Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-25T16:49:41.213Z Has data issue: false hasContentIssue false
  • English
  • Français

Early assessment of innovation in a healthcare setting

Part of: Special Collection - Methods

Published online by Cambridge University Press:  12 February 2019

Linn Nathalie Støme ,
Tron Moger ,
Kristian Kidholm  and
Kari J. Kværner
Linn Nathalie Støme*
Affiliation:
Oslo University Hospital, Centre for Connected Care
Tron Moger
Affiliation:
University of Oslo, Institute for Health and Society
Kristian Kidholm
Affiliation:
University of Odense, Centre for Innovative Medical Technology
Kari J. Kværner
Affiliation:
Oslo University Hospital, Centre for Connected Care
*
Author for correspondence: Linn Nathalie Støme, E-mail: linast@ous-hf.no
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives

Early assessment can assist in allocating resources for innovation effectively and produce the most beneficial technology for an institution. The aim of the present study was to identify methods and discuss the analytical approaches applied for the early assessment of innovation in a healthcare setting.

Methods

Knowledge synthesis based on a structured search (using the MEDLINE, Embase, and Cochrane databases) and thematic analysis was conducted. An analytical framework based on the stage of innovation (developmental, introduction, or early diffusion) was applied to assess whether methods vary according to stage. Themes (type of innovation, study, analysis, study design, method, and main target audience) were then decided among the authors. Identified methods and analysis were discussed according to the innovation stage.

Results

A total of 1,064 articles matched the search strategy. Overall, thirty-nine articles matched the inclusion criteria. The use of methods has a tendency to change according to the stage of innovation. Stakeholder analysis was a prominent method in the innovation stages and particularly in the developmental stage, as the introduction and early diffusion stage has more availability of data and may apply more complex methods. Barriers to the identified methods were also discussed as all of the innovation stages suffered from lack of data and substantial uncertainty.

Conclusions

Although this review has identified applicable approaches for early assessment in different innovation stages, research is required regarding the value of the available data and methods and tools to enhance interactions between different parties at different stages of innovation.

