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Статті в журналах з теми "Routinely Collected Health Data"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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1

Roberts, Christine L., Carolyn A. Cameron, Jane C. Bell, Charles S. Algert, and Jonathan M. Morris. "Measuring Maternal Morbidity in Routinely Collected Health Data." Medical Care 46, no. 8 (August 2008): 786–94. http://dx.doi.org/10.1097/mlr.0b013e318178eae4.

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2

Koo, Malcolm. "Reporting of secondary data analysis using routinely collected health data." European Journal of Internal Medicine 34 (October 2016): e34. http://dx.doi.org/10.1016/j.ejim.2016.05.018.

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3

Rosella, Laura, and Vinyas Harish. "Machine Learning Applied to Routinely Collected Health Administrative Data." Healthcare Quarterly 25, no. 1 (April 27, 2022): 12–16. http://dx.doi.org/10.12927/hcq.2022.26813.

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4

Prytherch, D. R., J. S. Briggs, P. C. Weaver, P. Schmidt, and G. B. Smith. "Measuring clinical performance using routinely collected clinical data." Medical Informatics and the Internet in Medicine 30, no. 2 (January 2005): 151–56. http://dx.doi.org/10.1080/14639230500298966.

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5

Zeng, X. "Modeling the Effects of Epidemics on Routinely Collected Data." Journal of the American Medical Informatics Association 9, no. 90061 (November 1, 2002): 17S—22. http://dx.doi.org/10.1197/jamia.m1219.

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6

Fleming, D. M., N. J. Andrews, J. S. Ellis, A. Bermingham, P. Sebastianpillai, A. J. Elliot, E. Miller, and M. Zambon. "Estimating influenza vaccine effectiveness using routinely collected laboratory data." Journal of Epidemiology & Community Health 64, no. 12 (November 12, 2009): 1062–67. http://dx.doi.org/10.1136/jech.2009.093450.

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7

Glover, Gyles. "Use of routinely collected data on psychiatric in-patient care." Advances in Psychiatric Treatment 9, no. 4 (July 2003): 300–307. http://dx.doi.org/10.1192/apt.9.4.300.

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Анотація:

Since the start of the National Health Service, data have been collected on admissions to psychiatric in-patient units, first as the Mental Health Enquiry, then as part of Hospital Episode Statistics. Some details have changed but many have stayed remarkably consistent. Published literature on the wide range of research and policy work undertaken using this data source is reviewed. Early work was central to the government's deinstitutionalisation policy in the early 1960s. Subsequent studies cover a wide range of epidemiological and health services research issues. A new statistical base, the Mental Health Minimum Data Set, covering individuals receiving all types of health care is currently being set up. This will supplement (but not replace) admission statistics.

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8

van Ginneken, A. M., T. Timmers’, H. Stam, R. F. A. Weber, and F. H. Pierik. "Restructuring Routinely Collected Patient Data: ORCA Applied to Andrology." Methods of Information in Medicine 36, no. 03 (July 1997): 184–90. http://dx.doi.org/10.1055/s-0038-1636842.

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Hospital information systems do not always cover all required detail per specialty. This may lead to scattering of data over disparate systems and the paper record. The ORCA (Open Record for CAre) CPR offers a generic structure for record sharing, and record keeping tailored to specific needs. We studied whether a semantic integration of existing and new data was possible, using the ORCA structure. Existing andrology data, originating from separate sources, were utilized for this purpose. During normalization, validation and explication steps, latent problems in the source data were exposed and removed, followed by a merge with new data items. By conversion of source data to ORCA, a unique representation of medical concepts in the database was attained, facilitating retrieval of univocal data for multiple purposes. We conclude that the expansion to the andrology domain, including transparent integration of existing data, provides support for the generality of ORCA.

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9

Fry, Richard J., Sarah E. Rodgers, Jennifer Morgan, Scott Orford, and David L. Fone. "Using Routinely Collected Administrative Data in Public Health Research: Geocoding Alcohol Outlet Data." Applied Spatial Analysis and Policy 10, no. 2 (March 18, 2016): 301–15. http://dx.doi.org/10.1007/s12061-016-9184-4.

