{"id":57955,"date":"2026-09-06T13:45:02","date_gmt":"2026-09-06T13:45:02","guid":{"rendered":"https:\/\/www.bridge-global.com\/blog\/?p=57955"},"modified":"2026-09-11T04:19:41","modified_gmt":"2026-09-11T04:19:41","slug":"guide-to-healthcare-digital-innovation","status":"publish","type":"post","link":"https:\/\/www.bridge-global.com\/blog\/guide-to-healthcare-digital-innovation\/","title":{"rendered":"Healthcare Digital Innovation: A Strategic Guide"},"content":{"rendered":"<p>In 2024, digital health services reached 82% average availability across comparable OECD countries, up from 79% in 2023, according to the <a href=\"https:\/\/www.oecd.org\/en\/publications\/health-at-a-glance-2025_8f9e3f98-en\/full-report\/data-and-digital_fd9fbb54.html\" target=\"_blank\" rel=\"noopener\">OECD&#8217;s health and digital data<\/a>. That shift changes the question for healthcare leaders. Digital care is no longer a side experiment. The harder question is whether your data, workflows, reimbursement model, governance, and patient-access strategy can support it safely.<\/p>\n<p>Healthcare digital innovation succeeds when technology becomes part of the operating model. It fails when an organization buys an impressive tool that cannot exchange reliable data, fit clinical work, satisfy regulators, or reach the people who need it most. This guide focuses on those less glamorous conditions, because they determine whether an AI platform, telehealth service, connected device, or patient app creates durable value.<\/p>\n<h2>What Healthcare Digital Innovation Actually Means<\/h2>\n<p>Healthcare digital innovation is a measurable change in how care is accessed, delivered, coordinated, documented, and reimbursed. It includes artificial intelligence, telehealth, connected devices, cloud platforms, automation, and interoperability, but none of those technologies qualifies as innovation solely because it has been deployed.<\/p>\n<p>The OECD&#8217;s 82% average availability of digital health services in 2024 shows that online health access has become an operational feature of health systems, not an isolated pilot. The increase from 79% in 2023 also signals steady institutionalization, although availability alone doesn&#8217;t prove that services are clinically effective, equitable, or well integrated. Leaders need to distinguish between putting a service online and redesigning the underlying care journey.<\/p>\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.bridge-global.com\/blog\/wp-content\/uploads\/2026\/09\/healthcare-digital-innovation-doctor-technology.jpg\" alt=\"A female doctor in a hospital corridor using a transparent futuristic digital tablet to view medical data.\" \/><\/figure>\n<h3>From digitization to operational change<\/h3>\n<p>Scanning a paper form is digitization. A patient completing structured intake before an appointment, with the information validated, routed into the clinical record, and used by the care team, is a workflow improvement. The distinction matters because clinical environments punish tools that add clicks, duplicate documentation, or create uncertain responsibility.<\/p>\n<p>A useful definition has four parts:<\/p>\n<ul>\n<li><strong>Clinical purpose:<\/strong> The product improves a defined care, safety, access, or coordination problem.<\/li>\n<li><strong>Workflow fit:<\/strong> Clinicians, administrators, and patients can use it without creating hidden work.<\/li>\n<li><strong>System connectivity:<\/strong> Data moves through controlled interfaces and retains its meaning.<\/li>\n<li><strong>Economic alignment:<\/strong> The organization understands how the service will be funded, reimbursed, or justified through operating value.<\/li>\n<\/ul>\n<p>That model applies to a remote monitoring service as much as it applies to a generative AI documentation assistant. A device may capture excellent data, but the program still needs an escalation pathway, clinician ownership, patient consent, data-quality checks, and an economic model.<\/p>\n<p>Patient communication illustrates the point. Secure messaging can support reminders, follow-up, triage, and care-plan engagement, but its value depends on identity verification, message routing, response expectations, and accessibility. Teams designing this layer can review practical guidance on <a href=\"https:\/\/www.callloop.com\/blog\/healthcare-patient-engagement-solutions\" target=\"_blank\" rel=\"noopener\">secure messaging for patient communication<\/a> as part of a broader engagement architecture.