Introduction
The process of controlling the intake of the required medications is especially challenging in outpatients. For numerous reasons, ranging from memory issues to the failure to understand the importance of regular medication intake multiple patients fail to adhere to the prescribed framework (Amico et al., 2018). Therefore, tools for monitoring compliance with the established and prescribed standards for drug use must be introduced. Among the frameworks that provide the best patient outcomes, one must mention the Medication Event Monitoring System (MEMS). Due to the extensive understanding of psychological and physiological factors that shape patients’ ability and willingness to comply with the prescribed standards for medicine intake, MEMS should be incorporated into most clinical and nursing contexts to establish tighter control over the patients’ ability to meet the provided health management guidelines, thus, promoting self-care habits among the target audiences.
Mems and Key Factors
The concept of MEMS is fairly simple since it implies the presence of a cap on medication packages, which records the amount and time of medicine intake (Gast & Mathes, 2019). When dissecting the effectiveness of MEMS, one must examine how the data that MEMS collects and analyzes is defined by the presence of psychological and physiological factors. Thus, the mechanism of MEMS functioning becomes explicitly evident, and its ability to capture the psychological and physiological characteristics in question to produce the expected results turns apparent. To evaluate MEMS’ capacities and the extent of its efficacy with the target demographic, namely, outpatients with medicine intake issues, one must study both physiological and psychological drivers of the tool’s performance, as well as their connection to the relevant concepts and theories. For this purpose, the Health Belief Theory and the Medication Adherence Model have been used as the core theoretical foundations for the analysis (Amico et al., 2018).
Psychological Factors: Personal Beliefs
When examining the physiological factors that define the performance of MEMS, one must mention personal beliefs about medicine. Despite the active emphasis on the tremendous role that health literacy plays in the management of public health issues, multiple health-related myths, as well as the lack of essential health-related issues, persist in modern society (Gast & Mathes, 2019). Particularly, the ability to recognize the importance of proper medication dosage and align with the prescriptions appears to be a problem among a range of outpatients (Gast & Mathes, 2019). In turn, the MEMS system allows for mitigating the threat of a patient mismanaging the prescribed instructions by introducing a mechanism preventing a patient from consuming an unreasonably large amount of medication of using it excessively frequently. Remarkably, the absence of a mechanism that encourages a patient to take medications in case a patient rejects them represents a major flaw of the MEMS tool. Nevertheless, the designed approach still sheds important information on the number of attempts of drug misuse in patients, supplying the relevant information to nursing experts and, therefore, defining the further course of therapy and patient education.
Psychological Factors: Mental Health
The presence of mental health issues exacerbated by the presence of a severe health condition for which the medication is prescribed serves as another psychological factor that may encourage a patient to break the rules for consuming a specific medication. Specifically, studies have indicated that anxiety as a major mental health issue often encourages a patient to neglect the prescriptions regarding the dosage of medicine and consume the drug too frequently or in too large an amount (Gast & Mathes, 2019). The specified factor is also integrated into the MEMS system, which, while being quite simple, introduces rather accurate information concerning the number of attempts made by the patient to increase the dosage of the drug or the frequency of its use.
Psychological Factors: PTSD
Another issue related directly to a patient’s mental health, the presence of PTSD and the related issues that may impede the development of the necessary habits must be mentioned as one of the major drivers in the collection of the data in the MEMS tool. Namely, when being affected by the presence of PTSD, a patient is likely to develop anxiety-related issues that will encourage the misuse of medications. In turn, the MEMS design and framework allow controlling the specified issues, therefore, contributing to the patient’s well-being. As a result, the data collected by MEMS illustrates the number of instances when a patient attempted at using an overly large amount of the medicine or tried to increase the frequency of the drug consumption.
Depression
The phenomenon of depression also constitutes an important psychological concern that is likely to affect the accuracy of data collection with the help of MEMS. Namely, the increase in vital signs coupled with the increased intake of medications and the rise in the frequency of their use will cloud the data, therefore, delivering unsatisfactory results. For this reason, the necessity to address mental health issues along with the application of MEMS to the management of relevant health concerns must be viewed as necessary. With the help of the specified change, the opportunity to receive more accurate data or to analyze it more precisely based on the changes in a patient’s depression levels will rise exponentially.
Motivation
However, not all psychological factors taken into account when designing MEMS are conducive to the misuse of medications. In addition to the issues listed above, psychological factors such as the presence of responsibility and the willingness to overcome the barriers to the patient’s well-being should be mentioned as the primary drivers in the data collection facilitated by MEMS. Namely, the tool design informs the healthcare provider regarding the number of cases when a patient opened a bottle, as well as the frequency of the specified action. Consequently, the willingness to adhere to the prescribed schedule and, therefore, to follow the path to recovery informs the process of data collection, thus, providing a nurse with critical information about positive changes in the patient’s habits.
Finally, the data collected by the MEMS tool is heavily influenced by psychological factors such as the effects of the psychological therapy that a patient may be undergoing. Having been exposed to specific experiences that can be described as strenuous or mentally and emotionally exhausting, a patient may experience the desire to increase the dosage of the medication or the frequency of its intake. In turn, the MEMS tool allows signaling about the instances in question, therefore, providing a nurse with the illustration of a behavior pattern displayed by the patient. As a result, essential changes in the approach to therapy, as well as modifications to the existing framework of patient-nurse and patient-therapist communication can be applied. Therefore, the data collected with the help of MEMS is largely determined by the specified factor.
