Remote symptom monitoring integrated into electronic health records: A systematic review

Abstract Objective People with long-term conditions require serial clinical assessments. Digital patient-reported symptoms collected between visits can inform these, especially if integrated into electronic health records (EHRs) and clinical workflows. This systematic review identified and summarized EHR-integrated systems to remotely collect patient-reported symptoms and examined their anticipated and realized benefits in long-term conditions. Materials and Methods We searched Medline, Web of Science, and Embase. Inclusion criteria were symptom reporting systems in adults with long-term conditions; data integrated into the EHR; data collection outside of clinic; data used in clinical care. We synthesized data thematically. Benefits were assessed against a list of outcome indicators. We critically appraised studies using the Mixed Methods Appraisal Tool. Results We included 12 studies representing 10 systems. Seven were in oncology. Systems were technically and functionally heterogeneous, with the majority being fully integrated (data viewable in the EHR). Half of the systems enabled regular symptom tracking between visits. We identified 3 symptom report-guided clinical workflows: Consultation-only (data used during consultation, n = 5), alert-based (real-time alerts for providers, n = 4) and patient-initiated visits (n = 1). Few author-described anticipated benefits, primarily to improve communication and resultant health outcomes, were realized based on the study results, and were only supported by evidence from early-stage qualitative studies. Studies were primarily feasibility and pilot studies of acceptable quality. Discussion and Conclusions EHR-integrated remote symptom monitoring is possible, but there are few published efforts to inform development of these systems. Currently there is limited evidence that this improves care and outcomes, warranting future robust, quantitative studies of efficacy and effectiveness.

[1]  Albert W Wu,et al.  Feasibility and value of PatientViewpoint: a web system for patient‐reported outcomes assessment in clinical practice , 2013, Psycho-oncology.

[2]  David Cella,et al.  Implementing electronic health record–integrated screening of patient‐reported symptoms and supportive care needs in a comprehensive cancer center , 2019, Cancer.

[3]  Kenneth D. Mandl,et al.  SMART on FHIR: a standards-based, interoperable apps platform for electronic health records , 2016, J. Am. Medical Informatics Assoc..

[4]  Haniye Sadat Sajadi,et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 , 2018, The Lancet.

[5]  L. Koppert,et al.  Implementation of Value Based Breast Cancer Care. , 2019, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[6]  Daniel Gottlieb,et al.  SMART Markers: collecting patient-generated health data as a standardized property of health information technology , 2020, npj Digital Medicine.

[7]  Anthony Arnold,et al.  eHealth System for Collecting and Utilizing Patient Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care) Among Cancer Patients: Mixed Methods Approach to Evaluate Feasibility and Acceptability , 2017, Journal of medical Internet research.

[8]  Jack Chen,et al.  A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting , 2013, BMC Health Services Research.

[9]  Michele Angelaccio,et al.  Remote Patient Monitoring via Non-Invasive Digital Technologies: A Systematic Review , 2017, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[10]  David Cella,et al.  Bringing PROMIS to practice: Brief and precise symptom screening in ambulatory cancer care , 2015, Cancer.

[11]  Olga Svestkova,et al.  Mapping European Welfare Models: State of the Art of Strategies for Professional Integration and Reintegration of Persons with Chronic Diseases , 2018, International journal of environmental research and public health.

[12]  Lena Mamykina,et al.  A visual analytics approach for pattern-recognition in patient-generated data , 2018, J. Am. Medical Informatics Assoc..

[13]  Lucy Yardley,et al.  Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop , 2017, Journal of medical Internet research.

[14]  Mark Conner,et al.  Electronic Systems for Patients to Report and Manage Side Effects of Cancer Treatment: Systematic Review , 2019, Journal of medical Internet research.

[15]  Saptarshi Purkayastha,et al.  Implementation of a single sign-on system between practice, research and learning systems , 2017, Applied Clinical Informatics.

[16]  Ida Sim,et al.  Mobile Devices and Health. , 2019, The New England journal of medicine.

