Good Example Of Research Paper On Quality Improvement In Mental Health Care

Patients admitted for acute mental health conditions need to adhere to follow-up consultations for treatments and other interventions intended to prevent deterioration and acute exacerbations. However, the rate of adherence to scheduled appointments may sometimes be suboptimal with eventual drop-out from treatment. The drop-out rate based on a national survey was found by Olfson et al. (2009) to average 22.4%. Missing appointments is commonly due to patients forgetting about the schedules. A quality improvement (QI) initiative was developed and implemented by Filippidou et al. (2014) to improve appointment adherence rates in the mental health outpatient setting. This paper discusses the translation of the QI study findings to the chosen microsystem, consideration of the IOM quality care aims, selection of a suitable QI framework, strategies in applying the findings, and the development of a focused clinical question on the topic.

Connection of QI Article to Practice Area

The chosen practice area is outpatient mental health which is similar to the QI study setting. However, the study was conducted in the United Kingdom which delivers mental health care through a health care system different from the US. The problem of adult patients who do not attend (DNA) their scheduled appointments was identified, and stakeholder consultations undertaken by a health trust were conducted as primary method to ascertain the contributory factors and the most effective and efficient strategy to engage patients (Filippidou et al., 2014). In contrast, the QI project involves a single mental health clinic albeit, similarly, it also caters to adults. The chosen setting for the QI project also has the same problem with patients who DNA. Hence, the QI study helps inform solutions to this issue to enhance the care received by patients and reduce the health care burden of mental illness in the community.

Benefits to the Microsystem of Implementing the QI Study

The QI study benefits the selected microsystem’s purpose, patient or problem, providers, processes, and patterns. The purpose of the clinic is to provide mental health treatments and monitoring as continuing care to patients discharged from inpatient settings following acute mental illness. Patients are referred to the clinic and are then set up for subsequent appointments. Patients who DNA comprise about 1 to 5 patients per day of the 16 patients the clinic can accommodate. The phenomenon often leads to suboptimal symptom management that contradicts the microsystem’s aim of achieving good treatment response and eventual remission. These outcomes are proposed indicators of mental-health care quality (Fisher et al., 2012). Ensuring quality care therefore means addressing the issue of patients who DNA.
The literature identifies having comorbidities as a risk factor to missing appointments and dropping out of treatment (Olfson et al., 2009). This is a similar trend observed in the chosen microsystem. In addition, ethnicity is also a risk factor noted in the chosen microsystem with more Black Americans not showing up for treatments compared with Whites contributing to health disparity. The difficulty engaging patients belonging to ethnic groups has been documented by Agius et al. (2010) and Holden et al. (2014). The QI study provides insights on strategies to engage this client subset albeit the admission that the barriers to consistently showing up for treatment are complex.
There is a lack of recognition among the clinic providers and staff regarding the significance of missed appointments. As such, it is typically considered a non-issue because the patient is deemed to have made his or her conscious choice. However, there are modifiable factors internal and external to the individual that influence such choices. Determining what these factors or barriers are and addressing them reflects the ethical duty to do what is good and prevent harm (Fisher et al., 2012; Fortney et al., 2012). Furthermore, the practice of ethical care and learning to analyze and resolve clinical issues through a QI project represent opportunities for professional growth in the providers and staff as well as a genuine contribution to advancing the quality of mental-health care.
The selected microsystem’s process entails scheduling patients for treatment and walk-ins are rarely accommodated because of full schedules. However, there is no mechanism to remind patients of their scheduled appointments given that forgetting them is a major factor to not showing up. Thus, the adoption of the practice of text messaging patients prior to their appointments to confirm attendance, as shown by Filippidou et al. (2014) in their QI study, represents a small change in practice that can significantly reduce the number of patients who DNA.
Finally, the pattern of patients failing to come in for their scheduled treatments or follow-up can be changed at the systems level. Sub-optimally managed mental illness entails economic and social costs that can be prevented by ensuring that patients adhere to the treatment plan (Holden et al., 2014). Improving the quality of care and changing this pattern aligns with the current health care reform that aims to reduce health care costs and ensure value for money. Hence, a benefit of the QI project is that it facilitates compliance with legally mandated reforms.

QI and the IOM Aims for Quality Care

Adopting the text-messaging intervention implemented in the QI study by Filippidou et al. (2014) fulfills the Institute of Medicine’s (IOM) aims for quality care, namely safety, effectiveness, efficiency, equity, timeliness, and patient-centeredness. Improving compliance to treatment and management through attendance of scheduled appointments improves safety given that inadequately managed mental illness can lead to consequences such as self-harm, harm to others, and adverse effects associated with medications (Bener, Dafeeah & Salem, 2013). The intervention also enhances the effectiveness of mental health interventions as it promotes greater utilization of care so that the treatment plan can be carried out (Lopez-Torres et al., 2013). Care cannot be rendered and received if patients do not come in as scheduled. Sims et al. (2012), in a pilot study adopting the QI intervention, found significant improvement in the rate of patient attendance post implementation.
Text messaging patients to remind them of their appointments promotes efficiency as well. Given the demand for mental health services, walk-ins at the clinic can seldom be accommodated. On the other hand, patients not showing up leads to waste in time and resources as the fixed costs of care remain despite care not being delivered whereas these could have been optimized by accommodating other patients (Filippidou et al., 2014; Olfson et al., 2009). In addition, the ensuing drop-out or suboptimal outcomes increase the costs of care because of the potential for admission for acute illness that also equates to inefficiency. Furthermore, the QI intervention is not costly or difficult to implement in practice. Promoting patient adherence to scheduled appointments through text messaging remains the best way to manage limited resources.
The process of checking patient appointments and sending text messages as reminders does not cause discrimination based on any demographic attribute. In addition, the Pew Research Center (2013) survey showed that 91% of adults in the US have cell phones. Hence, access to a cell phone is not deemed to be a factor that will create disparity. Alternative methods of communication such as e-mail or telephone can be explored among the minority of patients who will report that they do not own a cell phone.
Adopting the QI intervention will improve the timeliness of care because patients come in as scheduled in their treatment plan (Sims et al., 2012). Conversely, missing appointments causes delays in treatment as there is a need to reschedule it. It will also enhance the patient-centeredness of care as it addresses forgetting which is a common barrier to showing up. The intervention thereby fulfills the need to be reminded in recognition that patients may have difficulty keeping track of their scheduled treatments warranting this form of support (Filippidou et al., 2014; Lopez-Torres et al., 2013).

