopters believed the benefits outweighed the risks). The second was adopters' concerns (especially about workload and the ethicality of sharing "confidential" information on an implied consent model). The third influence was interpersonal influence (for example, opinion leaders, champions, facilitators), and the fourth was organisational antecedents for innovation (for example past experience with information technology projects, leadership and management capacity, effective data capture systems, slack resources). The fifth was organisational readiness for the SCR (for example, innovation-system fit, tension for change, power balances between supporters and opponents, baseline data quality). The sixth was the implementation process (including the nature of the change model and the extent to which new routines associated with the SCR aligned with existing organisational routines). The seventh influence was the nature and quality of links between different parts of the system, and the final one was the wider environment (especially the political context of the programme).Conclusion Shared electronic records are not plug-in technologies. They are complex innovations that must be accepted by individual patients and staff and also embedded in organisational and inter-organisational routines. This process is heavily influenced at the microlevel by the material properties of the technology, individuals' attitudes and concerns, and interpersonal influence; at the meso-level by organisational antecedents, readiness, and operational aspects of implementation; and at the macro-level by institutional and socio-political forces. A case study approach and multi-level theoretical analysis can illuminate how contextual factors shape, enable, and constrain new, technology supported models of patient care. INT...

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Section: Consent Modelmentioning

confidence: 96%

Introduction of shared electronic records: multi-site case study using diffusion of innovation theory

Greenhalgh

Stramer

Bratan

et al. 2008

BMJ

196

162

View full text Add to dashboard Cite

show abstract

“…However, this approach has its own issues with the stored information sometimes being inaccurate and often incomplete[23–25]. There are also concerns around obtaining patient consent to use their data, with many patients not being informed[26]. …”

Section: Introductionmentioning

confidence: 99%

The prevalence of diagnosed chronic conditions and multimorbidity in Australia: A method for estimating population prevalence from general practice patient encounter data

et al. 2017

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ObjectivesTo estimate the prevalence of common chronic conditions and multimorbidity among patients at GP encounters and among people in the Australian population. To assess the extent to which use of each individual patient’s GP attendance over the previous year, instead of the average for their age-sex group, affects the precision of national population prevalence estimates of diagnosed chronic conditions.Design, setting and participantsA sub-study (between November 2012 and March 2016) of the Bettering the Evaluation and Care of Health program, a continuous national study of GP activity. Each of 1,449 GPs provided data for about 30 consecutive patients (total 43,501) indicating for each, number of GP attendances in previous year and all diagnosed chronic conditions, using their knowledge of the patient, patient self-report, and patient's health record.ResultsHypertension (26.5%) was the most prevalent diagnosed chronic condition among patients surveyed, followed by osteoarthritis (22.7%), hyperlipidaemia (16.6%), depression (16.3%), anxiety (11.9%), gastroesophageal reflux disease (GORD) (11.3%), chronic back pain (9.7%) and Type 2 diabetes (9.6%).After adjustment, we estimated population prevalence of hypertension as 12.4%, 9.5% osteoarthritis, 8.2% hyperlipidaemia, 8.0% depression, 5.8% anxiety and 5.2% asthma. Estimates were significantly lower than those derived using the previous method.About half (51.6%) the patients at GP encounters had two or more diagnosed chronic conditions and over one third (37.4%) had three or more. Population estimates were: 25.7% had two or more diagnosed chronic conditions and 15.8% had three or more.ConclusionsOf the three approaches we have tested to date, this study provides the most accurate method for estimation of population prevalence of chronic conditions using the GP as an expert interviewer, by adjusting for each patient’s reported attendance.

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“…However, as has been defined by privacy legislations such as HIPAA privacy rule, Data Privacy Rule UK, NSW Health Record Information Privacy Act and other legislations, health professionals can access patient data without explicit consent in medical emergencies(Win & Fulcher 2007;Win 2005;Sun et al 2011), and the healthcare provider is not forced to obtain patient consent to use or disclose such data for payment, treatment or healthcare operations(Murray, Calhoun & Philipsen 2011). The Digital Rights Management technique helps to provide patient consent in EHR systems(Chen, Lu & Jan 2012).…”

mentioning

confidence: 99%

A Systematic Literature Review on Security and Privacy of Electronic Health Record Systems: Technical Perspectives

Rezaeibagha

Win

Susilo

2015

HIM J

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Consent Mechanisms for Electronic Health Record Systems: A Simple Yet Unresolved Issue

Cited by 31 publications

References 14 publications

Introduction of shared electronic records: multi-site case study using diffusion of innovation theory

Introduction of shared electronic records: multi-site case study using diffusion of innovation theory

The prevalence of diagnosed chronic conditions and multimorbidity in Australia: A method for estimating population prevalence from general practice patient encounter data

A Systematic Literature Review on Security and Privacy of Electronic Health Record Systems: Technical Perspectives

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