<\/p>\n<p>As we explored in our <a href=\"https:\/\/www.bridge-global.com\/blog\/healthcare-innovation-consulting\/\">healthcare innovation consulting guide<\/a>, the strongest programs begin with a service or operational constraint, then select technology that can be governed within the health system. That is the difference between a digital feature and healthcare digital innovation.<\/p>\n<h2>Core Technologies Powering Modern Health Systems<\/h2>\n<p>Modern health systems rarely depend on one technology. The useful architecture is a chain. Connected devices produce observations, interoperability services transport them, cloud infrastructure stores and processes them, machine learning identifies patterns, and automation routes the next action into an operational system.<\/p>\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.bridge-global.com\/blog\/wp-content\/uploads\/2026\/09\/healthcare-digital-innovation-health-technologies.jpg\" alt=\"An infographic showing seven core technologies powering modern health systems including AI, telehealth, IoT, and cloud infrastructure.\" \/><\/figure>\n<h3>The technology stack in practice<\/h3>\n<p><strong>AI and machine learning<\/strong> support prediction, classification, prioritization, and decision support. The safe use case isn&#8217;t \u201cadd AI to the EHR.\u201d It&#8217;s a bounded task, such as identifying records that need review, detecting patterns in monitoring data, or helping staff prioritize work. Human review, model monitoring, and clear escalation rules remain essential.<\/p>\n<p><strong>Telehealth<\/strong> extends consultations and follow-up beyond physical facilities. It can improve convenience and reach, but it must account for clinical suitability, connectivity, identity, consent, documentation, and the circumstances in which a virtual encounter must become an in-person visit.<\/p>\n<p><strong>IoT and remote monitoring<\/strong> connect wearables, sensors, medical devices, and home-based equipment. The difficult engineering problem is not collecting a reading. It&#8217;s managing device identity, missing data, calibration, alert thresholds, battery constraints, patient onboarding, and the clinical response to an alert.<\/p>\n<p><strong>Interoperability standards<\/strong>, particularly FHIR and HL7, provide the exchange layer. FHIR-based APIs can expose structured patient information to applications, but an API is only as reliable as the source data, terminology mapping, authorization model, and implementation discipline behind it.<\/p>\n<p><strong>Cloud infrastructure<\/strong> offers elastic computing, managed services, centralized observability, and controlled environments for data processing. Healthcare teams still need a clear data-classification policy, backup strategy, access controls, incident response, and an understanding of where workloads are allowed to run.<\/p>\n<p><strong>Robotic process automation<\/strong> works best for repetitive, rules-based administrative tasks. Prior authorization preparation, document routing, reconciliation, and status updates are possible targets, but automation should not conceal ambiguous policy or poor master data.<\/p>\n<p><strong>Generative AI<\/strong> can assist with documentation, summarization, search, and knowledge workflows. It should produce traceable drafts, not unreviewed clinical conclusions. Grounding, source visibility, prompt controls, retention rules, and testing against realistic clinical language are part of the product, not optional add-ons.<\/p>\n<p>A detailed <a href=\"https:\/\/www.bridge-global.com\/blog\/healthcare-cloud-architecture\/\">healthcare cloud architecture perspective<\/a> is useful when deciding which workloads belong in managed cloud services and which require tighter isolation. The practical rule is simple: select the smallest technology combination that solves the defined problem, then design the interfaces before expanding the feature set.<\/p>\n<h2>Business Drivers and Strategic Benefits<\/h2>\n<p>The commercial case for healthcare digital innovation is strong, but market growth does not guarantee a return for a particular provider or product. A neutral academic review projects that the global digital healthcare industry will reach $549.7 billion by 2028, with a 25% compound annual growth rate from 2023 to 2028. Executives should treat that projection as evidence of demand, then test whether their own workflows, data quality, reimbursement model, and governance can support value.