Healthcare Data Analytics Consulting

Optimizing inpatient care, or, in particular, optimizing LOS, often means targeted interventions to improve inpatient financial performance and mitigate the financial impact of LOS challenges. However, this is only possible if length-of-stay management relies on an integrated technical infrastructure, including an enterprise data warehouse and an associated analytics platform. In organizations where it's implemented, clinicians have near real-time access to LOS performance metrics, updated by the minute rather than just by the day. Challenges in Reducing Length of Stay LOS Data is Needed Right Now, While Patients are Hospitalized Reducing LOS by adjusting clinical decision-making is possible when providers, care team members, and leaders within a healthcare network have access to LOS data and recognize its clinical relevance. However, if manual processes are used for gathering and sharing LOS data (which are typically very resource-intensive), it can take several weeks or even months before this data is disseminated across the organization. By then, patients may have been discharged long ago, making the data useless for clinicians. Calculating LOS in Whole Days is Inaccurate If calculating and reporting LOS is based on data from financial systems and insurance claims, where it is recorded in days rather than hours, it creates confusion in the true utilization of hospital resources. The issue lies in the methodology: a patient discharged in the morning, who frees up a bed, may be recorded as having occupied the bed for a full day. Adjusting Acuity Can No Longer Rely on Legacy Approaches It only takes a few complex surgical patients to skew LOS numbers. The traditional method to adjust LOS for patient acuity uses CMI (Case Mix Index), based on the assigned DRG (categorize patients with similar clinical diagnoses), which does not consider all required factors that affect patient acuity and cost. As a result, LOS of a very sick patient may be compared to the LOS of a healthier patient. A doctor may be forced to discharge patients before completing their treatment in order to meet average benchmarks calculated this way. Patients within the same diagnosis group often require similar resources and share comparable clinical complexity. Grouping patients by similar diagnoses (MS-DRGs) and comparing their LOS to the GMLOS (a national average for each diagnosis group) provides a more accurate way to determine whether a patient’s LOS is appropriate. Dividing each patient’s actual LOS by the MS-DRG-specific GMLOS better highlights areas where LOS is either above or below the expected standard, helping to identify opportunities for reduction. Missing Discharge Information Increases LOS The common practice is that social workers and nurses don’t know when particular patients are ready to leave the hospital or what the anticipated discharge date is, leaving them with little time to prepare for the patient’s discharge. This often leads to spending more time ordering medical equipment, finding a bed in a nursing facility, or confirming a ride, delaying the patient’s discharge (unnecessary hospital stays). What Benefits to Expect After Implementing Length of Stay Analytics Performance reports reveal insights that completely shift the focus of LOS improvement initiatives. For example: It’s possible to estimate cost savings per day through automated calculations based on complex formulas. The ability for providers to view their own performance levels (e.g., LOS differences due to practice pattern variation) motivates them to achieve higher performance. When clinically relevant near real-time data is available, hospitalists become more engaged, leading to reduced practice pattern variation through clinical transformation (ultimately reducing LOS systematically). Finally, it’s possible to create a discharge planning process where the team is consistently informed about both the anticipated discharge date and the actual timing of discharge orders. Or more specific findings, such as: Hospitalists often complete discharge orders in the early morning, but patients are discharged only later in the day. This highlights an opportunity to reduce LOS. LOS may vary by the day of the week, especially on weekends, due to limited availability of diagnostic procedures and challenges in discharging patients to specialized nursing facilities. How Belitsoft Can Help Belitsoft is a full-cycle software development and analytics consulting company that specializes in healthcare software development. We help top healthcare data analytics companies build robust data analytics platforms. For integrated data platforms developed to collect, store, process, and analyze large volumes of data from various sources (Electronic Medical Records, clinic management systems, laboratory systems, financial systems, etc.), we: Automate data processing workflows (cleansing, standardization, and normalization). Configure scalable data warehouses. Set up and implement analytical tools for creating dashboards, reports, and data visualizations. Ensure a high level of data security and compliance with healthcare regulations such as HIPAA. Integrate machine learning and AI into analytics. We also help build: Inpatient data marts (to store and structure patient information from EHR, including demographics, diagnoses, timestamps across care processes and pathways, and billing details) Inpatient dashboards, which do not require significant technical skills to segment the population (by “method of arrival,” “discharge destination,” “clinical service line,” “discharge unit,” “ICU utilization,” and other variables), but provide the possibility to create detailed reports in near real-time and share them for distribution, and export them in customizable formats (such as Excel, PDF, PowerPoint, or image files). If you're looking for expertise in data analytics, data integration, data infrastructure, data platforms, HL7 interfaces, workflow engineering, and development within cloud (AWS, Azure, Google Cloud), hybrid, or on-premises environments, we are ready to serve your needs. Contact us today to discuss your project requirements.

