Advertisement

Forum

, Volume 33, Issue 2, pp 94–100 | Cite as

Telemedizinische Erfassung von „patient-reported outcomes“

  • V. Siefert
  • G. Welzel
  • M. Blessing
  • L. Jahnke
  • J. Hesser
  • F. Wenz
  • F. A. GiordanoEmail author
Fokus
  • 142 Downloads

Zusammenfassung

Patienten können heute in Echtzeit per Software (Applikationen, kurz Apps) auf modernen (Tele‑)Kommunikationssystemen wie Smartphones oder Tablets an ihre Behandler berichten, wie sie ihren subjektiven Gesundheitszustand, ihre Stimmung und ihr Zurechtkommen im Alltag, in der Summe als „patient-reported outcomes“ (PROs) bezeichnet, einschätzen. Die zunehmende Patientenzentrierung bei der Erhebung von PROs verspricht dabei erstmals, dass aufgrund verbesserter Datenqualität (bessere Compliance, mehr Messpunkte etc.) Therapieentscheidungen auf allen Ebenen, d. h. von der Leitlinie bis zur täglichen individuellen Einschätzung, von PROs beeinflusst werden. Jedoch ist noch keine einheitliche Strategie erkennbar, wie und mit welcher Gewichtung PROs in den klinischen Alltag implementiert werden, um daraus therapeutische Konsequenzen abzuleiten. Dieser Beitrag gibt einen Überblick über die Terminologie und fasst gegenwärtige Herausforderungen auf dem Weg zur Etablierung von PROs als anerkannte Daten im klinischen Alltag zusammen.

Schlüsselwörter

Telemedizin Software Elektronische Patientendaten Entscheidungsfindung Lebensqualität 

Remote monitoring of patient-reported outcomes

Abstract

Modern communication systems such as smartphones and tablets allow patients to submit real-time reports on their mood, everyday functioning, and subjective health to their care providers via software. These reports and evaluations, summarized under the umbrella term “patient-reported outcomes” (PROs), are generated by locally installed applications (or, in short, apps). Increasingly patient-centered app-based PRO collection promises to significantly contribute to care plans and therapies at all levels, from guidelines to individual evaluation, as they gather more high-quality data due to improved patient compliance and more individual measurements. However, there is no clear path regarding how and with what weighting PROs are to be implemented into daily clinical practice in order to derive consequences. Herein, we summarize the terminology and most significant challenges that have to be tackled before PROs might be established as “valid” data in clinical routine.

Keywords

Telemedicine Software Electronic health record Decision-making Quality of life 

Notes

Einhaltung ethischer Richtlinien

Interessenkonflikt

V. Siefert, G. Welzel, M. Blessing, L. Jahnke, J. Hesser, F. Wenz und F. A. Giordano geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Literatur