Keywords

Early assessmentHealth innovationOrganizational innovationKnowledge synthesisHealth technology assessment
Type
Method
Information
International Journal of Technology Assessment in Health Care , Volume 35 , Issue 1 , 2019 , pp. 17 - 26
Copyright
Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Strønen, F, Hoholm, T, Kværner, KJ, Støme, LN (2017) Dynamic capabilities and innovation capabilities: The case of the ‘innovation clinic’. J Entrep Manag Innov 13, 89–116.Google Scholar
2.Tarricone, R, Torbica, A, Drummond, M (2017) Challenges in the assessment of medical devices: The MedtecHTA Project. Health Econ 26 (Suppl 1), 5–12.10.1002/hec.3469Google Scholar
3.Kristensen, FB, Lampe, K, Chase, DL, Lee-Robin, SH, Wild, C, Moharra, M, et al. (2009) Practical tools and methods for health technology assessment in Europe: Structures, methodologies, and tools developed by the European Network for Health Technology Assessment, EUnetHTA. Int J Technol Assess Health Care 25(Suppl 2):1–8.Google Scholar
4.Husereau, D, Henshall, C, Sampietro-Colom, L, Thomas, S (2016) Changing health technology assessment paradigms? Int J Technol Assess Health Care 32, 191–199.10.1017/S0266462316000386Google Scholar
5.Sampietro-Colom, L, Lach, K, Cicchetti, A, Kidholm, K, Pasternack, I, Fure, B, et al. (2015) The AdHopHTA handbook: A handbook of hospitalbased Health Technology Assessment (HB-HTA); Public deliverable; The AdHopHTA Project (FP7/2007-13 grant agreement nr 305018); http://www.adhophta.eu/sites/files/adhophta/media/adhophta_handbook_website.pdf (accessed January 3, 2019).Google Scholar
6.Nielsen, CP, Funch, TM, Kristensen, FB (2011) Health technology assessment: Research trends and future priorities in Europe. J Health Serv Res Policy 16(Suppl 2):6–15.Google Scholar
7.Packer, C, Simpson, S, de Almeida, RT (2015) Euroscan International Network Member Agencies: Their structure, processes, and outputs. Int J Technol Assess Health Care 31, 78–85.Google Scholar
8.Hartz, S, John, J (2008) Contribution of economic evaluation to decision making in early phases of product development: A methodological and empirical review. Int J Technol Assess Health Care 24, 465–472.Google Scholar
9.Redekop, K, Mikudina, B (2013) Early medical technology assessments of medical devices and tests. J Health Policy 1, 26–37.Google Scholar
10.Fasterholdt, I, Krahn, M, Kidholm, K, Tderstræde, KB, Møller Pedersen, KM (2017) Review of early assessment models of innovative medical technologies. Health Policy 121, 870–879.10.1016/j.healthpol.2017.06.006Google Scholar
11.PRISMA. 2017. http://www.prisma-statement.org/ (accessed January 3, 2019).Google Scholar
12.Assessment(INAHTA) INoAfHT. International Network of Agencies for Health Technology Assessment(INAHTA). http://www.inahta.org/HTA/ (accessed April 16, 2014).Google Scholar
13.Ijzerman, MJ, Steuten, LM (2011) Early assessment of medical technologies to inform product development and market access: A review of methods and applications. Appl Health Econ Health Policy 9, 331–347.10.2165/11593380-000000000-00000Google Scholar
14.Steuten, LM (2016) Early stage health technology assessment for precision biomarkers in oral health and systems medicine. OMICS 20, 30–35.Google Scholar
15.Retel, VP, Joosten, SE, van Harten, WH (2014) Expert elicitation used for early technology assessment to inform on cost-effectiveness of next generation sequencing. Value Health 17, A652.10.1016/j.jval.2014.08.2373Google Scholar
16.Beuscart-Zephir, MC, Watbled, L, Carpentier, AM, Degroisse, M, Alao, O (2002) A rapid usability assessment methodology to support the choice of clinical information systems: A case study. Proc AMIA Symp, 46–50.Google Scholar
17.Brear, M (2006) Evaluating telemedicine: Lessons and challenges. Health Inf Manage J 35, 23–31.Google Scholar
18.Markiewicz, K, van Til, JA, Ijzerman, MJ (2014) Medical devices early assessment methods: Systematic literature review. Int J Technol Assess Health Care 30, 137–146.10.1017/S0266462314000026Google Scholar
19.Bartelmes, M, Neumann, U, Luhmann, D, Schonermark, MP, Hagen, A (2009) Methods for assessment of innovative medical technologies during early stages of development. GMS Health Technol Assess 5, Doc15.Google Scholar
20.Cosh, E, Girling, A, Lilford, R, McAteer, H, Young, T (2007) Investing in new medical technologies: A decision framework. J Commer Biotechnol 13, 263–271.Google Scholar
21.Di Capua, P, Wu, B, Sednew, R, Ryan, G, Wu, S (2016) Complexity in redesigning depression care: Comparing intention versus implementation of an automated depression screening and monitoring program. Popul Health Manag 19, 349–356.Google Scholar
22.Retel, VP, Joore, MA, Linn, SC, Rutgers, EJ, van Harten, WH (2012) Scenario drafting to anticipate future developments in technology assessment. BMC Res Notes 5, 442.Google Scholar
23.Sayres, LC, Allyse, M, Cho, MK (2012) Integrating stakeholder perspectives into the translation of cell-free fetal DNA testing for aneuploidy. Genome Med 4, 49.Google Scholar
24.Kip, MM, Steuten, LM, Koffijberg, H, Ijzerman, MJ, Kusters, R (2018) Using expert elicitation to estimate the potential impact of improved diagnostic performance of laboratory tests: A case study on rapid discharge of suspected non-ST elevation myocardial infarction patients. J Eval Clin Pract 24, 31–41.10.1111/jep.12626Google Scholar
25.Jastremski, M, Jastremski, C, Shepherd, M, Friedman, V, Porembka, D, Smith, R, et al. (1995) A model for technology assessment as applied to closed loop infusion systems. Technology Assessment Task Force of the Society of Critical Care Medicine. Crit Care Med 23, 1745–1755.Google Scholar
