Modeling healthcare authorization and claim submissions using the openEHR dual-model approach

<p>Abstract</p> <p>Background</p> <p>The TISS standard is a set of mandatory forms and electronic messages for healthcare authorization and claim submissions among healthcare plans and providers in Brazil. It is not based on formal models as the new generation of health informatics standards suggests. The objective of this paper is to model the TISS in terms of the openEHR archetype-based approach and integrate it into a patient-centered EHR architecture.</p> <p>Methods</p> <p>Three approaches were adopted to model TISS. In the first approach, a set of archetypes was designed using ENTRY subclasses. In the second one, a set of archetypes was designed using exclusively ADMIN_ENTRY and CLUSTERs as their root classes. In the third approach, the openEHR ADMIN_ENTRY is extended with classes designed for authorization and claim submissions, and an ISM_TRANSITION attribute is added to the COMPOSITION class. Another set of archetypes was designed based on this model. For all three approaches, templates were designed to represent the TISS forms.</p> <p>Results</p> <p>The archetypes based on the openEHR RM (Reference Model) can represent all TISS data structures. The extended model adds subclasses and an attribute to the COMPOSITION class to represent information on authorization and claim submissions. The archetypes based on all three approaches have similar structures, although rooted in different classes. The extended openEHR RM model is more semantically aligned with the concepts involved in a claim submission, but may disrupt interoperability with other systems and the current tools must be adapted to deal with it.</p> <p>Conclusions</p> <p>Modeling the TISS standard by means of the openEHR approach makes it aligned with ISO recommendations and provides a solid foundation on which the TISS can evolve. Although there are few administrative archetypes available, the openEHR RM is expressive enough to represent the TISS standard. This paper focuses on the TISS but its results may be extended to other billing processes. A complete communication architecture to simulate the exchange of TISS data between systems according to the openEHR approach still needs to be designed and implemented.</p

Analisis Kinerja Dokter Verifikator Internal dalam Menurunkan Angka Klaim Pending di RSUD Koja Tahun 2018

ABSTRAK Dokter verifikator internal memiliki tugas yang penting didalam menurunkan angka klaim pending terutama untuk mengontrol kesesuaian koding dengan diagnosa pada resume medis. Penelitian ini membahas tentang kinerja dokter verifikator internal didalam menurunkan angka klaim pending di RSUD Koja pada tahun 2018 dengan melakukan telaah berkas klaim dan observasi pada data klaim dari tahun 2017 hingga tahun 2019. Penelitian ini menggunakan desain studi evaluasi intervensi dengan menganalisa data kuantitatif dan kualitatif. Metode yang digunakan adalah dengan membandingkan data kesalahan koding pada klaim pending rawat inap Pra Intervensi dan Pasca Intervensi dokter verifikator internal baik secara jumlah klaim maupun nominal klaim. Kemudian melakukan wawancara mendalam untuk mengetahui penyebab terjadinya kesalahan koding hingga menyebabkan klaim pending. Hasil penelitian ini adalah bahwa terbukti dokter verifikator internal dapat menurunkan angka klaim pending rawat inap karena kesalahan koding dan didapatkan penyebab terjadinya kesalahan koding yaitu ketidaklengkapan resume medis, kurang telitinya koder, kurangnya pengetahuan koder, ketidakseragaman informasi terkait koding dan overload berkas klaim yang tidak diiringi dengan kesesuaian jumlah koder. Hal tersebut dapat diminimalisir dengan penggunaan rekam medis elektronik, pelatihan tenaga koder, team building dan penambahan tenaga koder.  ABSTRACT The doctor's internal verifier has an important task in reducing the number of pending claims especially for controlling the suitability of coding with diagnoses on medical resumes. This research explain that the performance of internal verifier doctors in reducing the number of pending claims in Koja Hospital in 2018 by reviewing claims files and observations on claim data from 2017 to 2019. This study uses an intervention evaluation study design by analyzing quantitative and qualitative data. The method used is to compare data coding errors on pending hospitalization claims Pre-intervention and Post-Intervention doctor internal verifiers both in number of claims and nominal claims. Then conduct in-depth interviews to find out the cause of coding errors to cause pending claims. The results of this study are that the proven internal verifier can reduce the number of pending hospitalization claims due to coding errors and obtained the causes of coding errors, namely incomplete medical resumes, lack of coder accuracy, lack of coder knowledge, lack of uniformity of information related to claim file coding and overload not accompanied by suitability of the number of coders. This can be minimized by the use of electronic medical records, training of coder personnel, team building and the addition of coder personnel

