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BMC Medical Informatics and Decision Making

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Open Access 01-12-2020 | Research article

Definitions, components and processes of data harmonisation in healthcare: a scoping review

Authors: Bey-Marrié Schmidt, Christopher J. Colvin, Ameer Hohlfeld, Natalie Leon

Published in: BMC Medical Informatics and Decision Making | Issue 1/2020

Abstract

Background

Data harmonisation (DH) has emerged amongst health managers, information technology specialists and researchers as an important intervention for routine health information systems (RHISs). It is important to understand what DH is, how it is defined and conceptualised, and how it can lead to better health management decision-making. This scoping review identifies a range of definitions for DH, its characteristics (in terms of key components and processes), and common explanations of the relationship between DH and health management decision-making.

Methods

This scoping review identified relevant studies from 2000 onwards (date filter), written in English and published in PubMed, Web of Science and CINAHL. Two reviewers independently screened records for potential inclusion for the abstract and full-text screening stages. One reviewer did the data extraction, analysis and synthesis, with built-in reliability checks from the rest of the team. We developed a narrative synthesis of definitions and explanations of the relationship between DH and health management decision-making.

Results

We sampled 61 of 181 included to synthesis definitions and concepts of DH in detail. We identified six common terms for data harmonisation: record linkage, data linkage, data warehousing, data sharing, data interoperability and health information exchange. We also identified nine key components of data harmonisation: DH involves (a) a process of multiple steps; (b) integrating, harmonising and bringing together different databases (c) two or more databases; (d) electronic data; (e) pooling data using unique patient identifiers; and (f) different types of data; (g) data found within and across different departments and institutions at facility, district, regional and national levels; (h) different types of technical activities; (i) has a specific scope. The relationship between DH and health management decision-making is not well-described in the literature. Several studies mentioned health providers’ concerns about data completeness, data quality, terminology and coding of data elements as barriers to data utilisation for clinical decision-making.

Conclusion

To our knowledge, this scoping review was the first to synthesise definitions and concepts of DH and address the causal relationship between DH and health management decision-making. Future research is required to assess the effectiveness of data harmonisation on health management decision-making.

Liu D, et al. Harmonization of health data at national level: a pilot study in China. Int J Med Inform. 2010;79(6):450 https://doi.org/10.1016/j.ijmedinf.2010.03.002.PubMed

Nutley T, Reynolds H. Improving the use of health data for health system strengthening. Glob Health Action. 2013;6(1):20001 https://doi.org/10.3402/gha.v6i0.20001.PubMed

Lippeveld T. Routine health information systems: the glue of a unified health system. In: Keynote address at the Workshop on Issues and Innovation in Routine Health Information in Developing Countries. Potomac; 2001.

World Health Organization. Everybody's business-strengthening health systems to improve health outcomes: WHO's framework for action; 2007. Retrieved from https://www.who.int/healthsystems/strategy/everybodys_business.pdf?ua=1.

World Health Organization. Country health information systems assessments: overview and lessons learnt. 2012.

Heywood A, Boone D. Guidelines for data management standards in routine health information systems. Measure Evaluation. 2015; Retrieved from https://www.measureevaluation.org/resources/publications/ms-15-99.

Karuri J, et al. DHIS2: the tool to improve health data demand and use in Kenya. J Health Informatics Dev Countries. 2014;8(1):38 Retrieved from https://jhidc.org/index.php/jhidc/article/view/113.

Harrison MI, et al. Unintended consequences of information technologies in health care—an interactive sociotechnical analysis. J Am Med Inform Assoc. 2007;14(5):542 https://doi.org/10.1197/jamia.M2384.PubMedPubMedCentral

Olmen JV, et al. The Health System Dynamics Framework: The introduction of an analytical model for health system analysis and its application to two case-studies. Health Culture Soc. 2012;2(1):1 Retrieved from https://hcs.pitt.edu/ojs/index.php/hcs/article/view/71/0.

10.

Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. BMJ Qual Saf. 2010;19(Suppl 3):i68 https://doi.org/10.1136/qshc.2010.042085.

11.

Plsek, P. Complexity and the adoption of innovation in health care. Accelerating Quality Improvement in Health Care: Strategies to Accelerate the Diffusion of Evidence-Based Innovations. National Institute for Healthcare Management Foundation and National Committee for Quality in Health Care. 2003. Retrieved from https://www.nihcm.org/pdf/Plsek.pdf.

12.

Cresswell KM, Sheikh A. Undertaking sociotechnical evaluations of health information technologies. J Innovation Health Informatics. 2014;21(2):78 https://doi.org/10.14236/jhi.v21i2.54.

13.

Cresswell KM, et al. Ten key considerations for the successful optimization of large-scale health information technology. J Am Med Inform Assoc. 2016;24(1):182 https://doi.org/10.1093/jamia/ocw037.PubMed

14.

