Skip to main content
Top
Published in: BMC Medical Informatics and Decision Making 1/2017

Open Access 01-12-2017 | Research article

The development and feasibility of a personal health-optimization system for people with bipolar disorder

Authors: Øystein Eiring, Kari Nytrøen, Simone Kienlin, Soudabeh Khodambashi, Magne Nylenna

Published in: BMC Medical Informatics and Decision Making | Issue 1/2017

Login to get access

Abstract

Background

People with bipolar disorder often experience ill health and have considerably reduced life expectancies. Suboptimal treatment is common and includes a lack of effective medicines, overtreatment, and non-adherence to medical interventions and lifestyle measures. E- and m-health applications support patients in optimizing their treatment but often exhibit conceptual and technical shortcomings. The objective of this work was to develop and test the usability of a system targeting suboptimal treatment and compare the service to other genres and strategies.

Methods

Based on the frameworks of shared decision-making, multi-criteria decision analysis, and single-subject research design, we interviewed potential users, reviewed research and current approaches, and created a first version using a rapid prototyping framework. We then iteratively improved and expanded the service based on formative usability testing with patients, healthcare providers, and laypeople from Norway, the UK, and Ukraine. The evidence-based health-optimization system was developed using systematic methods. The System Usability Scale and a questionnaire were administered in formative and summative tests. A comparison of the system to current standards for clinical practice guidelines and patient decision aids was performed.

Results

Seventy-eight potential users identified 82 issues. Driven by user feedback, the limited first version was developed into a more comprehensive system. The current version encompasses 21 integrated core features, supporting 6 health-optimization strategies. One crucial feature enables patients and clinicians to explore the likely value of treatments based on mathematical integration of self-reported and research data and the patient’s preferences. The mean ± SD (median) system usability score of the patient-oriented subsystem was 71 ± 18 (73). The mean ± SD (median) system usability score in the summative usability testing was 78 ± 18 (75), well above the norm score of 68. Feedback from the questionnaire was generally positive. Eighteen out of 23 components in the system are not required in international standards for patient decision aids and clinical practice guidelines.

