For this assignment, you will create a written plan and a PowerPoint presentation. Based on the attached assignment you completed, you will now take the system that you selected for evaluation and cre

Value-Based Payment Modifier (VBM)

Abstract

Value-Based Payment Modifier (VBM) plays an important role in transforming Medicare into value-based care. Value-based modifiers (VBM), which are under the Medicare physician fee schedule, which permits a physician or group of physicians to receive differential payment depending on the cost-quality of treatment received during a performance period. Clinical decision support is one type of healthcare information that is advised. The clinical decision support system (CDSS) provides patient data, clinical expertise, and other health information with the aim of improving medical decision-making. The aim of the VBM is to improve quality and efficiency of healthcare services and support cost control and to achieve that then VBM is supported by the clinical decision support system (CDSS). This research explores the selection criteria towards selecting a vendor or building a system in-house, including Health Insurance Portability and Accountability Act (HIPAA) compliance, Systems Development Life Cycle (SDLC) implications and necessary security elements.

Value-Based Payment Modifier (VBM)

Introduction

Healthcare systems across most countries of the world are moving towards quality over quantity and paying more attention to value-based care systems as the reimbursement of providers focuses on the improved outcomes of patients and their efficiency levels. The Centers for Medicare & Medicaid Services (CMS) have introduced diverse programs, such as Value-Based Payment Modifier (VBM), to match levels of payment and the quality of provided care. Value-based modifiers (VBM), which are based on the quality of treatment provided in relation to cost during a performance period, allow for differential payment to a physician or group of doctors under the Medicare physician fee schedule. This research will select value based modifiers, recommend the healthcare technology which in this case CDSS was selected and support evidence-based health care practice and robust data reporting systems.

Healthcare Objective under the VBM Program

Value-based modifiers (VBM), which are based on the quality of treatment provided in relation to cost during a performance period, allow for differential payment to a physician or group of doctors under the Medicare physician fee schedule(Edmiston, 2022). As part of Medicare's efforts to enhance the effectiveness and quality of healthcare, the value modifiers program will give doctors access to comparative performance data (Edmiston, 2022). Each practice receives a composite score that compares the cost and quality of care to national standards based on the CMS calculation and quality measures submitted through PQRS. The primary objective of value based modifier (VBM) includes enhancing the quality and efficiency of healthcare and management of the healthcare expenditure. The objective encourages physicians to provide better treatment without performing unnecessary tests, operations, or hospital stays. One thing to be aware of is that Medicare penalizes providers more severely the better they perform and the more they are reimbursed. This dual situation promotes accountability and creates a competitive environment, which makes high-quality treatment the standard.

Implementing Clinical Decision Support Systems (CDSS)

Clinical Decision Support Systems (CDSS) should be implemented by healthcare organizations to support the VBM program's objectives. The clinical decision support system (CDSS) aims to improve medical decision-making by offering focused clinical knowledge, patient information, and other health data (Sutton et al., 2020). The main application of CDSS nowadays is at the point of care, where clinicians use the data and recommendations they give. However, CDSSs are increasingly being built that can use data and observations that people would not otherwise be able to access or understand. A health information technology is a CDSS solution designed to help professionals/clinicians make data-driven and evidence-based decisions (Sutton et al., 2020). A CDSS when combined with Electronic Health Records (EHRs) offers real-time alerts, clinical guidelines, risk assessment and diagnostic support. Such capabilities are all factors in directly lowered patient outcome and variability in care, which are both integral to the VBM assessment criteria. CDSS tools provide the improvements in clinical workflows, minimize medication errors, and the implementation of standard care processes, eventually resulting in the improved quality metric performance (Sutton et al., 2020).

Criteria for Vendor Selection or Internal Development

The factors considered in selecting CDSS solution is the judgment between developing new system together with the peripheral parties and purchasing system from third-party supplier. Such a decision needs a complex evaluation with the inclusion of compliance analysis, developmental processes, and security features. Primarily, the CDSS that will be chosen should abide by the Health Insurance Portability and Accountability Act (HIPAA) (Borycki, & Kushniruk, 2023). The privacy rule standards address the use and disclosure of individuals protected health information (PHI) by entities subject to the rule. The HIPAA expected CDSS to protect the health information of a patient with strong data protection measures such as data encryption, user authentication, access control, audit trails etc. Hence non-compliance on this measure attracts legal sanctions and jeopardize the identity of the healthcare organization.

Another consideration is the Systems Development Life Cycle (SDLC). The process of creating, implementing, and retiring an information system through a series of steps, from inception, analysis, design, implementation, and maintenance to disposal, is known as the system development life cycle. Organizations that chose to develop the system in-house must have a well-organized SDLC approach which entails system design, development, testing, deployment, maintenance as well as a requirement analysis stage (Borycki, & Kushniruk, 2023). Following this system development life cycle will ensure the CDSS development ensures clinical needs are met and at the same time be within the regulatory requirements. In the process of vendor selection, a number of important considerations have to be factored.

The vendor must demonstrate a successful history in healthcare technologies and experience with the implementation of CDSS applications that allow it to be configured to value-based care models. The successful history indicates reliability and consistency and be able to delivery on their promises consistently and this may include on-time delivery, meeting quality standard and providing reliable support. The system must comply with the clients and other EHRs deployed and must meet the standards like HL7 and FHIR to maximize the course of information (Sittig et al., 2020). The other factor to consider during the choice of vendor is that it is cost effective, scalable, and has support services by the vendor like training and updating of the systems. The vendor must be inexpensive and should have the capacity to offer supplementary support services.

Moreover, the selection factor might as well involve security of the CDSS such as avoiding the occurrence of bugs in the systems that may affect the operation capacity of the system. It should have the system of role-based access control (RBAC), intrusion detection and prevention systems (IDPS), and security checks conducted regularly (Sittig et al., 2020). These are to curb unauthorized access and Internet-based malicious deeds that are to the healthcare sector significant since the repercussions of data exploitation in the health industry are urgent. Lastly the principal factors influencing adoption are the usability and interoperability. CDSS should be most appropriate to the clinical trends of the clinicians, friendly and not an obstacle to clinical decision-making. An effective implementation and a long-term usage are also achieved through proper training and constant technical support.

Conclusion

The modern healthcare organization can largely contribute to the development of clinical decision support systems that will help them to meet the requirements of the Value-Based Payment Modifier program. Differential payment to a physician or group of doctors under the Medicare physician fee schedule is possible through value-based modifiers (VBM) that are predicated on the quality of treatment administered compared to cost of treatment over a performance period. These systems facilitate clinical decision making, improve patient related outcomes as well as facilitating compliance with quality and cost-effectiveness provisions. The choice of either in-house construction or the use of vendor construction should focus on HIPAA compliance, advanced SDLC methodology, solid security capabilities as well as systems integration with the existing ones. Healthcare organizations are able to maximize their performance in the value-based payment model through the strategic use of technology and provide high-quality and affordable care.

References

Borycki, E. M., & Kushniruk, A. W. (2023, March). Health technology, quality and safety in a learning health system. In Healthcare management forum (Vol. 36, No. 2, pp. 79-85). Sage CA: Los Angeles, CA: SAGE Publications.

Edmiston, K. D. (2022). Alternative payment models, value-based payments, and health disparities. Center for Insurance Policy & Research Report at the National Association of Insurance Commissioners.

Sittig, D. F., Wright, A., Coiera, E., Magrabi, F., Ratwani, R., Bates, D. W., & Singh, H. (2020). Current challenges in health information technology–related patient safety. Health informatics journal, 26(1), 181-189.

Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I. (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ digital medicine, 3(1), 17.