DHA 8007 Week 6 Assignment Accounts Receivable Management

Accounts Receivable Management

Student Name

Capella University

DHA 8007

Professor Name

Submission Date

The days in accounts receivable (AR) analysis are critical to determining the financial performance of the healthcare setting. The comparison of the AR management of the Westside Clinic in 2022 demonstrated better results than in 2021, as it took the AR management 58 days to complete the required tasks in 59.2 days. The positive trend of the AR management was observed in 2022, and there is a necessity to make additional cuts in the days to come to enhance the cash flow.

Financial leaders should be informed about the analysis of the AR to ensure the normal functioning of healthcare facilities (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. Also, the trends that influence the revenue cycle and influence the organisation’s strategy, patient outcome, and community health are offered.

Strategic Assessment

Financial analysis of the AR assisted in determining the mean days it takes to collect the receipts for the healthcare services. According to the analysis of the data conducted in 2021-2022, AR days decreased to 58, which enhanced the cash flow and financial stability of the organisation as they dropped to 59.2. The strategic analysis is based on the three methods of cutting the AR days. The three options to decrease the AR days are the technology use, the denial management system and the predictive analytics.

To start with, the artificial intelligence (AI) technology was implemented to automate billing and collection processes (Nasution et al., 2020). The financial analysis application of a machine learning algorithm is expected to reduce the duration of the process and expedite payments, reducing 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. Enhancing the claim settlement decreases the claim reprocessing, and the AR cycle time is shortened.

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 were useful in the future payment forecast for the RCM system. Gathering data to determine the ratio of patients who have received care contributed to the ability to access the revenue and resulted in the proactive decision, which enabled the decrease in the AR growth in healthcare facilities.

Plan for Managing Risk

Cash flow disruptions and additional bad debt are the risks of the organisational environment in the process of collecting AR receivables. Increased AR days tie up the working capital, which can be used to operate or make other productive investments. The extension of receivables over 120 days influences 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. The pre-verification process assists in minimising claim denials. Secondly, the analysis of the denial will be provided on a monthly basis in order to evaluate the frequent issues, including coding errors or information deficiency.

Thirdly, claims will be submitted automatically using the AI technology, claim status will be tracked online, and updates on the receivables will be received. The technology reduces the risk of human error and provides crucial data to streamline the methods of collection and financial forecasting. Moreover, improving patient knowledge will also minimise payment problems, which is relevant to the timely collection of the AR and overcome delays.

Strategic Assessment to Monitor Days in AR

AR requires monitoring days that will help in streamlining 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 is a ratio that indicates the days between which a healthcare organisation collects billed amounts into cash (Antysheva et al., 2020). Thus, it is essential to evaluate monitoring days in AR since the fewer AR days, the quicker the collection and, therefore, the hospital can manage cash flow.

Key performance indicators (KPI), predictive analytics, and AR tracking tools are the three methods that healthcare providers can use to track the AR days. To begin with, AR tracking applications are financial applications, which are presented in the form of interface dashboards with days in AR, time taken in the AR and payer performance (Arora et al., 2024). The messages in the tracking instruments also assisted in determining the cases where the AR days are exceeding the deadline. Thus, the real-time monitoring tools will be used to assist the staff in responding to the AR issues in a proactive manner and enhance the efficiency of the collection.

Secondly, KPIs assist the healthcare provider in establishing the primary goals of the AR management. The comparison of the hospital-related data on the AR days and national and regional benchmarks assisted in the identification of the days that were used to clear AR (Komarraju et al., 2024). Some of the KPIs are the percentage of claims paid in the first thirty days and the percentage of over ninety-day receivables. Thirdly, predictive analytics will be employed to detect the potential delays of payments (Antysheva et al., 2020). Predictive analytics can be used to reduce the AR days by determining the accounts in which the clearance of payment is likely to be problematic. The inclusion of predictive analytics in the RCM assists the healthcare provider in tracking the mean days spent 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 remove manual work, whereas real-time dashboards accelerate the decision-making process in relation to the AR management (Arora et al., 2024). Also, automated notifications become handy when it comes to follow-ups on cases that need claims.