Conclusion

We have developed the first evidence-based health-optimization system enabling patients, clinicians, and caregivers to collaborate in optimizing the patient’s health on a shared platform. User tests indicate that the feasibility of the system is acceptable.
Appendix
Available only for authorised users
Literature
1.
go back to reference Merikangas KR, Jin R, He JP, Kessler RC, Lee S, Sampson NA, et al. Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Arch Gen Psychiatry. 2011;68(3):241–51.CrossRefPubMedPubMedCentral Merikangas KR, Jin R, He JP, Kessler RC, Lee S, Sampson NA, et al. Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Arch Gen Psychiatry. 2011;68(3):241–51.CrossRefPubMedPubMedCentral
2.
go back to reference Gitlin MJ, Miklowitz DJ. The difficult lives of individuals with bipolar disorder: A review of functional outcomes and their implications for treatment. J Affect Disord. 2017;209:147-54. doi:10.1016/j.jad.2016.11.021. Gitlin MJ, Miklowitz DJ. The difficult lives of individuals with bipolar disorder: A review of functional outcomes and their implications for treatment. J Affect Disord. 2017;209:147-54. doi:10.​1016/​j.​jad.​2016.​11.​021.
4.
go back to reference Levin JB, Krivenko A, Howland M, Schlachet R, Sajatovic M. Medication adherence in patients with bipolar disorder: a comprehensive review. CNS Drugs. 2016;30(9):819–35.CrossRefPubMed Levin JB, Krivenko A, Howland M, Schlachet R, Sajatovic M. Medication adherence in patients with bipolar disorder: a comprehensive review. CNS Drugs. 2016;30(9):819–35.CrossRefPubMed
6.
go back to reference Yeaw J, Benner JS, Walt JG, Sian S, Smith DB. Comparing adherence and persistence across 6 chronic medication classes. J Manag Care Pharm. 2009;15(9):728–40.PubMed Yeaw J, Benner JS, Walt JG, Sian S, Smith DB. Comparing adherence and persistence across 6 chronic medication classes. J Manag Care Pharm. 2009;15(9):728–40.PubMed
8.
go back to reference Royal Pharmaceutical Society (RPS). Medicines optimisation: helping patients to make the most of medicines. England: RPS; 2013. Royal Pharmaceutical Society (RPS). Medicines optimisation: helping patients to make the most of medicines. England: RPS; 2013.
9.
go back to reference Stacey D, Legare F, Col NF, Bennett CL, Barry MJ, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;1:Cd001431. Stacey D, Legare F, Col NF, Bennett CL, Barry MJ, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;1:Cd001431.
10.
go back to reference Bright TJWA, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, Samsa G, Hasselblad V, Williams JW, Musty MD, Wing L, Kendrick AS, Sanders GD, Lobach D. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(7):29–43.CrossRefPubMed Bright TJWA, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, Samsa G, Hasselblad V, Williams JW, Musty MD, Wing L, Kendrick AS, Sanders GD, Lobach D. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(7):29–43.CrossRefPubMed
11.
go back to reference Blum D, Raj SX, Oberholzer R, Riphagen II, Strasser F, Kaasa S, et al. Computer-based clinical decision support systems and patient-reported outcomes: a systematic review. The patient. 2015;8(5):397–409.CrossRefPubMed Blum D, Raj SX, Oberholzer R, Riphagen II, Strasser F, Kaasa S, et al. Computer-based clinical decision support systems and patient-reported outcomes: a systematic review. The patient. 2015;8(5):397–409.CrossRefPubMed
12.
go back to reference Ranji SR, Rennke S, Wachter RM. Computerised provider order entry combined with clinical decision support systems to improve medication safety: a narrative review. BMJ Qual Saf. 2014;23(9):773–80.CrossRefPubMed Ranji SR, Rennke S, Wachter RM. Computerised provider order entry combined with clinical decision support systems to improve medication safety: a narrative review. BMJ Qual Saf. 2014;23(9):773–80.CrossRefPubMed
13.
go back to reference Vervloet M, Linn AJ, van Weert JC, de Bakker DH, Bouvy ML, van Dijk L. The effectiveness of interventions using electronic reminders to improve adherence to chronic medication: a systematic review of the literature. J Am Med Inform Assoc. 2012;19(5):696–704.CrossRefPubMedPubMedCentral Vervloet M, Linn AJ, van Weert JC, de Bakker DH, Bouvy ML, van Dijk L. The effectiveness of interventions using electronic reminders to improve adherence to chronic medication: a systematic review of the literature. J Am Med Inform Assoc. 2012;19(5):696–704.CrossRefPubMedPubMedCentral
