Insight: Semantic Provenance and Analysis Platform for Multi-center Neurology Healthcare Research

Provenance Data Management in Health Information Systems: A Systematic Literature Review

AIMS

This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results.

METHOD

An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied.

RESULTS

Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs.

CONCLUSION

It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs.

Self-management for adults with epilepsy: Aggregate Managing Epilepsy Well Network findings on depressive symptoms

OBJECTIVE

To assess depressive symptom outcomes in a pooled sample of epilepsy self-management randomized controlled trials (RCTs) from the Managing Epilepsy Well (MEW) Network integrated research database (MEW DB).

METHODS

Five prospective RCTs involving 453 adults with epilepsy compared self-management intervention (n = 232) versus treatment as usual or wait-list control outcomes (n = 221). Depression was assessed with the nine-item Patient Health Questionnaire. Other variables included age, gender, race, ethnicity, education, income, marital status, seizure frequency, and quality of life. Follow-up assessments were collapsed into a visit 2 and a visit 3; these were conducted postbaseline.

RESULTS

Mean age was 43.5 years (SD = 12.6), nearly two-thirds were women, and nearly one-third were African American. Baseline sample characteristics were mostly similar in the self-management intervention group versus controls. At follow-up, the self-management group had a significantly greater reduction in depression compared to controls at visit 2 (P < .0001) and visit 3 (P = .0002). Quality of life also significantly improved in the self-management group at visit 2 (P = .001) and visit 3 (P = .005).

SIGNIFICANCE

Aggregate MEW DB analysis of five RCTs found depressive symptom severity and quality of life significantly improved in individuals randomized to self-management intervention versus controls. Evidence-based epilepsy self-management programs should be made more broadly available in neurology practices.

Correlates of quality of life among individuals with epilepsy enrolled in self-management research: From the US Centers for Disease Control and Prevention Managing Epilepsy Well Network

RATIONALE

Epilepsy is a chronic neurological condition that causes substantial burden on patients and families. Quality of life may be reduced due to the stress of coping with epilepsy. For nearly a decade, the Centers for Disease Control (CDC) Prevention Research Center's Managing Epilepsy Well (MEW) Network has been conducting research on epilepsy self-management to address research and practice gaps. Studies have been conducted by independent centers across the U.S. Recently, the MEW Network sites, collaboratively, began compiling an integrated database to facilitate aggregate secondary analysis of completed and ongoing studies. In this preliminary analysis, correlates of quality of life in people with epilepsy (PWE) were analyzed from pooled baseline data from the MEW Network.

METHODS

For this analysis, data originated from 6 epilepsy studies conducted across 4 research sites and comprised 459 PWE. Descriptive comparisons assessed common data elements that included gender, age, ethnicity, race, education, employment, income, seizure frequency, quality of life, and depression. Standardized rating scales were used for quality of life (QOLIE-10) and for depression (Patient Health Questionnaire, PHQ-9).

RESULTS

While not all datasets included all common data elements, baseline descriptive analysis found a mean age of 42 (SD 13.22), 289 women (63.0%), 59 African Americans (13.7%), and 58 Hispanics (18.5%). Most, 422 (92.8%), completed at least high school, while 169 (61.7%) were unmarried, divorced/separated, or widowed. Median 30-day seizure frequency was 0.71 (range 0-308). Depression at baseline was common, with a mean PHQ-9 score of 8.32 (SD 6.04); 69 (29.0%) had depression in the mild range (PHQ-9 score 5-9) and 92 (38.7%) had depression in the moderate to severe range (PHQ-9 score >9). Lower baseline quality of life was associated with greater depressive severity (p<.001), more frequent seizures (p<.04) and lower income (p<.05).

CONCLUSIONS

The MEW Network Integrated Database offers a unique opportunity for secondary analysis of data from multiple community-based epilepsy research studies. While findings must be tempered by potential sample bias, i.e. a relative under-representation of men and relatively small sample of some racial/ethnic subgroups, results of analyses derived from this first integrated epilepsy self-management database have potential to be useful to the field. Associations between depression severity and lower QOL in PWE are consistent with previous studies derived from clinical samples. Self-management efforts that focus on mental health comorbidity and seizure control may be one way to address modifiable factors that affect quality of life in PWE.