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10

Carpenter, Lucy M., Noreen E. S. Maconochie, Eve Roman, and D. R. Cox. "Examining Associations between Occupation and Health by using Routinely Collected Data." Journal of the Royal Statistical Society: Series A (Statistics in Society) 160, no. 3 (September 1997): 507–21. http://dx.doi.org/10.1111/j.1467-985x.1997.00077.x.

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11

Taylor and Prictor. "Insight or Intrusion? Correlating Routinely Collected Employee Data with Health Risk." Social Sciences 8, no. 10 (October 16, 2019): 291. http://dx.doi.org/10.3390/socsci8100291.

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The volume, variety and velocity of data available to companies about their employees is already significant and likely to increase. Employers hold data about employees that could be used to explore the relationship between workplace practice in their organisation and risks to employee health. However, there is significant uncertainty about whether employers subject to English law are permitted to use this data for this purpose, and even whether they may be under a legal obligation to do so. In this article, the question of whether employers are legally permitted or legally obliged to use employee data to identify associations between workplace practice and risk to employee health is answered through an analysis of two spheres of English Law: data protection law, and health and safety law. The authors establish a hypothetical case study concerning a company that wishes to use employee data in this way, to illuminate a set of detailed legal issues. In particular, the question of whether a reasonable and prudent employer is under an obligation under health and safety law to use the data and analytic tools at his or her disposal to assess risk and inform his or her actions is considered. Also addressed is the question of whether such processing would satisfy the data protection law principles of “lawful, fair, and transparent” processing and that of “purpose limitation”. A complex picture emerges. The analysis reveals that data protection legislation may not support a trend towards the re-use of employee data to enhance workplace health and safety; nor is there currently a clear mandate that responsible employers use data in this way. The line between useful insight into workplace practices and intrusion into employees’ privacy remains blurred.

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12

Carpenter, Lucy M., Noreen E. S. Maconochie, Eve Roman, and D. R. Cox. "Examining Associations between Occupation and Health by using Routinely Collected Data." Journal of the Royal Statistical Society: Series A (Statistics in Society) 160, no. 3 (October 1997): 507–21. http://dx.doi.org/10.1111/1467-985x.00077.

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13

Hand, D. J., and W. E. Henley. "Examining Associations between Occupation and Health by using Routinely Collected Data." Journal of the Royal Statistical Society: Series A (Statistics in Society) 160, no. 3 (October 1997): 523–41. http://dx.doi.org/10.1111/1467-985x.00078.

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14

Wilkinson, Tim, Amanda Ly, Christian Schnier, Kristiina Rannikmäe, Kathryn Bush, Carol Brayne, Terence J. Quinn, and Cathie L. M. Sudlow. "Identifying dementia cases with routinely collected health data: A systematic review." Alzheimer's & Dementia 14, no. 8 (April 2, 2018): 1038–51. http://dx.doi.org/10.1016/j.jalz.2018.02.016.

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15

Quan, Hude, and Tyler Williamson. "Guiding the reporting of studies that use routinely collected health data." Canadian Medical Association Journal 188, no. 8 (February 16, 2016): 559–60. http://dx.doi.org/10.1503/cmaj.151470.

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16

Abratt, R. P., and F. Macbeth. "Reporting of studies based on the analysis of routinely collected health data." South African Medical Journal 110, no. 12 (November 27, 2020): 1146. http://dx.doi.org/10.7196/samj.2020.v110i12.15370.

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17

Van Deynse, Helena, Wilfried Cools, Bart Depreitere, Ives Hubloue, Carl Ilunga Kazadi, Eva Kimpe, Maarten Moens, Karen Pien, Griet Van Belleghem, and Koen Putman. "Quantifying injury severity for traumatic brain injury with routinely collected health data." Injury 53, no. 1 (January 2022): 11–20. http://dx.doi.org/10.1016/j.injury.2021.10.013.

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18

Mirza, Aziza, Victoria Yorke-Edwards, Sarah Lensen, Macey L. Murray, Carlos Diaz-Montana, James Carpenter, Matthew R. Sydes, and Sharon B. Love. "Why are feasibility studies accessing routinely collected health data? A systematic review." F1000Research 10 (August 16, 2021): 815. http://dx.doi.org/10.12688/f1000research.52486.1.

