What Are Complex eHealth Innovations and How Do You Measure Them?

 

 Buy Article Permissions and Reprints

Summary

Objectives: eHealth and innovation are often regarded as synonyms – not least because eHealth technologies and applications are new to their users. This position paper challenges this view and aims at exploring the nature of eHealth innovation against the background of common definitions of innovation and facts from the biomedical and health informatics literature. A good understanding of what constitutes innovative eHealth developments allows the degree of innovation to be measured and interpreted.

Methods: To this end, relevant biomedical and health informatics literature was searched mainly in Medline and ACM digital library. This paper presents seven facts about implementing and applying new eHealth developments hereby drawing on the experience published in the literature.

Results: The facts are: 1. eHealth innovation is relative. 2. Advanced clinical practice is the yardstick. 3. Only used and usable eHealth technology can give birth to eHealth innovatio. 4. One new single eHealth function does not make a complex eHealth innovation. 5. eHealth innovation is more evolution than revolution. 6. eHealth innovation is often triggered behind the scenes; and 7. There is no eHealth innovation without sociocultural change.

Conclusions: The main conclusion of the seven facts is that eHealth innovations have many ingredients: newness, availability, advanced clinical practice with proven outcomes, use and usability, the supporting environment, other context factors and the stakeholder perspectives. Measuring eHealth innovation is thus a complex matter. To this end we propose the development of a composite score that expresses comprehensively the nature of eHealth innovation and that breaks down its complexity into the three dimensions: i) eHealth adoption, ii) partnership with advanced clinical practice, and iii) use and usability of eHealth. In order to better understand the momentum and mechanisms behind eHealth innovation the fourth dimension, iv) eHealth supporting services and means, needs to be studied. Conceptualising appropriate measurement instruments also requires eHealth innovation to be distinguished from eHealth sophistication, performance and quality, although innovation is intertwined with these concepts. The demanding effort for defining eHealth innovation and measuring it properly seem worthwhile and promise advances in creating better systems. This paper thus intends to stimulate the necessary discussion.

