Background
Methods
Study objectives
Identifying relevant studies
Eligibility criteria
Search strategy
Selecting studies for inclusion
Screening records
Sampling of studies
Data extraction
Data synthesis: collating, summarising and reporting findings
Reflexivity
Results
Results of the search
An overview of key characteristics of data harmonisation studies
Study name | Date | Type of study | Intervention term | Country | Level of the health care system |
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Commentary | |||||
Burris | 2017 | Commentary | HIE | USA | Frontline: hospitals |
Figge | 2010 | Commentary | HIE | USA | Management |
McIlwain | 2009 | Commentary | HIE | USA | Management |
Murphy | 2010 | Commentary | HIE | USA | Management |
Overhage | 2007 | Commentary | HIE | USA | Management |
Rudin | 2010 | Commentary | HIE | USA | Frontline: workers |
Conceptual | |||||
Boyd | 2014 | Conceptual | RL | Australia | Research |
Carr | 2013 | Conceptual | HIE | USA | Frontline: hospitals |
Cimino | 2014 | Conceptual | HIE | USA | Management |
Deas | 2012 | Conceptual | HIE | USA | Management |
Del Fiol | 2015 | Conceptual | HIE | USA | Frontline: prisons, hospitals |
Dimitropoulos | 2009 | Conceptual | HIE | USA | Management |
Downs | 2010 | Conceptual | HIE | USA | Management |
Feldman | 2017 | Conceptual | HIE | USA | Management |
Frisse | 2010 | Conceptual | HIE | USA | Frontline: patients, workers |
Frisse | 2008 | Conceptual | HIE | USA | Frontline: organisations |
Frohlich | 2007 | Conceptual | HIE | USA | Management |
Godlove | 2015 | Conceptual | HIE | USA | Frontline: patients |
Greene | 2016 | Conceptual | HIE | USA | Management |
Grossman | 2008 | Conceptual | HIE | USA | Management |
Haarbrandt | 2016 | Conceptual | DW | USA | Management |
Hu | 2007 | Conceptual | DS | USA | Management |
Jones | 2012 | Conceptual | DS | USA | Management |
Kuperman | 2013 | Conceptual | HIE | USA | Management |
Langabeer | 2016 | Conceptual | HIE | USA | Management |
Liu | 2011 | Conceptual | HIE | China | Management |
McDonald | 2009 | Conceptual | HIE | USA | Management |
McMurray | 2015 | Conceptual | HIE | USA | Management |
Miller | 2014 | Conceptual | HIE | USA | Frontline: hospitals |
Nelson | 2016 | Conceptual | HIE | USA | Frontline: prisons, hospitals |
Politi | 2014 | Conceptual | HIE | n/a | Management |
Ranade-Kharkar | 2014 | Conceptual | HIE | USA | Management |
Shapiro | 2016 | Conceptual | HIE | USA | Frontline: workers, organisations |
Shapiro | 2006 | Conceptual | HIE | USA | Management |
Thorn | 2013 | Conceptual | HIE | USA | Frontline: health care workers |
Thorn | 2014 | Conceptual | HIE | USA | Frontline: health care workers |
Vest | 2010 | Conceptual | HIE | USA | Management |
Williams | 2012 | Conceptual | HIE | USA | Management |
Yaraghi | 2014 | Conceptual | HIE | USA | Management |
Zafar | 2007 | Conceptual | HIE | USA | Management |
Zaidan | 2015 | Conceptual | HIE | Malaysia | Management |
Primary studies | |||||
Abramson | 2012 | Primary, quantitative | EHR, HIE | USA | Frontline, hospitals |
Adjerid | 2011 | Primary, quantitative | HIE | USA | Management, states |
Adler-Milstein | 2011 | Primary, quantitative | HIE | USA | Frontline: organisations |
Adler-Milstein | 2013 | Primary, quantitative | HIE | USA | Management, organisations |
Adler-Milstein | 2016 | Primary, quantitative | HIE | USA | Management |
Alexander | 2016 | Primary, qualitative | HIE | USA | Frontline, health care workers |
Alexander | 2015 | Primary, qualitative | HIE | USA | Frontline, health care workers |
Ancker | 2012 | Primary, quantitative | HIE | USA | Frontline, consumers |
Bahous | 2016 | Primary, quantitative | HIE | Israel | Frontline, hospital |
Bailey | 2013 | Primary, quantitative | HIE | USA | Frontline: hospital |
Ben-Assuli | 2013 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Boockvar | 2017 | Primary, quantitative | HIE | USA | Frontline: hospital |
Butler | 2014 | Primary, qualitative | HIE | USA | Frontline: prisons, communities |
Campion | 2012 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Campion | 2013 | Primary, quantitative | HIE | USA | Frontline: communities |
Campion | 2013 | Primary, quantitative | HIE | USA | Frontline: clinics, hospitals |
Campion | 2014 | Primary, quantitative | DE | USA | Frontline: organisations |
