Defining the content of a minimal dataset for acquired brain injury using a Delphi procedure

Long-Term Follow-Up of Critically Ill Patients With Traumatic Brain Injury: From Intensive Care Parameters to Patient and Caregiver-Reported Outcome

Abstract Traumatic brain injury (TBI) is associated with a high social and financial burden due to persisting (severe) disabilities. The consequences of TBI after intensive care unit (ICU) admission are generally measured with global disability screeners such as the Glasgow Outcome Scale-Extended (GOSE), which may lack precision. To improve outcome measurement after brain injury, a comprehensive clinical outcome assessment tool called the Minimal Dataset for Acquired Brain Injury (MDS-ABI) was recently developed. The MDS-ABI covers 12 life domains (demographics, injury characteristics, comorbidity, cognitive functioning, emotional functioning, energy, mobility, self-care, communication, participation, social support, and quality of life), as well as informal caregiver capacity and strain. In this cross-sectional study, we used the MDS-ABI among formerly ICU admitted patients with TBI to explore the relationship between dichotomized severity of TBI and long-term outcome. Our objectives were to: 1) summarize demographics, clinical characteristics, and long-term outcomes of patients and their informal caregivers, and 2) compare differences between long-term outcomes in patients with mild-moderate TBI and severe TBI based on Glasgow Coma Scale (GCS) scores at admission. Participants were former patients of a Dutch university hospital (total n = 52; mild-moderate TBI n = 23; severe TBI n = 29) and their informal caregivers (n = 45). Hospital records were evaluated, and the MDS-ABI was administered during a home visit. On average 3.2 years after their TBI, 62% of the patients were cognitively impaired, 62% reported elevated fatigue, and 69% experienced restrictions in ≥2 participation domains (most frequently work or education and going out). Informal caregivers generally felt competent to provide necessary care (81%), but 31% experienced a disproportionate caregiver burden. All but four patients lived at home independently, often together with their informal caregiver (81%). Although the mild-moderate TBI group and the severe TBI group had significantly different clinical trajectories, there were no persisting differences between the groups for patient or caregiver outcomes at follow-up. As a large proportion of the patients experienced long-lasting consequences beyond global disability or independent living, clinicians should implement a multi-domain outcome set such as the MDS-AB to follow up on their patients.

A cross-sectional comparison of patient characteristics across healthcare settings using the minimal dataset for adults with acquired brain injury (MDS-ABI)

Acquired Brain Injury (ABI) can have lifelong consequences and accordingly, persons with ABI often receive various types of healthcare. Facilities have their own preferences towards measurement instruments used to evaluate patients, impeding data comparison across healthcare settings. In this cross-sectional study, we used the previously developed minimal dataset for persons with ABI (MDS-ABI) to uniformly document and compare characteristics and outcomes of ABI patients in three healthcare settings: (1) residential care (n = 21), (2) non-residential care (n = 80), and (3) no ABI-related care (n = 22). Overall, patients of residential care settings had the lowest functional outcome compared with patients in the remaining groups. Nonetheless, all groups showed substantial disabilities within numerous life domains, indicating that the consequences of ABI are widespread among patients within and outside of healthcare facilities. These results demonstrate the need for a broad measurement of the potential consequences of ABI. The MDS-ABI covers twelve life domains most frequently affected by ABI and therefore helps to better recognize the consequences of ABI. In research contexts, implementation of the MDS-ABI allows for direct comparison of research findings. Future directions should be aimed at further implementation of the MDS-ABI to guide clinical decision-making and assist in identifying treatment goals specific to each healthcare setting.

Gaining consensus on clinical quality outcomes for eating disorders: Framework for the development of an Australian national minimum dataset

OBJECTIVES

Eating disorders (EDs) are complex psychiatric illnesses requiring multidisciplinary care across both mental and medical healthcare settings. Currently, no nationally comprehensive, consistent, agreed on or mandated data set or data collection strategy exists for EDs in Australia: thus, little is known about the outcomes of care nor treatment pathways taken by individuals with EDs. InsideOut Institute was contracted by the Australian Government Department of Health to develop a minimum dataset (MDS) for the illness group with consideration given to data capture mechanisms and the scoping of a national registry.

DESIGN

A four-step modified Delphi methodology was used, including national consultations followed by three rounds of quantitative feedback by an expert panel.

SETTING

Due to social distancing protocols throughout the global SARS-CoV-2 pandemic, the study was conducted online using video conferencing (Zoom and Microsoft Teams) (Step 1), email communication and the REDCap secure web-based survey platform (Steps 2-4).

PARTICIPANTS

14 data management organisations, 5 state and territory government departments of health, 2 Aboriginal and Torres Strait Islander advising organisations and 28 stakeholders representing public and private health sectors across Australia participated in consultations. 123 ED experts (including lived experience) participated in the first quantitative round of the Delphi survey. Retention was high, with 80% of experts continuing to the second round and 73% to the third.

