Engineering Requirements of a Herpes Simplex Virus Patient Registry: Discovery Phase of a Real-World Evidence Platform to Advance Pharmacogenomics and Personalized Medicine

Surodina, Svitlana; Lam, C. S.; Cock, Caroline de; Velthoven, M Van; Milne‐Ives, Madison; Meinert, Edward

doi:10.3390/biomedicines7040100

Cited by 9 publications

(19 citation statements)

References 22 publications

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“…Since physicians and specialists are busy, enforcing them to enter data is very challenging [ 29 ]. Therefore, to facilitate this task, it is recommended that the interoperability between the registry software and other information systems such as electronic health record systems (EHRs) [ 67 , 68 ] should be considered to import all types of data from these systems to the registry software. Furthermore, issuing data quality certificates can motivate physicians to participate in a registry system to be increased [ 65 ].…”

Section: Discussionmentioning

confidence: 99%

Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation

Lazem

Sheikhtaheri

Hooman

2021

Orphanet J Rare Dis

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Background Hemolytic uremic syndrome (HUS) is a rare condition which diagnosed with the triad of thrombocytopenia, microangiopathic hemolytic anemia, and acute renal injury. There is a high requirement for research to discover treatments. HUS registries can be used as an important information infrastructure. In this study, we identified and compared the different features of HUS registries to present a guide for the development and implementation of HUS registries. Results The purposes of registries were classified as clinical (9 registries), research (7 registries), and epidemiological (5 registries), and only 3 registries pursued all three types of purposes. The data set included demographic data, medical and family history, para-clinical and diagnostic measures, treatment and pharmacological data, complications, and outcomes. The assessment strategies of data quality included monthly evaluation and data audit, the participation of physicians to collect data, editing and correcting data errors, increasing the rate of data completion, following guidelines and data quality training, using specific data quality indicators, and real-time evaluation of data at the time of data entry. 8 registries include atypical HUS patients, and 7 registries include all patients regardless of age. Only two registries focused on children. 4 registries apply prospective and 4 applied both prospective, and retrospective data collection. Finally, specialized hospitals were the main data source for these registries. Conclusion Based on the findings, we suggested a learning framework for developing and implementing an HUS registry. This framework includes lessons learned and suggestions for HUS registry purposes, minimum data set, data quality assurance, data collection methods, inclusion and exclusion criteria as well as data sources. This framework can help researchers develop HUS registries.

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Section: Discussionmentioning

confidence: 99%

Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation

Lazem

Sheikhtaheri

Hooman

2021

Orphanet J Rare Dis

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“…The ultimate aim is to increase the quality and quantity of data collected and improve the probability of users disclosing their personally identifiable information and volunteering for clinical trials. The system was prototyped on the publicly available data of a small population of US citizens published in the NHANES database [10]. The next step is to integrate it into an independent backend module and connect it with the question-outputting and answer-collecting front-end to further improve the model and test its self-improvement capabilities on real world data.…”

Section: Discussionmentioning

confidence: 99%

“…A previous analysis of the challenges medical registries are facing, and user/patient and researcher use cases, identified several problems [10]:…”

Section: Challenges Of Patient Registriesmentioning

confidence: 99%

Requirements Engineering of a Herpes Simplex Virus Patient Registry: Alpha Phase

Surodina¹,

Lam²,

Grbich³

et al. 2020

Preprint

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Abstract Background Collecting data from people with herpes simplex virus is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity. This project aimed to improve data collection for a real-world HSV registry by identifying predictors of HSV infection and selecting a limited number of relevant questions to ask new registry users in order to determine the HSV infection risk group. Methods. The US National Health and Nutrition Examination Survey (NHANES, 2015-16) database has confirmed HSV1 and HSV2 status of American participants (14-49 years) as well as a wealth of demographic and health-related data. Two datasets – for HSV1 and HSV2 – were formed using this database, and an anonymous lifestyle-data based questionnaire with a Random Forest algorithm was devised using Python. The algorithm was optimised to reduce the number of questions and to identify risk groups for HSV. Data was split into subsets to train and test the model. Results The model selected a reduced number of questions from the NHANES questionnaire that predicted HSV infection risk with high accuracy scores of 0.91 and 0.96 and high recall scores of 0.88 and 0.98 for HSV1 and HSV2 datasets, respectively. The number of questions was reduced from 150 to an average of 40, depending on age and gender, that together provides high predictability of the infection Conclusions This machine-learning algorithm for risk identification of people infected with HSV can be used in a real-world evidence registry to collect relevant lifestyle data. A current limitation is the absence of real user data and integration with electronic medical records that would enable model learning and improvement. Future work will explore model adjustments, anonymisation options, explicit permissions and standardised data schema that meet GDPR, HIPAA and third-party interface connectivity requirements.