Carr | 2014 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Carr | 2016 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Cochran | 2015 | Primary, qualitative | HIE | USA | Frontline: clinics, communities |
Cross | 2016 | Primary, qualitative | HIE | USA | Management, organisations |
Dalan | 2010 | Primary, qualitative | DM | USA | Research |
Dimitropoulos | 2011 | Primary, quantitative | HIE | USA | Frontline: consumers |
Dixon | 2013 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Dixon | 2011 | Primary, quantitative | HIE | USA | Frontline: laboratories |
Downing | 2017 | Primary, quantitative | HIE | USA | Management: policy |
Dullabh | 2013 | Primary, qualitative | HIE | USA | Management: organisations |
Elysee | 2017 | Primary, quantitative | HIE, IO | USA | Frontline: hospitals |
Foldy | 2007 | Primary, quantitative | HIE | USA | Management: organisations |
Fontaine | 2010 | Primary, qualitative | HIE | USA | Frontline: primary health care |
French | 2016 | Primary, quantitative | HIE | USA | Management: organisations |
Fricton | 2008 | Primary, quantitative | HIE | USA | Frontline: patients, workers |
Frisse | 2012 | Primary, quantitative | HIE | USA | Frontline: organisations |
Furukawa | 2013 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Furukawa | 2014 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Gadd | 2011 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Garg | 2014 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Gill | 2001 | Primary, quantitative | DL | South Africa | Frontline: patients, disease |
Grinspan | 2013 | Primary, quantitative | HIE | USA | Frontline: patients |
Grinspan | 2014 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Grinspan | 2015 | Primary, quantitative | HIE | USA | Frontline: patients |
Hassol | 2014 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Herwehe | 2012 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Hincapie | 2011 | Primary, qualitative | HIE | USA | Frontline: health care workers |
Holman | 2008 | Primary, quantitative | DL | USA | Frontline: organisations, research |
Hypponen | 2014 | Primary, quantitative | HIE | Finland | Frontline: health care workers |
Ji | 2017 | Primary, quantitative | HIE | Korea | Frontline: hospitals |
Johnson | 2011 | Primary, mixed | HIE | USA | Frontline: hospitals |
Jung | 2015 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Kaelber | 2013 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Kierkegaard | 2014 | Primary, qualitative | HIE | USA | Frontline: health care workers |
Kierkegaard | 2014 | Primary, qualitative | HIE | USA | Management |
Kim | 2012 | Primary, qualitative | HIE | Korea | Management |
Knaup | 2006 | Primary. quantitative | DS | Germany | Frontline: hospitals |
Kralewski | 2012 | Primary, qualitative | CIE | USA | Frontline: organisations, workers |
Laborde | 2011 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Lee | 2012 | Primary, quantitative | HIE | South Korea | Frontline: health care workers |
Li | 2011 | Primary, quantitative | DE | Japan & China | Frontline: organisations |
Liu | 2010 | Primary, qualitative | DH | China | Management |
Lobach | 2007 | Primary, quantitative | HIE | USA | Management |
Maenpaa | 2011 | Primary, quantitative | HIE | Finland | Frontline: hospital |
Maiorana | 2012 | Primary, mixed | HIE | USA | Frontline: workers, disease |
Martinez | 2015 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Massoudi | 2016 | Primary, qualitative | HIE | USA | Frontline: organisations |
Mastebroek | 2017 | Primary, qualitative | HIE | Netherlands | Frontline: patients |
Mastebroek | 2017 | Primary, qualitative | HIE | Netherlands | Frontline: patients |
Mastebroek | 2016 | Primary, quantitative | HIE | Netherlands | Frontline: health care workers |
Matsumoto | 2017 | Primary, qualitative | HIE | USA | Frontline: workers, hospitals |
Medford-Davis | 2017 | Primary, quantitative | HIE | USA | Frontline: patients, hospitals |
Mello | 2018 | Primary, qualitative | HIE | USA | Management: policies |
Merrill | 2013 | Primary, quantitative | HIE | USA | Frontline: managers |
Messer | 2012 | Primary, mixed | HIE | USA | Frontline: clinics, organisations |
Miller | 2012 | Primary, qualitative | HIE | USA | Frontline: consumers, organisations |
