2016 ACC/ASE/ASNC/HRS/SCAI Health Policy Statement on Integrating the Healthcare Enterprise

Windle, John R.; Katz, Alan S.; Dow, John; Fry, Edward T.A.; Keller, Andrew; Lamp, Terran; Lippitt, Alexander; Paruche, Marianne P.; Resnic, Frederic S.; Serwer, Gerald A.; Slotwiner, David J.; Tcheng, James E.; Tilkemeier, Peter L.; Weiner, Bonnie H.; Weintraub, William S.

doi:10.1016/j.jacc.2016.04.017

Cited by 10 publications

(10 citation statements)

References 5 publications

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“…We asked registries to report on the methods they used to collect data. Given the need to reduce data entry burden, [ 11 12 ] we wanted to understand the methods by which registries extract data from electronic health records (EHRs), given that EHR data vary in content and format [ 13 14 15 ]. Given these variations, registry data are often captured by trained abstractors using a manual process [ 16 17 18 ].…”

Section: Methodsmentioning

confidence: 99%

The Use of Clinical Registries in the United States: A Landscape Survey

Blumenthal¹

2017

eGEMs

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Introduction:The use of information from clinical registries for improvement and value-based payment is increasing, yet information about registry use is not widely available. We conducted a landscape survey to understand registry uses, focus areas and challenges. The survey addressed the structure and organization of registry programs, as well as their purpose and scope.Setting:The survey was conducted by the National Quality Registry Network (NQRN), a community of organizations interested in registries. NQRN is a program of the PCPI, a national convener of medical specialty and professional societies and associations, which constitute a majority of registry stewards in the United States.Methods:We surveyed 152 societies and associations, asking about registry programs, governance, number of registries, purpose and data uses, data collection, expenses, funding and interoperability.Results:The response rate was 52 percent. Many registries were self-funded, with 39 percent spending less than $1 million per year, and 32 percent spending $1-9.9 million. The typical registry had three full-time equivalent staff. Registries were frequently used for quality improvement, benchmarking and clinical decision support. 85 percent captured outpatient data. Most registries collected demographics, treatments, practitioner information and comorbidities; 53 percent captured patient-reported outcomes. 88 percent used manual data entry and 18 percent linked to external secondary data sources. Cost, interoperability and vendor management were barriers to continued registry development.Conclusions:Registries captured data across a broad scope, audited data quality using multiple techniques, and used a mix of automated and manual data capture methods. Registry interoperability was still a challenge, even among registries using nationally accepted data standards.

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Section: Methodsmentioning

confidence: 99%

The Use of Clinical Registries in the United States: A Landscape Survey

Blumenthal¹

2017

eGEMs

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“…Two recent statements of the American Scientific community have addressed this methodological approach which places the registries at the centre of quality based medicine 4 , 5 …”

Section: Population Digital Healthmentioning

confidence: 99%

Big data: is clinical practice changing?

Tavazzi

2019

European Heart Journal Supplements

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The widespread diffusion of the digital culture and technology, involving both individual and population, together with the fast pacing digital globalization process (far surpassing ‘political’ globalization), is radically changing the world social landscape, including medicine and clinical research. The most significant change in clinical research is the ever more frequent acceptance of observational data, both through the use of registry of rare or common conditions and the implementation of capillary networks recording the daily clinical practice (Electronic Health Recording system). By becoming ‘observational’ clinical practice should change significantly: (i) record of different data (epidemiological, clinical, and administrative) in inter-operational database, producing a dynamic map of the health demands, either met or not, that allows a reconfiguration of the health systems capable to adapt to the shifting clinical needs. Implicate the larger group possible of patients and healthy individuals, who, through smartphone technology, could participate in primary and secondary prevention projects and epidemiological analyses. (ii) Support scientific research by integrating it with the clinical practice as instrument of good government that is scientific evidence-based Public Health System: the Learning Health System . The road will be long and gruelling. A first negative by-product is the proliferation of cybercrime throughout digital medicine.

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“…Appendix 6 provides a diagram of the 17-segment model with corresponding vascular territories. Mid anterior (7) Mid anterior (7) Mid anteroseptal (8) Mid anteroseptal (8) Mid anteroseptal (8) Mid inferoseptal (9) Mid inferoseptal (9) Mid inferoseptal (9) Mid inferior (10) Mid inferior (10) Mid inferior (10) Mid inferolateral (11) Mid inferolateral (11) Mid inferolateral (11) Mid anterolateral (12) Mid anterolateral (12) Mid anterolateral (12) Apical anterior (13) Apical anterior (13) Apical anterior (13) Apical septal (14) Apical septal (14) Apical septal (14) Apical inferior (15) Apical inferior (15) Apical inferior (15) Apical lateral (16) Apical lateral (16) Apical lateral (16) Apex (17) Apex (17) Apex ( Technique At rest, the patient received x mCi of x tracer. X minutes later, resting tomographic images of the heart were obtained.…”

Section: Registries and Public Reportingmentioning

confidence: 99%

“…This is supported through the utilization of the IHE standards for communication of data among different vendor systems and single and multimodality imaging environments. 11,12 The data from this new IHE standard have been incorporated into this document.…”

Section: Introductionmentioning

confidence: 99%