  1. 1.
    Pennacchini M et al (2011) A brief history of the quality of life: its use in medicine and in philosophy. Clin Ter 162(3):e99–e103PubMedGoogle Scholar
  2. 2.
    Vodicka E et al (2015) Inclusion of patient-reported outcome measures in registered clinical trials: evidence from ClinicalTrials.gov (2007–2013). Contemp Clin Trials 43:1–9CrossRefPubMedGoogle Scholar
  3. 3.
    Schlachta-Fairchild L, Elfrink V, Deickman A (2008) Chapter 48 patient safety, telenursing, and telehealth. In: Hughes R (Hrsg) Patient safety and quality: an evidence-based handbook for nurses. Agency for Healthcare Research and Quality, Rockville (https://www.ncbi.nlm.nih.gov/books/NBK2687/)Google Scholar
  4. 4.
    Fayers PM, Machin D (2015) Quality of life: the assessment, analysis and reporting of patient-reported outcomes. John Wiley & Sons, HobokenCrossRefGoogle Scholar
  5. 5.
    Corrigan J (2005) Crossing the quality chasm. In: Building a better delivery systemGoogle Scholar
  6. 6.
    Sood S et al (2007) What is telemedicine? A collection of 104 peer-reviewed perspectives and theoretical underpinnings. Telemed E Health 13(5):573–590CrossRefGoogle Scholar
  7. 7.
    Sood SP, Bhatia J (2005) Development of telemedicine technology in India:’„Sanjeevani“-an integrated telemedicine application. J Postgrad Med 51(4):308PubMedGoogle Scholar
  8. 8.
    Korzilius H (2008) Hausärztemangel in Deutschland: Die große Landflucht. Dtsch Arztebl 105(8):A373–A374Google Scholar
  9. 9.
    Denis F et al (2017) Randomized trial comparing a web-mediated follow-up with routine surveillance in lung cancer patients. J Natl Cancer Inst 109(9):djx29CrossRefGoogle Scholar
  10. 10.
    Orlov OI et al (2001) Wireless ECG monitoring by telephone. Telemed J E Health 7(1):33–38CrossRefPubMedGoogle Scholar
  11. 11.
    Tachakra S et al (2003) Mobile e‑health: the unwired evolution of telemedicine. Telemed J E Health 9(3):247–257CrossRefPubMedGoogle Scholar
  12. 12.
    Zhao X et al (2004) A telemedicine system for wireless home healthcare based on bluetooth™ and the internet. Telemed J E Health 10(Supplement 2):S-110–S-116CrossRefGoogle Scholar
  13. 13.
    Basch E et al (2015) Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. J Clin Oncol 34(6):557–565CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Bottomley A et al (2016) Analysing data from patient-reported outcome and quality of life endpoints for cancer clinical trials: a start in setting international standards. Lancet Oncol 17(11):e510–e514CrossRefPubMedGoogle Scholar
  15. 15.
    Schlachta L, Sparks S (1998) Definitions of telenursing, telemedicine. In: Encyclopedia of nursing research. Springer, New York, S 558–559Google Scholar
  16. 16.
    Marescaux J et al (2002) Transcontinental robot-assisted remote telesurgery: feasibility and potential applications. Ann Surg 235(4):487CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    FDA-NIH Biomarker Working Group (2016) BEST (Biomarkers, EndpointS, and other Tools) resource (https://www.ncbi.nlm.nih.gov/books/NBK326791/pdf/Bookshelf_NBK326791.pdf)Google Scholar
  18. 18.
    US Department of Health Human Services FDA Center for Drug Evaluation Research, US Department of Health Human Services FDA Center for Biologics Evaluation Research, US Department of Health Human Services FDA Center for Devices Radiological Health (2006) Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims: draft guidance. Health Qual Life Outcomes 4:1–20CrossRefGoogle Scholar
  19. 19.
    Mokkink LB et al (2010) The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol 63(7):737–745CrossRefPubMedGoogle Scholar
  20. 20.
    Basch E et al (2014) Development of the National Cancer Institute’s patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE). J Natl Cancer Inst 106(9):dju244CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Kaasa S et al (1995) The EORTC core quality of life questionnaire (QLQ-C30): validity and reliability when analysed with patients treated with palliative radiotherapy. Eur J Cancer 31(13–14):2260–2263CrossRefGoogle Scholar
  22. 22.
    Hjermstad MJ et al (1995) Test/retest study of the European organization for research and treatment of cancer core quality-of-life questionnaire. J Clin Oncol 13(5):1249–1254CrossRefPubMedGoogle Scholar
  23. 23.