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Background: Feasibility trials are often undertaken to determine whether a larger randomised controlled trial (RCT) is achievable. In a recent review, 15 feasibility trials accessed routinely collected health data (RCHD) from UK national databases and registries. This paper looks at attributes of these trials and the reasons why they accessed RCHD. Methods: We extracted data from all publicly available sources for the 15 feasibility studies found in a previous review of trials successfully accessing RCHD in the UK between 2013–2018 for the purpose of informing or supplementing participant data. We extracted trial characteristics, the registry accessed, and the way the RCHD was used. Results: The 15 feasibility RCTs were conducted in a variety of disease areas, and were generally small (median sample size 100, range 41–4061) and individually randomised (60%, 9/15). The primary trial outcome was predominantly administrative (non-clinical) (80%, 12/15) such as feasibility of patient recruitment. They were more likely to recruit from secondary care (67%, 10/15) settings than primary (33%, 5/15). NHS Digital was the most commonly accessed registry (33% (5/15)) with SAIL databank (20% (3/15)), electronic Data Research and Innovation Service (eDRIS) and Paediatric Intensive Care Audit Network (PICANET) (each 13% 2/15) also being accessed. Where the information was clear, the trials used RCHD for data collection during the trial (47%, 7/15), follow-up after the trial (27%, 4/15) and recruitment (13%, 2/15). Conclusions: Between 2013 and 2018, 15 feasibility trials successfully accessed UK RCHD. Feasibility trials would benefit, as with other trials, from guidance on reporting the use of RCHD in protocols and publications.

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19

Hemkens, Lars G., Eric I. Benchimol, Sinéad M. Langan, Matthias Briel, Benjamin Kasenda, Jean-Marie Januel, Emily Herrett, and Erik von Elm. "The reporting of studies using routinely collected health data was often insufficient." Journal of Clinical Epidemiology 79 (November 2016): 104–11. http://dx.doi.org/10.1016/j.jclinepi.2016.06.005.

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20

McKay, Andrew J., Ashley P. Jones, Carrol L. Gamble, Andrew J. Farmer, and Paula R. Williamson. "Use of routinely collected data in a UK cohort of publicly funded randomised clinical trials." F1000Research 9 (May 4, 2020): 323. http://dx.doi.org/10.12688/f1000research.23316.1.

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Routinely collected data about health in medical records, registries and hospital activity statistics is now routinely collected in an electronic form. The extent to which such sources of data are now being routinely accessed to deliver efficient clinical trials, is unclear. The aim of this study was to ascertain current practice amongst a United Kingdom (UK) cohort of recently funded and ongoing randomised controlled trials (RCTs) in relation to sources and use of routinely collected outcome data. Recently funded and ongoing RCTs were identified for inclusion by searching the National Institute for Health Research journals library. Trials that have a protocol available were assessed for inclusion and those that use or plan to use routinely collected health data for at least one outcome were included. Routinely collected data sources and outcome information were extracted. A total of 279 studies were identified with 102 eligible for data extraction. An Electronic Health Record (EHR) was the sole source of outcome data for at least one outcome in 46 trials. The most frequent sources are Hospital Episode Statistics (HES) and Office for National Statistics (ONS), with the most common outcome data to be extracted being on mortality, hospital admission, and health service resource use. Our study has found that around half of publicly funded trials in a UK cohort plan to collect outcome data from routinely collected data sources. This is much higher than the figure of 8% found in a cohort of 189 RCTs published since 2000, the majority of were carried out in North America (McCord et al., 2019).

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21

Brunson, Jason Cory, and Reinhard C. Laubenbacher. "Applications of network analysis to routinely collected health care data: a systematic review." Journal of the American Medical Informatics Association 25, no. 2 (September 13, 2017): 210–21. http://dx.doi.org/10.1093/jamia/ocx052.

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Abstract Objective To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research. Materials and Methods A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis. Results The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities. Discussion We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.

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22

McKay, Andrew J., Ashley P. Jones, Carrol L. Gamble, Andrew J. Farmer, and Paula R. Williamson. "Use of routinely collected data in a UK cohort of publicly funded randomised clinical trials." F1000Research 9 (March 12, 2021): 323. http://dx.doi.org/10.12688/f1000research.23316.3.