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“…There are some literature and frameworks regarding barriers and facilitators for disease registries. Based on a review of this literature and frameworks [ 9 , 14 , 15 , 18 , 23 – 25 ], we developed a semi-structured interview guide (Additional file 1 ) with 8 main questions. According to the interview guide, we asked questions about experts’ experiences with DRSs, the barriers and problems they have encountered in the implementation, setting up, running, continuity, and sustainability of DRSs, and subsequently the proposed solutions and facilitators.…”

Section: Methodsmentioning

confidence: 99%

“…The DRSs face various barriers and facilitators [ 8 – 11 ]. The lack of interoperability of registries with other systems [ 12 – 14 ], insufficient financial resources, the lack of staff, and poor data quality [ 15 ] are among the barriers. On the other hand, providing resources and adequate training [ 16 ], user-friendly software [ 10 ], observing patients’ confidentiality, improving data quality [ 15 ], and using specific guidelines [ 17 – 19 ] can be considered facilitators.…”

Section: Introductionmentioning

confidence: 99%

Barriers and facilitators for disease registry systems: a mixed-method study

Lazem

Sheikhtaheri

2022

BMC Med Inform Decis Mak

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Background A Disease Registry System (DRS) is a system that collects standard data on a specific disease with an organized method for specific purposes in a population. Barriers and facilitators for DRSs are different according to the health system of each country, and identifying these factors is necessary to improve DRSs, so the purpose of this study was to identify and prioritize these factors. Methods First, by conducting 13 interviews with DRS specialists, barriers and facilitators for DRSs were identified and then, a questionnaire was developed to prioritize these factors. Then, 15 experts answered the questionnaires. We prioritized these factors based on the mean of scores in four levels including first priority (3.76–5), second priority (2.51–3.75), third priority (1.26–2.50), and the fourth priority (1–1.25). Results At first, 139 unique codes (63 barriers and 76 facilitators) were extracted from the interviews. We classified barriers into 9 themes, including management problems (24 codes), data collection-related problems (8 codes), poor cooperation/coordination (7 codes), technological problems and lack of motivation/interest (6 codes for each), threats to ethics/data security/confidentiality (5 codes), data quality-related problems (3 codes), limited patients’ participation and lack of or non-use of standards (2 codes for each). We also classified facilitators into 9 themes including management facilitators (36 codes), improving data quality (8 codes), proper data collection and observing ethics/data security/confidentiality (7 codes for each), appropriate technology (6 codes), increasing patients’ participation, increasing motivation/interest, improving cooperation/coordination, and the use of standards (3 codes for each). The first three ranked barriers based on mean scores included poor stakeholder cooperation/coordination (4.30), lack of standards (4.26), and data quality-related problems (4.06). The first three ranked facilitators included improving data quality (4.54), increasing motivation/interest (4.48), and observing ethics/data security/confidentiality (4.36). Conclusion Stakeholders’ coordination, proper data management, standardization and observing ethics, security/confidentiality are the most important areas for planning and investment that managers must consider for the continuation and success of DRSs.

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Engineering Requirements of a Herpes Simplex Virus Patient Registry: Discovery Phase of a Real-World Evidence Platform to Advance Pharmacogenomics and Personalized Medicine

Cited by 9 publications

References 22 publications

Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation

Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation

Requirements Engineering of a Herpes Simplex Virus Patient Registry: Alpha Phase

Barriers and facilitators for disease registry systems: a mixed-method study

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