{"id":164184,"date":"2026-01-18T00:18:22","date_gmt":"2026-01-18T00:18:22","guid":{"rendered":""},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-30T00:00:00","slug":"the-importance-of-data-visibility-in-denial-management-how-analytics-can-improve-revenue-cycle-outcomes-4337578","status":"publish","type":"post","link":"https:\/\/www.simbo.ai\/blog\/the-importance-of-data-visibility-in-denial-management-how-analytics-can-improve-revenue-cycle-outcomes-4337578\/","title":{"rendered":"The Importance of Data Visibility in Denial Management: How Analytics Can Improve Revenue Cycle Outcomes"},"content":{"rendered":"<p>Denial management means following up on and reducing claim denials sent to payers. Almost 90% of denied claims can be avoided. This means healthcare groups can get back a lot of lost money by improving how they handle denials. Studies show only about two-thirds of denied claims are recovered, which leads to a lot of lost revenue.<\/p>\n<p>For example, MultiCare Health System, a large healthcare provider, faced financial problems because its denial management was not effective. By bringing different teams together and focusing on the main problems, MultiCare reduced denials and avoidable write-offs by $14.99 million. Their experience shows why managing and preventing denials is important.<\/p>\n<p>In the wider U.S. healthcare system, billions of dollars are lost every year from denied claims. Out of $3 trillion in claims, $262 billion were denied. Many healthcare providers lose nearly $5 million each due to denials. The American Medical Association says claim processing inefficiencies cost between $21 billion and $210 billion every year.<\/p>\n<p>These losses are not just about money. They also hurt staff morale, make operations less efficient, and lower patient satisfaction. Denials cause accounts receivable (A\/R) days to go up, reduce cash flow, and add more work for revenue teams.<\/p>\n<h2>The Role of Data Visibility in Denial Management<\/h2>\n<p>Data visibility means having clear, real-time access to all important information during the revenue cycle\u2014from patient registration and insurance checks to submitting claims and getting payments. It helps healthcare workers use accurate information at every step.<\/p>\n<p>Poor data visibility causes delays and confusion. Healthcare groups create large amounts of data like clinical notes, billing records, and lab results. But often this data sits in separate systems that do not connect. For example, billing systems may not talk well with Electronic Health Records (EHR) or practice management systems. This makes workflows difficult, delays claim follow-ups, and hides errors until it is too late.<\/p>\n<p>The Healthcare Financial Management Association (HFMA) says 22% of healthcare leaders lose at least $500,000 every year because denied claims happen due to poor data transparency. Fixing denied claims costs about $47.77 for each Medicare Advantage claim and $63.76 per commercial claim. This shows that inefficient denial handling can add up fast.<\/p>\n<p>When data visibility is limited, organizations find it hard to spot exact reasons for denials. Problems like missing paperwork, outdated doctor orders, or medical necessity issues stay hidden. This stops accurate appeals and makes accounts receivable cycles longer.<\/p>\n<h2>How Analytics Enhances Denial Management<\/h2>\n<p>Analytics helps turn raw revenue cycle data into useful information. This makes it easier to prevent, manage, and recover from denials.<\/p>\n<h2>Real-Time Monitoring and Reporting<\/h2>\n<p>Analytics platforms show trends in denials and key measures like denial rates, clean claim rates, and accounts receivable days. These systems can sort data by payer, claim type, denial reason, or department. This helps teams quickly find repeated problems and main causes. MultiCare used the Health Catalyst\u00ae Analytics Platform to help analysts work faster. Staff used analytics twice as much and focused their efforts better.<\/p>\n<p>Hospitals and medical groups can track important numbers such as:<\/p>\n<ul>\n<li><strong>Denial rate<\/strong> \u2014 Good organizations keep this below 5%. The average is usually 6-10%.<\/li>\n<li><strong>Clean claims rate<\/strong> \u2014 The goal is 95% or higher to lower denials and rework.<\/li>\n<li><strong>Days in A\/R<\/strong> \u2014 Keeping accounts receivable below 45 days helps cash flow.<\/li>\n<li><strong>First-pass yield<\/strong> \u2014 This shows the percent of claims paid at first submission. The target is 90% or more.<\/li>\n<\/ul>\n<p>By watching these numbers, providers learn where money is leaking and can fix problems quickly.<\/p>\n<h2>Predictive Analytics and Root Cause Analysis<\/h2>\n<p>Beyond just showing data, predictive models use past information to guess which claims might be denied. For example, Banner Health uses AI tools to spot denials likely caused by coverage gaps or authorization problems. This lets them fix these issues before submitting claims.