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Routinely collected data about health in medical records, registries and hospital activity statistics is now routinely collected in an electronic form. The extent to which such sources of data are now being routinely accessed to deliver efficient clinical trials, is unclear. The aim of this study was to ascertain current practice amongst a United Kingdom (UK) cohort of recently funded and ongoing randomised controlled trials (RCTs) in relation to sources and use of routinely collected outcome data. Recently funded and ongoing RCTs were identified for inclusion by searching the National Institute for Health Research journals library. Trials that have a protocol available were assessed for inclusion and those that use or plan to use routinely collected health data (RCHD) for at least one outcome were included. RCHD sources and outcome information were extracted. Of 216 RCTs, 102 (47%) planned to use RCHD. A RCHD source was the sole source of outcome data for at least one outcome in 46 (45%) of those 102 trials. The most frequent sources are Hospital Episode Statistics (HES) and Office for National Statistics (ONS), with the most common outcome data to be extracted being on mortality, hospital admission, and health service resource use. Our study has found that around half of publicly funded trials in a UK cohort (NIHR HTA funded trials that had a protocol available) plan to collect outcome data from routinely collected data sources.

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23

Oinasmaa, S., J. Heiskanen, J. Hartikainen, M. Hippeläinen, H. Miettinen, JA Martikainen, RP Roine, and A. Tolppanen. "Representativeness of Routinely Collected Patient-Reported Outcome Data in Coronary Revascularization Patients?" Value in Health 20, no. 9 (October 2017): A619. http://dx.doi.org/10.1016/j.jval.2017.08.1344.

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24

Morisod, Kevin, Xhyljeta Luta, Joachim Marti, Jacques Spycher, Mary Malebranche, and Patrick Bodenmann. "Measuring Health Equity in Emergency Care Using Routinely Collected Data: A Systematic Review." Health Equity 5, no. 1 (December 1, 2021): 801–17. http://dx.doi.org/10.1089/heq.2021.0035.

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25

Langan, Sinéad M., Chad Cook, and Eric I. Benchimol. "Improving the Reporting of Studies Using Routinely Collected Health Data in Physical Therapy." Journal of Orthopaedic & Sports Physical Therapy 46, no. 3 (March 2016): 126–27. http://dx.doi.org/10.2519/jospt.2016.0103.

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26

Allen, Harris. "Using Routinely Collected Data to Augment the Management of Health and Productivity Loss." Journal of Occupational and Environmental Medicine 50, no. 6 (June 2008): 615–32. http://dx.doi.org/10.1097/jom.0b013e31817b610c.

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27

Benchimol, Eric I., Liam Smeeth, Astrid Guttmann, Katie Harron, David Moher, Irene Petersen, Henrik T. Sørensen, Erik von Elm, and Sinéad M. Langan. "The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement." PLOS Medicine 12, no. 10 (October 6, 2015): e1001885. http://dx.doi.org/10.1371/journal.pmed.1001885.

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28

Raina, Parminder, Vicki Torrance-Rynard, Micheline Wong, and Christel Woodward. "Agreement between Self-reported and Routinely Collected Health-care Utilization Data among Seniors." Health Services Research 37, no. 3 (June 2002): 751–74. http://dx.doi.org/10.1111/1475-6773.00047.

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29

Dizon, M. P., A. M. Yu, R. K. Singh, J. Wan, D. J. Margolis, S. M. Langan, and K. Abuabara. "173 Systematic review of atopic dermatitis disease definitions in routinely-collected health data." Journal of Investigative Dermatology 137, no. 5 (May 2017): S29. http://dx.doi.org/10.1016/j.jid.2017.02.188.

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30

Tsang, Carmen, William Palmer, Alex Bottle, Azeem Majeed, and Paul Aylin. "A Review of Patient Safety Measures Based on Routinely Collected Hospital Data." American Journal of Medical Quality 27, no. 2 (September 6, 2011): 154–69. http://dx.doi.org/10.1177/1062860611414697.

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31

Muscatello, David, and Rebecca Mitchell. "Identifying work-related injury and disease in routinely collected NSW hospitalisation data." New South Wales Public Health Bulletin 12, no. 7 (2001): 195. http://dx.doi.org/10.1071/nb01066.

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32

Carpenter, Lucy, and Eve Roman. "Cancer and Occupation in Women: Identifying Associations Using Routinely Collected National Data." Environmental Health Perspectives 107 (May 1999): 299. http://dx.doi.org/10.2307/3434420.