If Accountable Care Organizations manage to improve healthcare quality and reduce costs, they are rewarded with a share of the generated Medicare savings. To be eligible for that share, ACOs pass an annual assessment and prove their efficiency in thirty-four categories. However, a lack of relevant tools that would allow ACOs to estimate progress on the way and make timely improvements often prevents them from scoring high. As a result, ACOs fail to reach their aims and get a share of the generated Medicare savings. Applying data analytics and several other organizational measures helps tackle such issues. Challenges of Data Access for Analytical Purposes The benchmarks for the ACO annual performance assessment become higher with every new year. That is why the quality and transparency of the data from each provider inside the ACO are vital. It should appear timely and be easily accessible for further analysis and sustainable results. While tackling those demands, ACOs face the following issues: Delays in getting actionable data to engage patients Some providers receive the data about their ACO group aggregated performance once a month Some clinics have limited access to data, which restricts the possibility to use it for improvements—for example, if only one person has access to the information Limited access to data leads to delays in sharing the results about the performance and a lack of knowledge about how to use the analytics and how to apply the insights generated by it Limited access to the analytics app also leads to concerns regarding the data accuracy Insufficient transparency results in the inability to track the high performance of peer providers. This creates an impression of unachievable goals and an absence of possibility to provide mutual coaching and training Lack of different information levels about performance for various stakeholders Absence of holistic approach to motivate providers to improve for sustainable results Features of Data Analytics Software to Track ACO MSSP Measures ACOs should be able to track and manage the performance of their providers during the year and check the compliance with the CMS requirements. A necessary precondition for that is wide access to analytics software for business executives, practice managers, doctors, nurses, and other stakeholders. They should be able to: Identify the specific measures that need to be completed for each patient (by integration of the provider schedule with patient-specific data into the analytics application) Evaluate both individual and general clinic performance Examine the data in the analytics application before the patient visits. It allows medical experts to select the right measure that has not been yet applied Be able to specify each measure at any moment and improve it before the dates of the reports Based on their roles, analyze visualizations that demonstrate performance assessment results and get actionable insights on possible ways of improvements and required numbers of patients who need care to be able to show better measures. Clinician visualizations allow for peer comparison, in the result of which providers may contact the top performers to understand how to improve ACOs, in partnership with reliable healthtech software product companies, develop a strategy to drive improvements in data analytics. This may even include reaching out to CMS to clarify measure requirements, clearly identifying the inclusion criteria, exclusion criteria, and denominator for each measure. Organizational Measures to Implement Analytics Software It’s not enough just to implement any analytics software to automate workflows. A lot of organizational efforts are required. Some of them are critical because they directly affect the quality, on top of which the high-quality analytics is laid. Provider workflow should be standardized, ensuring consistency in documentation within the EMR All stakeholders should pass personalized education. It is important to understand how to apply filters to find and visualize the most relevant data, create bookmarks for the information that is often referred to, such as individual performance dashboards, and see the comparison with other providers in the group. At regular weekly meetings, reports and visualization dashboards are presented to providers so they can assess performance, compare it with previous data, validate information iteratively, and make improvements before preparing internal or external reports. What Benefits Can Practices Expect from Using Data Analytics? The ACOs that had already benefited from the analytics software notice such improvements as: increased indicators of influenza immunization and pneumonia vaccination raised numbers of population who passed body mass screenings increased screenings for future risk of falls, tobacco use, and cessation intervention better monitoring of the patients with clinical depression and developing a follow-up plan for them increased number of patients with blood pressure monitoring prescribing antithrombotic drugs, such as aspirin, for those suffering from ischemic vascular disease improvement in diabetes HgbA1c poor control, and in the