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Mooses K, Šavrova A, Pajusalu M, Oja M, Tamm S, Haug M, Padrik L, Laanpere M, Uusküla A, Kolde R. Using electronic health records to evaluate the adherence to cervical cancer prevention guidelines: A cross-sectional study. Prev Med 2024; 183:107982. [PMID: 38701952 DOI: 10.1016/j.ypmed.2024.107982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/29/2024] [Accepted: 04/30/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE The fight against cervical cancer requires effective screening together with optimal and on-time treatment along the care continuum. We examined the impact of cervical cancer testing and treatment guidelines on testing practices, and follow-up adherence to guidelines. METHODS Data from Estonian electronic health records and healthcare provision claims for 50,702 women was used. The annual rates of PAP tests, HPV tests and colposcopies during two guideline periods (2nd version 2012-2014 vs 3rd version 2016-2019) were compared. To assess the adherence to guidelines, the subjects were classified as adherent, over- or undertested based on the timing of the appropriate follow-up test. RESULTS The number of PAP tests decreased and HPV tests increased during the 3rd guideline period (p < 0.01). During the 3rd guideline period, among 21-29-year-old women, the adherence to guidelines ranged from 38.7% (44.4…50.1) for ASC-US to 73.4% (62.6…84.3) for HSIL and among 30-59-year-old from 49.0% (45.9…52.2) for ASC-US to 65.7% (58.8…72.7) for ASCH. The highest rate of undertested women was for ASC-US (21-29y: 25.7%; 30-59y: 21.9%). The rates of over-tested women remained below 12% for all cervical pathologies observed. There were 55.2% (95% CI 49.7…60.8) of 21-24-year-olds and 57.1% (95% CI 53.6…60.6) of 25-29-year-old women who received HPV test not adherent to guidelines. CONCLUSIONS Our findings highlighted some shortcomings in guideline adherence, especially among women under 30. The insights gained from this study help to improve the quality of care and, thus, reduce cervical cancer incidence and mortality.
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Affiliation(s)
- Kerli Mooses
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia.
| | | | - Maarja Pajusalu
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia.
| | - Marek Oja
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia.
| | - Sirli Tamm
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia.
| | - Markus Haug
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia.
| | - Lee Padrik
- Tartu University Hospital Women's Clinic, L. Puusepa 8, 50406 Tartu, Estonia.
| | - Made Laanpere
- Tartu University Hospital Women's Clinic, L. Puusepa 8, 50406 Tartu, Estonia; Institute of Clinical Medicine, University of Tartu, L. Puusepa 8, 50406 Tartu, Estonia.
| | - Anneli Uusküla
- Institute of Family Medicine and Public Health, University of Tartu, Ravila 19, 50411 Tartu, Estonia.
| | - Raivo Kolde
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia.
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Haug M, Oja M, Pajusalu M, Mooses K, Reisberg S, Vilo J, Giménez AF, Falconer T, Danilović A, Maljkovic F, Dawoud D, Kolde R. Markov modeling for cost-effectiveness using federated health data network. J Am Med Inform Assoc 2024; 31:1093-1101. [PMID: 38472144 PMCID: PMC11031209 DOI: 10.1093/jamia/ocae044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/19/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
OBJECTIVE To introduce 2 R-packages that facilitate conducting health economics research on OMOP-based data networks, aiming to standardize and improve the reproducibility, transparency, and transferability of health economic models. MATERIALS AND METHODS We developed the software tools and demonstrated their utility by replicating a UK-based heart failure data analysis across 5 different international databases from Estonia, Spain, Serbia, and the United States. RESULTS We examined treatment trajectories of 47 163 patients. The overall incremental cost-effectiveness ratio (ICER) for telemonitoring relative to standard of care was 57 472 €/QALY. Country-specific ICERs were 60 312 €/QALY in Estonia, 58 096 €/QALY in Spain, 40 372 €/QALY in Serbia, and 90 893 €/QALY in the US, which surpassed the established willingness-to-pay thresholds. DISCUSSION Currently, the cost-effectiveness analysis lacks standard tools, is performed in ad-hoc manner, and relies heavily on published information that might not be specific for local circumstances. Published results often exhibit a narrow focus, central to a single site, and provide only partial decision criteria, limiting their generalizability and comprehensive utility. CONCLUSION We created 2 R-packages to pioneer cost-effectiveness analysis in OMOP CDM data networks. The first manages state definitions and database interaction, while the second focuses on Markov model learning and profile synthesis. We demonstrated their utility in a multisite heart failure study, comparing telemonitoring and standard care, finding telemonitoring not cost-effective.