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33

Straatmann, Viviane S., Anna Pearce, Steven Hope, Benjamin Barr, Margaret Whitehead, Catherine Law, and David Taylor-Robinson. "How well can poor child health and development be predicted by data collected in early childhood?" Journal of Epidemiology and Community Health 72, no. 12 (September 21, 2018): 1132–40. http://dx.doi.org/10.1136/jech-2018-211028.

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BackgroundIdentifying children at risk of poor developmental outcomes remains a challenge, but is important for better targeting children who may benefit from additional support. We explored whether data routinely collected in early life predict which children will have language disability, overweight/obesity or behavioural problems in later childhood.MethodsWe used data on 10 262 children from the UK Millennium Cohort Study (MCS) collected at 9 months, 3, and 11 years old. Outcomes assessed at age 11 years were language disability, overweight/obesity and socioemotional behavioural problems. We compared the discriminatory capacity of three models: (1) using data currently routinely collected around the time of birth; (2) Model 1 with additional data routinely collected at 3 years; (3) a statistically selected model developed using a larger set of early year’s risk factors for later child health outcomes, available in the MCS—but not all routinely collected.ResultsAt age 11, 6.7% of children had language disability, 26.9% overweight/obesity and 8.2% socioemotional behavioural problems. Model discrimination for language disability was moderate in all three models (area under the curve receiver-operator characteristic 0.71, 0.74 and 0.76, respectively). For overweight/obesity, it was poor in model 1 (0.66) and moderate for model 2 (0.73) and model 3 (0.73). Socioemotional behavioural problems were also identified with moderate discrimination in all models (0.71; 0.77; 0.79, respectively).ConclusionLanguage disability, socioemotional behavioural problems and overweight/obesity in UK children aged 11 years are common and can be predicted with moderate discrimination using data routinely collected in the first 3 years of life.

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34

McKay, Andrew J., Ashley P. Jones, Carrol L. Gamble, Andrew J. Farmer, and Paula R. Williamson. "Use of routinely collected data in a UK cohort of publicly funded randomised clinical trials." F1000Research 9 (June 1, 2020): 323. http://dx.doi.org/10.12688/f1000research.23316.2.

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Анотація:

Routinely collected data about health in medical records, registries and hospital activity statistics is now routinely collected in an electronic form. The extent to which such sources of data are now being routinely accessed to deliver efficient clinical trials, is unclear. The aim of this study was to ascertain current practice amongst a United Kingdom (UK) cohort of recently funded and ongoing randomised controlled trials (RCTs) in relation to sources and use of routinely collected outcome data. Recently funded and ongoing RCTs were identified for inclusion by searching the National Institute for Health Research journals library. Trials that have a protocol available were assessed for inclusion and those that use or plan to use routinely collected health data (RCHD) for at least one outcome were included. RCHD sources and outcome information were extracted. Of 216 RCTs, 102 (47%) planned to use RCHD. A RCHD source was the sole source of outcome data for at least one outcome in 46 (45%) of those 102 trials. The most frequent sources are Hospital Episode Statistics (HES) and Office for National Statistics (ONS), with the most common outcome data to be extracted being on mortality, hospital admission, and health service resource use. Our study has found that around half of publicly funded trials in a UK cohort (NIHR HTA funded trials that had a protocol available) plan to collect outcome data from routinely collected data sources. This is much higher than the figure of 8% found in a cohort of 189 RCTs published since 2000, the majority of which were carried out in North America (McCord et al., 2019).

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35

Kwakkenbos, Linda, Mahrukh Imran, Kimberly A. McCord, Margaret Sampson, Ole Fröbert, Chris Gale, Lars G. Hemkens, et al. "Protocol for a scoping review to support development of a CONSORT extension for randomised controlled trials using cohorts and routinely collected health data." BMJ Open 8, no. 8 (August 2018): e025266. http://dx.doi.org/10.1136/bmjopen-2018-025266.