<\/p>\n<p>Root cause analysis finds specific mistakes in workflows or paperwork causing denials. MultiCare created standard steps to check medical necessity and send advance notices, guided by analytics. This reduced preventable denials and made sure payer rules were followed.<\/p>\n<h2>Workflow Integration for Continuous Improvement<\/h2>\n<p>Analytics is not just a one-time task. It is an ongoing process to review and improve. Organizations review denial data every month or quarter. They adjust workflows, get ready for rule changes, and talk with insurers for clarifications. This way, denial rates keep going down, improving financial results.<\/p>\n<h2>AI and Automation in Denial Management and Workflow Optimization<\/h2>\n<p>Artificial Intelligence (AI) and automation are now key tools for better denial management. They make workflows faster and help with tough administrative work.<\/p>\n<h2>AI-Driven Automation<\/h2>\n<p>Healthcare providers use AI to automate boring, repetitive tasks like insurance checks, authorization work, and writing appeal letters. Banner Health uses AI bots to handle payer requests and make appeal documents based on denial codes. This saves time and speeds up responses.<\/p>\n<p>Community health providers in Fresno use AI tools. They cut prior authorization denials by 22% and service coverage denials by 18%. This saves 30\u201335 hours a week that staff would spend on appeals and follow-ups.<\/p>\n<h2>Natural Language Processing (NLP) and Machine Learning (ML)<\/h2>\n<p>NLP helps automate coding and billing by understanding doctor notes and clinical documents. This improves accuracy and compliance. ML looks at large claim histories to spot risky claims before submission. This lowers rejection rates and helps assign resources better.<\/p>\n<h2>Risk Management and Quality Control<\/h2>\n<p>Even with AI, experts say human checks are important. People must watch for data bias and mistakes in AI results. This ensures billing and payment decisions are fair and correct.<\/p>\n<h2>Workflow Enhancements Through Integration<\/h2>\n<p>When patient registration, clinical notes, billing, and claims systems are connected using AI and robotic process automation (RPA), data silos and mismatches drop. Automated claim scrubbers check claims as they are made to catch problems early. This helps keep claims clean from the start.<\/p>\n<p>Good communication workflows help different revenue departments work together. Teams from patient access, clinical services, Health Information Management (HIM), coding, billing, and collections can fix issues before they cause denials.<\/p>\n<h2>Revenue Cycle Analytics for US Healthcare Providers<\/h2>\n<p>Adding revenue cycle analytics software to healthcare finance systems gives clear benefits.<\/p>\n<ul>\n<li><strong>Improved Financial Outcomes:<\/strong> Analytics show real-time data from EHRs, billing, and practice management. This helps healthcare providers use resources well, find bottlenecks, and lower denials.<\/li>\n<li><strong>Revenue Leakage Reduction:<\/strong> Analytics help spot money lost from unbilled claims, duplicates, coding mistakes, or late medical necessity checks.<\/li>\n<li><strong>Value-Based Reimbursement Support:<\/strong> Analytics help providers match value-based payment models by tracking patient outcomes, care costs, and readmission rates. This supports good care and financial health.<\/li>\n<li><strong>Patient-Centered Billing:<\/strong> Data visibility helps communicate clearly with patients, lowering disputes and speeding payments.<\/li>\n<\/ul>\n<p>Mid-sized hospitals with about $500 million in yearly income could regain $10\u201320 million by using strong revenue cycle analytics. Currently, analytics use is below full potential. Only about 40% of healthcare finance leaders say they have mature systems, even though 90% know analytics is important.<\/p>\n<h2>The Importance of Training and Culture for Data Visibility<\/h2>\n<p>Technology is important, but organizations also need a culture that values data responsibility. Training staff regularly helps leaders, clinicians, and revenue teams understand how data quality and denial management affect finances. Training helps teams use analytics tools well and follow consistent workflows. This lowers mistakes and variation.<\/p>\n<p>MultiCare\u2019s experience shows that teaching leaders and clinicians raised analytics use by over 100%. This helped departments track how they are doing in real time and keep improving over the long term.<\/p>\n<h2>Challenges and Considerations for US Medical Practices<\/h2>\n<p>Medical practice administrators, owners, and IT managers face several challenges when improving data visibility and denial management:<\/p>\n<ul>\n<li><strong>Disparate Systems:<\/strong> Many practices still use old systems that do not connect well, causing data silos.<\/li>\n<li><strong>Complex Payer Policies:<\/strong> Insurance rules change often, requiring constant updates.<\/li>\n<li><strong>Resource Constraints:<\/strong> Limited staff time and skills can slow adoption of analytics and AI tools.