Fichtinger A, et al. Data harmonisation put into practice by the HUMBOLDT project. Int J Spatial Data Infrastructures Res. 2011;6:234 https://doi.org/10.2902/ijsdir.v6i0.191.

15.

Akhlaq A, et al. Barriers and facilitators to health information exchange in low- and middle-income country settings: a systematic review. Health Policy Plan. 2016;31(9):1310 https://doi.org/10.1093/heapol/czw056.PubMed

16.

Boyd JH, et al. Technical challenges of providing record linkage services for research. BMC Med Informatics Decision Making. 2014;14(1):23 https://doi.org/10.1186/1472-6947-14-23.

17.

Hu PJ, et al. System for infectious disease information sharing and analysis: design and evaluation. IEEE Trans Inf Technol Biomed. 2007a;11(4):483 https://doi.org/10.1109/titb.2007.893286.PubMedPubMedCentral

18.

Aqil A, et al. PRISM framework: a paradigm shift for designing, strengthening and evaluating routine health information systems. Health Policy Plan. 2009;24(3):217 https://doi.org/10.1093/heapol/czp010.PubMedPubMedCentral

19.

Arksey H, O'Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19 https://doi.org/10.1080/1364557032000119616.

20.

Schmidt B-M, et al. Defining and conceptualising data harmonisation: a scoping review protocol. Syst Rev. 2018;7(1):226 https://doi.org/10.1186/s13643-018-0890-7.PubMedPubMedCentral

21.

Cimino JJ, et al. Consumer-mediated health information exchanges: the 2012 ACMI debate. J Biomed Inform. 2014;48(2014):5 https://doi.org/10.1016/j.jbi.2014.02.009.PubMedPubMedCentral

22.

Tricco AC, et al. A scoping review on the conduct and reporting of scoping reviews. BMC Med Res Methodol. 2016;16(1):15 https://doi.org/10.1016/j.jbi.2014.02.009.PubMedPubMedCentral

23.

Cochrane Effective Practice and Organisation of Care (EPOC) Group. EPOC Qualitative Evidence Syntheses: protocol template. 2018. Retrieved from https://epoc.cochrane.org/news/qualitative-evidence-synthesis-template.

24.

Suri H. Purposeful sampling in qualitative research synthesis. Qual Res J. 2011;11(2):63 https://doi.org/10.3316/QRJ1102063.

25.

Popay J, et al. Guidance on the conduct of narrative synthesis in systematic reviews. In: A product from the ESRC methods programme; 2006. https://doi.org/10.13140/2.1.1018.4643.

26.

Leon N, et al. Routine Health Information System (RHIS) interventions to improve health systems management. Cochrane Database Syst Rev. 2015;12(CD012012):1 https://doi.org/10.1002/14651858.CD012012.

27.

Mastebroek M, Naaldenberg J, Lagro-Janssen AL, van Schrojenstein Lantman de Valk H. Health information exchange in general practice care for people with intellectual disabilities: a qualitative review of the literature. Res Dev Disabil. 2014;35(9):1978–87 https://doi.org/10.1016/j.ridd.2014.04.029.PubMed

28.

Haarbrandt BE, et al. Automated population of an i2b2 clinical data warehouse from an openEHR-based data repository. J Biomed Inform. 2016;63(2016):277 https://doi.org/10.1016/j.jbi.2016.08.007.PubMed

29.

Elysee GJ, et al. An observational study of the relationship between meaningful use-based electronic health information exchange, interoperability, and medication reconciliation capabilities. Medicine (Baltimore). 2017;96(41):e8274 https://doi.org/10.1097/MD.0000000000008274.

30.

Ji H, et al. Technology and policy challenges in the adoption and operation of health information exchange systems. Adv Health Care Manag. 2017;23(4):314 https://doi.org/10.4258/hir.2017.23.4.314.

31.

Santos MR, et al. Health information exchange for continuity of maternal and neonatal care supporting: a proof-of-concept based on ISO standard. Applied Clin Informatics. 2017;8(4):1082 https://doi.org/10.4338/ACI-2017-06-RA-0106.

32.

Downs SM, van Dyck PC, Rinaldo P, McDonald C, Howell RR, Zuckerman A, Downing G. Improving newborn screening laboratory test ordering and result reporting using health information exchange. J Am Med Inform Assoc. 2010;17(1):13–8 https://doi.org/10.1197/jamia.M3295.PubMedPubMedCentral

33.

Dixon BE, Zafar A, Overhage JM. A Framework for evaluating the costs, effort, and value of nationwide health information exchange. J Am Med Inform Assoc. 2010;17(3):295–301 https://doi.org/10.1136/jamia.2009.000570.PubMedPubMedCentral

34.

