Design and multicentric Implementation of a generic Software Architecture for Patient Recruitment Systems re-using existing HIS tools and Routine Patient Data

Trinczek, Benjamin; Köpcke, Felix; Leusch, Thomas; Majeed, Raphael W.; Schreiweis, Björn; Wenk, Joachim; Bergh, Björn; Ohmann, Christian; Röhrig, Rainer; Prokosch, Hans‐Ulrich; Dugas, Martin

doi:10.4338/aci-2013-07-ra-0047

Cited by 31 publications

(10 citation statements)

References 19 publications

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“…Patients with the appropriate diagnoses were identified with a patient recruitment system [30] within the electronic health record based on the diagnosis entered by the treating clinician after an initial examination and diagnostic exploration on the day of admission to the ward. The clinical team approved research participation for all included patients and could dissent to participation when patients were not suitable due to their mental and cognitive symptom severity or insufficient language skills.…”

Section: Methodsmentioning

confidence: 99%

Repeated Digitized Assessment of Risk and Symptom Profiles During Inpatient Treatment of Affective Disorder: Observational Study

Richter¹,

Storck²,

Blitz³

et al. 2020

JMIR Ment Health

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Background Predictive models have revealed promising results for the individual prognosis of treatment response and relapse risk as well as for differential diagnosis in affective disorders. Yet, in order to translate personalized predictive modeling from research contexts to psychiatric clinical routine, standardized collection of information of sufficient detail and temporal resolution in day-to-day clinical care is needed. Digital collection of self-report measures by patients is a time- and cost-efficient approach to gain such data throughout treatment. Objective The objective of this study was to investigate whether patients with severe affective disorders were willing and able to participate in such efforts, whether the feasibility of such systems might vary depending on individual patient characteristics, and if digitally acquired assessments were of sufficient diagnostic validity. Methods We implemented a system for longitudinal digital collection of risk and symptom profiles based on repeated self-reports via tablet computers throughout inpatient treatment of affective disorders at the Department of Psychiatry at the University of Münster. Tablet-handling competency and the speed of data entry were assessed. Depression severity was additionally assessed by a clinical interviewer at baseline and before discharge. Results Of 364 affective disorder patients who were approached, 242 (66.5%) participated in the study; 88.8% of participants (215/242) were diagnosed with major depressive disorder, and 27 (11.2%) had bipolar disorder. During the duration of inpatient treatment, 79% of expected assessments were completed, with an average of 4 completed assessments per participant; 4 participants (4/242, 1.6%) dropped out of the study prematurely. During data entry, 89.3% of participants (216/242) did not require additional support. Needing support with tablet handling and slower data entry pace were predicted by older age, whereas depression severity at baseline did not influence these measures. Patient self-reporting of depression severity showed high agreement with standardized external assessments by a clinical interviewer. Conclusions Our results indicate that digital collection of self-report measures is a feasible, accessible, and valid method for longitudinal data collection in psychiatric routine, which will eventually facilitate the identification of individual risk and resilience factors for affective disorders and pave the way toward personalized psychiatric care.

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Section: Methodsmentioning

confidence: 99%

Repeated Digitized Assessment of Risk and Symptom Profiles During Inpatient Treatment of Affective Disorder: Observational Study

Richter¹,

Storck²,

Blitz³

et al. 2020

JMIR Ment Health

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“…EMRs can implement clinical trial protocol (TM1) either with integrated functionality or by extending functionality [ 16 , 18 , 19 , 32 - 35 ]. Because the purpose of EMRs is to facilitate documentation of patients’ medical histories for duty of medical documentation and billing purposes, the integration of patients’ health care information (GR2) is achieved by implementing a patient recruitment support system with an EMR.…”

Section: Resultsmentioning

confidence: 99%

Applicability of Different Electronic Record Types for Use in Patient Recruitment Support Systems: Comparative Analysis

