Background: With the rise of digital health technologies and telemedicine, the need for evidence-based evaluation is growing. Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) are recommended as an essential part of the evaluation of telemedicine. For the first time, a systematic review has been conducted to investigate the use of PROMs and PREMs in the evaluation studies of telemedicine covering all application types and medical purposes. Objective: This study investigates the following research questions: in which scenarios are PROMs and PREMs collected for evaluation purposes, which PROM and PREM outcome domains have been covered and how often, which outcome measurement instruments have been used and how often, does the selection and quantity of PROMs and PREMs differ between study types and application types, and has the use of PROMs and PREMs changed over time. Methods: We conducted a systematic literature search of the MEDLINE and Embase databases and included studies published from inception until April 2, 2020. We included studies evaluating telemedicine with patients as the main users; these studies reported PROMs and PREMs within randomized controlled trials, controlled trials, noncontrolled trials, and feasibility trials in English and German. Results: Of the identified 2671 studies, 303 (11.34%) were included; of the 303 studies, 67 (22.1%) were feasibility studies, 70 (23.1%) were noncontrolled trials, 20 (6.6%) were controlled trials, and 146 (48.2%) were randomized controlled trials. Health-related quality of life (n=310; mean 1.02, SD 1.05), emotional function (n=244; mean 0.81, SD 1.18), and adherence (n=103; mean 0.34, SD 0.53) were the most frequently assessed outcome domains. Self-developed PROMs were used in 21.4% (65/303) of the studies, and self-developed PREMs were used in 22.3% (68/303). PROMs (n=884) were assessed more frequently than PREMs (n=234). As the evidence level of the studies increased, the number of PROMs also increased (τ=−0.45), and the number of PREMs decreased (τ=0.35). Since 2000, not only has the number of studies using PROMs and PREMs increased, but the level of evidence and the number of outcome measurement instruments used have also increased, with the number of PREMs permanently remaining at a lower level. Conclusions: There have been increasingly more studies, particularly high-evidence studies, which use PROMs and PREMs to evaluate telemedicine. PROMs have been used more frequently than PREMs. With the increasing maturity stage of telemedicine applications and higher evidence level, the use of PROMs increased in line with the recommendations of evaluation guidelines. Health-related quality of life and emotional function were measured in almost all the studies. Simultaneously, health literacy as a precondition for using the application adequately, alongside proper training and guidance, has rarely been reported. Further efforts should be pursued to standardize PROM and PREM collection in evaluation studies of telemedicine.

Zusammenfassung: Digitale Interventionen (DI) zu gesundheitsbezogenen Themen gewinnen zunehmend an Bedeutung. Oftmals sind sie komplexe Interventionen, die in einem komplexen Versorgungskontext evaluiert und implementiert werden. Aufgrund der Merkmale digitaler Interventionen ist die Versorgungsforschung vor methodische Herausforderungen gestellt. Daher hat die Arbeitsgruppe Digital Health des Deutschen Netzwerks Versorgungsforschung (DNVF) ein Diskussionspapier erstellt. Darin wird diskutiert, welche Herausforderungen mit der Entwicklung und Evaluation von DI einhergehen. Es werden Lösungsansätze und zukünftige Forschungsbedarfe aufgezeigt.

As integrated care is recognized as crucial to meet the challenges of chronic conditions such as Parkinson’s disease (PD), integrated care networks have emerged internationally and throughout Germany. One of these networks is the Parkinson Network Eastern Saxony (PANOS). PANOS aims to deliver timely and equal care to PD patients with a collaborative intersectoral structured care pathway. Additional components encompass personalized case management, an electronic health record, and communicative and educative measures. To reach an intersectoral consensus of the future collaboration in PANOS, a structured consensus process was conducted in three sequential workshops. Community-based physicians, PD specialists, therapists, scientists and representatives of regulatory authorities and statutory health insurances were asked to rate core pathway-elements and supporting technological, personal and communicative measures. For the majority of core elements/planned measures, a consensus was reached, defined as an agreement by >75% of participants. Additionally, six representatives from all partners involved in the network-design independently assessed PANOS based on the Development Model for Integrated Care (DMIC), a validated model addressing the comprehensiveness and maturity of integrated care concepts. The results show that PANOS is currently in an early maturation state but has the potential to comprehensively represent the DMIC if all planned activities are implemented successfully. Despite the favorable high level of consensus regarding the PANOS concept and despite its potential to become a balanced integrated care concept according to the DMIC, its full implementation remains a considerable challenge.

Zusammenfassung: Methodische Herausforderungen bei der Evaluation digitaler Interventionen (DI) sind für die Versorgungsforschung allgegenwärtig. Die Arbeitsgruppe Digital Health des Deutschen Netzwerks Versorgungsforschung (DNVF) hat in einem zweiteiligen Diskussionspapier diese Herausforderungen dargestellt und diskutiert. Im ersten Teil wurden begriffliche Abgrenzungen sowie die Entwicklung und Evaluation von DI thematisiert. In diesem zweiten Teil wird auf Outcomes, das Reporting von Ergebnissen, die Synthese der Evidenz sowie die Implementierung von DI eingegangen. Lösungsansätze und zukünftige Forschungsbedarfe zur Adressierung dieser Herausforderungen werden diskutiert.