The KPIs provide particular objectives and help the clinic to control the performance and benchmarking. The establishment of standards will also assist healthcare providers in attaining the targets for the performance of AR. Analytical tools provide data on payment trends and assist in solving the problems of AR, which can support the strategic decision-making process in the healthcare environment (Antysheva et al., 2020).

The disadvantages associated with the adoption of actions are high start-up costs and additional expenses in terms of maintenance and accessories purchase (Wassie, 2021). The initial costs also involve the possibility of having to train a large number of staff to operate the tracking and predictive analytics as a competitive advantage in the new systems. Moreover, healthcare providers also face barriers and setbacks when integrating the new gadgets with the already existing financial platforms (Yeboah, 2024). On the one hand, the excessive focus on the KPI targets may cause pressure, which may either demotivate the employees or lead to shortcuts in processing the claims.

Long-Term Financial Trends for AR Management

AR management automation is useful in enhancing the claim processing system, and it minimises the chances of errors that might be introduced by hand. Automation will enhance efficiency, reduce spending, and reduce the AR cycle (Wassie, 2021). Predictive analytics is also advantageous in that it allows predicting the pattern of payments to ensure that the healthcare providers can make timely payments on the receivables.

Its cost of implementation is costly, and regular updating and training of employees may be expensive to exercise, particularly for those who have few employees. Nevertheless, the long-term horizons pointed out that healthcare professionals must adopt technology to enhance the AR management in healthcare facilities (Nasution et al., 2020).

The other financial trend is the changing nature of the care delivery process. The healthcare industry also transformed the model of care delivery, whereby the fee-for-service model was adopted to value-based care. Value-based care is associated with payment systems, which are performance incentives. 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). To maintain the financial stability of the organisation, healthcare providers are forced to match AR strategies with the value-based contracts. Another trend is the growing responsibility of patients in the control of medical costs in the form of high deductibles and co-payments.

The trend shows that patient payments constitute a proportion of receivables. The improved cash flow and reduced bad debts are the results of the implementation of patient engagement in the medical payment process in different 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. AR management requires improvement in the skills to deal with patients related to financial issues.

Analysing Risks Surrounding Inadequate AR Management

The AR management is very significant since failure to manage it appropriately can cause undesirable effects in the form of disruption of cash flows, bad debts and even drainage of resources. Ineffective AR management translates into a slow collection of cash, which has a negative impact on cash inflow (Laghari and Ahmed, 2023). The insurers can cause cash flow issues in which the healthcare institution might not have the capacity to cover the cost of operation because of the delay in payment. Moreover, the cash flow disturbances indicate that additional capital is required to meet any shortfalls and, regrettably, increases the cost of capital and risk profile of the organisation.

Bad debt is another one of the risks related to the inadequate handling of AR (Kramoliš and Dobeš, 2020). Specifically, bad debts that require over 120 days to collect are even worse to recover. Long collections of AR lead to high bad debt, which influences the performance of the organisation (Kramoliš & Dobeš, 2020). Regarding profit margins, there is a direct correlation to the increase in bad debts in regard to the reinvestment of funds that influences the performance and productivity of the organisation.

There was also a problem of loss of resources due to poor management of AR, because the augmented manual work increased the threat of claims. The inability to effectively manage AR means a great deal of unnecessary work and more claims being denied. The assertion requires additional time and labour, which has an impact on the resources. The deterioration of the total organisational efficiency is a consequence of the loss of efficiency through poor AR management (Hanifah and Bastian, 2020). Furthermore, the bad AR management also postponed the collection times, which influenced the efficiency of the organisation’s functioning because of the resource drainage. In addition, insufficient resources caused by the ineffective AR management become an obstacle to quality care delivery, reducing patient satisfaction.

Impact of Significant Change on Revenue Cycle

The revenue cycle is the term that defines the process of payment by a patient in a clinic, from the patient billing process to collecting money. The healthcare industry was going through emerging trends that assisted in controlling the revenue cycle management (Chaturvedi and Sharma, 2024). Patient financial responsibility, value-based care, and the use of AI technology to manage the AR are the three important trends that influence the revenue cycle.

