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Overcoming Barriers to the Broader Adoption of Telehealth

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp April 9, 2020 Note: This paper was written during 2019 and early 2020 and is a summary of WEDI’s fall 2018 Barriers to the Broader Adoption of Telehealth survey and the industry’s on telehealth adoption between fall 2018 and…

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COVID-19 Resources & Information

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp Updated May 18, 2020 WEDI is providing the following links to resources related to COVID-19 (aka “coronavirus”).  We recognize that the information on COVID-19 is changing rapidly and hope these links can provide you with up-to-date information on privacy…

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Provider Adjustments (PLB) in the Electronic Remittance Advice (835)

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp March 12, 2020 The purpose of this paper is to provide guidance and information on the functionality and usage of the Provider Adjustment Segment (PLB) within the electronic remittance advice (ASC X12N 835 transaction) for specific business use cases,…

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WEDI Comments: 2020-2025 Federal Health IT Strategic Plan

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp March 9, 2020 WEDI has reviewed the Office of the National Coordinator for Health Information Technology (ONC) 2020-2025 Federal Health IT Strategic Plan (Strategic Plan) released in January 2020. Overall, we support the high-level goals and objectives identified in…

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ERA/EFT Reconciliation in Dentistry

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp February 14, 2020 In dentistry, adoption of the 835 and EFT remains markedly low in comparison to other sectors of the health care industry. This Issue Brief is intended to educate, and to assist, industry stakeholders regarding efforts to…

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Claim Reporting for Appropriate Use Criteria for Advanced Diagnostic Imaging

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp November 14, 2019 The purpose of this issue brief is to provide information regarding the Center for Medicare & Medicaid Services’ (CMS) Appropriate Use Criteria (AUC) for Advanced Diagnostic Imaging program. The program requires actions to be taken by…

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Comment Letter: NIST Privacy Framework

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp October 25, 2019 On behalf of the Workgroup for Electronic Data Interchange (WEDI), the nation’s leading nonprofit authority on the use of information technology to create efficiencies in health care information exchange. We appreciate the opportunity to respond to…

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Comment Letter: Substance Use Disorder Patient Records Proposed Rule

Knowledge Center Episode 196: Clean Data, AI, and Interoperability to Eliminate “Pajama Time”. Sandra Johnson, CliniComp October 25, 2019 The Workgroup for Electronic Data Interchange (WEDI) appreciates the opportunity to comment on (SAMHSA’s) Confidentiality of Substance Use Disorder-Patient Records Notice of Proposed Rulemaking (Proposed Rule). We applaud SAMHSA for continuing to align the SUD regulations…

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Updated Telehealth Resource Guide

Table 1 provides a list of telehealth resources that the Telehealth Workgroup identified as being useful and informative for the industry. This list is not all inclusive. The Telehealth Workgroup plans to review and update this list semiannually. Please contact the Telehealth Workgroup co-chairs to have additional resources considered for inclusion in the guide.

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Understanding the Models and Definitions of Encounters

The purpose of this white paper is to provide a baseline understanding of the models and definitions of health care encounters. Following an overview of encounters, it will explore various models and how data are exchanged between health care plans, payers, providers, and other entities, as well as define commonly used terms related to encounters. This paper will establish a foundation for future work on more detailed reviews of encounter models and identification of data needs.

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