• References

• 1 Moen A, Hackl WO, Hofdijk J, Van Gemert-Pijnen L, Ammenwerth E, Nykänen P, Hoerbst A. eHealth in Europe - Status and Challenges. Yearb Med Inform 2013; 8 (01) 59-63.
  Article in Thieme ConnectPubMedGoogle Scholar
• 2 Commission of the European Communities - CEC. e-Health - making healthcare better for European citizens: An action plan for a European e-Health Area. 2004 Available from eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2004:0356:FIN:EN:PDF Accessed July 9, 2014.
  PubMedGoogle Scholar
• 3 European Communities - EC. eHealth priorities and strategies in European countries. Luxembourg. 2007 Available from ec.europa.eu/information_society/newsroom/cf/itemdetail.cfm?item_id=3346 Accessed July 9, 2014.
  PubMedGoogle Scholar
• 4 Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med 2010; 363 (06) 501-504.
  CrossrefPubMedGoogle Scholar
• 5 The Office of the National Coordinator for Health Information Technology (ONC). What is meaningful use? Available from. http://www.healthit.gov/policy-researchers-implementers/meaningful-use Accessed July 9 2014
  PubMedGoogle Scholar
• 6 Organisation for Economic Co-operation and Development (OECD). Defining innovation. http://www.oecd.org/site/innovationstrategy/defininginnovation.htm Accessed July 9 2014
  PubMedGoogle Scholar
• 7 Organisation for Economic Co-operation and Development (OECD)/Eurostat. Oslo Manual. Guidelines for Collecting and Interpreting Innovation Data. 3rd ed. Paris: OECD; 2005. Available from http://www.oecd-ilibrary.org/science-and-technology/oslo-manual_9789264013100-en Accessed July 9, 2014.
  Google Scholar
• 8 Rogers EM. New Product Adoption and Diffusion. Journal of Consumer Research 1976; 2: 290-301.
  CrossrefPubMedGoogle Scholar
• 9 Rogers EM. Diffusion of Innovation. 5th ed. New York: Free Press; 2003. (first published in 1962 by The Free Press of Glencoe, New York).
  Google Scholar
• 10 Russell LB. The diffusion of new hospital technologies in the United States. Int J Health Serv 1976; 6 (04) 557-580.
  CrossrefPubMedGoogle Scholar
• 11 Greer AL. Advances in the study of diffusion of innovation in health care organizations. Milbank Mem Fund Q Health Soc 1977; 55 (04) 505-532.
  CrossrefPubMedGoogle Scholar
• 12 Audet AM, Squires D, Doty MM. Where Are We on the Diffusion Curve? Trends and Drivers of Primary Care Physicians’ Use of Health Information Technology. Health Serv Res. 2013
  Google Scholar
• 13 Ford EW, Menachemi N, Peterson LT, Huerta TR. Resistance is futile: but it is slowing the pace of EHR adoption nonetheless. J Am Med Inform Assoc 2009; 16 (03) 274-281.
  CrossrefPubMedGoogle Scholar
• 14 Yaraghi N, Du AY, Sharman R, Gopal RD, Ramesh R, Singh R, Singh G. Professional and geographical network effects on healthcare information exchange growth: does proximity really matter?. J Am Med Inform Assoc 2013. 2012: 001293.
  Google Scholar
• 15 Kellermann AL, Jones SS. What it will take to achieve the as-yet-unfulfilled promises of health information technology. Health Aff (Millwood) 2013; 32 (01) 63-68.
  CrossrefPubMedGoogle Scholar
• 16 Wright A, Feblowitz J, Samal L, McCoy AB, Sittig DF. The Medicare Electronic Health Record Incentive Program: Provider Performance on Core and Menu Measures. Health Serv Res. 2013. doi: 10.1111/1475-6773.12134.
  Google Scholar
• 17 Cresswell K, Sheikh A. Organizational issues in the implementation and adoption of health information technology innovations: an interpretative review. Int J Med Inform 2013; 82 (05) e73-86.
  CrossrefPubMedGoogle Scholar
• 18 Meyer I, Hüsing T, Didero M, Korte WB. eHealth Benchmarking (Phase II). Final Report. Bonn: 2009. Available from http://www.ehealth-benchmarking.eu/results/results.html Accessed July 9, 2014.
  Google Scholar
• 19 Hübner U, Ammenwerth E, Flemming D, Schaubmayr C, Sellemann B. IT adoption of clinical information systems in Austrian and German hospitals: results of a comparative survey with a focus on nursing. BMC Medical Informatics and Decision Making 2010; 10: 8.
  CrossrefPubMedGoogle Scholar