MAIN OUTCOME MEASURES

Items and categories endorsed by the expert panel (defined a priori as >85% rating an item or category 'very important' or 'imperative').

RESULTS

High consensus across dataset items and categories led to the stratification of an identified MDS. Medical status and quality of life were rated the most important outcomes to collect in an MDS. Other items meeting high levels of consensus included anxiety disorders, depression and suicidality; type of treatment being received; body mass index and recent weight change.

CONCLUSIONS

Understanding presentation to and outcomes from ED treatment is vital to drive improvements in healthcare delivery. A nationally agreed MDS has been defined to facilitate this understanding and support improvements.

Measurement Feedback System for Intensive Neurorehabilitation after Severe Acquired Brain Injury

Outcome of acquired brain injury (ABI) and the potential for neurorehabilitation are subject to distinct heterogeneity between patients. Limited knowledge of the complex constellation of determinants at play interferes with the possibility to deploy precision medicine in neurorehabilitation. Measurement Feedback Systems (MFS) structure clinical data collection and deliver the measurement results as feedback to clinicians, thereby facilitating progress monitoring, promoting balanced patient-centered discussion and shared decision making. Accumulation of clinical data in the MFS also enables data-driven precision rehabilitation medicine. This article describes the development and implementation of a MFS for neurorehabilitation after ABI. The MFS consists of specialized measurement tracks which are developed together with representatives of each discipline in the multidisciplinary team. The MFS is built into a digital platform that automatically distributes measurements among clinicians, at predetermined time points during the inpatient treatment, outpatient treatment and follow-up. The results of all measurements are visualized in individual patient dashboards that are accessible for all clinicians involved in treatment. Since step-wise implementation, 124 patients have been registered on the MFS platform so far, providing an average of more than 200 new measurements per week. Currently, more than 15,000 clinical measurements are captured in the MFS. The current overall completion rate of measurements is 86,4%. This study shows that structured clinical assessment and feedback is feasible in the context of neurorehabilitation after severe ABI. The future directions are discussed for MFS data in our Health Intelligence Program, which aims at periodic care evaluation and the transition of neurorehabilitation care towards precision medicine.

Minimum data and core outcomes for subacute rehabilitation: A scoping review

OBJECTIVE

In clinical practice and research, standardised sets of data and outcomes are routinely collected to facilitate data comparison, benchmarking and quality improvement. Most existing data sets are condition-specific and cannot be applied to all patients in a given clinical setting. This review aimed to determine whether the development of a minimum data set for subacute rehabilitation is feasible by collating and comparing existing rehabilitation minimum data sets and core outcome sets.

DATA SOURCES

Published literature was identified through database searches (Scopus, PubMed, EMBASE, CINAHL and the COMET Initiative) in September 2021. Additional data sets were identified through a grey literature search.

REVIEW METHODS

This review was conducted in alignment with the PRISMA-ScR recommendations. Datasets were included if they were published in English, designed for adults, and intended for use in subacute rehabilitation. Data were extracted and taxonomically organised to identify commonalities. Items present in ≥50% of data sets were considered common.

RESULTS

Twenty minimum data sets and seven core outcome sets were included. There were 29 common minimum data set domains, with 19 relating to Patient Information, seven relating to Outcomes, two relating to Service Delivery and one relating to Provider Demographics. Four common domains were identified within the Core Outcome Set analysis, which all related to Life Impact, specifically Physical Functioning (86%), Emotional Functioning/Wellbeing (57%), Social Functioning (86%) and Global Quality of Life (100%).

CONCLUSION

Common item domains in conditions requiring subacute rehabilitation have been identified, suggesting that development of a dataset for subacute rehabilitation may be feasible.

A study to design minimum data set of COVID-19 registry system

BACKGROUND

From the beginning of the COVID-19 pandemic, the development of infrastructures to record, collect and report COVID-19‏ ‏data has become a fundamental necessity in the world. The disease registry system can help build an infrastructure to collect data systematically. The study aimed to design a minimum data set for the COVID-19 registry system.

METHODS

A qualitative study to design an MDS for the COVID-19 registry system was performed in five phases at Ahvaz University of Medical Sciences in Khuzestan Province in southwestern Iran, 2020-2021. In the first phase, assessing the information requirements was performed for the COVID-19 registry system. Data elements were identified in the second phase. In the third phase, the MDS was selected, and in the four phases, the COVID-19 registry system was implemented as a pilot study to test the MDS. Finally, based on the experiences gained from the COVID-19 registry system implementation, the MDS were evaluated, and corrections were made.

RESULTS

MDS of the COVID-19 registry system contains eight top groups including administrative (34 data elements), disease exposure (61 data elements), medical history and physical examination (138 data elements), findings of clinical diagnostic tests (101 data elements), disease progress and outcome of treatment (55 data elements), medical diagnosis and cause of death (12 data elements), follow-up (14 data elements), and COVID-19 vaccination (19 data elements) data, respectively.

