Straight-Through Billing
Medical billing complexity and massive volumes of daily claims render manual claims processes incapable of protecting both the provider and the payer from underpayments, overpayments, and billing compliance violations. Straight-Through Billing (STB) addresses complexity and volume processing problems by automating the majority of the claim flow and focusing the billing follow-up specialists on exceptions only. An STB process flags problems routes them for follow-up and enables online correction and resubmission. The STB methodology implements billing service transparency and focuses management on strategic process improvement opportunities. Straight-Through Billing integrates the billing process into the practice management workflow, automates the vast majority of transactions, focuses manual labor on exceptions, and establishes a process for continuous improvement. Remember: Straight-Through Billing offers a comprehensive approach to improving the billing process, integrating various components, and promoting continuous improvement. Practice Management Integration First, integrated practice management and billing workflow connects patient scheduling, medical record management, and billing into a single process. Every participant in the practice management workflow receives a unified and coherent picture of the practice workload, patient and provider location, resource availability, and cash flow. However, integrated with Electronic Health Records, practice management systems are more beneficial. Electronic health records (EHR) are digital formats of a patient’s chart. They contain all the information about a patient’s health. This includes medical history, allergies, immunizations, previous treatments, medication history, past diagnoses, history of substance abuse (if any), and so forth (Shah, 2021). Transaction Automation Transaction automation streamlines and expedites the billing process by automating claim validation, payer message reconciliation, and billing workflow management: Automated claim validation eliminates errors downstream and reduces processing time because it flags errors before submitting the claim to the payer. Automated claim message reconciliation eliminates the costly search for the original claim and standardizes message communication, eliminating the need to decipher the (often cryptic) payer’s message. Automated billing workflow management drives the follow-up discipline required for the resolution of claim denial and underpayment incidents, and it establishes a high degree of process transparency for all billing process participants, resulting in full and timely payments. Automated billing increases the net collection rate due to quick claim turnaround and efficient follow-up. Respond to your denials within 5-21 business days of receiving them, using our Daily Denial Email Alerts (Qureshi, 2022). Focus on Exceptions Focusing manual labor on exceptions requires timely exception identification, routing to follow-up personnel, online error correction, and rigorous follow-up tracking. Again, process transparency enables tracking exception follow-up as implemented in ClinicMind-like systems. Another significant benefit of automated medical billing is the ability to track and analyze financial data. With this, healthcare facilities can monitor their revenue cycles, identify growth opportunities, and generate detailed financial reports (Polo, 2023). Continuous Process Improvement Finally, a process for continuous improvement requires continuous observability of every process attribute and a modification methodology for both automated claim processing and manual exception follow-up tracking. Straight-Through Billing implements billing transparency by design because billing transparency is an integral attribute of every component of the STB process. It also enables businesses to streamline their billing operations, reduce errors, enhance efficiencies, and improve the customer experience (Ward, 2023). Straight-Through Billing Architecture The Straight-Through Billing systems architecture mirrors the architecture of general Straight-Through Processing (STP) systems developed for the financial services industry. Such systems require effective workflow management, a knowledge-based validation system, connectivity to all process participants (including online data reconciliation), and tracking of problem resolution. Therefore, a typical ClinicMind-like STB system has a three-tiered architecture: Back-end processing engine designed for a high-volume transaction processing environment Middle tier, using Java Servlet technology Front end, using an HTML-JavaScript, zero-footprint client Did You Know? The STB architecture is inspired by the systems used in the financial services industry, showcasing the transferability of advanced processing concepts across different domains. An STB system (e.g., ClinicMind) based on the methodology outlined here implements rich functionality, which allows the following to be automated: Computer-aided preferential patient scheduling Integrated electronic medical records Online computer-aided coding Real-time claim validation and patient eligibility testing Electronic claim submission Payment posting, reconciliation, and verification of meeting contractual obligations Monitoring of audit risk and billing compliance Tracking of denial appeal process Quantitative STB Management Straight-Through Billing methodology allows for quantitative management since the likelihood of the entire process failing can be estimated as the product of such items for each individual workflow