Physiological Factors: Physical Impairments
In addition to psychological factors shaping the process of data collection and, thus, providing the nurse with the required information, physiological contributors to the process of gathering patient-related information must be considered. Specifically, the presence of physical disorders that prevent patients from taking the actions necessary to consume the required amount of medicine needs to be taken into consideration. Factors such as the patient’s physical inability to open the pill box are most likely to affect the outcomes of data collection, therefore, shaping the process of the analysis and informing a nurse about the physical constraints that impede the administering of medicine. Therefore, understanding the physiological contributors to the data collection process, particularly, the threats of obtaining correct information needed for the further management of outpatients’ health, is nonetheless important and must be assessed accordingly.
Physical Strength
Similarly, the presence of excessive physical strength may influence the process of data collection. Specifically, in case a patient possesses the amount of physical strength needed to break the MEMS device installed on the medication box cap, the data collected in the process will complicate the analysis, while also establishing that the patient lacks the awareness required for using the medicine in question properly. Therefore, while the MEMS device as the tool for administering medicine to outpatients in their home setting is not perfect and could be prone to specific impacts, particularly, physical ones, it can also supply vital data concerning how a patient utilizes the device and consumes the medicine.
Mobility
The presence of musculoskeletal issues, namely, related disorders, also represents the main driver in data collection in MEMS. Specifically, the study by Hope et al. (2016) concludes that disorders such as inflammatory arthritis, which determine a patient’s inability to move and, therefore, perform carefully coordinated movements such as opening a box of medication, represent a major obstacle to administering the required drugs at home. In turn, the MEMS device allows capturing the specified data by collecting the information regarding the extent of force that a patient has applied to open the box, the number of times that the specified action was attempted, the frequency of the action, and the number of instances in which it was successful. Therefore, the collection of data that MEMS helps supply will be significantly affected by the presence of musculoskeletal issues in patients.
Comorbidities
Furthermore, the presence of previously unknown comorbidities and side effects that may arise after the medication intake may prevent the collection of accurate data with the help of the MEMS system since the specified factor is likely to cause the patient to fail to adhere to the prescribed dosage and frequency of the medicine consumption. In turn, the specified effect is likely to skew the outcomes of data collection performed by MEMS, which will suggest that the tool in question will not serve its function properly. Therefore, it is vital to introduce the tests required to identify the presence of negative responses toward a specific medication in a patient carefully to void scenarios in which a combination of severe side effects combined with possible mental health issues prevents an outpatient from reporting the issue of taking medication.
Vital Signs
The opportunity to monitor the physiological factors such as heart rate and respiration also serves to shape the process of data collection as the specified factors determine the accuracy of the data collection process and, therefore, inform the further management of the patient’s case for a nurse or a healthcare provider. While some MEMS gadgets do not provide the function of BP or heart rate monitoring, a range of the specified devices offers the described option as well (Gast & Mathes, 2019). Therefore, the data collection process facilitated by MEMS is determined significantly by the extent of the patient’s BP rates and the related parameters, including the extent of the patient’s respiration. Indeed, when having an increased aspiration rate or a significant drop in blood pressure, a patient is likely to have significant challenges opening the cap of a medication bottle. Similarly, MEMS devices placed on a patient’s hand as a bracelet also serve to determine the extent of heart rate and blood pressure, thus, supplying even more accurate data concerning the patient’s state and the relevant changes in the patient’s condition.
Memory Impairment
Finally, among the physiological factors that shape the process of MEMS data collection to a notable extent and, therefore, are often seen as the focus of MEMS design updates, one must mention the factor of impaired memory as a critical contributing factor to the process of gathering patient-related data with the help of the MEMS device. Specifically, without the tool that could serve as a reminder of the patient to comply with the set standards for medicine intake, the MEMS tool will be useless, with little to no data being supplied. Remarkably, the factor under analysis represents a unique issue in MEMS application since it requires the integration of additional techniques likely to be unrelated to the patient’s condition for which MEMS has been integrated. Specifically, the problem of poor memory can be handled by the inclusion of techniques and tools for memory training. Similarly, digital tools for setting reminders about the need to take medications will need to be included to counteract the specified obstacle to proper data collection within the MEMs framework (Gast & Mathes, 2019).
Conclusion
Due to its ability to capture the psychological and physiological factors that may shape a patient’s willingness or ability to adhere to the prescribed medication intake model, the MEMS tool can be considered an essential advancement in managing outpatients’ well-being. Furthermore, due to the ample focus on the factors in question, the MEMS tool allows the prevention of aggravation of a patient’s condition and identifying the signs of a possible health crisis. As a result, a relevant support framework can be implemented, and the necessary measures can be applied to manage a health issue and ensure a patient’s well-being. Due to its ability to encompass the data defined both by psychological and physiological factors in a patient’s decision-making concerning the intake of medications, the MEMS tool represents an excellent opportunity for effective health management.
References
Amico, K. R., Mugavero, M., Krousel-Wood, M. A., Bosworth, H. B., & Merlin, J. S. (2018). Advantages to using social-behavioral models of medication adherence in research and practice. Journal of General Internal Medicine, 33(2), 207-215. Web.
Gast, A., & Mathes, T. (2019). Medication adherence influencing factors—an (updated) overview of systematic reviews. Systematic Reviews, 8(1), 1-17. Web.
Hope, H. F., Bluett, J., Barton, A., Hyrich, K. L., Cordingley, L., & Verstappen, S. M. (2016). Psychological factors predict adherence to methotrexate in rheumatoid arthritis; findings from a systematic review of rates, predictors and associations with patient-reported and clinical outcomes. RMD Open, 2(1),1-15. Web.