    Smets E et al (1998) Fatigue and radiotherapy:(B) experience in patients 9 months following treatment. Br J Cancer 78(7):907–912CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Basch E, Abernethy AP (2011) Supporting clinical practice decisions with real-time patient-reported outcomes. J Clin Oncol 29(8):954–956CrossRefPubMedGoogle Scholar
  25. 25.
    Gotay CC et al (2008) The prognostic significance of patient-reported outcomes in cancer clinical trials. J Clin Oncol 26(8):1355–1363CrossRefPubMedGoogle Scholar
  26. 26.
    Quinten C et al (2009) Baseline quality of life as a prognostic indicator of survival: a meta-analysis of individual patient data from EORTC clinical trials. Lancet Oncol 10(9):865–871CrossRefPubMedGoogle Scholar
  27. 27.
    Fromme EK et al (2004) How accurate is clinician reporting of chemotherapy adverse effects? A comparison with patient-reported symptoms from the quality-of-life questionnaire C30. J Clin Oncol 22(17):3485–3490CrossRefPubMedGoogle Scholar
  28. 28.
    Testa MA et al (1993) Quality of life and antihypertensive therapy in men – a comparison of Captopril with Enalapril. N Engl J Med 328(13):907–913CrossRefPubMedGoogle Scholar
  29. 29.
    Denis F et al (2014) Detecting lung cancer relapse using self-evaluation forms weekly filled at home: the sentinel follow-up. Support Care Cancer 22(1):79–85CrossRefPubMedGoogle Scholar
  30. 30.
    Pew-Research-Center (2015) The smartphone difference (http://www.pewinternet.org/files/2015/03/PI_Smartphones_0401151.pdf)Google Scholar
  31. 31.
    Ganser AL, Raymond SA, Pearson JD (2010) Data quality and power in clinical trials: a comparison of ePRO and paper in a randomized trial. In: ePRO: electronic solutions for patient-reported data, S 49Google Scholar
  32. 32.
    Stone AA et al (2002) Patient non-compliance with paper diaries. BMJ 324(7347):1193–1194CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Appelboom G et al (2014) Smart wearable body sensors for patient self-assessment and monitoring. Arch Public Health 72(1):28CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Bauer KA (2007) Wired patients: implantable microchips and biosensors in patient care. Camb Q Healthc Ethics 16(3):281–290CrossRefPubMedGoogle Scholar
  35. 35.
    Gwaltney CJ, Shields AL, Shiffman S (2008) Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: a meta-analytic review. Value Health 11(2):322–333CrossRefPubMedGoogle Scholar
  36. 36.
    Garg AX et al (2005) Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 293(10):1223–1238CrossRefPubMedGoogle Scholar
  37. 37.
    Kawamoto K et al (2005) Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 330(7494):765CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Calvert M et al (2014) Patient-reported outcome (PRO) assessment in clinical trials: a systematic review of guidance for trial protocol writers. PLoS ONE 9(10):e110216CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Calvert M et al (2018) Guidelines for inclusion of patient-reported outcomes in clinical trial protocols: the SPIRIT-PRO extension. JAMA.  https://doi.org/10.1001/jama.2017.21903 PubMedGoogle Scholar
  40. 40.
    Garcia SF et al (2007) Standardizing patient-reported outcomes assessment in cancer clinical trials: a patient-reported outcomes measurement information system initiative. J Clin Oncol 25(32):5106–5112CrossRefPubMedGoogle Scholar
  41. 41.
    Turner L et al (2012) Does use of the CONSORT statement impact the completeness of reporting of randomised controlled trials published in medical journals? A Cochrane review a. Syst Rev 1(1):60CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Calvert M et al (2013) Reporting of patient-reported outcomes in randomized trials: the CONSORT PRO extension. JAMA 309(8):814–822CrossRefPubMedGoogle Scholar

Copyright information

© Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2018

Authors and Affiliations

  • V. Siefert
    • 1
  • G. Welzel
    • 1
  • M. Blessing
    • 2
  • L. Jahnke
    • 1
  • J. Hesser
    • 2
  • F. Wenz
    • 1
  • F. A. Giordano
    • 1
    Email author
  1. 1.Klinik für Strahlentherapie und RadioonkologieUniversitätsmedizin Mannheim, Medizinische Fakultät Mannheim der Universität HeidelbergMannheimDeutschland
  2. 2.Experimentelle StrahlentherapieUniversitätsmedizin Mannheim, Medizinische Fakultät Mannheim der Universität HeidelbergMannheimDeutschland

Personalised recommendations