Using the dual-level modeling approach to develop applications for pervasive healthcare

Health information technology is the area of IT involving the design, development, creation, use and maintenance of information systems for the healthcare industry. Automated and interoperable healthcare information systems are expected to lower costs, improve efficiency and reduce error, while also providing better consumer care and service. Pervasive Healthcare focuses on the use of new technologies, tools, and services, to help patients play a more active role in the treatment of their conditions. Pervasive Healthcare environments demand a huge amount of information exchange, and specific technologies have been proposed to provide interoperability between the systems that comprise such environments. However, the complexity of these technologies makes it difficult to fully adopt them and to migrate Centered Healthcare Environments to Pervasive Healthcare Environments. Therefore, this paper proposes an approach to develop applications in the Pervasive Healthcare environment, through the use of dual-level modeling based on Archetypes. This approach was demonstrated and evaluated in a controlled experiment that we conducted in the cardiology department of a hospital located in the city of Marilia (São Paulo, Brazil). An application was developed to evaluate this approach, and the results showed that the approach is suitable for facilitating the development of healthcare systems by offering generic and powerful capabilities

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of the American Medical Informatics Association following peer review. The version of record is available online at: http://dx.doi.org/10.1093/jamia/ocv008[EN] [Objective] This systematic review aims to identify and compare the existing processes and methodologies that have been published in the literature for defining clinical information models (CIMs) that support the semantic interoperability of electronic health record (EHR) systems. [Material and Methods] Following the preferred reporting items for systematic reviews and meta-analyses systematic review methodology, the authors reviewed published papers between 2000 and 2013 that covered that semantic interoperability of EHRs, found by searching the PubMed, IEEE Xplore, and ScienceDirect databases. Additionally, after selection of a final group of articles, an inductive content analysis was done to summarize the steps and methodologies followed in order to build CIMs described in those articles. [Results] Three hundred and seventy-eight articles were screened and thirty six were selected for full review. The articles selected for full review were analyzed to extract relevant information for the analysis and characterized according to the steps the authors had followed for clinical information modeling. [Discussion] Most of the reviewed papers lack a detailed description of the modeling methodologies used to create CIMs. A representative example is the lack of description related to the definition of terminology bindings and the publication of the generated models. However, this systematic review confirms that most clinical information modeling activities follow very similar steps for the definition of CIMs. Having a robust and shared methodology could improve their correctness, reliability, and quality. [Conclusion] Independently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler.This research has been partially funded by the Instituto de Salud Carlos III (Platform for Innovation in Medical Technologies and Health), grant PT13/0006/0036 and the Spanish Ministry of Economy and Competitiveness, grants TIN2010-21388-C02-01 and PTQ-12-05620.Moreno-Conde, A.; Moner Cano, D.; Da Cruz, WD.; Santos, MR.; Maldonado Segura, JA.; Robles Viejo, M.; Kalra, D. (2015). Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis. Journal of the American Medical Informatics Association. 22(4):925-934. https://doi.org/10.1093/jamia/ocv008S925934224Goossen W Goossen-Baremans A van der Zel M . Detailed clinical models: a review. Healthc Inform Res. 2010;16:201.Beeler, G. W. (1998). HL7 Version 3—An object-oriented methodology for collaborative standards development1Presented at the International Medical Informatics Association Working Group 16 Conference on Standardisation in Medical Informatics—Towards International Consensus and Cooperation, Bermuda, 12 September, 1997.1. International Journal of Medical Informatics, 48(1-3), 151-161. doi:10.1016/s1386-5056(97)00121-4Dolin, R. H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F. M., Biron, P. V., & Shabo (Shvo), A. (2006). HL7 Clinical Document Architecture, Release 2. Journal of the American Medical Informatics Association, 13(1), 30-39. doi:10.1197/jamia.m1888Fast Health Interoperability Resources (FHIR). http://www.hl7.org/fhir/. Accessed July 18, 2014.Beale T . Archetypes: constraint-based domain models for futureproof information systems. OOPSLA 2002 Workshop Behav Semant. 2002.ISO 13606:2008 - Health informatics - Electronic health record communication. 