• 20 Adler-Milstein J, Ronchi E, Cohen GR, Winn LA, Jha AK. Benchmarking health IT among OECD countries: better data for better policy. J Am Med Inform Assoc 2014; 21: 111-116.
  CrossrefPubMedGoogle Scholar
• 21 Liebe JD, Hübner U. Developing and Trialling an Independent, Scalable and Repeatable IT-benchmarking Procedure for Healthcare Organisations. Methods Inf Med 2013; 52 (04) 360-369.
  Article in Thieme ConnectPubMedGoogle Scholar
• 22 Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG. et al. Use of electronic health records in U.S. hospitals. N Engl J Med 2009; 360 (16) 1628-1638.
  CrossrefPubMedGoogle Scholar
• 23 DesRoches CM, Worzala C, Joshi MS, Kralovec PD, Jha AK. Small, nonteaching, and rural hospitals continue to be slow in adopting electronic health record systems. Health Aff (Millwood) 2012; 31 (05) 1092-1099.
  CrossrefPubMedGoogle Scholar
• 24 Yoon D, Chang BC, Kang SW, Bae H, Park RW. Adoption of electronic health records in Korean tertiary teaching and general hospitals. Int J Med Inform 2012; 81 (03) 196-203.
  CrossrefPubMedGoogle Scholar
• 25 Lambooij MS, Hummel MJ. Differentiating innovation priorities among stakeholder in hospital care. BMC Med Inform Decis Mak 2013; 13: 91 doi: 10.1186/1472-6947-13-91.
  CrossrefPubMedGoogle Scholar
• 26 Krist AH, Beasley JW, Crosson JC, Kibbe DC, Klinkman MS, Lehmann CU, Fox CH, Mitchell JM, Mold JW, Pace WD, Peterson KA, Phillips RL, Post R, Puro J, Raddock M, Simkus R, Waldren SE. Electronic health record functionality needed to better support primary care. J Am Med Inform Assoc. 2014
  Google Scholar
• 27 Hübner U, Sellemann B. Current and Future Use of ICT for Patient Care and Management in German Acute Hospitals - a Comparison between the Nursing and the Hospital Managers’ Perspectives. Methods Inf Med 2005; 44: 528-536.
  Article in Thieme ConnectPubMedGoogle Scholar
• 28 McCullough J, Casey M, Moscovice I, Burlew M. Meaningful use of health information technology by rural hospitals. J Rural Health 2011; 27 (03) 329-337.
  CrossrefPubMedGoogle Scholar
• 29 Paez K, Roper RA, Andrews RM. Health information technology and hospital patient safety: a conceptual model to guide research. Jt Comm J Qual Patient Saf 2013; 39 (09) 415-425.
  PubMedGoogle Scholar
• 30 Restuccia JD, Cohen AB, Horwitt JN, Shwartz M. Hospital implementation of health information technology and quality of care: are they related?. BMC Med Inform Decis Mak 2012; 12: 109.
  CrossrefPubMedGoogle Scholar
• 31 Ricciardi L, Mostashari F, Murphy J, Daniel JG, Siminerio EP. A national action plan to support consumer engagement via e-health. Health Aff (Millwood) 2013; 32 (02) 376-384.
  CrossrefPubMedGoogle Scholar
• 32 Lyden JR, Zickmund SL, Bhargava TD, Bryce CL, Conroy MB, Fischer GS, Hess R, Simkin-Silverman LR, McTigue KM. Implementing health information technology in a patient-centered manner: patient experiences with an online evidence-based lifestyle intervention. J Healthc Qual 2013; 35 (05) 47-57. doi: 10.1111/jhq.12026.
  PubMedGoogle Scholar
• 33 Reed P, Conrad DA, Hernandez SE, Watts C, Marcus-Smith M. Innovation in patient-centered care: lessons from a qualitative study of innovative health care organizations in Washington State. BMC Fam Pract 2012; 13: 120 doi: 10.1186/1471-2296-13-120.
  CrossrefPubMedGoogle Scholar
• 34 Winter A, Brigl B, Funkat G, Häber A, Heller O, Wendt T. 3LGM2-modeling to support management of health information systems. Int J Med Inform 2007; 76 2–3 145-150.
  CrossrefPubMedGoogle Scholar
• 35 Lau AY, Sintchenko V, Crimmins J, Magrabi F, Gallego B, Coiera E. Impact of a web-based personally controlled health management system on influenza vaccination and health services utilization rates: a randomized controlled trial. J Am Med Inform Assoc 2012; 19 (05) 719-727.
  CrossrefPubMedGoogle Scholar
• 36 Beuscart-Zéphir MC, Borycki E, Carayon P, Jaspers MW, Pelayo S. Evolution of human factors research and studies of health information technologies: the role of patient safety. Yearb Med Inform 2013; 8 (01) 67-77.
  Article in Thieme ConnectPubMedGoogle Scholar