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Affiliation(s)
- Markus Haug
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Marek Oja
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Maarja Pajusalu
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Kerli Mooses
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Sulev Reisberg
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Jaak Vilo
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | | | - Thomas Falconer
- Columbia University Irving Medical Center, New York, NY 10032, United States
| | | | - Filip Maljkovic
- Department of Health Information Systems, Heliant, Belgrade 11000, Serbia
| | - Dalia Dawoud
- National Institute for Health and Care Excellence, London WC1V 6NA, United Kingdom
| | - Raivo Kolde
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
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Oja M, Tamm S, Mooses K, Pajusalu M, Talvik HA, Ott A, Laht M, Malk M, Lõo M, Holm J, Haug M, Šuvalov H, Särg D, Vilo J, Laur S, Kolde R, Reisberg S. Transforming Estonian health data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model: lessons learned. JAMIA Open 2023; 6:ooad100. [PMID: 38058679 PMCID: PMC10697784 DOI: 10.1093/jamiaopen/ooad100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 11/15/2023] [Indexed: 12/08/2023] Open
Abstract
Objective To describe the reusable transformation process of electronic health records (EHR), claims, and prescriptions data into Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM), together with challenges faced and solutions implemented. Materials and Methods We used Estonian national health databases that store almost all residents' claims, prescriptions, and EHR records. To develop and demonstrate the transformation process of Estonian health data to OMOP CDM, we used a 10% random sample of the Estonian population (n = 150 824 patients) from 2012 to 2019 (MAITT dataset). For the sample, complete information from all 3 databases was converted to OMOP CDM version 5.3. The validation was performed using open-source tools. Results In total, we transformed over 100 million entries to standard concepts using standard OMOP vocabularies with the average mapping rate 95%. For conditions, observations, drugs, and measurements, the mapping rate was over 90%. In most cases, SNOMED Clinical Terms were used as the target vocabulary. Discussion During the transformation process, we encountered several challenges, which are described in detail with concrete examples and solutions. Conclusion For a representative 10% random sample, we successfully transferred complete records from 3 national health databases to OMOP CDM and created a reusable transformation process. Our work helps future researchers to transform linked databases into OMOP CDM more efficiently, ultimately leading to better real-world evidence.
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Affiliation(s)
- Marek Oja
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Sirli Tamm
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Kerli Mooses
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Maarja Pajusalu
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Harry-Anton Talvik
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
- STACC, 51009 Tartu, Estonia
| | - Anne Ott
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Marianna Laht
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Maria Malk
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Marcus Lõo
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Johannes Holm
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Markus Haug
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Hendrik Šuvalov
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Dage Särg
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
- STACC, 51009 Tartu, Estonia
| | - Jaak Vilo
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
- STACC, 51009 Tartu, Estonia
| | - Sven Laur
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Raivo Kolde
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
| | - Sulev Reisberg
- Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia
- STACC, 51009 Tartu, Estonia
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Haug M, Kolde R, Oja M, Pajusalu M. Modeling Patient Treatment Trajectories Using Markov Chains for Cost Analysis. Stud Health Technol Inform 2023; 302:755-756. [PMID: 37203488 DOI: 10.3233/shti230258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Electronically stored medical records offer a rich source of data for investigating treatment trajectories and identifying best practices in healthcare. These trajectories, which consist of medical interventions, give us a foundation to evaluate the economics of treatment patterns and model the treatment paths. The aim of this work is to introduce a technical solution for the aforementioned tasks. The developed tools use the open source Observational Health Data Sciences and Informatics Observational Medical Outcomes Partnership Common Data Model to construct treatment trajectories and implement these to compose Markov models for composing financial analysis between standard of care and alternatives.
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Affiliation(s)
- Markus Haug
- Institute of Computer Science, University of Tartu, Estonia
| | - Raivo Kolde
- Institute of Computer Science, University of Tartu, Estonia
| | - Marek Oja
- Institute of Computer Science, University of Tartu, Estonia
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Pajusalu M, Ilbis E, Ilves T, Veske M, Kalde J, Lillmaa H, Rantsus R, Pelakauskas M, Leitu A, Voormansik K, Allik V, Lätt S, Envall J, Noorma M. Design and pre-flight testing of the electrical power system for the ESTCube-1 nanosatellite. Proc Estonian Acad Sci 2014. [DOI: 10.3176/proc.2014.2s.04] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Envall J, Janhunen P, Toivanen P, Pajusalu M, Ilbis E, Kalde J, Averin M, Kuuste H, Laizans K, Allik V, Rauhala T, Seppänen H, Kiprich S, Ukkonen J, Haeggström E, Kalvas T, Tarvainen O, Kauppinen J, Nuottajärvi A, Koivisto H. E-sail test payload of the ESTCube-1 nanosatellite. Proc Estonian Acad Sci 2014. [DOI: 10.3176/proc.2014.2s.02] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Lätt S, Slavinskis A, Ilbis E, Kvell U, Voormansik K, Kulu E, Pajusalu M, Kuuste H, Sünter I, Eenmäe T, Laizans K, Zalite K, Vendt R, Piepenbrock J, Ansko I, Leitu A, Vahter A, Agu A, Eilonen E, Soolo E, Ehrpais H, Lillmaa H, Mahhonin I, Mõttus J, Viru J, Kalde J, Šubitidze J, Mucenieks J, Šate J, Kütt J, Poļevskis J, Laks J, Kivistik K, Kusmin KL, Kruus KG, Tarbe K, Tuude K, Kalniņa K, Joost L, Lõoke M, Järve M, Vellak M, Neerot M, Valgur M, Pelakauskas M, Averin M, Mikkor M, Veske M, Scheler O, Liias P, Laes P, Rantsus R, Soosaar R, Reinumägi R, Valner R, Kurvits S, Mändmaa SE, Ilves T, Peet T, Ani T, Tilk T, Tamm TC, Scheffler T, Vahter T, Uiboupin T, Evard V, Sisask A, Kimmel L, Krömer O, Rosta R, Janhunen P, Envall J, Toivanen P, Rauhala T, Seppänen H, Ukkonen J, Haeggström E, Kurppa R, Kalvas T, Tarvainen O, Kauppinen J, Nuottajärvi A, Koivisto H, Kiprich S, Obraztsov A, Allik V, Reinart A, Noorma M. ESTCube-1 nanosatellite for electric solar wind sail in-orbit technology demonstration. Proc Estonian Acad Sci 2014. [DOI: 10.3176/proc.2014.2s.01] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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