Miller | 2017 | Primary, quantitative | HIE | USA | Frontline: disease, workers |
Moore | 2012 | Primary, quantitative | HIE | USA | Frontline: workers, hospitals |
Motulsky | 2018 | Primary, quantitative | HIE | Canada | Frontline: workers |
Myers | 2012 | Primary, qualitative | HIE | USA | Frontline: disease, workers |
Obeidat | 2014 | Primary, quantitative | IE | Jordan | Frontline: hospitals |
O’Donnell | 2011 | Primary, quantitative | HIE | USA | Frontline: workers |
Onyile | 2013 | Primary, quantitative | HIE | USA | Frontline: patients |
Opoku-Agyeman | 2016 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Overhage | 2017 | Primary, quantitative | HIE | USA | Management |
Ozkaynak | 2013 | Primary, qualitative | HIE | USA | Frontline: hospitals, workers |
Park | 2015 | Primary, quantitative | HIE | South Korea | Frontline: clinics, hospitals |
Park | 2013 | Primary, quantitative | HIE | South Korea | Frontline: clinics, hospitals |
Patel | 2011 | Primary, quantitative | HIE | USA | Frontline: clinics, hospitals |
Politi | 2015 | Primary, quantitative | HIE | Israel | Frontline: hospital |
Ramos | 2016 | Primary, mixed | HIE | USA | Frontline: patients |
Ramos | 2014 | Primary, qualitative | HIE | USA | Frontline: patients |
Reis | 2016 | Primary, quantitative | HDE | USA | Frontline: hospital |
Richardson | 2014 | Primary, qualitative | HIE | USA | Frontline: organisations, workers |
Ross | 2010 | Primary, qualitative | HIE | USA | Frontline: clinics |
Ross | 2013 | Primary, quantitative | HIE | USA | Frontline: workers, clinics, hospitals |
Rudin | 2009 | Primary, qualitative | HIE | USA | Frontline: health care workers |
Rundall | 2016 | Primary, qualitative | HIE | USA | Management: policy makers, leaders |
Saef | 2014 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Santos | 2017 | Primary, quantitative | HIE | Brazil | Frontline: clinics, hospitals |
Shade | 2012 | Primary, quantitative | HIE | USA | Frontline: clinics, hospitals |
Shank | 2012 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Shapiro | 2013 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Shapiro | 2007 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Sicotte | 2010 | Primary, qualitative | HIE | Canada | Frontline: workers, hospitals |
Sprivulis | 2007 | Primary, quantitative | HIE | Australia | Frontline: workers, organisations |
Squire | 2002 | Primary, mixed | HIE | USA | Frontline: health care workers |
Sridhar | 2012 | Primary, quantitative | HIE | USA | Frontline: hospital |
Thornewill | 2011 | Primary, mixed | HIE | USA | Frontline: consumers, organisations |
Unertl | 2012 | Primary, qualitative | HIE | USA | Frontline: clinics, hospitals |
Vest | 2010 | Primary, qualitative | HIE | USA | Frontline: hospitals |
Vest | 2017 | Primary, qualitative | HIE | USA | Frontline: consumers, organisations |
Vest | 2015 | Primary, qualitative | HIE | USA | Frontline: consumers, organisations |
Vest | 2013 | Primary, qualitative | HIE | USA | Management: policy makers |
Vest | 2009 | Primary, quantitative | HIE | Frontline: workers, patients | |
Vest | 2017 | Primary, quantitative | HIE | USA | Frontline: consumers, organisations |
Vest | 2011 | Primary, quantitative | HIE | USA | Frontline: patients, hospitals |
Vest | 2014 | Primary, quantitative | HIE | USA | Frontline: patients, hospitals |
Vest | 2014 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Vest | 2015 | Primary, quantitative | HIE | USA | Frontline: hospitals |
Vreeman | 2008 | Primary, quantitative | HIE | USA | Frontline: laboratory, radiology |
Wen | 2010 | Primary, quantitative | HIE | USA | Frontline: patients |
Winden | 2014 | Primary, quantitative | HIE | USA | Frontline: clinical care |
Wright | 2010 | Primary, quantitative | HIE | USA | Frontline: health care workers |
Yeager | 2014 | Primary, qualitative | HIE | USA | Frontline: consumers |
Yeaman | 2015 | Primary, quantitative | HIE | USA | Frontline: hospital |
Zech | 2015 | Primary, quantitative | HIE | USA | Frontline: patients, organisations |
Zech | 2016 | Primary, quantitative | HIE | USA | Frontline: patients, organisations |
Zhu | 2010 | Primary quantitative | HIE | USA | Research |
Study protocol | |||||
Dixon | 2013 | Protocol, mixed | HIE | USA | Frontline: organisations |
Reviews | |||||
