DHA 8007 Week 6 Assignment Accounts Receivable Management

Student Name

Capella University

DHA8007 Strategic Financial Management in Health Care

Professor Name

Submission Date

Accounts Receivable Management

The AR analysis days are crucial in evaluating the financial performance of the healthcare setting. The comparison of 2022 AR management of Westside Clinic showed improved results compared to 2021, when the AR management required 58 days to accomplish the required tasks in 59.2days. The AR management showed a positive tendency in 2022, and further reduction of the days is needed in the future to increase the cash flow. The analysis of the AR should inform financial leaders to make sure that healthcare facilities operate normally (Antysheva et al., 2020). During the evaluation, detailed information about the strategic evaluation, the financial trends in a long-term perspective, and risks of poor AR management is delivered. In addition, the trends that impact the revenue cycle and have an effect on the organisation strategy, patient outcome, and community health are provided.

Strategic Assessment

Financial analysis of the AR assisted in determining the mean days it takes to collect the receipts for the healthcare services. Based on the data analysis in 2021-2022, AR days declined to 58, which optimised the cash flow and financial stability of the organisation as they fell to 59.2. The strategic analysis is based on the three methods of cutting the AR days. The three alternatives to reducing the AR days are the use of technology, denial management system, and predictive analytics. Firstly, the implementation of artificial intelligence (AI) technology was to automate billing and collection processes (Nasution et al., 2020). The machine learning algorithm as a financial analysis tool would shorten the time of SCO and fasten the payments, lowering the AR days. 

Secondly, the management of denials was done to reduce the chances of claim declines and rejections (Chaudhuri et al., 2022). This is where a pre-investigation done prior to the claims would mean that there would be no erroneous claims that would cause denial. Improvement in the settlement of claims reduces claim reprocessing, and the AR cycle time is reduced. Thirdly, predictive analytics is applied throughout the revenue management cycle (RCM) to determine possible payment issues to avoid AR delays (Chaudhuri et al., 2022). The analytics came in handy in future payment prediction of the RCM system. Gathering data to determine the ratio of patients who have received care contributed to the ability to assess revenue and resulted in proactive decisions, which enabled the decrease in the AR growth in healthcare facilities.

• Plan for Managing Risk

The organisational environment risks in the process of collecting AR receivables are the disruption of the cash flow and the extra bad debts. More AR days are held as working capital; capital that can be utilized to traffic or engage in other productive activities. Receivables extension above 120 days affects the profitability of an organisation (Laghari and Ahmed, 2023). To start with, the verification system will be put into practice to confirm the patient’s insurance prior to the healthcare services. Pre-verification will help in reducing the number of rejections on claims. Secondly, monthly analysis of the denials shall be given to assess the common issues, such as coding mistakes or lack of information involved. Third, the AI technology will automatically submit claims, track their status online, and receive updates on the receivables. The technology helps to minimize the chance of human error and offers key information to optimize the process of collection and financial forecasting. Furthermore, patient knowledge will be enhanced, too, preventing payment issues, which applies to the on-time retrieval of the AR and removes delays.

Strategic Assessment to Monitor Days in AR

AR needs to monitor days, which will assist in the simplification of the cash flows and financial performance of the organisation. Monitoring of AR days in Westside Clinic will be critical to reduce the delays in collection, loss in revenues, and general financial stability of the organisation. The AR days ratio is used to denote the number of days between which a healthcare organisation receives billed amounts turned into cash (Antysheva et al., 2020). Therefore, monitoring days assessment in AR is necessary because the fewer AR days, the faster the collection and, consequently, the hospital is capable of cash management.

The three strategies with which healthcare providers can monitor the AR days are key performance indicators (KPI), predictive analytics, and AR tracking tools. Firstly, AR tracking applications are financial apps, which are displayed as interface dashboards with days in AR, time in the AR, and payer performance (Arora et al., 2024). The messages in the tracking instruments also assist in determining the cases where the AR days are exceeding the deadline. The real-time monitoring devices will therefore be employed to help the staff respond to the AR problems in a proactive fashion and make the collection more efficient.

Secondly, KPIs help the healthcare provider to define the main objectives of the AR management. The comparison between the hospital-related data on the AR days and national and regional benchmarks helped to identify the days that were used to clear AR (Komarraju et al., 2024). The percentage of over ninety-day receivables and the percentage of claims paid out in the first thirty days are some of the KPIs. Thirdly, predictive analytics will be utilized to identify possible payment delays (Antysheva et al., 2020). The AR days can be minimized using predictive analytics, which will identify the accounts where the clearance of payment is likely to become an issue. Inclusion of predictive analytics in the RCM will help the healthcare provider monitor the mean days on AR in healthcare facilities.