2008. www.iso.org/iso/catalogue_detail.htm?csnumber=40784.OpenEHR. http://www.openehr.org/. Accessed July 18, 2014.Clinical Information Modeling Initiative (CIMI). http://www.opencimi.org/. Accessed July 18, 2014.Goossen WT . Using detailed clinical models to bridge the gap between clinicians and HIT. Stud Health Technol Inf. 2008;141:3–10.Oniki TA Coyle JF Parker CG . Lessons learned in detailed clinical modeling at Intermountain Healthcare. J Am Med Inform Assoc. 2014. Advance access published; doi:10.1136/amiajnl-2014-002875.Jacobson I Booch G Rumbaugh J . The Unified Software Development Process. Massachusetts, USA: Addison-Wesley Reading; 1999.Ahn, S., Huff, S. M., Kim, Y., & Kalra, D. (2013). Quality metrics for detailed clinical models. International Journal of Medical Informatics, 82(5), 408-417. doi:10.1016/j.ijmedinf.2012.09.006Kalra D . Editorial principles for the development of standards for the structure and content of health records. 2012. https://www.rcplondon.ac.uk/sites/default/files/documents/editorial-principles-for-the-development-of-record-standards.pdf. Accessed July 16, 2014.Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ, 339(jul21 1), b2535-b2535. doi:10.1136/bmj.b2535Transparent reporting of systematic reviews and meta-analyses (PRISMA). http://www.prisma-statement.org/. Accessed July 18, 2014.US National Library of Medicine. http://www.pubmed.gov. Accessed July 18, 2014.IEEE Xplore Digital Library. http://ieeexplore.ieee.org/. Accessed July 18, 2014.ScienceDirect. http://www.sciencedirect.com/. Accessed July 18, 2014.Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107-115. doi:10.1111/j.1365-2648.2007.04569.xRinner C Kohler M Hübner-Bloder G . Creating ISO/EN 13606 archetypes based on clinical information needs. In: Proceedings of EFMI Special Topic Conference, 14–15 April 2011, Lǎsko, Slovenia e-Health Across Borders Without Boundaries. 2011:14–15.Muñoz Carrero A Romero Gutiérrez A Marco Cuenca G . Manual práctico de interoperabilidad semántica para entornos sanitarios basada en arquetipos. Unidad de investigación en Telemedicina y e-Salud. Instituto de Salud Carlos III - Ministerio de Economía y Competitividad. 2013.Kalra D . Editorial principles for the development of standards for the structure and content of health records. 2012. https://www.rcplondon.ac.uk/sites/default/files/documents/editorial-principles-for-the-development-of-record-standards.pdf . Accessed July 18, 2015.Yuksel, M., & Dogac, A. (2011). Interoperability of Medical Device Information and the Clinical Applications: An HL7 RMIM based on the ISO/IEEE 11073 DIM. IEEE Transactions on Information Technology in Biomedicine, 15(4), 557-566. doi:10.1109/titb.2011.2151868Nagy M Hanzlicek P Precková P . Semantic interoperability in Czech healthcare environment supported by HL7 version 3. Methods Inf Med. 2010;49:186.LOPEZ, D., & BLOBEL, B. (2009). A development framework for semantically interoperable health information systems. International Journal of Medical Informatics, 78(2), 83-103. doi:10.1016/j.ijmedinf.2008.05.009Lopez DM Blobel B . Enhanced semantic interoperability by profiling health informatics standards. Methods Inf Med. 2009;48:170–177.Lopez DM Blobel B . Enhanced semantic interpretability by healthcare standards profiling. Stud Health Technol Inform. 2008;136:735.Knaup, P., Garde, S., & Haux, R. (2007). Systematic planning of patient records for cooperative care and multicenter research. International Journal of Medical Informatics, 76(2-3), 109-117. doi:10.1016/j.ijmedinf.2006.08.002Goossen, W. T. F., Ozbolt, J. G., Coenen, A., Park, H.-A., Mead, C., Ehnfors, M., & Marin, H. F. (2004). Development of a Provisional Domain Model for the Nursing Process for Use within the Health Level 7 Reference Information Model. Journal of the American Medical Informatics Association, 11(3), 186-194. doi:10.1197/jamia.m1085Anderson, H. V., Weintraub, W. S., Radford, M. J., Kremers, M. S., Roe, M. T., Shaw, R. E., … Tcheng, J. E. (2013). Standardized Cardiovascular Data for Clinical Research, Registries, and Patient Care. Journal of the American College of Cardiology, 61(18), 1835-1846. doi:10.1016/j.jacc.2012.12.047Jian, W.-S., Hsu, C.-Y., Hao, T.-H., Wen, H.-C., Hsu, M.-H., Lee, Y.-L., … Chang, P. (2007). Building a portable data and information interoperability infrastructure—framework for a standard Taiwan Electronic Medical Record Template. Computer Methods and Programs in Biomedicine, 88(2), 102-111. doi:10.1016/j.cmpb.2007.07.014Spigolon, D. N., & Moro, C. M. C. (2012). Arquétipos do conjunto de dados essenciais de enfermagem para atendimento de portadoras de endometriose. Revista Gaúcha de Enfermagem, 33(4), 22-32. doi:10.1590/s1983-14472012000400003Späth, M. B., & Grimson, J. (2011). Applying the archetype approach to the database of a biobank information management system. International Journal of Medical Informatics, 80(3), 205-226. doi:10.1016/j.ijmedinf.2010.11.002Smith, K., & Kalra, D. (2008). Electronic health records in complementary and alternative medicine. International Journal of Medical Informatics, 77(9), 576-588. doi:10.1016/j.ijmedinf.2007.11.005Bax, M. P., Kalra, D., & Santos, M. R. (2012). Dealing with the Archetypes Development Process for a Regional EHR System. Applied Clinical Informatics, 03(03), 258-275. doi:10.4338/aci-2011-12-ra-0074Moner D Moreno A Maldonado JA . Using archetypes for defining CDA templates. Stud Health Technol Inform. 