[17]  Brennan M. R. Spiegel,et al.  Impact of remote patient monitoring on clinical outcomes: an updated meta-analysis of randomized controlled trials , 2018, npj Digital Medicine.

[18]  P. Pluye,et al.  Testing the reliability and efficiency of the pilot Mixed Methods Appraisal Tool (MMAT) for systematic mixed studies review. , 2012, International journal of nursing studies.

[19]  Matthew Machin,et al.  Providing ‘the bigger picture’: benefits and feasibility of integrating remote monitoring from smartphones into the electronic health record , 2019, Rheumatology.

[20]  Nicholas Genes,et al.  From smartphone to EHR: a case report on integrating patient-generated health data , 2018, npj Digital Medicine.

[21]  Rafael Perera,et al.  Personalised care planning for adults with chronic or long-term health conditions. , 2015, The Cochrane database of systematic reviews.

[22]  Aziz Sheikh,et al.  Five key strategic priorities of integrating patient generated health data into United Kingdom electronic health records , 2018, BMJ Health & Care Informatics.

[23]  K. Lomborg,et al.  Patient-initiated versus fixed-interval patient-reported outcome-based follow-up in outpatients with epilepsy: a pragmatic randomized controlled trial , 2019, Journal of Patient-Reported Outcomes.

[24]  Sara Chokshi,et al.  Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions , 2019, JMIR mHealth and uHealth.

[25]  David Russell,et al.  The impact of home care nurses’ numeracy and graph literacy on comprehension of visual display information: implications for dashboard design , 2018, J. Am. Medical Informatics Assoc..

[26]  Galina Velikova,et al.  Online tool for monitoring adverse events in patients with cancer during treatment (eRAPID): field testing in a clinical setting , 2019, BMJ Open.

[27]  Jacqueline Merrill,et al.  Converging and diverging needs between patients and providers who are collecting and using patient-generated health data: an integrative review , 2018, J. Am. Medical Informatics Assoc..

[28]  Rachel Hess,et al.  Patient reported outcomes – experiences with implementation in a University Health Care setting , 2018, Journal of Patient-Reported Outcomes.

[29]  Roma Maguire,et al.  What is the value of the routine use of patient-reported outcome measures toward improvement of patient outcomes, processes of care, and health service outcomes in cancer care? A systematic review of controlled trials. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[30]  Ilana Graetz,et al.  Use of a web-based app to improve breast cancer symptom management and adherence for aromatase inhibitors: a randomized controlled feasibility trial , 2018, Journal of Cancer Survivorship.

[31]  Gillian R. Hayes,et al.  Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign , 2016, JMIR human factors.

[32]  T. Vos,et al.  Global, regional, and national incidence and prevalence, and years lived with disability for 328 diseases and injuries in 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016 , 2017 .

[33]  Per Sidenius,et al.  AmbuFlex: tele-patient-reported outcomes (telePRO) as the basis for follow-up in chronic and malignant diseases , 2016, Quality of Life Research.

[34]  Matthew J. Crowley,et al.  Bridging the integration gap between patient-generated blood glucose data and electronic health records , 2019, J. Am. Medical Informatics Assoc..

[35]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement , 2009, BMJ : British Medical Journal.

[36]  N. Lv,et al.  Personalized Hypertension Management Using Patient-Generated Health Data Integrated With Electronic Health Records (EMPOWER-H): Six-Month Pre-Post Study , 2017, Journal of medical Internet research.

[37]  Deborah Schrag,et al.  Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[38]  Angela M. Stover,et al.  Collection of electronic patient-reported symptoms in patients with advanced cancer using Epic MyChart surveys , 2019, Supportive Care in Cancer.

[39]  George A. Gellert,et al.  Clinical impact and value of workstation single sign-on , 2017, Int. J. Medical Informatics.

[40]  William G. Dixon,et al.  Using technology to support clinical care and research in rheumatoid arthritis , 2018, Current opinion in rheumatology.