<\/li>\n<li><strong>Compliance Requirements:<\/strong> Medicare and Medicaid require complete documents and timely submissions to avoid penalties.<\/li>\n<\/ul>\n<p>To meet these challenges, healthcare providers should invest in integrated revenue cycle software with advanced analytics and AI, focus on staff training, and encourage teamwork among departments handling the revenue cycle.<\/p>\n<p>By improving data visibility, using analytics to track denial trends, and applying AI and automation wisely, healthcare groups in the United States can reduce denials, recover lost money, and keep their finances stable while giving good patient care.<\/p>\n<section class=\"faq-section\">\n<h2 class=\"section-title\">Frequently Asked Questions<\/h2>\n<div class=\"faq-container\">\n<details>\n<summary>What is denial management in revenue cycle management?<\/summary>\n<div class=\"faq-content\">\n<p>Denial management is the process of following up on and reducing claims that are denied or rejected by payers. It is critical for ensuring appropriate reimbursement and maximizing revenue.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What percentage of claim denials are preventable?<\/summary>\n<div class=\"faq-content\">\n<p>Nearly 90 percent of claim denials are preventable, highlighting the need for improved processes to reduce them and enhance revenue capture.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What was the financial impact of MultiCare&#8217;s denial management improvement?<\/summary>\n<div class=\"faq-content\">\n<p>MultiCare achieved a reduction of $14.99 million in denials and avoidable write-offs through improved denial management processes.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What role does data visibility play in denial management?<\/summary>\n<div class=\"faq-content\">\n<p>Effective denial management requires visibility into data to assess opportunities for improvement. Poor visibility limits an organization&#8217;s ability to tackle denials effectively.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>How did MultiCare approach improving its denial management?<\/summary>\n<div class=\"faq-content\">\n<p>MultiCare organized a denials management workgroup composed of interdisciplinary members to standardize workflows, enhance visibility, and address root causes of denials.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What specific processes did MultiCare standardize to improve denial management?<\/summary>\n<div class=\"faq-content\">\n<p>MultiCare implemented standard workflows for screening medical necessity, issuing advanced beneficiary notices, and securing appropriate payer notifications.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>How did MultiCare enhance data access for denial management?<\/summary>\n<div class=\"faq-content\">\n<p>MultiCare utilized the Health Catalyst\u00ae Analytics Platform to provide timely and actionable data on denials, allowing for quicker identification of trends and root causes.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What training did MultiCare provide to improve denial management?<\/summary>\n<div class=\"faq-content\">\n<p>MultiCare provided training for operational leaders and clinicians on using analytics applications and EHR to investigate and understand the causes of denials.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What is the long-term goal of MultiCare&#8217;s denial management improvement efforts?<\/summary>\n<div class=\"faq-content\">\n<p>The long-term goal is to sustain gains in revenue capture by equipping leaders with tools to track departmental performance in real-time.<\/p>\n<\/p><\/div>\n<\/details>\n<details>\n<summary>What future opportunities does MultiCare plan to explore in revenue cycle management?<\/summary>\n<div class=\"faq-content\">\n<p>MultiCare intends to explore improvements in professional billing through focused workflows, informed by data analytics, following their denial management success.<\/p>\n<\/p><\/div>\n<\/details><\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Denial management means following up on and reducing claim denials sent to payers. Almost 90% of denied claims can be avoided. This means healthcare groups can get back a lot of lost money by improving how they handle denials. Studies show only about two-thirds of denied claims are recovered, which leads to a lot of [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[],"class_list":["post-164184","post","type-post","status-publish","format-standard","hentry"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/posts\/164184","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/comments?post=164184"}],"version-history":[{"count":0,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/posts\/164184\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/media?parent=164184"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/categories?post=164184"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/tags?post=164184"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}