number of patients with diabetes receiving eye exams improvement in the documentation of current medications in the medical record Improved above-mentioned measures may result in achieving the top position among national ACOs. How Else Can Practices Use the ACO Analytics Software? ACO analytics software may indicate lower-than-expected metrics, for instance, for breast cancer screenings. Thanks to this insight, practices may focus on raising awareness among the population about the necessity of completing mammograms – by proactively contacting patients who have not yet passed screenings. During a patient visit, the care team can see that a patient hasn’t received a required mammogram. The procedure may be scheduled for the same day. In case of detection of an early stage of breast cancer, lifesaving treatment starts as early as possible. Without the patient data from the analytics software, the treatment might never happen. Analytics software also helps to identify knowledge gaps. For instance, the clinic may perform required counseling, however, it may fail to save this data correctly. As a result, the measured performance can be assessed negatively even if patients received proper care. Analytics applications help to find the errors in the documentation and correct them before the deadlines. Not only do members of ACOs benefit from the ACO analytics software. Some specialized providers do not have to report ACO measures but may still use the tool to identify patients who, for example, could achieve improved blood pressure control. Therefore, the distribution of best practices in preventative care results in better patient outcomes. How Belitsoft Can Help Belitsoft is a full-cycle software development and analytics consulting company that specializes in healthcare software development. We help top healthcare data analytics companies build robust data analytics platforms. For integrated data platforms developed to collect, store, process, and analyze large volumes of data from various sources (Electronic Medical Records, clinic management systems, laboratory systems, financial systems, etc.), we: Automate data processing workflows (cleansing, standardization, and normalization) Configure scalable data warehouses Set up and implement analytical tools for creating dashboards, reports, and data visualizations Ensure a high level of data security and compliance with healthcare regulations such as HIPAA Integrate machine learning and AI into analytics. We also help build specialized analytical applications like ACO MSSP Measures to: Monitor 34 quality measures covering various domains such as patient experience, care coordination, preventive health, and management of at-risk patient populations Compare their performance metrics against industry standards and best practices, identify areas for improvement, and track progress over time Understand complex data and quickly identify trends and anomalies with interactive dashboards and visualizations Prepare reports for submission to the Centers for Medicare & Medicaid Services (CMS) by automating data collection and generating necessary documents If you're looking for expertise in data analytics, data integration, data infrastructure, data platforms, HL7 interfaces, workflow engineering, and development within cloud (AWS, Azure, Google Cloud), hybrid, or on-premises environments, we are ready to serve your needs. Contact us today to discuss your project requirements.

Hospitals The average hospital generates terabytes of data every day - from EHRs, labs, pharmacy systems, billing systems, scheduling apps, and devices. Without BI, the data stays separate, slow to use, and not helpful when quick decisions are needed. BI consultants bring it together. They build dashboards for clinical staff, predictive models for risk managers, and workflow analytics for COOs. And increasingly, they’re sitting closer to the C-suite - not just reporting numbers, but highlighting what matters. Hospital systems, from top-tier academic centers to regional providers, are building dedicated BI departments.  Rely on our dedicated Power BI developers, experienced in building custom BI solutions tailored to clinical, financial, and operational needs. We help hospitals track the right KPIs, spot risks early, and make confident, data-driven decisions. BI Use Case #1: Better Care Hospitals can’t improve outcomes if they don’t know what’s going wrong, where, and with whom. BI teams monitor outcome KPIs: Readmission rates Post-op infection trends Discharge delays Clinical adherence gaps When BI is embedded in clinical teams, providers get alerts - not after the fact, but in time to act. One real-world case: hospitals using BI to flag sepsis early based on vitals and lab values — reducing ICU admissions and mortality rates. BI doesn’t replace clinicians but amplifies their vision. BI Use Case #2: Operational Efficiency BI consultants deliver performance insights on: Bed occupancy forecasting Nurse shift utilization Equipment downtime Patient flow bottlenecks Cleveland Clinic’s deployment of BI tools across operations is a gold standard: digitized workflows, integrated scheduling, and