step. A ClinicMind-like STB system tracks the percentage of clean claims (claims paid in full, and within the allocated time frame, without any manual intervention) and focuses the management on those process aspects that yield the greatest potential improvement. Thus, STB methodology focuses on exceptions at both the tactical and strategic management levels and can help to improve cash flow and reduce outstanding invoices by providing real-time visibility into billing and payment status (Mielnicki, 2022). Modern Insights and Research In the ever-evolving field of medical billing, staying ahead of the curve is crucial for achieving financial excellence in the healthcare industry. Let’s embark on an exhilarating journey into the future of medical billing, where the convergence of electronic health records (EHRs), artificial intelligence (AI), real-time analytics, and collaborative efforts reshapes the revenue cycle landscape. Brace yourself for a transformative exploration that revolutionizes processes, enhances data accuracy, maximizes financial outcomes, and ushers in an era of unparalleled efficiency and effectiveness in the dynamic realm of medical billing. 1- Role of Blockchain Technology in Billing Systems The seamless integration of electronic health records (EHRs) and billing systems is revolutionizing the field of medical billing. Gone are the days of fragmented medical records scattered across various healthcare organizations. With blockchain at the helm, a distributed EHR ecosystem emerges, ensuring a smooth flow of information between providers. By eliminating manual data entry and ensuring accurate documentation, this innovative technology guarantees accurate and secure documentation, eliminating errors and speeding up reimbursement processes (Cerchione et al., 2022). But that’s not all. Blockchain brings an unparalleled level of data integrity and security, employing cryptographic techniques to safeguard patient information from prying eyes.
No-Show Risk Management
When patients miss appointments, they interrupt the flow of patient care, impede clinic productivity, and signal an eroding patient loyalty. The rate of no-shows runs at 30% for the average family practice. A missed appointment amounts to missed billing revenue. Worse, if clinicians are part-time or full-time staff rather than contracted, they sit idle on the company clock, losing money with each passing minute. Finally, a missed appointment could be a symptom of a deserting patient, signaling a potential loss of long-term billing revenue. Most clinics lose an average of 20% of their revenue due to missed appointments. Lost revenue may not be the largest problem caused by no-shows. Other problems span health damage, patient liability risks, reduced accessibility, and impeded resident education. Rigorous no-show management methods using advanced technologies integrate scheduling and billing data, reduce no-show rates, and improve associated revenues by more than 50%. They also mention the comparable improvement of long-term patient loyalty (Hashim et al., 2001). No-Show Impact on the Clinic Figure 1. No-Show Impact (Hayhurst, AthenaHealth) A missed appointment poses five kinds of problems: Health damage – A patient’s health can be damaged due to interrupted continuity of care or a missed opportunity to solve an acute health problem. The doctor also loses an opportunity for a timely review of patient health, treatment progress, etc. Liability risk – A patient who misses an appointment and suffers an injury may have a viable cause for a lawsuit against the practice. To avoid such risk, the doctor must maintain evidence of giving clear directions and making reasonable efforts to ensure the patient’s compliance with the care program, including keeping follow-up appointments. Reduced accessibility – Other patients are postponed and don’t get access to care because of a no-show or canceled appointment. Impedance to medical education – A resident or intern misses an opportunity to learn and improve care skills. Loss of revenue – The clinic cannot make up revenue due to missed appointments. A financial impact arises from wasted resources, such as staff time, equipment, and facility utilization, that were allocated for the no-show patient. No-Show Frequency Distribution No-show rates average about 20%: 10% of clinics have less than 10% no-shows, 42% of clinics have 10%–20%, 34% of clinics have 20%–30%, and 14% of clinics have more than 30% no-shows (Izard, 2005). Further, the top 10 clinics regarding the lowest no-show rates range from 3%–9% for no-shows, while the bottom ten clinics reach 33%–57% (Moore et al. 2001). Common reasons behind No-show Forgetfulness: Patients may simply forget about their appointments due to a busy schedule, lack of reminder systems, or cognitive factors. Transportation issues: Lack of transportation or difficulty accessing reliable transportation can prevent patients from attending appointments. Fear or anxiety: Some patients may experience fear or anxiety related to medical procedures, test results, or hospital settings, leading them to avoid or cancel their appointments. Financial constraints: Financial limitations, such as the inability to afford healthcare services or medications, may result in patients skipping or postponing appointments. Illness or emergencies: Patients may have unexpected illnesses or emergencies that prevent them from attending their scheduled appointments. Lack of awareness or understanding: Patients may not fully comprehend the importance of their appointments or the consequences of missing them, particularly for