Esmaeilzadeh P, Sambasivan M. Health Information Exchange (HIE): A literature review, assimilation pattern and a proposed classification for a new policy approach. J Biomed Inform. 2016;64:74–86. https://doi.org/10.1016/j.jbi.2016.09.011.PubMedCrossRef

35.

Esmaeilzadeh P, Sambasivan M. Patients’ support for health information exchange: a literature review and classification of key factors. BMC Med Inform Decis Mak. 2017;17:33 https://doi.org/10.1186/s12911-017-0436-2.PubMedPubMedCentral

36.

Fontaine P, Ross SE, Zink T, Schilling LM. Systematic review of health information exchange in primary care practices. J Am Board Fam Med. 2010;23(5):655–70. https://doi.org/10.3122/jabfm.2010.05.090192.PubMedCrossRef

37.

Grossman JM, Kushner KL, November EA. Creating sustainable local health information exchanges: can barriers to stakeholder participation be overcome? Res Brief. 2008;2:1–12.

38.

Hopf YM, Bond C, Francis J, Haughney J, Helms PJ. Views of healthcare professionals to linkage of routinely collected healthcare data: a systematic literature review. J Am Med Inform Assoc. https://doi.org/10.1136/amiajnl-2012-001575.

39.

Kash BA, Baek J, Davis E, Champagne-Langabeer T, Langabeer JR 2nd. Review of successful hospital readmission reduction strategies and the role of health information exchange. Int J Med Inform. 2017;104:97–104 https://doi.org/10.1016/j.ijmedinf.2017.05.012.PubMed

40.

Kuperman GJ, McGowan JJ. Potential unintended consequences of health information exchange. J Gen Intern Med. 2013;28(12):1663–6 https://doi.org/10.1007/s11606-012-2313-0.PubMedPubMedCentral

41.

Politi L, Codish S, Sagy I, Fink L. Use patterns of health information exchange through a multidimensional lens: conceptual framework and empirical validation. J Biomed Inform. 2014;52:212–21 https://doi.org/10.1016/j.jbi.2014.07.003.PubMed

42.

Parker C, Weiner M, Reeves M. Health information exchanges--Unfulfilled promise as a data source for clinical research. Int J Med Inform. 2016;87:1–9 https://doi.org/10.1016/j.ijmedinf.2015.12.005.PubMed

43.

Vest JR, Gamm LD. Health information exchange: persistent challenges and new strategies. J Am Med Inform Assoc. 2010;17(3):288–94 https://doi.org/10.1136/jamia.2010.003673.PubMedPubMedCentral

44.

Rahurkar S, Vest JR, Menachemi N. Despite the spread of health information exchange, there is little evidence of its impact on cost,use, and quality of care. Health Aff. 2015;34(3):477–83 https://doi.org/10.1377/hlthaff.2014.0729.

45.

Rudin RS, Motala A, Goldzweig CL, Shekelle PG. Usage and effect of health information exchange: a systematic review. Ann Intern Med. 2014;161(11):803–11 https://doi.org/10.7326/M14-0877.PubMed

46.

Sadoughi F, Nasiri S, Ahmadi H. The impact of health information exchange on healthcare quality and cost-effectiveness: A systematic literature review. Comput Methods Prog Biomed. 2018;161:209–32 https://doi.org/10.1016/j.cmpb.2018.04.023.

47.

Shapiro JS, Kannry J, Lipton M, Goldberg E, Conocenti P, Stuard S, Wyatt BM, Kuperman G. Approaches to Patient Health Information Exchange and Their Impact on Emergency Medicine. Ann Emerg Health. 2006; https://doi.org/10.1016/j.annemergmed.2006.03.032.

48.

Vest JR, Jasperson S. How are health professionals using health information exchange systems? Measuring usage for evaluation and system improvement. J Med Syst. 2012;36(5):3195–204 https://doi.org/10.1007/s10916-011-9810-2.PubMed

49.

Vest JR, Abramson E. Organizational Uses of Health Information Exchange to Change Cost and Utilization Outcomes: A Typology from a Multi-Site Qualitative Analysis. AMIA Annu Symp Proc. 2015:1260–8.

50.

Zaidan BB, Haiqi A, Zaidan AA, Abdulnabi M, Mat Kiah ML, Muzamel H. A Security Framework for Nationwide Health Information Exchange based on Telehealth Strategy. J Med Syst. 2015;39(5):235. https://doi.org/10.1007/s10916-015-0235-1.CrossRef

Title: Definitions, components and processes of data harmonisation in healthcare: a scoping review
Authors: Bey-Marrié Schmidt
Christopher J. Colvin
Ameer Hohlfeld
Natalie Leon
Publication date: 01-12-2020
Publisher: BioMed Central
Published in: BMC Medical Informatics and Decision Making / Issue 1/2020
Electronic ISSN: 1472-6947
DOI: https://doi.org/10.1186/s12911-020-01218-7

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Definitions, components and processes of data harmonisation in healthcare: a scoping review

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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