14.
go back to reference Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res. 2015;17(2):e52.CrossRefPubMedPubMedCentral Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res. 2015;17(2):e52.CrossRefPubMedPubMedCentral
15.
go back to reference Roshanov PS, Fernandes N, Wilczynski JM, Hemens BJ, You JJ, Handler SM, et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ (Clinical research ed). 2013;346:f657. Roshanov PS, Fernandes N, Wilczynski JM, Hemens BJ, You JJ, Handler SM, et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ (Clinical research ed). 2013;346:f657.
16.
go back to reference Quaglini S, Sacchi L, Lanzola G, Viani N. Personalization and patient involvement in decision support systems: current trends. Yearb Med Inform. 2015;10(1):106–18.CrossRefPubMedPubMedCentral Quaglini S, Sacchi L, Lanzola G, Viani N. Personalization and patient involvement in decision support systems: current trends. Yearb Med Inform. 2015;10(1):106–18.CrossRefPubMedPubMedCentral
17.
go back to reference Lobach DF. The road to effective clinical decision support: are we there yet? BMJ (Clinical research ed). 2013;346:f1616. Lobach DF. The road to effective clinical decision support: are we there yet? BMJ (Clinical research ed). 2013;346:f1616.
18.
go back to reference Council TGM. Good medical practice. The General Medical Council: UK; 2013. Council TGM. Good medical practice. The General Medical Council: UK; 2013.
20.
21.
go back to reference Liu NH, Daumit GL, Dua T, Aquila R, Charlson F, Cuijpers P, et al. Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy and research agendas. World Psychiatry. 2017;16(1):30–40.CrossRefPubMedPubMedCentral Liu NH, Daumit GL, Dua T, Aquila R, Charlson F, Cuijpers P, et al. Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy and research agendas. World Psychiatry. 2017;16(1):30–40.CrossRefPubMedPubMedCentral
22.
go back to reference Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns. 2006;60(3):301–12.CrossRefPubMed Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns. 2006;60(3):301–12.CrossRefPubMed
24.
go back to reference Elwyn G, O’Connor A, Stacey D, Volk R, Edwards A, Coulter A, et al. Developing a quality criteria framework for patient decision aids: online international Delphi consensus process. BMJ (Clinical research ed). 2006;333(7565):417.CrossRef Elwyn G, O’Connor A, Stacey D, Volk R, Edwards A, Coulter A, et al. Developing a quality criteria framework for patient decision aids: online international Delphi consensus process. BMJ (Clinical research ed). 2006;333(7565):417.CrossRef
26.
go back to reference Thokala P, Devlin N, Marsh K, Baltussen R, Boysen M, Kalo Z, et al. Multiple criteria decision analysis for health care decision making-an introduction: report 1 of the ISPOR MCDA emerging good practices task force. Value Health. 2016;19(1):1–13.CrossRefPubMed Thokala P, Devlin N, Marsh K, Baltussen R, Boysen M, Kalo Z, et al. Multiple criteria decision analysis for health care decision making-an introduction: report 1 of the ISPOR MCDA emerging good practices task force. Value Health. 2016;19(1):1–13.CrossRefPubMed
27.
go back to reference Adunlin G, Diaby V, Xiao H. Application of multicriteria decision analysis in health care: a systematic review and bibliometric analysis. Health Expect. 2015;18(6):1894–905.CrossRefPubMed Adunlin G, Diaby V, Xiao H. Application of multicriteria decision analysis in health care: a systematic review and bibliometric analysis. Health Expect. 2015;18(6):1894–905.CrossRefPubMed
28.
go back to reference Dowie J, Kjer Kaltoft M, Salkeld G, Cunich M. Towards generic online multicriteria decision support in patient-centred health care. Health Expect. 2015;18(5):689–702.CrossRefPubMed Dowie J, Kjer Kaltoft M, Salkeld G, Cunich M. Towards generic online multicriteria decision support in patient-centred health care. Health Expect. 2015;18(5):689–702.CrossRefPubMed
29.