follow-up care or chronic conditions. Language and cultural barriers: Language barriers or cultural differences can impede effective communication and understanding, leading to missed appointments. Long waiting times: Lengthy wait times at hospitals can discourage patients from attending appointments, particularly if they have competing priorities or other time constraints. Stigma or fear of judgment: Patients with certain medical conditions or mental health issues may experience stigma or fear of judgment, causing them to avoid seeking care or attending appointments. Personal or work-related conflicts: Conflicts arising from personal commitments, work schedules, or other obligations may interfere with appointment attendance (Marbouh et al., 2020). The image below shows common reasons for missed appointments (Saif et al., 2018). According to a study, among all patients, those who never have a no-show appointment have an attrition rate of slightly less than 19 percent. In contrast, almost 32 percent of patients with one or more no-shows do not return to the same practice within 18 months (Hayhurst, AthenaHealth). Three-Phase No-Show Management Strategy An effective no-show management strategy is based on tracking, rescheduling, and follow-up: Tracking Record all no-shows and reconcile them with billing daily. Record no-show reasons and follow-up notes in patient records. Review end-of-day reports daily. Rescheduling in real-time Allow patients to request appointments online using the Internet Overbook and use waiting lists. Fill new openings with walk-ins or patients from the waiting list. Follow-up Activate a sequence of reminder calls/emails to all patients ten days, two days, and one day before their appointments. Place follow-up calls to determine reasons for no-shows and reschedule the patients. Reminder calls for upcoming appointments and follow-up calls on recent no-shows are effective strategies for billing revenue protection because they reduce the number of no-shows and help early identification of incipient patient attrition and other patient-related problems (Hashim et al., 2001). Follow up with warning letters after one no-show. Dismiss patients from the practice after three no-shows. Reminder calls or emails before an appointment remains the most effective method to prevent missed appointments. Additionally, sending reminders via email and allowing patients to confirm online turns an office reminder into a patient’s action item, significantly outperforming the impact of a voice message or postcard. While recognizing the benefits of reminder calls, busy practice owners often neglect or postpone reminder and follow-up calls because of other office management priorities, such as personnel issues or billing. As with any other management initiative, a reminder call strategy must be implemented systematically and consistently to get results. Note that outsourcing reminder calls to calling services and using the Internet reduce the cost of reminders. Therefore, reaching all patients before their appointments makes good business sense. Ways to reduce No-shows Automation of appointment reminders: Implementing automated appointment reminders can significantly reduce
AI for outcomes-based compensation in healthcare
What is outcomes-based compensation in healthcare? Compensation plans in the healthcare industry have undergone a paradigm shift, with more providers moving away from volume-based to outcome-based compensation for their employees. This is partly attributable to the rising healthcare costs and enhanced patient empowerment, with a growing need for better quality of service delivery (Zigrang, 2022). Volume-based models compensate providers for the quantity of care delivered rather than the impact on the health status of patients (Tai et al, 2014). The vision for outcomes-based compensation in healthcare revolves around incentivizing and rewarding healthcare providers based on the outcomes they achieve in patient care rather than just on the volume of services delivered. This approach aims to improve the overall quality of care, enhance patient outcomes, and reduce healthcare costs. However, existing literature on outcomes-based compensation models shows mixed results in terms of impacts on quality of care and costs, with some reporting significant cost savings and others reporting increased costs of care, as expounded later on in this chapter. In an outcomes-based compensation model in healthcare, providers are encouraged to focus on delivering measurable results and positive patient experiences. This may involve achieving specific health outcomes, such as reducing hospital readmission rates, improving patient satisfaction scores, or effectively managing chronic conditions. By aligning compensation with outcomes, healthcare organizations aim to drive better patient outcomes, ensure patient safety, and enhance healthcare delivery. Healthcare outcomes reflect the quality of care offered by practice and remain stable over time compared to process measures, which keep changing over time. For instance, the target outcomes in a diabetic care clinic include reduced blindness, reduced amputation rates, improved self-management and confidence, and reduced heart attacks. These target outcomes that matter to patients the most tend to remain stable over time regardless of where you practice. On the other hand, process measures such as fundoscopic examination, blood glucose assessment, foot care, and medication review may vary over time. This forms one of the basis for outcomes-based compensation models (Dunbar-Rees, 2018). The outcomes-based