real-time resource tracking. The result? Fewer delays, less waste, better care. BI Use Case #3: Financial Visibility Healthcare finance is about seeing where revenue leaks, cost creeps, and margins disappear. BI dashboards surface: Revenue by service line Payer mix trends Length of stay vs. cost curves Denial rates and root causes The smartest CFOs use BI to answer questions faster: “Which DRG categories are underwater?” “Where are we losing revenue cycle velocity?” “How does staffing level affect case cost?” BI consultants don’t just help you measure the cost of care - they help you redesign it. BI Use Case #4: Compliance Healthcare is among the most regulated industries in the U.S. CMS, HIPAA, HEDIS, Joint Commission - the acronyms just keep coming. BI makes compliance predictable: Automated reporting to regulators Real-time privacy monitoring (unusual EHR access, etc.) Flags for missing documentation before audits occur Instead of scrambling when auditors arrive, hospitals with strong BI systems are already prepared, and logged. And when privacy breaches or billing errors are caught early? That’s BI saving reputation, not just revenue. Every large hospital system in the U.S. is now actively building analytics teams. The demand isn’t for domain-specific BI consultants who can work across: Epic/Cerner data models Claims systems Operational data from ERP and HR platformsHIPAA-aligned reporting frameworks In competitive health markets - especially value-based care regions - BI has shifted from innovation to necessity. Health Insurance Companies (Payers) Health insurers are becoming population health platforms, fraud monitors, and consumer engagement engines. The companies winning in 2025 are the ones with the sharpest visibility into cost, risk, and value. BI Use Case #1: Controlling Spend Healthcare costs are still rising. Wasteful utilization, unoptimized provider networks, and uncontrolled chronic conditions erode profitability daily. BI consultants are how insurers fight back  with math. BI teams analyze: Claims by cost driver, region, provider, or condition Patterns of overutilization (unnecessary imaging or ER visits, etc.) Projected future costs based on comorbidities, age, lifestyle, and geography When payers automate utilization management with BI, they flag the wrong services earlier. BI gives insurers the data to negotiate smarter contracts, with hard numbers behind every rate and benchmark. In a value-based care world, data is leverage. BI Use Case #2: Population Health The old model: react to illness, reimburse care. The new model: predict illness, prevent cost. BI is the bridge. Predictive analytics built by BI consultants can: Flag patients likely to be hospitalized within 12 months Identify populations trending toward costly conditions like diabetes or COPD Pinpoint care gaps by geography, provider, or demographic CMS star ratings, HEDIS scores, and ACA quality metrics are tied directly to financial performance and reimbursement. If your health plan can intervene early via a wellness campaign, a care manager phone call, or a targeted benefit - you lower spending and boost quality ratings. That’s margin expansion and market differentiation, powered by BI. BI Use Case #3: Fraud and Abuse In insurance, the fraud may be a pattern that looks plausible until you zoom out. That’s BI’s job. Advanced BI systems monitor: High-volume billers across time Duplicate or inflated claims Time-based logic (overlapping surgeries or implausible procedure schedules, etc.) Member usage anomalies Machine learning layered on top of BI platforms can score provider and member risk in real time - before the payout. Prevention beats recovery. This kind of proactive BI is both ROI-positive and a compliance win. BI Use Case #4: Personalization at Scale If your member experience still feels like a call center and a paper EOB, you’re going to lose to the next generation of digital-native plans. BI enables: Member segmentation based on health profile, engagement level, and benefit usage Targeted outreach for condition management, preventive screenings, and plan upgrades Product development tuned to real market needs (virtual care bundles for high-utilizers, etc.) Cigna’s “Health Advisor” wellness program is a perfect example. By mining member data, they identified who would benefit most from a health coach, prioritized outreach, and tracked the ROI in both satisfaction and downstream cost. This is retention science. BI Use Case #5: Compliance Star ratings, provider coverage, claims processing speed, and complaint handling - all of these reporting requirements need reliable, timely data. BI platforms automate: HEDIS and CMS measure tracking Denial rate reporting Claims aging and resolution summaries Audit logs and escalation flags BI lets you monitor your service quality in real time - from call center abandonment rates to claims processing times. That means you’re always audit-ready. Pharmaceutical and Life Sciences Companies Drug discovery, market strategy, regulatory compliance - every function now runs better with BI. Drug R&D: Turning Years into Quarters The cost of bringing a new drug to market still sits north