Schreiweis¹,

Brandner²,

Bergh³

2021

JMIR Form Res

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Background Clinical trials constitute an important pillar in medical research. It is beneficial to support recruitment for clinical trials using software tools, so-called patient recruitment support systems; however, such information technology systems have not been frequently used to date. Because medical information systems' underlying data collection methods strongly influence the benefits of implementing patient recruitment support systems, we investigated patient recruitment support system requirements and corresponding electronic record types such as electronic medical record, electronic health record, electronic medical case record, personal health record, and personal cross-enterprise health record. Objective The aim of this study was to (1) define requirements for successful patient recruitment support system deployment and (2) differentiate and compare patient recruitment support system–relevant properties of different electronic record types. Methods In a previous study, we gathered requirements for patient recruitment support systems from literature and unstructured interviews with stakeholders (15 patients, 3 physicians, 5 data privacy experts, 4 researchers, and 5 staff members of hospital administration). For this investigation, the requirements were amended and categorized based on input from scientific sessions. Based on literature with a focus on patient recruitment support system–relevant properties, different electronic record types (electronic medical record, electronic health record, electronic medical case record, personal health record and personal cross-enterprise health record) were described in detail. We also evaluated which patient recruitment support system requirements can be achieved for each electronic record type. Results Patient recruitment support system requirements (n=16) were grouped into 4 categories (consent management, patient recruitment management, trial management, and general requirements). All 16 requirements could be partially met by at least 1 type of electronic record. Only 1 requirement was fully met by all 5 types. According to our analysis, personal cross-enterprise health records fulfill most requirements for patient recruitment support systems. They demonstrate advantages especially in 2 domains (1) supporting patient empowerment and (2) granting access to the complete medical history of patients. Conclusions In combination with patient recruitment support systems, personal cross-enterprise health records prove superior to other electronic record types, and therefore, this integration approach should be further investigated.

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“…If a patient matches the inclusion criteria of a specific study, the research platform validates the consent status of the respective patient and checks the consent module for re-contact. Following the principles of Trinczek et al [ 38 ], the research platform then automatically generates and adds a recruitment proposal on the worklist for the staff of the respective clinical study within the primary clinical system. The responsible study nurse, for instance, just needs to confirm the proposal to start the digital documentation of the patient’s consent and include the patient in another study.…”

Section: Discussionmentioning

confidence: 99%

MAGIC: once upon a time in consent management—a FHIR® tale

Bialke¹,

Bahls²,

Geidel³

et al. 2018

J Transl Med

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BackgroundThe use of medical data for research purposes requires an informed consent of the patient that is compliant with the EU General Data Protection Regulation. In the context of multi-centre research initiatives and a multitude of clinical and epidemiological studies scalable and automatable measures for digital consent management are required. Modular form, structure, and contents render a patient’s consent reusable for varying project settings in order to effectively manage and minimise organisational and technical efforts.ResultsWithin the DFG-funded project “MAGIC” (Grant Number HO 1937/5-1) the digital consent management service tool gICS was enhanced to comply with the recommendations published in the TMF data protection guideline for medical research. In addition, a structured exchange format for modular consent templates considering established standards and formats in the area of digital informed consent management was designed. Using the new FHIR standard and the HAPI FHIR library, the first version for an exchange format and necessary import-/export-functionalities were successfully implemented.ConclusionsThe proposed exchange format is a “work in progress”. It represents a starting point for current discussions concerning digital consent management. It also attempts to improve interoperability between different approaches within the wider IHE-/HL7-/FHIR community. Independent of the exchange format, providing the possibility to export, modify and import templates for consents and withdrawals to be reused in similar clinical and epidemiological studies is an essential precondition for the sustainable operation of digital consent management.

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Design and multicentric Implementation of a generic Software Architecture for Patient Recruitment Systems re-using existing HIS tools and Routine Patient Data

Cited by 31 publications

References 19 publications

Repeated Digitized Assessment of Risk and Symptom Profiles During Inpatient Treatment of Affective Disorder: Observational Study

Repeated Digitized Assessment of Risk and Symptom Profiles During Inpatient Treatment of Affective Disorder: Observational Study

Applicability of Different Electronic Record Types for Use in Patient Recruitment Support Systems: Comparative Analysis

MAGIC: once upon a time in consent management—a FHIR® tale

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