compensation model offers several benefits to different players in the healthcare field. Patients get to enjoy quality care over volume, with the potential to address health inequalities. This is so because the model emphasizes outcomes that matter to patients, which tend to remain constant regardless of the geographical location. For instance, the target outcomes for a diabetic care clinic in Kisumu, Kenya, Africa, would be more or less the same as for a clinic in Atlanta, Georgia, USA. For the providers, outcomes-based compensation helps reduce the wastage of resources and unnecessary interventions by enabling efficient resource allocation. It also reduces fragmentation of care by encouraging collaboration and coordination across clinicians and specialties. The payers benefit through reduced wasted healthcare spend as well as focusing on buying healthcare that is based on outcomes that matter most to their beneficiaries (World Economic Forum, 2023). The outcomes-based model has been implemented across different healthcare facilities worldwide in a bid to improve the quality of care and reduce costs. There are several studies showing the impact of outcomes-based models on the quality of care, resource utilization, and healthcare costs. These studies show varied outcomes, with some reporting positive impacts and others reporting negative impacts or no significant impacts. For instance, the Pioneer Accountable Care Organizations (ACO) implemented by the Center for Medicare and Medicaid Services in the USA as an outcome-based compensation model reported a reduction in healthcare costs by approximately $385M in two years compared to the previous volume-based compensation model, with no difference in quality of care (McCarthy, 2015). The Medicare Shared Savings Program, which was also designed to incentivize cost reduction, reported similar cost savings of $385M dollars over one year of implementation (Eijkenaar & Schut, 2015). However, some studies suggest that outcomes-based models were associated with additional healthcare costs, mainly in the form of bonuses and incentives paid out to healthcare workers. For instance, the Quality and Outcomes Framework (QOF) implemented in the UK as a pay-for-performance program was reported to have spent about US $9 billion on incentive payments over a period of just seven years (Ryan et al, 2016). Outcomes-based compensation models impact on the quality of care delivered to patients, albeit to varying extents from the available literature. In one study, the Quality and Outcomes Framework model operationalized in the UK to incentivize family practitioners for target patient outcomes resulted in an increase in the median practices achieving the target HbA1C levels for diabetic patients from 59% to 66.7% in two years. (Vaghela et al, 2009). However, another study evaluating the impacts of the same Quality and Outcomes Framework in the UK on hypertension reported no significant change in blood pressure monitoring rates and treatment intensity attributable to the program. There was no significant difference in the cumulative incidence of stroke, renal failure, and heart failure as well (Serumaga et al, 2011). With such mixed data on the impacts of pay-for-performance on costs and outcomes, it is evident that this alone may not be sufficient to improve the quality of patient care, and more factors need to be accounted for in order to achieve optimal patient care quality. Another study in rural Kenya evaluated the utility of outcomes-based compensation models in improving the management of suspected malarial fevers. The program rewarded measures of process quality of care, including the proportion of patients correctly given antimalarial drugs based on test results. Incentives were provided to facilities with increased rates of treatment for confirmed malaria cases, as well as those with reduced treatment rates without any confirmatory tests. From the study, the odds of receiving treatment following a negative malaria test in the intervention arm was 0.15 relative to baseline, compared to 0.42 in the comparison facilities that were not enrolled in the program. This translated to a 2.75 times greater reduction of inappropriate prescription of antimalarial drugs in the incentivized groups compared to the comparison groups (Menya et al, 2015). Another instance in which the outcomes-based model has been utilized is through Humana’s
The Network Effect
People handle adversity differently; some break down sooner than others. When a team focused on a common goal faces adverse conditions, dissent among some team members precludes them from reaching a shared goal. Under extreme conditions, a mutiny isn’t just mission-critical—it can leave everybody dead. The famous explorer Ernest Shackleton, best remembered for his Antarctic expedition of 1914–1916 in the ship Endurance, managed such risks by assigning the whiny, complaining crew members to sleep in his own tent and share the chores with him. Clustering the “complainers” with him minimized their negative influence on others, and this helped his team survive and accomplish their goals. Medicare Vs. Private Payers It’s essential to acknowledge the contrasting dynamics between Medicare and private payers. Medicare, as a government-backed program, follows distinct regulations and reimbursement structures, while private payers operate in a competitive market with more flexible terms. The negotiation strategies and considerations may differ significantly when dealing with these two payer types. Payment negotiations Actively negotiating with payers is crucial for independent