Esmaeilzadeh | 2016 | Review | HIE | n/a | Management: policy |
Esmaeilzadeh | 2017 | Review | HIE | n/a | Frontline: patients |
Fontaine | 2010 | Review | HIE | n/a | Frontline: primary health care |
Hopf | 2014 | Review | DL | n/a | Frontline: health care workers |
Kash | 2017 | Review | HIE | n/a | Frontline: hospitals |
Mastebroek | 2014 | Review | HIE | USA | Frontline: disease, workers |
Parker | 2016 | Review | HIE | USA | Research |
Rahurkar | 2015 | Review | HIE | n/a | Frontline: hospital |
Rudin | 2014 | Review | HIE | USA | Frontline: clinical care |
Sadoughi | 2018 | Review | HIE | n/a | Management |
Vest | 2012 | Review | HIE | n/a | Management |
Dixon | 2010 | Review | HIE | USA | Research |
Akhlaq | 2016 | Review | HIE | LMICs | Management, countries |
Definitions, components and processes of data harmonisation
Study name | Date | Type of study | Intervention term | Country | Level of the health care system | Purpose of the study |
---|---|---|---|---|---|---|
Akhlaq | 2016 | Review, qualitative | HIE | LMICs | Management, countries | Barriers and facilitators of HIE |
Boyd Boyd | 2014 | Conceptual | RL | Australia | Research | Functions of record linkage |
Burris | 2017 | Commentary | HIE | USA | Frontline: hospitals | Benefits of HIE |
Campion | 2012 | Primary, quantitative | HIE | USA | Frontline: health care workers | Push and pull of HIE |
Cimino | 2014 | Conceptual | HIE | USA | Management | Debates around consumer-mediated HIE |
Dalan | 2010 | Conceptual | DM | USA | Management | Possibilities for clinical data mining and research |
Dimitropoulos | 2009 | Conceptual | HIE | USA | Management | Privacy and security of interoperable HIE |
Dixon | 2010 | Review, framework | HIE | USA | Research | Costs, effort and value of HIE |
Downing | 2017 | Primary, quantitative | HIE | USA | Management: policy | Relationship between HIE and organisational HIE policy decisions |
Downs | 2010 | Conceptual | HIE | USA | Management | Improving laboratory services through HIE |
Dullabh | 2013 | Primary, qualitative | HIE | USA | Management: organisations | Experience of HIE implementation |
Elysee Elysee | 2017 | Primary, quantitative | HIE, IO | USA | Frontline: hospitals | Relationship between HIE, interoperability and medication reconciliation |
Esmaeilzadeh | 2016 | Review | HIE | n/a | Management: policy | HIE assimilation and patterns for policy |
Esmaeilzadeh | 2017 | Review | HIE | n/a | Frontline: patients | Patients’ perceptions of HIE |
Fontaine | 2010 | Review | HIE | n/a | Frontline: primary health care | HIE for primary health care practices |
Fontaine | 2010 | Primary, qualitative | HIE | USA | Frontline: primary health care | Barriers and facilitators of HIE in primary care practices |
Frisse | 2010 | Conceptual | HIE | USA | Frontline: patients, workers | Impact of HIE on patient-provider relationships |
Gadd | 2011 | Primary, quantitative | HIE | USA | Frontline: health care workers | Users’ perspectives on the usability of a regional HIE |
Gill | 2001 | Primary, quantitative | DL | South Africa | Frontline: patients, disease | Linkage of non-communicable diseases data |
Greene | 2016 | Conceptual | HIE | USA | Management | Technical and financial aspects of HIE |
Grossman | 2008 | Conceptual | HIE | USA | Management | Barriers to stakeholder participation in HIE |
Haarbrandt | 2016 | Conceptual | DW | USA | Management | Approaches for a clinical data warehouse |
Herwehe | 2012 | Primary, quantitative | HIE | USA | Frontline: health care workers | Implementation of an electronic medical record and HIE |
Hincapie | 2011 | Primary, qualitative | HIE | USA | Frontline: health care workers | Physicians’ opinions of HIE |
Hopf | 2014 | Review | DL | n/a | Frontline: health care workers | Healthcare professionals’ views of linking routinely collected data |
Hu | 2007 | Conceptual | DS | USA | Management | Challenges in implementing an infectious disease information sharing and analysis system |
Hypponen | 2014 | Primary, quantitative | HIE | Finland | Frontline: health care workers | User experiences with different regional HIE |
Ji | 2017 | Primary, quantitative | HIE | Korea | Frontline: hospitals | Technology and policy changes for HIE |
Jones | 2012 | Conceptual | DS | USA | Management | An overview of electronic data sharing |