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IntroductionRandomised controlled trials (RCTs) conducted using cohorts and routinely collected health data, including registries, electronic health records and administrative databases, are increasingly used in healthcare intervention research. The development of an extension of the CONsolidated Standards of Reporting Trials (CONSORT) statement for RCTs using cohorts and routinely collected health data is being undertaken with the goal of improving reporting quality by setting standards early in the process of uptake of these designs. To develop this extension to the CONSORT statement, a scoping review will be conducted to identify potential modifications or clarifications of existing reporting guideline items, as well as additional items needed for reporting RCTs using cohorts and routinely collected health data.Methods and analysisIn separate searches, we will seek publications on methods or reporting or that describe protocols or results from RCTs using cohorts, registries, electronic health records and administrative databases. Data sources will include Medline and the Cochrane Methodology Register. For each of the four main types of RCTs using cohorts and routinely collected health data, separately, two investigators will independently review included publications to extract potential checklist items. A potential item will either modify an existing CONSORT 2010, Strengthening the Reporting of Observational Studies in Epidemiology or REporting of studies Conducted using Observational Routinely collected health Data item or will be proposed as a new item. Additionally, we will identify examples of good reporting in RCTs using cohorts and routinely collected health data.Ethics and disseminationThe proposed scoping review will help guide the development of the CONSORT extension statement for RCTs conducted using cohorts and routinely collected health data.

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Triep, Karen, Nenad Torbica, Luigi Raio, Daniel Surbek, and Olga Endrich. "The Robson classification for caesarean section—A proposed method based on routinely collected health data." PLOS ONE 15, no. 11 (November 30, 2020): e0242736. http://dx.doi.org/10.1371/journal.pone.0242736.

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Background With an increasing rate of caesarean sections as well as rising numbers of multiple pregnancies, valid classifications for benchmarking are needed. The Robson classification provides a method to group cases with caesarean section in order to assess differences in outcome across regions and sites. In this study we set up a novel method of classification by using routinely collected health data. We hypothesize i that routinely collected health data can be used to apply complex medical classifications and ii that the Robson classification is capable of classifying mothers and their corresponding newborn into meaningful groups with regard to outcome. Methods and findings The study was conducted at the coding department and the department of obstetrics and gynecology Inselspital, University Hospital of Bern, Switzerland. The study population contained inpatient cases from 2014 until 2017. Administrative and health data were extracted from the Data Warehouse. Cases were classified by a Structured Query Language code according to the Robson criteria using data from the administrative system, the electronic health record and from the laboratory system. An automated query to classify the cases according to Robson could be implemented and successfully validated. A linkage of the mother’s class to the corresponding newborn could be established. The distribution of clinical indicators was described. It could be shown that the Robson classes are associated to outcome parameters and case related costs. Conclusions With this study it could be demonstrated, that a complex query on routinely collected health data would serve for medical classification and monitoring of quality and outcome. Risk-stratification might be conducted using this data set and should be the next step in order to evaluate the Robson criteria and outcome. This study will enhance the discussion to adopt an automated classification on routinely collected health data for quality assurance purposes.

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Fogli, J., C. Carpentieri, A. Del Guerra, M. E. Fantacci, A. Marchi, V. Marzulli, and A. Tofani. "Dental radiology dosimetric data as routinely collected in an Italian hospital." Radiation Protection Dosimetry 129, no. 1-3 (February 18, 2008): 227–30. http://dx.doi.org/10.1093/rpd/ncn078.

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Péter, I., D. Elmer, R. Pónusz, A. Sebestyén, N. Németh, L. Horváth, T. Csákvári, D. Endrei, and I. Boncz. "PSY12 ANNUAL HEALTH INSURANCE TREATMENT COST OF PSORIASIS BASED ON ROUTINELY COLLECTED FINANCING DATA." Value in Health 23 (May 2020): S372—S373. http://dx.doi.org/10.1016/j.jval.2020.04.1439.

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Elmer, D., D. Endrei, R. Pónusz, A. Sebestyén, N. Németh, L. Horváth, T. Csákvári, I. Péter, and I. Boncz. "PSY15 EPIDEMIOLOGICAL DISEASE BURDEN OF PSORIASIS BASED ON ROUTINELY COLLECTED HEALTH INSURANCE CLAIMS DATA." Value in Health 23 (May 2020): S373. http://dx.doi.org/10.1016/j.jval.2020.04.1442.

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Németh, N., D. Endrei, R. Pónusz, D. Elmer, A. Sebestyén, L. Horváth, T. Csákvári, and I. Boncz. "PIH15 ANNUAL HEALTH INSURANCE TREATMENT COST OF ENDOMETRIOSIS BASED ON ROUTINELY COLLECTED FINANCING DATA." Value in Health 23 (May 2020): S153—S154. http://dx.doi.org/10.1016/j.jval.2020.04.410.