2012;180:53–57.Moner D Maldonado JA Boscá D . CEN EN13606 normalisation framework implementation experiences. In: Seamless Care, Safe Care: The Challenges of Interoperability and Patient Safety in Health Care: Proceedings of the EFMI Special Topic Conference, June 2–4, 2010; Reykjavik, Iceland. IOS Press; 2010: 136.Marcos, M., Maldonado, J. A., Martínez-Salvador, B., Boscá, D., & Robles, M. (2013). Interoperability of clinical decision-support systems and electronic health records using archetypes: A case study in clinical trial eligibility. Journal of Biomedical Informatics, 46(4), 676-689. doi:10.1016/j.jbi.2013.05.004Leslie H . International developments in openEHR archetypes and templates. Health Inf Manag J. 2008;37:38.Kohl CD Garde S Knaup P . Facilitating secondary use of medical data by using openEHR archetypes. Stud Health Technol Inform. 2009;160:1117–1121.Garde, S., Hovenga, E., Buck, J., & Knaup, P. (2007). Expressing clinical data sets with openEHR archetypes: A solid basis for ubiquitous computing. International Journal of Medical Informatics, 76, S334-S341. doi:10.1016/j.ijmedinf.2007.02.004Garcia D Moro CM Cicogna PE . Method to integrate clinical guidelines into the electronic health record (EHR) by applying the archetypes approach. Stud Health Technol Inform. 2012;192:871–875.Duftschmid, G., Rinner, C., Kohler, M., Huebner-Bloder, G., Saboor, S., & Ammenwerth, E. (2013). The EHR-ARCHE project: Satisfying clinical information needs in a Shared Electronic Health Record System based on IHE XDS and Archetypes. International Journal of Medical Informatics, 82(12), 1195-1207. doi:10.1016/j.ijmedinf.2013.08.002Dias, R. D., Cook, T. W., & Freire, S. M. (2011). Modeling healthcare authorization and claim submissions using the openEHR dual-model approach. BMC Medical Informatics and Decision Making, 11(1). doi:10.1186/1472-6947-11-60Buck, J., Garde, S., Kohl, C. D., & Knaup-Gregori, P. (2009). Towards a comprehensive electronic patient record to support an innovative individual care concept for premature infants using the openEHR approach. International Journal of Medical Informatics, 78(8), 521-531. doi:10.1016/j.ijmedinf.2009.03.001Puentes, J., Roux, M., Montagner, J., & Lecornu, L. (2012). Development framework for a patient-centered record. Computer Methods and Programs in Biomedicine, 108(3), 1036-1051. doi:10.1016/j.cmpb.2012.06.007Liu, D., Wang, X., Pan, F., Yang, P., Xu, Y., Tang, X., … Rao, K. (2010). Harmonization of health data at national level: A pilot study in China. International Journal of Medical Informatics, 79(6), 450-458. doi:10.1016/j.ijmedinf.2010.03.002Liu, D., Wang, X., Pan, F., Xu, Y., Yang, P., & Rao, K. (2008). Web-based infectious disease reporting using XML forms. International Journal of Medical Informatics, 77(9), 630-640. doi:10.1016/j.ijmedinf.2007.10.011Kim, Y., & Park, H.-A. (2011). Development and Validation of Detailed Clinical Models for Nursing Problems in Perinatal care. Applied Clinical Informatics, 02(02), 225-239. doi:10.4338/aci-2011-01-ra-0007Khan, W. A., Hussain, M., Afzal, M., Amin, M. B., Saleem, M. A., & Lee, S. (2013). Personalized-Detailed Clinical Model for Data Interoperability Among Clinical Standards. Telemedicine and e-Health, 19(8), 632-642. doi:10.1089/tmj.2012.0189Jing, X., Kay, S., Marley, T., Hardiker, N. R., & Cimino, J. J. (2012). Incorporating personalized gene sequence variants, molecular genetics knowledge, and health knowledge into an EHR prototype based on the Continuity of Care Record standard. Journal of Biomedical Informatics, 45(1), 82-92. doi:10.1016/j.jbi.2011.09.001Hsu, W., Taira, R. K., El-Saden, S., Kangarloo, H., & Bui, A. A. T. (2012). Context-Based Electronic Health Record: Toward Patient Specific Healthcare. IEEE Transactions on Information Technology in Biomedicine, 16(2), 228-234. doi:10.1109/titb.2012.2186149Hoy D Hardiker NR McNicoll IT . Collaborative development of clinical templates as a national resource. Int J Med Inf. 2009;78:S3–S8.Buyl, R., & Nyssen, M. (2009). Structured electronic physiotherapy records. International Journal of Medical Informatics, 78(7), 473-481. doi:10.1016/j.ijmedinf.2009.02.007D’Amore JD Mandel JC Kreda DA . Are Meaningful Use Stage 2 certified EHRs ready for interoperability? Findings from the SMART C-CDA Collaborative. J Am Med Inform Assoc. 2014. Advance access published; doi:10.1136/amiajnl-2014-002883.Kalra D Tapuria A Austin T . Quality requirements for EHR archetypes. In: MIE; 2012: 48–52.Garde S Hovenga EJ Gränz J . Managing archetypes for sustainable and semantically interoperable electronic health records. Electron J Health Inform. 2007;2:e9.Madsen M Leslie H Hovenga EJS . Sustainable clinical knowledge management: an archetype development life cycle. Stud Health Technol Inform. 2010;151:115–132.Kohl CD Garde S Knaup P . Facilitating the openEHR approach-organizational structures for defining high-quality archetypes. Stud Health Technol Inform. 2008;136:437.Stroetmann VN Kalra D Lewalle P . Semantic interoperability for better health and safer healthcare. European Commission, Directorate-General Information Society and Media; 2009. http://dx.doi.org/10.2759/38514