Kash | 2017 | Review | HIE | n/a | Frontline: hospitals | Hospital readmission reduction and the role of HIE |
Kierkegaard | 2014 | Primary, qualitative | HIE | USA | Frontline: health care workers | Applications of HIE information to public health practice |
Kierkegaard | 2014 | Primary, qualitative | HIE | USA | Management | Health practitioners’ needs and HIE |
Kuperman | 2013 | Conceptual | HIE | USA | Management | Potential unintended consequences of HIE |
Liu | 2010 | Primary, qualitative | DH | China | Management | Defining data elements for HIE |
Maiorana | 2012 | Primary, mixed | HIE | USA | Frontline: workers, disease | Trust, confidentiality and acceptability of sharing HIV data for HIE |
Massoudi | 2016 | Primary, qualitative | HIE | USA | Frontline: organisations | HIE for clinical quality measures |
Mastebroek | 2014 | Review | HIE | USA | Frontline: disease, workers | HIE in general care practice for people with disabilities |
Mastebroek | 2016 | Primary, quantitative | HIE | Netherlands | Frontline: health care workers | Priority setting and feasibility of HIE |
Mastebroek | 2017 | Primary, qualitative | HIE | Netherlands | Frontline: patients | Experiences of people with intellectual disabilities in HIE |
Matsumoto | 2017 | Primary, qualitative | HIE | USA | Frontline: workers, hospitals | HIE in managing hospital services |
Parker | 2016 | Review | HIE | USA | Research | The use of HIE in supporting clinical research |
Politi | 2014 | Conceptual | HIE | n/a | Management | Use patterns of HIE |
Rahurkar | 2015 | Review | HIE | n/a | Frontline: hospital | Impact of HIE on cost, use and quality of care |
Ramos | 2016 | Primary, mixed | HIE | USA | Frontline: patients | HIE consent process in an HIV clinic |
Ranade-Kharkar | 2014 | Conceptual | HIE | USA | Management | Improving data quality integrity through HIE |
Ross | 2010 | Primary, qualitative | HIE | USA | Frontline: clinics | Motivators, barriers, and potential facilitators of adoption of HIE |
Rudin | 2014 | Review | HIE | USA | Frontline: clinical care | Use and effect of HIE on clinical care |
Vest | 2016 | Primary, qualitative | HIE | USA | Management: policy makers, leaders | Information-sharing needs and HIE |
Sadoughi | 2018 | Review | HIE | n/a | Management | Quality and cost-effectiveness, and the rates of HIE adoption and participation |
Santos | 2017 | Primary, quantitative | HIE | Brazil | Frontline: clinics, hospitals | HIE for continuity of maternal and neonatal care |
Shade | 2012 | Primary, quantitative | HIE | USA | Frontline: clinics, hospitals | HIE for quality and continuity of HIV care |
Shapiro | 2016 | Conceptual | HIE | USA | Frontline: workers, organisations | HIE in emergency medicine |
Shapiro | 2006 | Conceptual | HIE | USA | Management | Approaches to patient HIE and their impact on emergency medicine |
Vest | 2012 | Review | HIE | n/a | Management | National and international approaches of health information exchange |
Vest | 2015 | Primary, qualitative | HIE | USA | Frontline: consumers, organisations | HIE to change cost and utilisation outcomes |
Vest | 2010 | Conceptual | HIE | USA | Management | Challenges and strategies for HIE |
Williams | 2012 | Conceptual | HIE | USA | Management | Strategies to advance HIE |
Yaraghi | 2014 | Conceptual | HIE | USA | Management | Professional and geographical network effects on HIE growth |
Yeager | 2014 | Primary, qualitative | HIE | USA | Frontline: consumers | Factors related to HIE participation and use |
Zaidan | 2015 | Conceptual | HIE | Malaysia | Management | Security framework for nationwide HIE |
Zhu | 2010 | Primary quantitative | HIE | USA | Research | Facilitating clinical research through HIE |
Alternative terms and definitions of data harmonisation
Liu 2010 [1] | Data harmonisation is the process of integrating life-long health data of a person that are distributed in inhomogeneous information systems through identifying, reviewing, matching, redefining and standardising information. This process involves two steps. Firstly, identifying whether all the information necessary for a single electronic platform is available in existing systems, where the information is, and how the information is defined and formatted. And secondly, to make the heterogeneous information recorded by various systems consistent or at least comparable with one another by reviewing, matching, redefining and standardising each data item. |