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Németh, N., D. Endrei, R. Pónusz, D. Elmer, A. Sebestyén, L. Horváth, T. Csákvári, and I. Boncz. "PIH41 EPIDEMIOLOGICAL DISEASE BURDEN OF ENDOMETRIOSIS BASED ON ROUTINELY COLLECTED HEALTH INSURANCE CLAIMS DATA." Value in Health 23 (May 2020): S159. http://dx.doi.org/10.1016/j.jval.2020.04.436.

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Danku, N., Z. Kívés, B. Molics, T. Gazsó, P. Ács, B. Szőts, D. Endrei, L. Horváth, A. Sebestyén, and I. Boncz. "PMS50 EPIDEMIOLOGICAL DISEASE BURDEN OF SCOLIOSIS BASED ON ROUTINELY COLLECTED HEALTH INSURANCE CLAIMS DATA." Value in Health 23 (May 2020): S224. http://dx.doi.org/10.1016/j.jval.2020.04.736.

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Pónusz, R., D. Endrei, D. Elmer, N. Németh, L. Horváth, T. Csákvári, A. Sebestyén, and I. Boncz. "PRS35 ANNUAL HEALTH INSURANCE TREATMENT COST OF ASTHMA BASED ON ROUTINELY COLLECTED FINANCING DATA." Value in Health 23 (May 2020): S354—S355. http://dx.doi.org/10.1016/j.jval.2020.04.1356.

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Pónusz, R., D. Endrei, D. Elmer, N. Németh, L. Horváth, T. Csákvári, A. Sebestyén, and I. Boncz. "PRS43 EPIDEMIOLOGICAL DISEASE BURDEN OF ASTHMA BASED ON ROUTINELY COLLECTED HEALTH INSURANCE CLAIMS DATA." Value in Health 23 (May 2020): S356. http://dx.doi.org/10.1016/j.jval.2020.04.1364.

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Chen, M. Y., S. Langan, and E. I. Benchimol. "Routinely collected electronic health data and STI research: RECORD extension to the STROBE guidelines." Sexually Transmitted Infections 92, no. 1 (December 14, 2015): 2–3. http://dx.doi.org/10.1136/sextrans-2015-052360.

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Blanch, Bianca, Joanna Sweeting, Christopher Semsarian, and Jodie Ingles. "Routinely collected health data to study inherited heart disease: a systematic review (2000–2016)." Open Heart 4, no. 2 (October 2017): e000686. http://dx.doi.org/10.1136/openhrt-2017-000686.

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Dizon, M. P., A. M. Yu, R. K. Singh, J. Wan, M. M. Chren, C. Flohr, J. I. Silverberg, D. J. Margolis, S. M. Langan, and K. Abuabara. "Systematic review of atopic dermatitis disease definition in studies using routinely collected health data." British Journal of Dermatology 178, no. 6 (April 25, 2018): 1280–87. http://dx.doi.org/10.1111/bjd.16340.

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Dizon, M. P., A. M. Yu, R. K. Singh, J. Wan, M. M. Chren, C. Flohr, J. Silverberg, D. J. Margolis, S. M. Langan, and K. Abuabara. "Systematic review of atopic dermatitis disease definition in studies using routinely collected health data." British Journal of Dermatology 178, no. 6 (June 2018): e441-e441. http://dx.doi.org/10.1111/bjd.16749.

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Nie, Xiaolu, Ying Zhang, Zehao Wu, Lulu Jia, Xiaoling Wang, Sinéad M. Langan, Eric I. Benchimol, and Xiaoxia Peng. "Evaluation of reporting quality for observational studies using routinely collected health data in pharmacovigilance." Expert Opinion on Drug Safety 17, no. 7 (June 12, 2018): 661–68. http://dx.doi.org/10.1080/14740338.2018.1484106.

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Henry, David, Paulina Stehlik, Ximena Camacho, and Sallie‐Anne Pearson. "Access to routinely collected data for population health research: experiences in Canada and Australia." Australian and New Zealand Journal of Public Health 42, no. 5 (July 23, 2018): 430–33. http://dx.doi.org/10.1111/1753-6405.12813.

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