<\/p>\n<p>Deloitte&#8217;s 2025 global health care outlook found that about 70% of survey respondents considered investment in technology platforms for digital tools and services important to their organizations. About 90% of C-suite executives expected digital technologies to accelerate in 2025, and half expected a significant impact. Those findings place digital capability within strategic resilience and operating model decisions, rather than leaving it as an IT preference.<\/p>\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.bridge-global.com\/blog\/wp-content\/uploads\/2026\/09\/healthcare-digital-innovation-strategic-benefits.jpg\" alt=\"An infographic showing business drivers and strategic benefits of healthcare digital innovation with statistics and key outcomes.\" \/><\/figure>\n<h3>The payment system decides what scales<\/h3>\n<p>Reimbursement often determines whether an initiative can move beyond a pilot. A 2025 industry report cited by the <a href=\"https:\/\/www.oecd.org\/en\/publications\/health-at-a-glance-2025_8f9e3f98-en\/full-report\/data-and-digital_fd9fbb54.html\" target=\"_blank\" rel=\"noopener\">OECD data on digital health<\/a> identified more than 300 billing codes supporting digital health and digital care, including 117 codes for software-based technologies such as software as a medical device, software in a medical device, and AI-enabled software as a medical device.<\/p>\n<p>Codes provide a payment framework, not automatic coverage. Payers may apply different rules by solution type, therapy area, and care setting. Product leaders should define the intended payment pathway before funding a large build, including who bills, who benefits, and what evidence supports the claim.<\/p>\n<p>A credible business case ties the technology to an operating or clinical objective:<\/p>\n<ul>\n<li><strong>Access:<\/strong> Reduce friction in scheduling, intake, navigation, or follow-up.<\/li>\n<li><strong>Capacity:<\/strong> Help staff manage administrative work while preserving clinical oversight.<\/li>\n<li><strong>Quality:<\/strong> Support guideline adherence, preventive reminders, or appropriate decisions.<\/li>\n<li><strong>Continuity:<\/strong> Connect patients, providers, payers, and care teams across settings.<\/li>\n<li><strong>Financial performance:<\/strong> Capture eligible reimbursement or reduce avoidable operational effort.<\/li>\n<\/ul>\n<p>The <a href=\"https:\/\/www.bridge-global.com\/blog\/healthcare-predictive-intelligence\/\">healthcare predictive intelligence guide<\/a> helps frame predictive capabilities around decisions, owners, and follow-up actions instead of treating analytics as a standalone dashboard. Teams should also test whether interoperability preserves meaning across systems and whether access, language, workflow, or payment barriers exclude the patients the product is meant to serve.<\/p>\n<blockquote><p><strong>Board-level test:<\/strong> If the business case cannot identify the workflow owner, payment logic, evidence plan, and equity risks, it is not ready for approval.<\/p><\/blockquote>\n<h2>Regulatory Compliance and Security Considerations<\/h2>\n<p>Healthcare software operates under overlapping obligations. HIPAA may govern protected health information in the United States, GDPR may apply to personal data in relevant European contexts, and software with a medical purpose can enter regulated software-as-a-medical-device pathways. The exact obligations depend on the product, market, data flows, clinical claims, and organizational role.<\/p>\n<p>Interoperability creates an additional design constraint. By February 2026, nearly 500 million health records had been exchanged through TEFCA, up from 10 million in January 2025, according to <a href=\"https:\/\/www.techtarget.com\/searchhealthit\/feature\/Where-healthcare-stands-on-interoperability-in-2026-progress-and-challenges\" target=\"_blank\" rel=\"noopener\">TechTarget&#8217;s 2026 interoperability coverage<\/a>. That growth shows why exchange infrastructure deserves architectural attention, but volume alone doesn&#8217;t guarantee semantic accuracy, patient matching, or clinical usefulness.<\/p>\n<h3>Standards and governance are moving targets<\/h3>\n<p>The <a href=\"https:\/\/healthit.gov\/news\/2026-interoperability-standards-advisory-reference-edition\/\" target=\"_blank\" rel=\"noopener\">ONC 2026 Interoperability Standards Advisory Reference Edition<\/a> reflects numerous changes made throughout 2025. Teams maintaining healthcare APIs should therefore treat standards tracking as ongoing product work, not a one-time integration task.