Boyd 2014 [16] | Record linkage is the process of bringing together data relating to the same individual from within and between different datasets. When a unique person-based identifier exists, linkage can be achieved by simply merging datasets on the identifier. However, when a person-based identifier does not exist, then some other form of data matching or record linkage is required for integrating data. |
Gill 2001 Hopf 2014 | Data linkage can be used to construct a register for a specific geographic area and disease (for example, a district non-communicable disease register). Linkage of routine datasets by unique patient identifiers can provide an opportunity for identifying adverse drug reactions and tracking exposed individuals in real time. Routine data linkage can also enable the creation of exposure cohorts to monitor long-term outcomes and enable a more efficient screening for adverse drug reactions due to an ever-increasing data pool. |
Haarbrandt 2016 [28] | Data warehousing is the process of establishing specialised databases by integrating information systems (the authors specifically referred to hospital information systems) to facilitate secondary use of data. Clinical data warehouses are generally built on one of two predominant architectural paradigms: either, data is directly extracted, transformed and loaded from applications systems and databases into a data mart (an integrated view over a defined subject), or it is stored in a centralised data repository from which data marts can be established. Both approaches rely on a process to extract data from sources, transform it appropriately and to load it (or copy it) to a specific database. |
Hu et al., 2007 [17] Jones 2012 | Data sharing is based on the need for a more robust method for defining and sharing expected and actual patient outcomes. It must leverage existing informatics tools since a great deal of patient-specific information is already available in medical record systems and billing and administrative systems. One type of data sharing system is an infectious disease informatics (IDI) system. An IDI system should encompass sophisticated algorithms for the automatic detection of emerging disease patterns and the identification of probable threats or events. It should also have advanced computational models that overlay health data for spatial–temporal analysis to support public health professionals’ analysis tasks. |
Elysee 2017 [29] | Data interoperability is one of two functionalities of an advanced electronic health record. The first function is health information exchange, which is the ability to electronically share patient-level information among unaffiliated providers across organisational boundaries. The second function is interoperability, which is the ability to produce standardised patient-level health information that can be integrated into unaffiliated health care providers’ electronic health records. |
Akhlaq 2016 [15] Esmaeilzadeh 2017 [35] Fontaine 2010 [36] Hopf 2014 [38] Kash 2017 [39] Mastebroek 2014 [27] Parker 2016 [42] Rahurkar 2015 [44] Rudin 2014 [45] Sadoughi 2018 [46] Vest 2012 [48] | Health information exchange (HIE) is a type of health information technology (HIT) intervention. It involves the electronic mobilisation of clinical and administrative data or information within or across data repositories or organisations in a community or region, between various systems as per recognised standards. This is to ensure that the HIE maintains the authenticity and accuracy of the information being exchanged, thereby enabling stakeholders to make informed decisions to enhance healthcare quality and delivery of patients and populations. Sharing clinical data can potentially improve patient safety, care coordination, quality of care and efficiency, facilitate public health efforts and reduce mortality and healthcare costs. Lastly, HIE involves multi-stakeholder organisations that oversee the business, operational and legal issues involved in the exchange of information. |
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Any type of DH intervention or activity is a process of multiple steps involving both technical and social processes.