of $1B. A lot of drugs still fail during development. BI helps by finding issues early and helping teams fix them faster. BI consultants in R&D work across: Clinical trial design - optimizing protocols using historical outcome data Real-time monitoring - spotting drop-off in recruitment or adverse events Trial performance analytics - comparing site efficacy, patient adherence, safety flags When Novartis invested in data lake infrastructure for its R&D arm, the intent was  faster iteration. BI makes it possible to adapt trial strategy while the trial is still in motion - saving time, dollars, and reputational risk. The result? Drugs move through phases with fewer surprises, and fewer delays. Manufacturing and Supply Chain When Pfizer partnered with AWS to deploy ML-powered BI tools on the factory floor, they were solving a problem: batch variability and quality control. BI systems help pharma manufacturers: Detect anomalies on the line - before defective batches are produced Optimize yield and machine uptime Forecast demand across global markets - and match production accordingly Monitor environmental data for compliance In an industry where a delay can derail national drug supply - or a single contaminated batch can trigger regulatory audits - BI is the difference between proactive control and expensive overreaction. At Merck, analytics-driven supply chain oversight improved on-time delivery rates and lowered operational overhead. BI helped operations and protected revenue. Commercial Strategy: Selling Smarter, Not Just More Pharma commercial teams are flooded with data — provider behavior, prescription trends, demographic shifts, campaign attribution.  BI consultants in commercial roles help answer: Which physicians are influencing prescribing trends in target geographies? What’s the ROI of our current drug marketing mix — by channel? Where is sales force activity misaligned with actual demand? Better BI enables precision sales: Tailored messaging by provider segment Optimized territory assignments Dynamic targeting based on real-time prescription activity BI isn't just showing where your sales are happening but where they should be. Compliance and Pharmacovigilance: BI Keeps You Out of the News In life sciences, regulatory risk is existential. FDA holds, label changes, or missed reporting deadlines can mean millions lost and years set back. BI platforms protect the enterprise by: Automating trial protocol compliance checks Surfacing adverse event trends post-launch Preparing standardized regulatory filings faster and with more accuracy Flagging quality issues before inspections Pharmacovigilance teams rely on BI to monitor global reports in real-time.  And from a governance standpoint, BI provides traceability and audit readiness - so when regulators ask “what did you know and when,” your team has the answer. Whether you're in drug discovery, clinical operations, manufacturing, or commercial, BI consultants are now embedded as strategic resources: Clinical data analysts supporting R&D velocity Supply chain BI architects driving predictive operations Market intelligence teams guiding brand launches and lifecycle management Compliance BI engineers ensuring regulatory readiness 24/7 Johnson & Johnson’s MedTech division hiring a Principal BI Consultant isn’t a one-off. BI is moving up the organization chart - into strategic planning, innovation councils, and executive dashboards. HealthTech Startups and Digital Health Companies HealthTech startups - ranging from digital health app makers and telemedicine providers to healthcare AI and analytics platforms - are another major source of demand for BI consultants.   BI Is the Feedback Loop Between Product and Patient Outcomes Most healthtech startups position themselves as outcomes-focused. You’re improving chronic care. Streamlining provider workflows. Reducing ER visits. But unless you can measure that impact, you’re just another well-designed app in a crowded App Store. BI gives you the feedback loop you need: Are patients using the tool as intended? Are outcomes improving across cohorts? Which features correlate with better results? A diabetes management platform, for example, is judged by changes in A1C, hospitalization rates, and care plan adherence. BI consultants build the dashboards that track those KPIs across thousands of users - and let your team iterate based on real impact. That’s what investors and enterprise customers expect in 2025: a line from product to health improvement, backed by live data. Startups live or die by resource efficiency. BI helps you: Identify your lowest CAC channels - and double down Monitor churn risk signals- and course-correct proactively Optimize clinician staffing - based on usage patterns and service bottlenecks Without these insights, you’re wasting ad dollars, burning cash on underused features, and missing key UX flaws. With BI in place? You’re making precision decisions: which A/B variant to ship, which referral program drives LTV, which user cohort needs a re-engagement campaign next week. Investors Don't Fund Claims BI is how you tell your story in numbers - not just in vision decks. Every enterprise