• Pros and Cons

The advantages of the adoption of AR analytic tools, KPIs, and predictive analytics are the decrease in the AR days through enhancing the cash flow. Tracking tools eliminate manual efforts, whereas real-time dashboards help in speeding up the decision-making process compared to AR management (Arora et al., 2024). In addition, automated notifications would also come in handy in terms of follow-ups to cases requiring claims. The KPIs give specific targets and assist the clinic in regulating performance and benchmarking. Installation of standards will also help the healthcare providers to achieve the targets of the performance of AR. Analytical tools will help with data about payment trends and assist in addressing the issues of AR, which could aid the strategic decision-making process in a healthcare setting (Antysheva et al., 2020).

The drawbacks of the implementation of actions include high start-up costs and extra costs related to maintenance and purchasing accessories (Wassie, 2021). Another initial cost is the potential need to instruct multitudes of personnel to use the tracking and predictive analytics as a competitive edge in the new systems. Besides, healthcare industry professionals also have obstacles and delays in implementing the novel devices into the already established financial systems (Yeboah, 2024). On one hand, too much emphasis on the KPI goals will create pressure, which can either empower the workers or end in shortcuts during the claims processing.

Long-Term Financial Trends for AR Management

Automation of AR management can be applied in the advancement of the claim processing system to reduce the risks of mistakes that could be made by a human. Automation will increase efficiency, cut costs, and decrease the AR loop (Wassie, 2021). Another benefit of predictive analytics is that predicting the pattern of payment is possible so the healthcare providers can make payments on the receivables in time. Its implementation cost is high, and frequent updates and training employees can be costly to practice, especially when the number of employees is small. However, the long-term horizons indicated that the technology has to be embraced by healthcare professionals to bolster the AR management in healthcare facilities (Nasution et al., 2020).

The other trend in finance is the transformation in the delivery of care process. The healthcare industry also changed the model of care delivery whereby the fee-for-service model was changed to value-based care. Payment systems are performance-based incentives and linked to value-based care. The promising cases of financial incentives in value-based care are a reduction in rehospitalisation rates and a decrease in healthcare access (Beauvais et al., 2022). Healthcare providers must align AR strategies to the value-based contracts in order to ensure the financial stability of the organisation. The other trend is increased patient accountability in both controlling medical expenses through high deductibles and co-payments. The pattern indicates that payment made by patients is a percentage of receivables. The outcome of the implementation of patient engagement into the process of medical payment is improved cash flow and reduced bad debts in various ways (Matolo, 2023). Increased patient responsibility comes at the cost of increased bad debt and prolonged AR, so there is a need for the creation of strong billing strategies and patient financial literacy programs. The AR management needs to be improved in terms of its ability to handle patients with financial matters.

Analysing Risks Surrounding Inadequate AR Management

AR management is highly important, and when it is not managed in the right manner, it may lead to unwanted consequences in the form of derailing cash flows, bad debts, as well as consumption of resources. Poor AR management corresponds to the slow accumulation of cash that negatively affects cash inflow (Laghari and Ahmed, 2023). The insurers may bring about cash flow problems where the institution to which the healthcare is provided may lack the capacity to meet the cost of running the institution due to the lapse in payment. Besides, the disruptions in the cash flows suggest that they need more capital to cover any deficit and, unfortunately, enhance the cost of capital and risk profile of the organisation. One more risk associated with the poor management of AR is bad debt (Kramoliš and Dobeš, 2020). In particular, it is more problematic to recover bad debts that take more than 120 days to collect. Prolonged AR sequences will result in bad debt, and this will affect the performance of the organisation (Kramoliš & Dobeš, 2020). Within the profit margins, there exists a direct linkage to the growth of bad debts as regards the reinvestment of funds that can affect the performance and productivity of the organisation.

It had the issue of resource loss through improper AR management as well, since the augmented manual work increased the risk of claims. Inability to properly manage AR implies a lot of unnecessary work and additional claims rejected. The assertion requires additional time and labour, which has an impact on resources. Loss of efficiency, due to poor AR management, has the consequence of reducing the overall organisational efficiency (Hanifah and Bastian, 2020). Moreover, the collection times were also delayed due to bad AR management, thereby affecting the effectiveness of the functioning of the organisation due to the drainage of resources. Moreover, the lack of sufficient resources due to failure of the AR management turns into a hindrance to delivering quality care, decreasing patient satisfaction.

Impact of Significant Change on Revenue Cycle

The process of payment by a patient in a clinic, the patient billing process up to the collection of money, is referred to as the revenue cycle. The healthcare industry was going through emerging trends that assisted in controlling the revenue cycle management (Chaturvedi and Sharma, 2024). The three significant trends affecting the revenue cycle are patient financial responsibility, value-based care, and AI technology to address the AR.

• AI Technology

AI technology will play a critical role in the AR management process, as it will advance the RCM in healthcare settings. Rebuilding the RCM process with the help of AI and machine learning algorithms reduces the amount of administrative work, eliminates mistakes, and enhances the efficiency of the work (Ali and Dzandu, 2023). The AI technology helped the organisations perform claims review, denial review, or payment reconciliation processes without employees and minimised human errors. Increases will also enable the healthcare providers to manage delays that are caused by AR, a factor that will improve the management of cash. Moreover, the AI can prevent denial of claims related to coding or documentation errors as well (Pennington and Coustasse, 2024). The data processing solutions allow the providers to have data on the financial standing of an organisation and more accurately manage AR using strategic actions.