Comparison of Quality Improvement Models

Two QI models include the Plan-Do-Study-Act (PDSA) and the FADE framework. The PDSA entails short cycles of implementing planned changes after which the outcomes are evaluated for effectiveness so that decisions as to wider implementation can be made (Duke University, 2014). A primary focus is on outcomes measurement where outcomes are compared with baseline measurements to determine changes that are the bases for judging the effectiveness of the intervention. The cyclical nature of the model enables continuous quality improvement.
On the other hand, the Focus-Analyze-Develop-Execute-Evaluate (FADE) framework focuses beyond outcomes to the process of implementing change. The stage of analysis involves root cause determination and identifying options to resolve the chosen clinical issue (Duke University, 2014). The resulting action plan encompasses not only implementation and measurement but also communication that is important when the change requires modifications in the thoughts and behaviors of the staff.
Given the simplicity of the intervention, the PDSA cycle is more appropriate. Inserting text-messaging to remind patients is relatively easy to incorporate into the workflow in one cycle and does not require extensive staff education and training. Baseline and post-implementation measurements of attendance and DNA rates are necessary to quantify the impact of the practice on patients and mental health care utilization.

Implementing the QI Changes

The QI intervention will be implemented through a policy requiring that patients be sent text messages to remind them of upcoming appointments. Patients will also be asked if they have cell phones that can be used to remind them and if none, alternative modes of reminding will be identified. The forms will be modified to ensure the patient’s cell phone number is obtained. In addition, the electronic patient appointment system will be modified to include information on the upcoming appointments of patients which prompts the staff to remind these patients via text.

PICO Question

Given that the evidence supporting text message reminders has not been firmly established, an appropriate PICO question involves adult mental health patients receiving care in the outpatient setting as population. The inclusion criteria would be age 18 years or older and with prior referral to the outpatient clinic because of mental health issues. Exclusion criteria include patients in acute care settings. The intervention would be text message reminders about appointments and will be compared to no reminders. The outcome would be attendance rates and conversely, the no-show rate. The question is stated as “In adult outpatient mental health patients, does text messaging to remind about upcoming appointments effective in reducing the no-show rate and increasing the attendance rate compared with no reminders?”

Conclusion

Compliance with scheduled appointments is an important clinical issue in the outpatient setting. A QI study addressed this problem by reminding patients of their appointments via text messages. The initiative resulted in a decline in missed appointments. The study setting and patient population are similar to the chosen microsystem which enables the application of the QI intervention. The change will benefit the purpose, patient, providers, processes, and patterns of the mental health clinic. It is also aligned with the aims of the IOM for quality health care. Adopting the QI intervention will require the use of the PDSA cycle. To ensure EBP, a focused question on the effectiveness of text message reminders was developed and will guide the literature search.

References

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Bener, A., Dafeeah, E.E., & Salem, M.O. (2013). A study of reasons of non-compliance of psychiatric treatment and patients’ attitudes towards illness and treatment. Issues in Mental Health Nursing, 34(4), 273-280. doi: 10.3109/01612840.2012.745039.
Duke University (2014). Methods of quality improvement. Retrieved from http://patientsafetyed.duhs.duke.edu/module_a/methods/methods.html
Filippidou, M., Lingwood, S., Barnet, I.M., & Haringey Mental Health Trust (2014). Reducing non-attendance rates in a community mental health team. BMJ Quality Improvement Reports, 3,1-4. doi: 10.1136/bmjquality.u202228.w1114.
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Holden, K., McGregor, B., Thandi, P., Fresh, E., Sheats, K., Belton, A., Satcher, D. (2014). Toward culturally centered integrative care for addressing mental health disparities among ethnic minorities. Psychological Services, 11(4), 357-368. Retrieved from http://www.apa.org/pubs/journals/releases/ser-a0038122.pdf
Lopez-Torres, J., Parraga, I., Del Campo, J.M., Villena, A., & ADSCAMFYC Group (2013). Follow up of patients who start treatment with antidepressants: Treatment satisfaction, treatment compliance, efficacy and safety. BMC Psychiatry, 13(65), 1-9. doi:10.1186/1471-244X-13-65.
Olfson, M., Mojtabai, R., Sampson, N.A., Hwang, I., & Kessler, R.C. (2010). Dropout from outpatient mental health care in the United States. Psychiatric Services, 60(7), 898- 907. doi: 10.1176/appi.ps.60.7.898.
Pew Research Center (2013). Smartphone ownership 2013. Retrieved from http://www.pewinternet.org/2013/06/05/smartphone-ownership-2013/
Sims, H., Sanghara, H., Hayes, D., Wandiembe, S., Finch, M., Jakobsen, H., Kravariti, E. (2012). Text message reminders of appointments: A pilot intervention at four community mental health clinics in London. Psychiatric Services, 63(2), 161-168. doi: http://dx.doi.org/10.1176/appi.ps.201100211
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