client and every investor in healthcare asks: Does it work? Show me the data. Whether it’s: A 22% drop in readmissions A 14-day reduction in average diagnosis cycle A 3x increase in therapy adherence You can’t make those claims without BI capturing, validating, and packaging the evidence. And when those metrics show up in dashboards you can demo live? You’re selling proof at scale. Startups that don’t build this layer early either find themselves retrofitting analytics under pressure - which is always more expensive and less convincing. Even pre-Series A startups are hiring BI consultants as fractional experts to get dashboards running, define KPIs, and structure the first data pipelines. BI-Driven Startups Are the Product Some of the most successful startups in healthtech are analytics-first. Think: Komodo Health — turning national-level healthcare data into predictive signals Innovaccer — creating infrastructure for value-based care through real-time insights Clarify Health — offering BI tooling directly to providers and payers These companies don’t just use BI. They sell it. They hire BI consultants as product engineers. As client success partners. As platform architects. If your company plays in AI, clinical decision support, or population health intelligence — your entire roadmap is tied to the quality and flexibility of your BI foundation. Every funded healthtech startup is hiring BI roles right now - not just engineers, butthinkers who know healthcare workflows, regulatory nuance, and go-to-market data strategy. Why? Because they need to track usage and engagement in week one. Because they need to launch with compliance and reporting infrastructure already running. Because they need evidence of value before the next raise, not after. Founders that prioritize BI staffing now? They move faster. How Belitsoft Can Help Belitsoft helps healthcare organizations turn raw data into strategic decisions - by combining deep BI expertise with custom software development. Whether you're a hospital modernizing operations, a payer optimizing cost and risk, a pharma company running trials, or a healthtech startup proving impact - Belitsoft builds the tools that make your data work. What Belitsoft Can Offer Across Healthcare Sectors Hospitals and Health Systems Belitsoft can deliver: Custom BI dashboards for clinical staff, COOs, and risk managers, using EHR, pharmacy, lab, and device data. Real-time alert systems for events like sepsis risk, readmission, discharge delays. Predictive analytics for staffing optimization, patient flow, and equipment uptime. Integration services for Epic, Cerner, and other hospital systems into centralized BI platforms. Financial BI modules: denial tracking, DRG profitability, length of stay vs cost curves. As a custom development firm, Belitsoft can also build tailored modules on top of existing hospital IT infrastructure (augmenting BI in existing Cerner/Epic stacks with custom visualization or alerting tools, etc.). Health Insurance Companies (Payers) Belitsoft can offer: BI dashboards for claims analysis, population health trends, overutilization, and risk scoring. ML-assisted fraud detection tools (detecting anomalies, overlapping claims, inflated codes). HEDIS, CMS, and ACA reporting automation. Custom data pipelines that consolidate member engagement, claims, and provider behavior into one analytics layer. Member segmentation engines for targeted outreach, retention campaigns, and benefit design. Belitsoft’s strength is in stitching together data from disparate sources - legacy systems, call centers, digital tools - into one coherent BI engine. Pharmaceutical and Life Sciences Companies Belitsoft can provide: Trial analytics platforms: real-time monitoring, protocol optimization, patient adherence tracking. BI dashboards for manufacturing: predictive quality control, batch anomaly detection, equipment performance, supply chain forecasting. Commercial analytics systems: provider-level prescribing behavior, marketing attribution, sales team alignment. Compliance monitoring tools: tracking adverse events, trial deviations, and filing readiness. Data lake architecture & integration to support high-scale, multi-source analytics across R&D, supply chain, and commercial divisions. If a pharma company needs a Looker-like system with specific regulatory rules or integration with AWS/Microsoft stacks, Belitsoft can custom-build it. HealthTech Startups & Digital Health Belitsoft can support with: Early-stage BI architecture: setting up dashboards, defining KPIs, building pipelines for product/clinical/outcome tracking. Engagement and retention analytics for SaaS platforms (telemedicine, chronic care apps, etc.). Custom modules for A/B testing impact, clinician utilization, UX bottlenecks, re-engagement triggers. Real-time outcomes monitoring (A1C drops, diagnosis cycle time, readmission rates, etc.). Embedded analytics in client-facing tools (providers, payers) - product-grade BI. For data-first startups (like Innovaccer or Komodo), Belitsoft can serve as an outsourced product analytics team - building BI tools not just for internal use, but as part of the actual product offering.