Validating archetypes for the Multiple Sclerosis Functional Composite

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time- consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool- enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model

Quality framework for semantic interoperability in health informatics: definition and implementation

Aligned with the increased adoption of Electronic Health Record (EHR) systems, it is recognized that semantic interoperability provides benefits for promoting patient safety and continuity of care. This thesis proposes a framework of quality metrics and recommendations for developing semantic interoperability resources specially focused on clinical information models, which are defined as formal specifications of structure and semantics for representing EHR information for a specific domain or use case. This research started with an exploratory stage that performed a systematic literature review with an international survey about the clinical information modelling best practice and barriers. The results obtained were used to define a set of quality models that were validated through Delphi study methodologies and end user survey, and also compared with related quality standards in those areas that standardization bodies had a related work programme. According to the obtained research results, the defined framework is based in the following models: Development process quality model: evaluates the alignment with the best practice in clinical information modelling and defines metrics for evaluating the tools applied as part of this process. Product quality model: evaluates the semantic interoperability capabilities of clinical information models based on the defined meta-data, data elements and terminology bindings. Quality in use model: evaluates the suitability of adopting semantic interoperability resources by end users in their local projects and organisations. Finally, the quality in use model was implemented within the European Interoperability Asset register developed by the EXPAND project with the aim of applying this quality model in a broader scope to contain any relevant material for guiding the definition, development and implementation of interoperable eHealth systems in our continent. Several European projects already expressed interest in using the register, which will now be sustained by the European Institute for Innovation through Health Data