Wearable-Triggered Ecological Momentary Assessments Are Feasible in People With Advanced Cancer and Their Family Caregivers: Feasibility Study from an Outpatient Palliative Care Clinic at a Cancer Center.

Background: Emerging digital health approaches could play a role in better personalized palliative care. Aim: We conducted a feasibility study testing wearable sensor (WS)-triggered ecological momentary assessments (EMAs) and electronic patient-reported outcomes in community palliative care with patient-caregiver dyads. Design: All wore consumer-grade WS for five weeks. Sensor-detected "stress" (heart rate variability algorithm) that passed individualized thresholds triggered a short smartphone survey. Daily sleep surveys, weekly symptom surveys (Integrated Palliative care Outcome Scale), and a poststudy experience survey were conducted. Setting/Participants: Fifteen dyads (n = 30) were recruited from an outpatient palliative care clinic for people with cancer. Results: Daytime sensor wear-time had 73% adherence. Participants perceived value in this support. Quantity and severity of "stress" events were higher in patients. Sleep disturbance was similar but for different reasons: patients (physical symptoms) and caregivers (worrying about the patient). Conclusions: EMAs are feasible and valued in community palliative care.

Introducing Computed Tomography Simulation-Free and Electronic Patient-Reported Outcomes-Monitored Palliative Radiation Therapy into Routine Care: Clinical Outcomes and Implementation Experience.

PURPOSE: Our purpose was to report outcomes of a novel palliative radiation therapy protocol that omits computed tomography simulation and prospectively collects electronic patient-reported outcomes (ePROs). METHODS AND MATERIALS: Patients receiving extracranial, nonstereotactic, linear accelerator-based palliative radiation therapy who met inclusion criteria (no mask-based immobilization and a diagnostic computed tomography within 4 weeks) were eligible. Global pain was scored with the 11-point numerical pain rating scale (NPRS). Patients were coded as having osseous or soft tissue metastases and no/mild versus severe baseline pain (NPRS ≥ 5). Pain response at 4 weeks was measured according to the international consensus (no analgesia adjustment). Transition to ePRO questionnaires was completed in 3 phases. Initially, pain assessments were collected on paper for 11 months, then pilot ePROs for 1 month and then, after adjustments, revised ePROs from 1 year onwards. ePRO feasibility criteria were established with reference to the paper-based process and published evidence. RESULTS: Between May 2018 and November 2019, 542 consecutive patients were screened, of whom 163 were eligible (30%), and 160 patients were successfully treated. The proportion of patients eligible for the study improved from approximately 20% to 50% by study end. Routine care pain monitoring via ePROs was feasible. One hundred twenty-seven patients had a baseline NPRS recording. Ninety-five patients had osseous (61% severe pain) and 32 had soft tissue (25% severe pain) metastases. Eighty-four patients (66%) were assessable for pain response at 4 weeks. In the 41 patients with severe osseous pain, overall and complete pain response was 78% and 22%, respectively. CONCLUSIONS: By study completion, 50% of patients receiving palliative extracranial radiation therapy avoided simulation, streamlining the treatment process and maximizing patient convenience. Pain response for patients with severe pain from osseous lesions was equivalent to published evidence.

Rolling out RapidPlan: What we've learnt.

INTRODUCTION: RapidPlan (RP), a knowledge-based planning system, aims to consistently improve plan quality and efficiency in radiotherapy. During the early stages of implementation, some of the challenges include knowing how to optimally train a model and how to integrate RP into a department. We discuss our experience with the implementation of RP into our institution. METHODS: We reviewed all patients planned using RP over a 7-month period following inception in our department. Our primary outcome was clinically acceptable plans (used for treatment) with secondary outcomes including model performance and a comparison of efficiency and plan quality between RP and manual planning (MP). RESULTS: Between November 2017 and May 2018, 496 patients were simulated, of which 217 (43.8%) had an available model. RP successfully created a clinically acceptable plan in 87.2% of eligible patients. The individual success of the 24 models ranged from 50% to 100%, with more than 90% success in 15 (62.5%) of the models. In 40% of plans, success was achieved on the 1st optimisation. The overall planning time with RP was reduced by up to 95% compared with MP times. The quality of the RP plans was at least equivalent to historical MP plans in terms of target coverage and organ at risk constraints. CONCLUSION: While initially time-consuming and resource-intensive to implement, plans optimised with RP demonstrate clinically acceptable plan quality, while significantly improving the efficiency of a department, suggesting RP and its application is a highly effective tool in clinical practice.

Big Data Readiness in Radiation Oncology: An Efficient Approach for Relabeling Radiation Therapy Structures With Their TG-263 Standard Name in Real-World Data Sets.

