This paper examines risk management strategies for the pharmaceutical prescription process in healthcare settings, with particular focus on reducing data entry errors. Using tools such as STEEPLE analysis, process scope diagrams, and gap assessments, the paper identifies key stakeholders, maps prescription workflows, and evaluates technology-based solutions. The recommended solution is a cloud-based machine learning application that integrates with existing electronic prescribing systems to flag errors, streamline authorization, and improve communication between doctors, nurses, and pharmacists. The paper also addresses implementation feasibility, cost projections, potential risks, and training requirements for staff transitioning to the new system.
The prescription process can incur high costs in the healthcare industry due to poor risk management. Lack of continued assessment, technological upgrades, and information sessions can lead to an increased rate of data entry errors. Data entry errors may result in patient deaths and lawsuits that diminish the financial success of any hospital or clinic. However, there is an opportunity to reduce data entry errors in order to minimize negative outcomes related to prescription errors and patient satisfaction. The recommendation for minimizing these negative outcomes is to incorporate a cloud service that allows for integration of existing electronic prescription records, enabling optimization of the prescription workflow from doctor or nurse to pharmacy to patient, thus minimizing potential data entry error. The impact a cloud service application can have on healthcare is significant: costs may be reduced and legal ramifications from human error can be avoided by emphasizing the risk management essentials of assessment, technological upgrades, and training.
Risk management for the prescription process entails analysis of problems existing in the pharmacy in relation to wait times, communication between different parties, and customer satisfaction. Regarding wait times, the average wait time for a prescription can take approximately half an hour. Examined from the perspective of risk management, wait time directly affects the satisfaction level of patients seeking their medications. If patients wait longer than expected, they may take their business elsewhere, minimizing profit potential for a pharmacy.
Another key aspect of risk management is identification of stakeholders. The stakeholders within this scenario are patients, doctors, nurses, and pharmacies. If doctors and nurses prescribe medications and the patient must wait a long time to receive them because of the pharmacy, there may be less motivation on the patient's part to follow through with acquiring the medication. This can lead to lower satisfaction with care and a lower quality of care delivery.
When understanding the risk a certain action produces — such as a data entry error — one cannot ignore the legal ramifications of that action in the prescription process. Potential legal ramifications associated with the prescription process include legal battles and expenses associated with court cases, wasteful healthcare spending, and lethal prescription errors. Such legal ramifications could worsen in light of recent healthcare policy changes.
Examining the problem through STEEPLE factors, new healthcare changes can lead to increased rates of data entry error. For example, the Affordable Care Act requires U.S. citizens to maintain health insurance or face monetary penalties (Rawal, 2016). This means more U.S. citizens will have access to healthcare than ever before. To meet the increased demand, hospitals and clinics must update their systems to provide effective and fast service. This can take the form of expanding the hospital or clinic by incorporating a pharmacy, or by updating older information technology systems.
The Lerdsin Hospital encountered prescription errors due to the structural constraints of its small pharmacy. When the pharmacy was enlarged and updated with new equipment, it was able to meet the demands of the increased patient volume. To acquire the information needed to make such changes, the assessment took the form of staff interviews and numerous observational studies conducted within and around the pharmacy.
Staff assessed pharmacy layout, prescription timing, and patient and staff traffic flow. They determined that the cashier step took the longest within the prescription process. From there, they identified the ineffective layout of the pharmacy and the overall prescription volume. Their recommendations included a restructuring of the existing layout for a low-end budget and, for the high-end option, a complete overhaul of equipment with a focus on information technology. By accommodating patient needs and placing prescription drugs in a convenient, easy-to-access location, they made more effective use of the existing space.
This is how risk management for the prescription process can lead to positive outcomes. By assessing and analyzing collected data, it is possible to develop a better understanding of the problem and prompt its resolution. Assessment involves detailing the input and output process. Doctors and nurses write out prescriptions for patients — this represents one part of the input aspect. In a process diagram, the second part of the input aspect involves the patient delivering his or her prescription to the pharmacy. On the output side, the pharmacy gives the medications to the patient, completing the process. This is a basic representation of the project scope.
A high-level process diagram of inputs and outputs proceeds in the following order: patient, doctor or nurse, and pharmacy. A patient must first undergo the process of determining whether a prescription is required. This involves a diagnosis performed by the doctor or nurse, followed by data entry into an electronic prescribing system. Should anything require authorization from health insurance or from the doctor in terms of prescription changes, the process continues at that stage. The pharmacy then receives the prescription and checks for authorization. Once authorization is confirmed, the pharmacist checks whether the prescription is dispensable. If it is, the medication is dispensed and the patient receives it.
Without a clear description of the prescription process, little can be done to minimize associated risks. Because data must be entered electronically, data entry becomes a focal point in the risk management process. Further exploration of the process narrative can yield even better results.
A more detailed narrative of the scope diagram incorporates healthcare policy, prescription drug regulations, and technology. For example, the FDA and HIPAA regulate prescription drugs and set the standards for security of health information systems, respectively. Legal services check the terms and guidelines of contracts. These elements represent the GUIDES component of the INPUTS and OUTPUTS prescription process.
The INPUTS side includes cloud service costs, prescription and patient data, and updated software and maintenance costs. These are what go into sending a prescription, receiving a prescription, and performing the necessary tasks to deliver the prescription to the patient. The OUTPUTS involve a cloud service license, support and maintenance, and generated prescription requests. ENABLERS — doctors and nurses, the billing department, pharmacists, Information Technology (IT), and healthcare administrators — are the parties with whom patients, doctors, nurses, and pharmacists must communicate and interact to achieve the goal of getting the patient the prescribed medication. By further detailing the prescription process, it becomes clear where the most significant problems arise: equipment and software purchasing, service, and maintenance.
The prescription process can encounter problems in several key areas, but the main area is technology. As identified, the current state of software and its service and maintenance is integral to managing data entry error. When this area lacks proper assessment, it can lead to service problems for the pharmacy, the doctors and nurses, and ultimately the patient. An opportunity exists to examine existing medical electronic systems and their compatibility for integration into a different process, potentially yielding a lower-cost solution than building a new system from scratch — one that can be implemented through employee information sessions. That solution is a prescription cloud service.
If the purchase and installation of necessary software and equipment are required to support a technology-based solution such as a cloud service application, this must be evaluated in terms of implementation feasibility and costs. Implementation feasibility consists of regular checks for functionality and updates, as well as installing equipment to prepare for future issues and ensure the system runs smoothly. Cloud service applications allow data entry errors and other human-produced errors to decline thanks to instant verification and improved communication.
Human-produced errors are the primary source of dissatisfaction. Medication errors can lead to lawsuits that are damaging to all parties involved. When technology is lacking for faster assessment and verification, problems persist, resulting in continued poor quality of care delivery, especially on the pharmacist's side. However, there are ways to improve and diminish the common problem of human error.
"TO-BE workflow, machine learning integration, recommendations"
"Training needs, cost estimates, and risk scenarios"
"Phased rollout schedule and final summary"
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