CONCLUSION

Creating a standard and comprehensive MDS can help to design any national data dictionary for COVID-19 and improve the quality of COVID-19 data.

Validity of the Utrecht scale for evaluation of rehabilitation-participation restrictions scale in a hospital-based stroke population 3 months after stroke

Background:The Utrecht Scale for Evaluation of Rehabilitation-Participation Restrictions scale (USER-P-R) is a promising patient-reported outcome measure, but has currently not been validated in a hospital-based stroke population. Objective:To examine psychometric properties of the USER-P-R in a hospital-based stroke population 3 months after stroke onset. Methods:Cross-sectional study including 359 individuals with stroke recruited through 6 Dutch hospitals. The USER-P-R, EuroQol 5-dimensional 5-level questionnaire (EQ-5D-5 L), Patient Reported Outcomes Measurement Information System 10-Question Global Health Short Form (PROMIS-10), modified Rankin Scale (mRS) and two items on perceived decrease in health and activities post-stroke were administered in a telephone interview 3 months after stroke. The internal consistency, distribution, floor/ceiling effects, convergent validity and discriminant ability of the USER-P-R were calculated. Results:Of all participants, 96.9% were living at home and 50.9% experienced no or minimal disabilities (mRS 0-1). The USER-P-R showed high internal consistency (α = 0.90) and a non-normal left-skewed distribution with a ceiling effect (21.4% maximum scores). A substantial proportion of participants with minimal disabilities (mRS 1) experienced restrictions on USER-P-R items (range 11.9-48.5%). The USER-P-R correlated strongly with the EQ-5D-5 L, PROMIS-10 and mRS. The USER-P-R showed excellent discriminant ability in more severely affected individuals with stroke, whereas its discriminant ability in less affected individuals was moderate. Conclusions:The USER-P-R shows good measurement properties and provides additional patient-reported information, proving its usefulness as an instrument to evaluate participation after 3 months in a hospital-based stroke population.

Developing the Minimum Dataset for the New Mexico Decedent Image Database

BACKGROUND

A minimum dataset (MDS) can be determined ad hoc by an investigator or small team; by a metadata expert; or by using a consensus method to take advantage of the global knowledge and expertise of a large group of experts. The first method is the most commonly applied.

OBJECTIVE

Here, we describe a use of the third approach using a modified Delphi method to determine the optimal MDS for a dataset of full body computed tomography scans. The scans are of decedents whose deaths were investigated at the New Mexico Office of the Medical Investigator and constitute the New Mexico Decedent Image Database (NMDID).

METHODS

The authors initiated the consensus process by suggesting 50 original variables to elicit expert reactions. Experts were recruited from a variety of scientific disciplines and from around the world. Three rounds of variable selection showed high rates of consensus.

RESULTS

In total, 59 variables were selected, only 52% of which the original resource authors selected. Using a snowball method, a second set of experts was recruited to validate the variables chosen in the design phase. During the validation phase, no variables were selected for deletion.

CONCLUSION

NMDID is likely to remain more "future proof" than if a single metadata expert or only the original team of investigators designed the metadata.

Feasibility of a minimal dataset for adults with acquired brain injury in Dutch healthcare practice

Objective

Data collection in the field of acquired brain injury (ABI) lacks uniformity due to the broad spectrum of available measurement instruments, leading to incomparability of data and the need for patients to ‘repeat their story’. To pursue uniform data collection, an ABI-specific minimal dataset (MDS-ABI) is currently under development. The current study aimed to assess the feasibility (performance according to protocol, user opinion, potential implementation barriers, and suggested improvements) of the MDS-ABI in clinical settings.

Methods

A mixed-methods approach was used in a range of healthcare sectors for persons with ABI. Clinicians of several relevant disciplines within these sectors were asked to administer the MDS-ABI to five patients. Subsequently, feasibility according to clinicians was assessed by means of a paper questionnaire about every administration and an online questionnaire about the feasibility in general. Feasibility according to patients was assessed with a paper questionnaire and think aloud interviews.

Results

Thirteen clinicians and 50 patients were included. In general, the MDS-ABI performed according to protocol. Both clinicians and patients were overall satisfied with the content of the MDS-ABI. The Cumulative Illness Rating Scale was regarded incomprehensible, leading to missing data. Further, clinicians indicated that the MDS-ABI would not be suitable for all ABI-patients, as some are incapable of self-report due to potential cognitive problems, communicative problems, fatigue, perceptual problems, or impaired awareness of deficits.

Conclusion

The MDS-ABI is a promising tool for obtaining core information on ABI-patients. The MDS-ABI will be adjusted according to the suggestions. For patients who are incapable of self-report, a proxy-reported version of the self-reported part was developed.