PURPOSE: To prepare for big data analyses on radiation therapy data, we developed Stature, a tool-supported approach for standardization of structure names in existing radiation therapy plans. We applied the widely endorsed nomenclature standard TG-263 as the mapping target and quantified the structure name inconsistency in 2 real-world data sets. METHODS AND MATERIALS: The clinically relevant structures in the radiation therapy plans were identified by reference to randomized controlled trials. The Stature approach was used by clinicians to identify the synonyms for each relevant structure, which was then mapped to the corresponding TG-263 name. We applied Stature to standardize the structure names for 654 patients with prostate cancer (PCa) and 224 patients with head and neck squamous cell carcinoma (HNSCC) who received curative radiation therapy at our institution between 2007 and 2017. The accuracy of the Stature process was manually validated in a random sample from each cohort. For the HNSCC cohort we measured the resource requirements for Stature, and for the PCa cohort we demonstrated its impact on an example clinical analytics scenario. RESULTS: All but 1 synonym group ("Hydrogel") was mapped to the corresponding TG-263 name, resulting in a TG-263 relabel rate of 99% (8837 of 8925 structures). For the PCa cohort, Stature matched a total of 5969 structures. Of these, 5682 structures were exact matches (ie, following local naming convention), 284 were matched via a synonym, and 3 required manual matching. This original radiation therapy structure names therefore had a naming inconsistency rate of 4.81%. For the HNSCC cohort, Stature mapped a total of 2956 structures (2638 exact, 304 synonym, 14 manual; 10.76% inconsistency rate) and required 7.5 clinician hours. The clinician hours required were one-fifth of those that would be required for manual relabeling. The accuracy of Stature was 99.97% (PCa) and 99.61% (HNSCC). CONCLUSIONS: The Stature approach was highly accurate and had significant resource efficiencies compared with manual curation.

A generic, web-based clinical information system architecture using HL7 CDA: successful implementation in dermatological routine care.

The requirements of highly specialized clinical domains are often underrepresented in hospital information systems (HIS). Common consequences are that documentation remains to be paper-based or external systems with insufficient HIS integration are used. This paper presents a solution to overcome this deficiency in the form of a generic framework based on the HL7 Clinical Document Architecture. The central architectural idea is the definition of customized forms using a schema-controlled XML language. These flexible form definitions drive the user interface, the data storage, and standardized data exchange. A successful proof-of-concept application in a dermatologic outpatient wound care department has been implemented, and is well accepted by the clinicians. Our work with HL7 CDA revealed the need for further practical research in the health information standards realm.

Generic screen representations for future proof systems--is it possible? Two-model approach to a generic GUI.

Semantic interoperability should not only cover system interpretation of incoming information, but should be extended to include screen representation. This article describes a two-model approach to generate a screen representation for archetype-based information, which is inspired by the two-model approach used by openEHR for their archetypes. It provides a separation between software-related display knowledge and domain-related display knowledge and is designed with reuse of components in mind. This approach leads to a flexible GUI that can adapt not only to information structures that are not predefined within the receiving system and display them in a meaningful way, but also to novel ways of displaying the information. We are working on a proof of concept implementation to validate the approach.

Towards sustainability of health information systems: how can we define, measure and achieve it?

Health information systems (HIS) in their current form are rarely sustainable. In order to sustain our health information systems and with it our health systems, we need to focus on defining and maintaining sustainable Health Information System building blocks or components. These components need to be easily updatable when clinical knowledge (or anything else) changes, easily adaptable when business requirements or processes change, and easily exchangeable when technology advances. One major prerequisite for this is that we need to be able to define and measure sustainability, so that it can become one of the major business drivers in HIS development. Therefore, this paper analyses general definitions and indicators for sustainability, and analyses their applicability to HIS. We find that general 'Emergy analysis' is one possibility to measure sustainability for HIS. Based on this, we investigate major enablers and inhibitors to sustainability in a highlevel framework consisting of four pillars: clinical, technical, socio-technical, and political/business.

Towards automatically generating graphical user interfaces from openEHR archetypes.

One of the main challenges in the field of Electronic Health Records (EHRs) is semantic interoperability. To utilise the full potential of interoperable EHR systems they have to be accepted by their users, the health care providers. Good Graphical User Interfaces (GUIs) that support customisation and data validation play a decisive role for user acceptance and data quality. This study investigates the use of openEHR archetypes to automatically generate coherent, customizable, data-validating GUIs. Using the Mozilla XML User Interface Language (XUL) a series of prototypes has been developed. The results show that the automatic generation of GUIs from openEHR archetypes is feasible in principle. Although XUL revealed some problems, the advantages of XML-based GUI languages are evident.

Can openEHR Archetypes Empower Multi-Centre Clinical Research?

The Electronic Health Record is of utmost importance to enable the provision of high-quality collaborative care; one prominent development is openEHR. On the other hand, a systematic approach to support the use of routine data for multi-centre clinical research is becoming increasingly important. One example of this is the extensible architecture for using routine data for additional purposes (eardap) which features comprehensive terminological support. However, as experiences in various medical fields have shown, the terminology-based approach is limited to specialized fields and it is argued that a comprehensive terminology is simply too complex and too difficult to maintain. As the openEHR archetype approach does not rely heavily on big standardized terminologies, it offers more flexibility during standardisation of clinical concepts and overcome the shortcomings of terminology-focused approaches. It is unknown, however, how far the more generic openEHR approach can also enable re-use of routinely collected data for clinical research purposes - the use case for which eardap was designed. We therefore explored the feasibility of using the openEHR approach to support multi-centre research in comparison to eardap. Generally speaking, our results show that both eardap and openEHR are suitable to enable the use of routine data for multi-centre clinical research. As the openEHR approach also ensures open, future-proof Electronic Health Records, we conclude that it is highly desirable that multi-centre clinical trials adopt openEHR.