go back to reference Kaltoft MK, Turner R, Cunich M, Salkeld G, Nielsen JB, Dowie J. Addressing preference heterogeneity in public health policy by combining cluster analysis and multi-criteria decision analysis: proof of method. Health Econ Rev. 2015;5:10.CrossRefPubMedPubMedCentral Kaltoft MK, Turner R, Cunich M, Salkeld G, Nielsen JB, Dowie J. Addressing preference heterogeneity in public health policy by combining cluster analysis and multi-criteria decision analysis: proof of method. Health Econ Rev. 2015;5:10.CrossRefPubMedPubMedCentral
30.
go back to reference Kaltoft MK. Towards improved decision quality in person-centred healthcare: exploring the implications of decision support via multi-criteria decision analysis. University of Southern, Denmark: PhD thesis; 2015. Kaltoft MK. Towards improved decision quality in person-centred healthcare: exploring the implications of decision support via multi-criteria decision analysis. University of Southern, Denmark: PhD thesis; 2015.
31.
go back to reference Salkeld G, Cunich M, Dowie J, Howard K, Patel MI, Mann G, et al. The role of Personalised choice in decision support: a randomized controlled trial of an online decision Aid for prostate cancer screening. PLoS One. 2016;11(4):e0152999.CrossRefPubMedPubMedCentral Salkeld G, Cunich M, Dowie J, Howard K, Patel MI, Mann G, et al. The role of Personalised choice in decision support: a randomized controlled trial of an online decision Aid for prostate cancer screening. PLoS One. 2016;11(4):e0152999.CrossRefPubMedPubMedCentral
32.
go back to reference Gast DL. Single subject research methodology in behavioral sciences. 1st ed. New York: Routledge; 2010. Gast DL. Single subject research methodology in behavioral sciences. 1st ed. New York: Routledge; 2010.
33.
go back to reference Smith JD. Single-case experimental designs: a systematic review of published research and current standards. Psychol Methods. 2012;17(4):510–50.CrossRefPubMed Smith JD. Single-case experimental designs: a systematic review of published research and current standards. Psychol Methods. 2012;17(4):510–50.CrossRefPubMed
35.
go back to reference Eiring Ø, Slaughter L. An Assessment of the Potential for Personalization in Patient Decision Aids. In: Kostkova P, Szomszor M, Fowler D, editors. Electronic Healthcare: 4th International Conference, eHealth 2011, Málaga, Spain, November 21-23, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012. p. 51-7. Eiring Ø, Slaughter L. An Assessment of the Potential for Personalization in Patient Decision Aids. In: Kostkova P, Szomszor M, Fowler D, editors. Electronic Healthcare: 4th International Conference, eHealth 2011, Málaga, Spain, November 21-23, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012. p. 51-7.
36.
go back to reference Eiring Ø, Nylenna M, Nytrøen K. Patient-important outcomes in long-term treatment of bipolar disorder: a mixed methods approach investigating relative preferences and a proposed taxonomy. The patient. 2016;9(2):91–102.CrossRefPubMed Eiring Ø, Nylenna M, Nytrøen K. Patient-important outcomes in long-term treatment of bipolar disorder: a mixed methods approach investigating relative preferences and a proposed taxonomy. The patient. 2016;9(2):91–102.CrossRefPubMed
37.
go back to reference Cunich M, Salkeld G, Dowie J, Henderson J, Bayram C, Britt H, et al. Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: an application to prostate cancer screening. The patient. 2011;4(3):153–62.CrossRefPubMed Cunich M, Salkeld G, Dowie J, Henderson J, Bayram C, Britt H, et al. Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: an application to prostate cancer screening. The patient. 2011;4(3):153–62.CrossRefPubMed
40.
go back to reference Eiring Ø. Personalised decision support for patients with bipolar disorder: Research protocol. Oslo: University of Oslo; 2013. Eiring Ø. Personalised decision support for patients with bipolar disorder: Research protocol. Oslo: University of Oslo; 2013.
41.
go back to reference Eiring Ø, Landmark BF, Aas E, Salkeld G, Nylenna M, Nytrøen K. What matters to patients? A systematic review of preferences for medication-associated outcomes in mental disorders. BMJ Open. 2015;5(4):e007848. doi:10.1136/bmjopen-2015-007848. Eiring Ø, Landmark BF, Aas E, Salkeld G, Nylenna M, Nytrøen K. What matters to patients? A systematic review of preferences for medication-associated outcomes in mental disorders. BMJ Open. 2015;5(4):e007848. doi:10.​1136/​bmjopen-2015-007848.