<\/p>\n<p>U.S. certified health IT had to accommodate <a href=\"https:\/\/healthit.gov\/wp-content\/uploads\/2025\/09\/2026AnnualMeeting_Progress-on-Interoperability-and-Ongoing-Improvements.pdf\" target=\"_blank\" rel=\"noopener\">USCDI v3 data using FHIR US Core profiles by January 1, 2026<\/a>, creating a concrete deadline for vendors building clinical workflow and patient-access integrations. A thorough release process should test profile conformance, terminology behavior, authorization, provenance, and failure handling.<\/p>\n<p><a href=\"https:\/\/www.medrxiv.org\/content\/10.64898\/2026.07.08.26357574v1\" target=\"_blank\" rel=\"noopener\">FHIRTrustBench found<\/a> five deployment-risk pathways in heterogeneous FHIR implementations: data integrity, semantic consistency, security, clinical workflow, and generative AI grounding. In its applied corpus of 10 representative standards and implementation sources, no source reported prospective external validation, while governance readiness remained at or below 1.0 across every category. That finding challenges the assumption that an interoperable API automatically creates AI readiness.<\/p>\n<p><a href=\"https:\/\/www.hhs.gov\/sites\/default\/files\/2025-hhs-ai-compliance-plan.pdf\" target=\"_blank\" rel=\"noopener\">HHS also stated that<\/a> by April 3, 2026, all HHS divisions should apply minimum risk-management practices for high-impact AI. If a division can&#8217;t meet the deadline, it must stop using the applicable AI tool or solution until compliant.<\/p>\n<p>Security architecture should cover identity, least-privilege access, encryption, audit logging, vendor risk, backup, incident response, and secure development. Teams assessing <a href=\"https:\/\/cloudvara.com\/hipaa-compliant-cloud-hosting\/\" target=\"_blank\" rel=\"noopener\">secure cloud hosting for healthcare SMBs<\/a> should evaluate contractual controls and operational accountability, not just a compliance label. Equity belongs in the same governance conversation. <a href=\"https:\/\/www.who.int\/europe\/news\/item\/17-03-2026-digital-health-equity-gaps-remain--but-solutions-are-becoming-clearer--new-report-shows\" target=\"_blank\" rel=\"noopener\">WHO\/Europe reports<\/a> that people with greater health needs and language barriers can face limited access, low digital literacy, and services that aren&#8217;t adapted to diverse needs.<\/p>\n<h2>Implementation Roadmap and Best Practices<\/h2>\n<p>A successful program starts with sequencing. Organizations that begin with an AI model before fixing identity, data quality, workflow ownership, and integration boundaries often create a polished demonstration that can&#8217;t survive production.<\/p>\n<h3>A practical five-phase sequence<\/h3>\n<p><strong>1. Discover the operating problem:<\/strong> Interview clinicians, patients, administrators, compliance teams, finance leaders, and support staff. Map the current journey, identify delays and duplicated work, define the intended decision, and document who owns the outcome. An AI Discovery Workshop can help separate valuable use cases from attractive but unsupported ideas.<\/p>\n<p><strong>2. Establish planning and governance:<\/strong> Create an inventory of data sources, systems, vendors, models, clinical claims, and regulatory obligations. Define approval gates, human oversight, retention, access, monitoring, incident response, and evidence requirements before development begins. The April 2026 HHS deadline is a useful planning anchor for high-impact AI, even when an organization isn&#8217;t an HHS division.<\/p>\n<p><strong>3. Build the foundation with a cross-functional team:<\/strong> Product, clinical, engineering, security, compliance, data, and operations representatives should work from one backlog. Build APIs, event handling, terminology mappings, audit trails, and observability alongside user-facing functionality. A <a href=\"https:\/\/www.bridge-global.com\/healthcare\">custom healthcare software development<\/a> team may be appropriate when the workflow or compliance model is too specialized for an off-the-shelf product.