AI Technology

The AI technology is essential in the AR management process, as it promotes the RCM in healthcare environments. 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 assisted organisations in administering claims, denial, or payment reconciliation procedures without human resources and reduced manual mistakes.

Improvements will also allow healthcare providers to handle AR delays, which will enhance cash management. In addition, the AI is also able to stop claim denial by detecting coding or documentation errors (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 value-based model of care redefined the process of delivering healthcare and payment. Services that were offered through the value-based model of care allowed organisations to get a payment based on the services that are offered rather than the amount 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.

As an example, when the patient has two services, then the payment will be doubled without any objection. Value-based care implies that the providers receive payment according to their performance and, therefore, are likely to pay more (Cattel & Eijkenaar, 2019). Nonetheless, keeping track of and capturing patient outcomes may influence the billing and reimbursement, which influences the performance of the organisation.

Patient Financial Responsibility

The financial process was left in the hands of the patient because of the increased out-of-pocket costs and health insurance costs. The proportion of healthcare costs being paid by patients is increasing more than before, either in the form of copayment, coinsurance or deductible. Since the patients are to make larger contributions to hospital bills, the providers are also experiencing a decrease in the AR days (Atluri & Thummisetti, 2023).

Nevertheless, a small number of patients cannot afford to pay huge amounts of money at a single time, resulting in a protracted payment schedule. Healthcare institutions need sufficient instruments that can be used to manage payment frameworks (Rebuin et al., 2023). Moreover, the financial assistance policies are also guided by the healthcare organisation to enhance the receivable process.

Impact of Significant Trends

Three trends that impact the organisational strategy, patient care, and community health include AI technology, value-based care, and patient financial responsibility. The measurement of the effect of the trends aided in determining the significance of AR management in healthcare. The trend of AI technology meant that automation was beneficial in terms of controlling the 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 financial responsibility of the patients also contributed to the management of the payment on time, which enhanced the performance of the organisation.

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 will reduce the risk of manual error, and increase effectiveness in collection. Moreover, AI technology enhanced financial stability through decreasing the number of days in AR and enhancing the cash flow (Ali and Dzandu, 2023). As well, value-based care centres on the amount of care that contributes to the new AR management approaches to reimbursement. Cash flows and the decrease in days in AR will be improved and result in enhanced financial stability.

Revenue of the clinic will be more predictable with faster collections, which will allow making budgets and strategic decisions more accurately (Cattel & Eijkenaar, 2019). The high-deductible and copayment also boosted the performance of the organisation since it increased the share of patient financial responsibility. Patients also make sure they pay their bills on time, hence guaranteeing predictable revenue, thus improving the performance of the organisation.

Impact on Patient Care

The AI technology saves time on billing and claims processing undertaken by the healthcare staff, which assists in delivering more effective care to the patient. Patients will receive the correct information in the form of billing, which increases satisfaction and confidence through the utilisation of automated billing solutions (Ali and Dzandu, 2023).

Moreover, patient trust and satisfaction can also be achieved through value-based care through offering effective services. Value-based care is patient-oriented, and as a result, there are enhanced health outcomes. 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 community health is also affected by trends. Firstly, AI technology enhanced the AR management process, which enabled the hospital to invest more in patient care services to boost healthcare availability to the community. Furthermore, the enhanced cash flow and debt reduction were also used to facilitate the outreach programs and enhance community health (Ali & Dzandu, 2023). Similarly, the value-based model also provides the delivery of effective and high-quality services to the community. 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). Also, the financial obligation of the patient will guarantee fair service delivery of care to the community, which will enhance health outcomes.

Conclusion

AR management strategic analysis is necessary in measuring the performance of the financial aspect of the healthcare context. Also, AR requires monitoring days to simplify the cash flows and the financial performance of the organisation. 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 may arise due to poor management of AR include cash flow, bad debt, and drainage of resources. These three trends are the patient financial responsibility, value-based care, and AI technology that influence the RCM in healthcare organisations. Also, patient health, organization strategy and community health are also affected by the trends.

For the week 3 assignment of this class visit: DHA 8007 Week 3 Assignment