• 37 Terner A, Lindstedt H, Sonnander K. Predefined headings in a multiprofessional electronic health record system. J Am Med Inform Assoc 2012; 19 (06) 1032-1038.
  CrossrefPubMedGoogle Scholar
• 38 Hanley J, Ure J, Pagliari C, Sheikh A, McKinstry B. Experiences of patients and professionals participating in the HITS home blood pressure telemonitoring trial: a qualitative study. BMJ Open 2013; 3 (05) pii e002671.
  CrossrefPubMedGoogle Scholar
• 39 Malone DC, Saverno KR. Evaluation of a wireless handheld medication management device in the prevention of drug-drug interactions in a Medicaid population. J Manag Care Pharm 2012; 18 (01) 33-45.
  PubMedGoogle Scholar
• 40 Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med 2011; 8 (01) e1000387 doi: 10.1371/journal.pmed.1000387.
  CrossrefPubMedGoogle Scholar
• 41 Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E. et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006; 144 (10) 742-752.
  CrossrefPubMedGoogle Scholar
• 42 Hyppönen H, Faxvaag A, Gilstad H, Hardardottir GA, Jerlvall L, Kangas M, Koch S, Nøhr C, Pehrsson T, Reponen J, Walldius A, Vimarlund V. Nordic eHealth Indicators: Organisation of Research, First Results and Plan for the Future. Stud Health Technol Inform 2013; 192: 273-277.
  PubMedGoogle Scholar
• 43 OECD and European Commission. Joint EC-OECD Workshop Benchmarking Information and Communication Technologies In Health Systems. Brussels: 18-19. April 2013. Available from http://www.himsa-info.eu/00him/events/joint-ec-oecd-workshop-benchmarking-information-and-communication-technologies-in-health-systems/ Accessed July 9, 2014.
  Google Scholar
• 44 Paré G, Sicotte C. Information technology sophistication in health care: an instrument validation study among Canadian hospitals. Int J Med Inform 2001; 63 (03) 205-223.
  CrossrefPubMedGoogle Scholar
• 45 Hübner-Bloder G, Ammenwerth E. Key performance indicators to benchmark hospital information systems - a Delphi study. Methods Inf Med 2009; 48 (06) 508-518.
  Article in Thieme ConnectPubMedGoogle Scholar
• 46 Saleem JJ, Flanagan ME, Wilck NR, Demetriades J, Doebbeling BN. The next-generation electronic health record: perspectives of key leaders from the US Department of Veterans Affairs. J Am Med Inform Assoc 2013; 20 e (01) e175-177.
  CrossrefPubMedGoogle Scholar
• 47 Hammer M, Champy J. Reengineering the Corporation: A Manifesto for Business Revolution. New York: Harper Business; 1993
  Google Scholar
• 48 Holland CA. Reengineering the mind, career, system, department. Clin Lab Manage Rev 1998; 12 (03) 169-175.
  PubMedGoogle Scholar
• 49 Slotkin JR, Casale AS, Steele Jr GD, Toms SA. Reengineering acute episodic and chronic care delivery: the Geisinger Health System experience. Neurosurg Focus 2012; 33 (01) E16 doi: 10.3171/2012.4.FOCUS1293.
  CrossrefPubMedGoogle Scholar
• 50 Meeks DW, Takian A, Sittig DF, Singh H, Barber N. Exploring the sociotechnical intersection of patient safety and electronic health record implementation. J Am Med Inform Assoc. 2013
  Google Scholar
• 51 Shea CM, Weiner BJ, Belden CM. Using Latent Class Analysis to Identify Sophistication Categories of Electronic Medical Record Systems in U.S. Acute Care Hospitals. Soc Sci Comput Rev 2012; 31: 2 doi: 10.1177/0894439312448726.
  PubMedGoogle Scholar
• 52 Lau F, Price M, Lesperance M. Developing a multivariate electronic medical record integration model for primary health care. Stud Health Technol Inform 2013; 183: 375-381.
  PubMedGoogle Scholar
• 53 HIMSS. Electronic Medical Record Adoption Model. 2013. Available from http://www.himssanalytics.org/emram/emram.aspx Accessed July 9, 2014.
  Google Scholar
• 54 Finch TL, Mair FS, O’Donnell C, Murray E, May CR. From theory to ’measurement’ in complex interventions: methodological lessons from the development of an e-health normalisation instrument. BMC Med Res Methodol 2012; 12: 69 doi: 10.1186/1471-2288-12-69.
  CrossrefPubMedGoogle Scholar
• 55 Takian A, Sheikh A, Barber N. We are bitter, but we are better off: case study of the implementation of an electronic health record system into a mental health hospital in England. BMC Health Serv Res 2012; 12: 484.