<\/p>\n<p><strong>4. Pilot and validate in the actual workflow:<\/strong> Test with representative users and imperfect data. Measure false positives, missing information, time added or removed, override behavior, patient comprehension, accessibility, and downstream operational impact. For patient-facing diagnostic or laboratory journeys, documenting <a href=\"https:\/\/reposehealthcare.co.uk\/online-lab-test-process-flowchart-showing-order-kit-sample-collection-and-secure-online-results\/\" target=\"_blank\" rel=\"noopener\">sample collection and results<\/a> can expose handoff risks that a screen-level prototype hides.<\/p>\n<p><strong>5. Scale through controlled release:<\/strong> Expand by site, workflow, or patient population only after the pilot meets defined safety and operational criteria. Use feature flags, staged rollouts, rollback plans, model monitoring, support playbooks, and recurring governance reviews.<\/p>\n<p>KPMG identifies cybersecurity, unreliable data, regulatory and compliance risk, legacy systems, disconnected data, integration complexity, resistance to change, and misaligned incentives as practical barriers. 42% of respondents cited weak governance and limited expertise as the most significant challenge, according to the <a href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC12860439\/\" target=\"_blank\" rel=\"noopener\">KPMG healthcare technology report<\/a>. That makes the delivery model a strategic choice. Compare <a href=\"https:\/\/www.bridge-global.com\/service-models\">software development service models<\/a>, then decide whether in-house engineering, a specialist <a href=\"https:\/\/www.bridge-global.com\/\">healthtech software development partner<\/a>, or a blended team gives the organization enough domain control and delivery capacity.<\/p>\n<h2>Common Pitfalls and How to Avoid Them<\/h2>\n<p>A provider can approve a digital program, fund a build, and still fail during rollout. The recurring pattern is a mismatch between the product team&#8217;s definition of success and the frontline team&#8217;s definition of usable care.<\/p>\n<h3>Four failure patterns from the field<\/h3>\n<p><strong>The showcase pilot:<\/strong> A healthtech startup demonstrates a compelling AI assistant using clean sample data. In production, the provider discovers that records use inconsistent terminology, patient identity matching is incomplete, and no one owns the review queue. The model wasn&#8217;t the only problem. The team skipped data profiling, workflow design, and operational accountability.<\/p>\n<p><strong>The disconnected integration:<\/strong> An enterprise connects a new platform to an EHR but leaves referral, scheduling, consent, and status data in separate systems. Staff still copy information manually, so the organization has purchased connectivity without achieving continuity. Define the minimum end-to-end data journey before approving interface work. Targeted <a href=\"https:\/\/www.bridge-global.com\/healthcare\/tools-and-integrations\">healthcare integrations<\/a> should support a clinical or administrative action, not just expose an endpoint.<\/p>\n<p><strong>The workflow shock.<\/strong> <a href=\"https:\/\/digital.ahrq.gov\/sites\/default\/files\/docs\/citation\/examining-the-relationship-between-health-it-and-ambulatory-care-workflow-redesign-final-report.pdf\" target=\"_blank\" rel=\"noopener\">An AHRQ practice-redesign study found<\/a> that health IT can reduce reliance on paper, improve aggregation and availability of patient information, and improve referral processes. It also documented adverse workflow impacts at some sites, while a review of clinical eHealth found moderate-quality evidence that point-of-care, workflow-integrated decision support can improve guideline adherence, preventive reminders, diagnostic appropriateness, and process efficiency, with mortality and readmission effects remaining uncertain. Redesign the work with clinicians, test interruption patterns, and measure what happens after the alert, not just whether the alert appears.<\/p>\n<p><strong>The invisible patient:<\/strong> A patient with limited connectivity, low digital literacy, a language barrier, or a disability may be unable to use a supposedly convenient service. WHO\/Europe warns that uneven infrastructure and poorly adapted services can widen unequal access. Offer multilingual content, accessible interfaces, assisted channels, human support, and a non-digital route that preserves care continuity.<\/p>\n<p>KPMG&#8217;s governance finding reinforces the operational lesson. Weak governance and limited expertise can fragment decisions, slow execution, and leave teams unsure who can approve a model, change a workflow, or stop a deployment. Establish one accountable product owner, one clinical safety owner, and a documented escalation route before launch.