medical practices. However, many providers lack experience or haven’t been successful in past negotiations due to inadequate preparation. To ensure a fruitful negotiation, it’s vital to: Know Your Data: Understand your practice-specific data, including patient volume, charges, reimbursement history, and more. Know the Terms of Each Contract: Familiarize yourself with your current payer-specific contract terms, especially the reimbursement schedule and the claims filing data. (Babcock, 2021) According to a KFF analysis, as seen in the image below, private insurers often pay nearly double the Medicare rates for hospital services. Specifically, for outpatient hospital services, private insurance rates were found to be significantly higher than Medicare rates, averaging 264% of the latter. This difference underscores the varying dynamics and market powers between Medicare and private insurers. Policymakers and analysts continue to debate the necessity of high payments from private payers to compensate for the lower Medicare payments. (How Much More Than Medicare Do Private Insurers Pay? A Review of the Literature | KFF, 2020) Classification of Payment Models Payment models dictate how healthcare providers, including physicians and hospitals, are remunerated for their services. Each model inherently carries incentives and disincentives that can influence the balance between cost reduction and improving care quality. These two objectives often stand at odds. This report delves into the implications of Alternative Payment Models (APMs) in either mitigating or intensifying health disparities. However, before exploring these implications, it’s essential to understand the incentives and disincentives embedded within the prevailing payment models. These incentives play a pivotal role in fostering cost-efficient, high-quality care. The primary distinction among these payment methods lies in the unit of payment. This determines how financial risk is distributed between the payer and the provider. The nature of this risk can significantly influence the behavior of healthcare providers and the overall efficiency and effectiveness of the healthcare system (Quinn, 2015). Factors affecting payment negotiations According to AMA, it’s not just about the rates but also about the terms and conditions that can impact payment. For instance, some contracts might have clauses that allow payers to change rates without notice, or they might have stringent requirements for prior authorizations. Providers should be wary of “most favored nation” clauses, which can restrict them from offering better rates to other payers. It’s also crucial to be aware of the dispute resolution process outlined in the contract, should any disagreements arise. By being well-prepared and understanding the intricacies of payer contracts, providers can position themselves for more favorable negotiations and better financial outcomes. (American Medical Association & American Medical Association, 2022) Payer-provider conflict In the payer-provider conflict, the providers who accept lower reimbursement and who don’t challenge underpayments or delayed payments make it easier for the payers to maintain their market control (oligopsony). Recent research supports this notion, indicating that payers with larger market shares have more negotiating power in contract negotiations (HealthPayer Intelligence). ClinicMind’s network helps providers maintain their payment schedules and motivation by establishing a shared discipline for clients and billers alike in terms of both thought and action. Payers with Larger Market Share and Their Negotiating Power Payers that have a dominant presence in the local market have a distinct advantage when it comes to negotiating lower prices for physician office visits. A study conducted by researchers from Harvard Medical School found that health insurance companies with a market share of 15% or more negotiated visit prices that were 21% lower than those set by payers with a market share of 5% or less. For instance, payers with less than 5% of the market negotiated prices of $88 per office visit. In contrast, those with 5 to 15% of the market share settled for a price of $72, and those with more than 15% of the market share negotiated even lower at $70 per visit. The graph below shows this analysis. From Policy Changes to Physician Consolidation In 2010, President Barack Obama signed the Affordable Care Act (ACA) into law, a move that expanded Medicare’s reach by adding millions to its coverage. This expansion meant that more physicians had to accept Medicare rates, which have been systematically reduced over time. The ACA not only aimed to extend healthcare access to uninsured Americans but also set in motion a wave of consolidation in healthcare services. As Medicare adjusted its rates, private insurance companies followed suit. While they still paid above Medicare rates, they too began to reduce their payouts. This trend forced physicians to grapple with a challenging reality: working more hours for less pay. The Power of the Network Effect In response to these financial pressures, physicians began to see the value in consolidating their practices. By joining larger organizations, they could harness the network effect, gaining more significant negotiating leverage with insurance companies. This consolidation is not just about survival; it’s about strength in numbers. Large groups, especially those with revenues exceeding $1 million annually, have more room to negotiate than smaller entities. The Rise of Management Service Organizations (MSO) Amidst these challenges,