Digitale Gesundheitsinterventionen entwickeln, evaluieren und implementieren (Teil I) – Diskussionspapier der Arbeitsgruppe Digital Health des Deutschen Netzwerk Versorgungsforschung (DNVF) Sven Kernebeck et al. Das Gesundheitswesen (efirst); DOI: 10.1055/a-1933-2779 Im oben genannten Artikel wurden die Institutszuordnungen der Autoren korrigiert: Richtig lauten sie wie folgt: Autorinnen/Autoren Sven Kernebeck¹ , Madlen Scheibe², Monika Sinha^3,4, Florian Fischer^5,6, Andreas Knapp⁷ , Patrick Timpel^2,8, Lorenz Harst² , Ulrich Reininghaus^9,10,11, Horst Christian Vollmar¹² Institute ¹ Lehrstuhl für Didaktik und Bildungsforschung im Gesundheitswesen – Fakultät für Gesundheit, Universität Witten Herdecke, Witten, Germany ² Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum und Medizinische Fakultät Carl Gustav Carus an der TU Dresden, Dresden, Germany ³ Mitglied AG Bioinformatik, Charité Universitätsmedizin Berlin, Berlin, Germany ⁴ Beratung im Gesundheitswesen – angewandte Versorgungsforschung, SINHA, Berlin, Germany ⁵ Bayerisches Forschungszentrum Pflege Digital, Hochschule Kempten, Kempten, Germany ⁶ Institut für Public Health, Charité Universitätsmedizin Berlin, Berlin ⁷ Mint Medical GmbH, Heidelberg ⁸ Wissenschaftliches Institut für Gesundheitsökonomie und Gesundheitssystemforschung , WIG2 GmbH, Leipzig, Germany ⁹ Department of Public Mental Health, Central Institute of Mental Health, University of Heidelberg, Manheim, Germany ¹⁰ ESRC Centre for Society and Mental Health, King’s College London, London, United Kingdom of Great Britain and Northern Ireland ¹¹ Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, Germany ¹² Abteilung für Allgemeinmedizin (AM RUB), Medizinische Fakultät, Ruhr-Universität Bochum, Bochum, Germany Im oben genannten Artikel war der Literaturnachweis 10 nicht korrekt. Richtig lautet er wie folgt: 10 Tokgöz, P, Hrynyschyn, R, Hafner, J et al. Digital health interventions in prevention, relapse, and therapy of mild and moderate depression: scoping review. JMIR Mental Health, 2021; 8(4), e26268. DOI: 10.2196/26268. Article published online: 21 December 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany

BACKGROUND With the rise of digital health technologies and telemedicine, the need for evidence-based evaluation is growing. Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) are recommended as an essential part of the evaluation of telemedicine. For the first time, a systematic review has been conducted to investigate the use of PROMs and PREMs in the evaluation studies of telemedicine covering all application types and medical purposes. OBJECTIVE This study investigates the following research questions: in which scenarios are PROMs and PREMs collected for evaluation purposes, which PROM and PREM outcome domains have been covered and how often, which outcome measurement instruments have been used and how often, does the selection and quantity of PROMs and PREMs differ between study types and application types, and has the use of PROMs and PREMs changed over time. METHODS We conducted a systematic literature search of the MEDLINE and Embase databases and included studies published from inception until April 2, 2020. We included studies evaluating telemedicine with patients as the main users; these studies reported PROMs and PREMs within randomized controlled trials, controlled trials, noncontrolled trials, and feasibility trials in English and German. RESULTS Of the identified 2671 studies, 303 (11.34%) were included; of the 303 studies, 67 (22.1%) were feasibility studies, 70 (23.1%) were noncontrolled trials, 20 (6.6%) were controlled trials, and 146 (48.2%) were randomized controlled trials. Health-related quality of life (n=310; mean 1.02, SD 1.05), emotional function (n=244; mean 0.81, SD 1.18), and adherence (n=103; mean 0.34, SD 0.53) were the most frequently assessed outcome domains. Self-developed PROMs were used in 21.4% (65/303) of the studies, and self-developed PREMs were used in 22.3% (68/303). PROMs (n=884) were assessed more frequently than PREMs (n=234). As the evidence level of the studies increased, the number of PROMs also increased (τ=−0.45), and the number of PREMs decreased (τ=0.35). Since 2000, not only has the number of studies using PROMs and PREMs increased, but the level of evidence and the number of outcome measurement instruments used have also increased, with the number of PREMs permanently remaining at a lower level. CONCLUSIONS There have been increasingly more studies, particularly high-evidence studies, which use PROMs and PREMs to evaluate telemedicine. PROMs have been used more frequently than PREMs. With the increasing maturity stage of telemedicine applications and higher evidence level, the use of PROMs increased in line with the recommendations of evaluation guidelines. Health-related quality of life and emotional function were measured in almost all the studies. Simultaneously, health literacy as a precondition for using the application adequately, alongside proper training and guidance, has rarely been reported. Further efforts should be pursued to standardize PROM and PREM collection in evaluation studies of telemedicine.