Our Core Services

Healthcare Consulting

OSP’s team of experienced healthcare experts offers quality healthcare consulting services for providers and health plans. Our team includes experts on enterprise software platforms, US government programs, digital innovation, and business operations.

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Enterprise Applications

OSP is proficient and experienced in building robust enterprise applications to address your complex and sophisticated software needs and execute your digital transformation lifecycle. We have comprehensive customized tools to solve your healthcare challenge.

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Healthcare Solutions Enhancement

Optimizing the healthcare system is essential for better productivity and quality performance. OSP’s team of developers can enhance and upgrade the healthcare solutions in modules, security, or interoperability sections with new custom components.

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Dedicated Quality Assurance

OSP’s QA team can resolve the challenges of disrupted workflow and application safety. We offer assurance in product quality with multiple levels of quality testing, including usability, performance, localization, and security testing.

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Explore Clinical Decision Data Support

Clinical decision support system is a healthcare application that carries the task of data analytics within the EHR to provide accurate directions and CDSS alerts to the healthcare providers. These advanced medical decision making helps caregivers to implement the evidence-based clinical guidelines at the point of care. There are a wide variety of clinical decision support examples like a CDSS for cardiovascular disease (CVD) prevention where the providers are reminded to screen patients with CVD risk factors and flag cases of hypertension. 

OSP can program clinical decision support systems based on healthcare rule inference engines navigate through a repertoire of clinical rules and multitudes of facts to help a clinical expert for the decision making in healthcare. On your demand, we can build a CDSS that incorporates a rule inferencing system where clinical data characteristics of a patient are matched to a clinical knowledge base to make patient-specific assessments for better case management. To solve your clinical decision-making challenges, we can leverage a cache-based lazy loading mechanism incorporating rule clustering and hashing kernel, combined with a prediction-based technique.


HITECH Act (Health Information Technology for Economic and Clinical Health Act) stated the providers need to comply with meaningful use of health IT systems or face a reduction in Medicare reimbursements. A decision support system is the best solution for the providers to comply with the HITECH Act and its requirement of meaningful use. CDSS is one of the essential clinical data analytics that helps providers in cost containment through timely and accurate clinical interventions. 

OSP can create customized clinical decision support tools for your needs that are COPE integrated and provide help in decreasing the inpatient length of stay and suggesting cost-effective medical alternatives. We can program CDSS based on your needs with multiple applications such as drug selection, drug-allergy checking, basic dosage guidance, drug interactions checking, suggesting alternative medical therapy, healthcare diagnostics support, and collaborative care management. By integrating CDSS in computerized physician order entry COPE, clinical facilities and hospitals can save hundreds of dollars per year.


Medical decision support system works as an expert clinician for a less experienced healthcare provider or as a second opinion for a veteran physician. A healthcare decision support system is based on case-based reasoning (CBR) and advanced knowledge management and healthcare analysis system. Replacing the raw medical data with some meaningful content can help to increase the efficiency of the clinical decision support system. Organized and transformed combination of medical data, adapted with a set of rules, procedures, and operations to create a universal set of rules, guidelines, operations, and knowledge. 

We program the CDSS medical to help match patient characteristics with digital knowledge bases and use algorithms to create patient-specific evaluations or treatment recommendations. We help you with a tailored system for clinical decision making with a Knowledge Manager. It is a knowledge database and rules engine for managing clinical regulations and medical data models. Knowledge manager breaks down the medical data into computerized rules which can comfortably be shared between different decision support applications to build a robust and flexible solution.


CDSS sifts through an enormous amount of EHR data to suggest next steps for medical treatment, alert providers to available information they may not have seen, or identify potential problems, such as dangerous medication interactions. A system for healthcare decision support has the clinical database layer to store information on diseases, diagnoses, and lab findings. The database also stores the patient data and a knowledge base in the form of ‘if-then’ rules or machine learning models. The content could be structured as the knowledge data such as FDBE database that contains drug-related data, or the medical content could be processed structured data from the EPR applications themselves.

Our team can solve the challenge of secure medical records management by building a dedicated data repository to hold all the medical data that is needed by the CDSS to present meaningful information to the healthcare providers. Guide us through your needs for the healthcare decision support system, and we will customize the information model of the data repository for CDSS. We have experience in medical data management and establishing a synchronization schedule for the data to maintain accurately and as near-real-time as possible between the EMR Clinical systems and your Data Repository.


Healthcare interoperability means the seamless data sharing potential of multiple health IT systems to help healthcare data readily accessible to all the users of these health systems. Interoperable clinical decision support systems help in improving efficiency, especially when the healthcare data are presented consistently, it is easier for practitioners to quickly get to the bottom of the issue as they make treatment decisions. Interoperable CDSS also helps for safer care transitions, especially for chronic care patients where continuity of care is crucial.  

OSP ensures interoperability in health IT systems to allow for safer transitions of care, which leads to better outcomes for patients in general. Semantic interoperability must be granted to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of clinical decision support systems in the areas of clinical information, decision logic, terminology, and web service interfaces. OSP can identify and provide an overview of the available standards that enable clinical decision support interoperability in the areas of clinical information, terminology, decision logic, and web service interfaces.


A computerized CDSS that integrates with multiple EMRs and multiple patient health records (PHR) is preferred by the healthcare providers for efficient healthcare decision making. Workflow integration is the major challenge in CDSS adoption. We work around the clock to customize clinical decision support system that can be easily integrated into your existing practice management and EHR. As per your needs, we can program a knowledge-based clinical decision support system to offer detailed medication classification surpassing mandated industry standards to reduce the potential for drug prescription errors. 

We modify the CDSS to build robust technical infrastructure to allow health systems such as advanced telehealth solutions to share data electronically. Our custom development services render complete information possible into CDS healthcare systems to enhance the decision-making process in the clinical workflow. We strive to solve clinical decision support system challenges by encouraging broader adoption of exceptional professional clinical guidelines and promote a culture of quality across the domain.


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