42.
go back to reference Eiring Ø, et al. Multi-criteria decision analysis of pharmacological maintenance treatment in bipolar disorder: Evaluation of an expedite yet comprehensive approach. [Original research article]. In submission. Eiring Ø, et al. Multi-criteria decision analysis of pharmacological maintenance treatment in bipolar disorder: Evaluation of an expedite yet comprehensive approach. [Original research article]. In submission.
43.
go back to reference Sauro J, Lewis JR. Quantifying the user experience. Practical statistics for user research. Waltham, MA, USA: Elsevier Inc.; 2012. Sauro J, Lewis JR. Quantifying the user experience. Practical statistics for user research. Waltham, MA, USA: Elsevier Inc.; 2012.
45.
go back to reference Garrett JJ. Elements of user experience: user-centered design for the Web and beyond (voices that matter). 2nd ed. New Riders: Berkely, CA; 2010. Garrett JJ. Elements of user experience: user-centered design for the Web and beyond (voices that matter). 2nd ed. New Riders: Berkely, CA; 2010.
46.
go back to reference Krug S. Rocket surgery made easy. New RIders: Berkeley, CA; 2010. Krug S. Rocket surgery made easy. New RIders: Berkeley, CA; 2010.
47.
go back to reference Brooke J. SUS: a “quick and dirty” usability scale. In: Jordan BT PW, Weerdmeester BA, McClelland AL, editors. Usability evaluation in industry. London, UK: Taylor and Francis; 1996. p. 189–94. Brooke J. SUS: a “quick and dirty” usability scale. In: Jordan BT PW, Weerdmeester BA, McClelland AL, editors. Usability evaluation in industry. London, UK: Taylor and Francis; 1996. p. 189–94.
48.
go back to reference Sauro J. A practical guide to the system usability scale: background, benchmarks, and best practices. Measuring Usability LLC: Denver, CO; 2011. Sauro J. A practical guide to the system usability scale: background, benchmarks, and best practices. Measuring Usability LLC: Denver, CO; 2011.
50.
go back to reference Bangor AKP, Miller J. Determining what individual SUS scores mean: adding an adjective rating scale. J Usability stud. 2009;4(3):114–23. Bangor AKP, Miller J. Determining what individual SUS scores mean: adding an adjective rating scale. J Usability stud. 2009;4(3):114–23.
52.
go back to reference Chouvarda IG, Goulis DG, Lambrinoudaki I, Maglaveras N. Connected health and integrated care: toward new models for chronic disease management. Maturitas. 2015;82(1):22–7.CrossRefPubMed Chouvarda IG, Goulis DG, Lambrinoudaki I, Maglaveras N. Connected health and integrated care: toward new models for chronic disease management. Maturitas. 2015;82(1):22–7.CrossRefPubMed
54.
go back to reference Felli JC, Noel RA, Cavazzoni PA. A multiattribute model for evaluating the benefit-risk profiles of treatment alternatives. Med Decis Making. 2009;29(1):104–15.CrossRefPubMed Felli JC, Noel RA, Cavazzoni PA. A multiattribute model for evaluating the benefit-risk profiles of treatment alternatives. Med Decis Making. 2009;29(1):104–15.CrossRefPubMed
55.
go back to reference Macefield R. How to specify the participant group size for usability studies: a Practitioner’s guide. J Usability Stud. 2009;5(1):34–45. Macefield R. How to specify the participant group size for usability studies: a Practitioner’s guide. J Usability Stud. 2009;5(1):34–45.
56.
go back to reference Virzi RA. Refining the test phase of usability evaluation: How many subjects is enough? J Hum Factors Ergon Soc. 1992;34(4):457–68. Virzi RA. Refining the test phase of usability evaluation: How many subjects is enough? J Hum Factors Ergon Soc. 1992;34(4):457–68.
Metadata
Title
The development and feasibility of a personal health-optimization system for people with bipolar disorder
Authors
Øystein Eiring
Kari Nytrøen
Simone Kienlin
Soudabeh Khodambashi
Magne Nylenna
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2017
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-017-0481-x

Other articles of this Issue 1/2017

BMC Medical Informatics and Decision Making 1/2017 Go to the issue