• Value-Based Care Model

The care model has redefined the healthcare provision and payment process through its value-based model. The services that were provided on the value-based model of care enabled organisations to receive a payment for the services that are provided and not the quantity of service. The value-based care emphasises the effectiveness of healthcare service provision in terms of patient satisfaction (Pounds, 2021). Also, value-based care will involve payment per treatment or procedure, which simplifies the financial procedure. The payment will not be objected to, and hence, with the patient having two services, payment will be doubled. Value-based care presupposes that the providers are paid a percentage based on their results and, thus, they may pay a higher price (Cattel & Eijkenaar, 2019). However, the method of tracking and recording the patient outcomes can affect the billing and reimbursement, which will affect the performance of the organisation.

• Patient Financial Responsibility

The patient was left alone to do the financial process due to the augmented out-of-pocket expenses and health insurance expenses. The percentage of healthcare expenses the patients have to pay is rising even further than it was previously in terms of copayment, coinsurance, or deductible. The providers are also witnessing a reduction in the AR days since the patients will contribute a bigger share towards hospital payments (Atluri & Thummisetti, 2023). However, there are a few patients who would have the financial capacity to finance the payment of enormous sums within a single session, leading to a very long payment system. Healthcare organizations require adequate tools that might be harnessed to deal with the payment systems (Rebuin et al., 2023). In addition, the financial assistance policies are also aided by the healthcare organisation in order to improve the receivable process.

Impact of Significant Trends

The AI technology, value-based care, and patient financial responsibility are three trends that influence the organisational strategy, patient care, and community health. The effectiveness of the trends was measured, which helped to establish the importance of AR management in health care. The trend of AI technology meant that automation was beneficial in terms of controlling mistakes in coding and enhancing the performance of organisations (Ali and Dzandu, 2023). Value-based care assisted in the management of billing and better patient safety. The cost-based factor for patients also aided in managing the payment in time, and this improved the functioning of the organization.

• Impact on Organisational Strategy

The AI technology enhances the AR management process in the healthcare setting, using claim management, follow-up to payments, and denials, which will reduce the risk of manual error and increase effectiveness in collection. Moreover, AI technology enhances financial stability through decreasing the number of days in AR and enhancing the cash flow (Ali and Dzandu, 2023). Further, value-based care focuses on the volume of care to add to the new AR management methods for reimbursement. The cash flow and days reduction in AR will be enhanced and lead to improved financial stability. The collections will be timely and could better predict the revenue of the clinic, making it possible to make more accurate budgets and strategic decisions (Cattel & Eijkenaar, 2019). The copayment and the high-deductible also improved the performance of the organisation because it improved the percentage of the financial responsibility of patients. The patients also ensure that they pay their bills in time, thereby ensuring that they have predictable revenue, consequently enhancing the performance of the organisation.

• Impact on Patient Care

The motorized AI technology helps save time on billing and claims processing completed by the healthcare members, which helps to provide more effective care to the patient. Billing will provide the patients with the appropriate information and enhance patient satisfaction and trust by using automated billing opportunities (Ali and Dzandu, 2023). In addition, value-based care can also be used to enhance patient trust and satisfaction by providing efficient services. Value-based care is patient-centric and hence improved health outcomes are realized. Moreover, the financial contribution of the patient also simplifies the payment process (Atluri & Thummisetti, 2023). The fact that it simplifies billing and payment is a positive aspect for the patients and enhances the confidence and satisfaction of the patient with the services.

• Impact on Community Health

The trends also impact community health. Firstly, the use of AI technology transformed the AR management process, which allowed the hospital to allocate increased funds in the area of patient care to increase the amount of healthcare available to the community. Moreover, the cash flow improvement and reduction of debt were also utilized to implement the outreach programs and improve community health (Ali and Dzandu, 2023). In the same way, the value-based model can also offer the community valued and high-quality services. In addition to enhancing community health, value-based care is based on disease prevention, early detection, and the overall management of chronic diseases (Pounds, 2021). The financial accountability of the patient will also ensure equitable service delivery of care by the community, increased health outcomes.

Conclusion

The healthcare context would require AR management strategic analysis in order to measure the performance of the financial aspect. Moreover, AR involves tracking days in order to make the cash flows and the financial performance of the organisation easier. The financial trends of a long-term perspective gave an understanding of the effects of AR management on the stability of healthcare organisations in terms of finances. The risks that can be realised as a result of ineffective management of AR are cash flow, bad debt, and waste of resources. The three trends, that determine the RCM within healthcare organisations are patient financial responsibility, value-based care, and AI technology. The trends also influence patient health, the strategy of the organization, and community health.