  CrossrefPubMedGoogle Scholar
• 56 Liebe JD, Egbert N, Frey A, Hübner U. Characteristics of German Hospitals Adopting Health IT Systems - Results of an Empirical Study. Stud Health Technol Inform 2011; 149: 335-338.
  PubMedGoogle Scholar
• 57 Winter A, Haux R, Ammenwerth E, Brigl B, Hellrung N, Jahn F. Health Information Systems - Architectures and Strategies. London: Springer; 2011
  Google Scholar
• 58 Winter A. The future of medical informatics. Some perspectives of intra- and inter-institutional information systems. Methods Inf Med 2009; 48 (01) 62-65.
  Article in Thieme ConnectPubMedGoogle Scholar
• 59 ISACA. COBIT 5- A Business Framework for the Governance and Management of Enterprise IT. 2013. Available from http://www.isaca.org/cobit/pages/default.aspx Accessed July 9, 2014.
  Google Scholar
• 60 HM Government. Essential ITIL. Processes and functions. London: TSO; 2013
  Google Scholar
• 61 Bradley RV, Byrd TA, Pridmore JL, Thrasher E, Pratt RM, Mbarika VW. An empirical examination of antecedents and consequences of IT-governance in US hospitals. J Inf Technol 2012; 27 (02) 156-177.
  CrossrefPubMedGoogle Scholar
• 62 Hoerbst A, Hackl WO, Blomer R, Ammenwerth E. The status of IT service management in health care - ITIL® in selected European countries. BMC Med Inform Decis Mak 2011; 11: 76 doi: 10.1186/1472-6947-11-76.
  CrossrefPubMedGoogle Scholar
• 63 Hübner U, Liebe DJ, Straede M, Thye J. IT-Report Gesundheitswesen - Schwerpunkt IT-Unterstützung klinischer Prozesse. Hannover: Schriftenreihe des Niedersächsischen Ministeriums für Wirtschaft, Arbeit und Verkehr Hannover. 2014
  Google Scholar
• 64 Baird A, Furukawa MF, Rahman B, Schneller ES. Corporate Governance and the Adoption of Health Information Technology Within Integrated Delivery Systems. Health Care Manage Rev 2014; 39 (03) 234-244.
  CrossrefPubMedGoogle Scholar
• 65 Ball MJ. Hospital information systems: perspectives on problems and prospects, 1979 and 2002. Int J Med Inform 2003; 69 2–3 83-89.
  CrossrefPubMedGoogle Scholar
• 66 Ball MJ, Douglas JV, Hinton Walker P, DuLong D, Gugerty B, Hannah KJ, Kiel J, Newbold SK, Sensmeier J, Skiba DJ, Troseth M. editors Nursing Informatics: Where Caring and Technology Meet. 4th ed. London, New York: Springer; 2011
  Google Scholar
• 67 Paré G, Sicotte C, Jacques H. The effects of creating psychological ownership on physicians’ acceptance of clinical information systems. J Am Med Inform Assoc 2006; 13 (02) 197-205.
  CrossrefPubMedGoogle Scholar
• 68 Li J, Talaei-Khoei A, Seale H, Ray P, Macintyre CR. Health Care Provider Adoption of eHealth: Systematic Literature Review. Interact J Med Res 2013; 2 (01) e7 doi: 10.2196/ijmr.2468.
  CrossrefPubMedGoogle Scholar
• 69 Runy LA. The changing role of the CMIO. Hosp Health Netw 2008; 82 (02) 37-42. 1.
  PubMedGoogle Scholar
• 70 Greenhalgh T, Morris L, Wyatt JC, Thomas G, Gunning K. Introducing a nationally shared electronic patient record: case study comparison of Scotland, England, Wales and Northern Ireland. Int J Med Inform 2013; 82 (05) e125-138.
  CrossrefPubMedGoogle Scholar
• 71 Ammenwerth E, Ehlers F, Hirsch B, Gratl G. HIS-Monitor: an approach to assess the quality of information processing in hospitals. Int J Med Inform 2007; 76 2–3 216-215.
  CrossrefPubMedGoogle Scholar
• 72 Otieno GO, Hinako T, Motohiro A, Daisuke K, Keiko N. Measuring effectiveness of electronic medical records systems: towards building a composite index for benchmarking hospitals. Int J Med Inform 2008; 77 (10) 657-669.
  CrossrefPubMedGoogle Scholar
• 73 Amarasingham R, Diener-West M, Plantinga L, Cunningham AC, Gaskin DJ, Powe NR. Hospital characteristics associated with highly automated and usable clinical information systems in Texas, United States. BMC Med Inform Decis Mak 2008; 8: 39.
  CrossrefPubMedGoogle Scholar
• 74 Kazley AS, Diana ML, Menachemi N. The agreement and internal consistency of national hospital EMR measures. Health Care Manag Sci 2011; 14 (04) 307-313.
  CrossrefPubMedGoogle Scholar