<\/p>\n<h2>Measuring Success and Planning Next Steps<\/h2>\n<p>Healthcare digital innovation needs a measurement system that follows the care journey. Track clinician adoption, patient engagement, interoperability throughput, data-quality exceptions, workflow time, escalation handling, accessibility, and reimbursement capture. These measures should answer whether the service is being used correctly and whether it improves the intended operation.<\/p>\n<p>Avoid vanity metrics. App downloads don&#8217;t prove access, generated summaries don&#8217;t prove documentation quality, and API traffic doesn&#8217;t prove useful exchange. Pair every activity measure with an outcome or safety measure, such as completed care actions, reviewed alerts, resolved exceptions, or validated documentation.<\/p>\n<p>Standards will continue to evolve. The ONC&#8217;s 2026 advisory edition and the USCDI v3 deadline show why architecture teams need a standards watchlist, compatibility testing, and version-aware release management. Governance should also include recurring equity reviews, patient feedback, clinician feedback, model-performance checks, and reimbursement reconciliation.<\/p>\n<p>Organizations that sustain innovation treat every deployment as a learning system. They preserve the useful parts of a pilot, remove unsupported features, improve data plumbing, and keep decision rights clear. They don&#8217;t confuse a successful demo with a dependable health service.<\/p>\n<blockquote><p><strong>Sustainable innovation<\/strong> is the discipline of improving care while preserving trust, interoperability, equity, and accountability.<\/p><\/blockquote>\n<p>Bridge Global provides <a href=\"https:\/\/www.bridge-global.com\/services\/artificial-intelligence-development\">AI development services<\/a>, <a href=\"https:\/\/www.bridge-global.com\/ai-advantage\">enterprise AI solutions<\/a>, an <a href=\"https:\/\/www.bridge-global.com\/service-models\/ai-transformation-framework\">AI implementation roadmap<\/a>, <a href=\"https:\/\/www.bridge-global.com\/services\/custom-software-development\">custom software development<\/a>, and <a href=\"https:\/\/www.bridge-global.com\/services\/saas-solutions\">SaaS product development<\/a> for teams building connected digital products. Review the available <a href=\"https:\/\/www.bridge-global.com\/client-cases\">client cases<\/a>, then visit <a href=\"https:\/\/www.bridge-global.com\">Bridge Global<\/a> to discuss an interoperable, governed healthcare digital innovation program grounded in your workflows and regulatory requirements.<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>In 2024, digital health services reached 82% average availability across comparable OECD countries, up from 79% in 2023, according to the OECD&#8217;s health and digital data. That shift changes the question for healthcare leaders. Digital care is no longer a &hellip;<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":83,"featured_media":57954,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1015],"tags":[953,1368,1434,1902,1903],"class_list":["post-57955","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-healthcare","tag-ai-in-healthcare","tag-healthcare-interoperability","tag-healthtech-software","tag-healthcare-digital-innovation","tag-digital-health-strategy"],"featured_image_src":"https:\/\/www.bridge-global.com\/blog\/wp-content\/uploads\/2026\/09\/healthcare-digital-innovation-ai-medical.jpg","author_info":{"display_name":"Preethi Saro Philip","author_link":"https:\/\/www.bridge-global.com\/blog\/author\/preethi\/"},"_links":{"self":[{"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/posts\/57955","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/users\/83"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/comments?post=57955"}],"version-history":[{"count":2,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/posts\/57955\/revisions"}],"predecessor-version":[{"id":57984,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/posts\/57955\/revisions\/57984"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/media\/57954"}],"wp:attachment":[{"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/media?parent=57955"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/categories?post=57955"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bridge-global.com\/blog\/wp-json\/wp\/v2\/tags?post=57955"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}