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The goal of a DH intervention or activity is to integrate, harmonise and bring together different electronic databases into useable formats.
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There are at least two or more databases involved in any DH intervention or activity.
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A data harmonisation intervention or activity involves electronic data (no reference is made to data found in paper-based sources).
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Data harmonisation occurs when there is an increasing availability of electronic data that can be pooled together using unique patient identifiers.
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Different types of data can be linked and shared such as individual patient clinical, pharmacy and laboratory data, health care utilisation and cost data, and personnel-related data.
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Electronic data required for DH processes can be found within and across different departments and institutions at facility, district, regional and national levels.
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A data harmonisation process consists of different types of technical activities such as identifying, reviewing, matching, defining, redefining, standardising, merging, linking, merging and formatting data.
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DH interventions or activities are defined according to a specific scope and purpose such as disease surveillance, monitoring of long-term outcomes, screening for adverse events, geographic area, secondary data use and data display mechanisms (data marts or dashboards).
Components and processes of data harmonisation
The relationship between data harmonisation and health management decision-making
Cimino 2014 [21] | “Data completeness: A promise of HIEs is to use consolidated information over time and across providers to improve medical decision-making for the patient. When presenting a medical timeline for a patient, how does a provider know whether the HIE presentation of history is missing information? The consequences to patients can be devastating.” |
Downs 2010 [32] | “… community-based approach to establish a common pathway based on common data standards to facilitate the incorporation of interoperable, clinically useful genetic or genomic information and analytical tools into EHRs to support clinical decision-making for the clinician and consumer.” |
Grossman 2008 [37] | “… the exchanges going beyond core clinical data exchange activities that give physicians access to data at the point of care to offering physicians clinical decision support, reminders and other quality improvement tools aimed at individual patients.” |
Kuperman 2013 [40] | “Ideally, a physician would have access to complete, accurate and timely patient data to support optimal decision making. Health information exchange capabilities will reduce the extent of data fragmentation but will not eliminate it entirely.” |
Politi 2014 [41] | “In this scenario, an HIE system is likely to have a significant impact on clinical decision making if information is readily accessible; the need for rapid decisions might render the scrutiny of an HIE system impractical.” |
Vest 2010 [43] | “The anticipated benefits of more data to inform physician decision making, sparing patients of needless tests, helping organization identify inappropriately managed patients, and improving the health of the public will only be achieved by HIE that does not exclude providers in an area, limit what data elements are available, or restrict exchange to specific subpopulations.” |
Shapiro 2006 [47] | “The goal of a nationwide health information network would be to deliver information to individuals– consumers, patients, and professionals –when and where they need it, so they can use this information to make informed decisions about health and health care.” |
Vest 2015 [49] | “Improved access to more comprehensive information may support decision-making, inform providers of additional medications or allegories, and help avoid repeated or duplicate testing.” |
Zaiden 2015 [50] | “Combined with data mining and statistical analysis tools, these repositories of health information can greatly advance medical knowledge, healthcare quality, and good strategic management.” |
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Clinical decision-making for individual patient clinical management or clinical support and quality improvement tools
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Operational and strategic decision-making for health system managers and policy-makers
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Population-level decision-making for disease surveillance and outbreak management