26.Gaultney, JG, Sanhueza, E, Janssen, JJ, Redekop, WK, Uyl-de Groot, CA (2011) Application of cost-effectiveness analysis to demonstrate the potential value of companion diagnostics in chronic myeloid leukemia. Pharmacogenomics 12, 411–421.Google Scholar
27.Harris-Roxas, BF, Harris, PJ (2007) Learning by doing: The value of case studies of health impact assessment. N S W Public Health Bull 18, 161–163.Google Scholar
28.Porzsolt, F, Ghosh, AK, Kaplan, RM (2009) Qualitative assessment of innovations in healthcare provision. BMC Health Serv Res 9, 50.Google Scholar
29.Esposito, D, Taylor, EF, Gold, M (2009) Using qualitative and quantitative methods to evaluate small-scale disease management pilot programs. Popul Health Manag 12, 3–15.Google Scholar
30.Retel, VP, Hummel, MJ, van Harten, WH (2008) Early phase technology assessment of nanotechnology in oncology. Tumori 94, 284–290.Google Scholar
31.Abrishami, P, Boer, A, Horstman, K (2015) How can we assess the value of complex medical innovations in practice? Expert Rev Pharmacoecon Outcomes Res 15, 369–371.10.1586/14737167.2015.1037834Google Scholar
32.Henshall, C, Schuller, T (2013) Health technology assessment, value-based decision making, and innovation. Int J Technol Assess Health Care 29, 353–359.10.1017/S0266462313000378Google Scholar
33.Bridges, JF (2006) Lean systems approaches to health technology assessment: A patient-focused alternative to cost-effectiveness analysis. PharmacoEconomics 24(Suppl 2), 101–109.10.2165/00019053-200624002-00011Google Scholar
34.Kummer, TF, Schafer, K, Todorova, N (2013) Acceptance of hospital nurses toward sensor-based medication systems: A questionnaire survey. Int J Nursing Stud 50, 508–517.Google Scholar
35.Gantner-Bar, M, Meier, F, Kolominsky-Rabas, P, Djanatliev, A, Metzger, A, Voigt, W, et al. (2014) Prospective Assessment of an innovative test for prostate cancer screening using the VITA process model framework. Stud Health Technol Inform 205, 236–240.Google Scholar
36.Hartz, S, John, J (2009) Public health policy decisions on medical innovations: What role can early economic evaluation play? Health Policy 89, 184–192.10.1016/j.healthpol.2008.05.011Google Scholar
37.Joosten, SE, Retel, VP, Coupe, VM, van den Heuvel, MM, van Harten, WH (2016) Scenario drafting for early technology assessment of next generation sequencing in clinical oncology. BMC Cancer 16, 66.10.1186/s12885-016-2100-0Google Scholar
38.Girling, A, Young, T, Brown, C, Lilford, R (2010) Early-stage valuation of medical devices: The role of developmental uncertainty. Value Health 13, 585–591.Google Scholar
39.Craig, JA, Carr, L, Hutton, J, Glanville, J, Iglesias, CP, Sims, AJ (2015) A review of the economic tools for assessing new medical devices. Appl Health Econ Health Policy 13, 15–27.Google Scholar
40.Postmus, D, de Graaf, G, Hillege, HL, Steyerberg, EW, Buskens, E (2012) A method for the early health technology assessment of novel biomarker measurement in primary prevention programs. Stat Med 31, 2733–2744.Google Scholar
41.Douma, KF, Karsenberg, K, Hummel, MJ, Bueno-de-Mesquita, JM, van Harten, WH (2007) Methodology of constructive technology assessment in health care. Int J Technol Assess Health Care 23, 162–168.Google Scholar
42.Retel, VP, Bueno-de-Mesquita, JM, Hummel, MJ, van de Vijver, MJ, Douma, KF, Karsenberg, K, et al. (2009) Constructive Technology Assessment (CTA) as a tool in coverage with evidence development: The case of the 70-gene prognosis signature for breast cancer diagnostics. Int J Technol Assess Health Care 25, 73–83.Google Scholar
43.Retel, VP, Hummel, MJ, van Harten, WH (2009) Review on early technology assessments of nanotechnologies in oncology. Mol Oncol 3, 394–401.Google Scholar
44.Retel, VP, Grutters, JP, van Harten, WH, Joore, MA (2013) Value of research and value of development in early assessments of new medical technologies. Value Health 16, 720–728.Google Scholar
45.Chang, WR, McLean, IP (2006) CUSUM: A tool for early feedback about performance? BMC Med Res Methodol 6:8.Google Scholar
46.Niederlander, C, Kriza, C, Wahlster, P, Djanatliev, A, Kolominsky-Rabas, P (2013) Early technology foresight for the development of biomarkers for prostate cancer screening: Prospective Health Technology Assessment (ProHTA). Eur J Cancer 49, S199.Google Scholar
47.Banta, HD, Gelijns, AC, Griffioen, J, Graaff, PJ (1987) An inquiry concerning future health care technology: Methods and general results. Health Policy 8, 251–264.Google Scholar
48.Manetti, S, Cecchi, F, Sgandurra, G, Cioni, G, Laschi, C, Dario, P, et al. (2015) Early stage economic evaluation of caretoy system for early intervention in preterm infants at risk of neurodevelopmental disorders. Value Health 18, A358.10.1016/j.jval.2015.09.683Google Scholar
49.Gagnon, MP, Candas, B, Desmartis, M, Gagnon, J, La Roche, D, Rhainds, M, et al. (2014) Involving patient in the early stages of health technology assessment (HTA): A study protocol. BMC Health Serv Res 14:273.Google Scholar
50.Gollamudi, SS, Topol, EJ, Wineinger, NE (2016) A framework for smartphone-enabled, patient-generated health data analysis. Peerj 4, e2284.Google Scholar
51.Ijzerman, MJ, Koffijberg, H, Fenwick, E, Krahn, M (2017) Emerging use of early health technology assessment in medical product development: A scoping review of the literature. PharmacoEconomics 35, 727–740.Google Scholar
Supplementary material: File

Støme et al. supplementary material

Appendix

Download Støme et al. supplementary material(File)
File 16.8 KB