DRAFT - University of Texas System



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Please complete all of the following sections.

Submission is limited to a maximum word count of 1500 (not including text in graphs).

Overview: Describe 1) where the work was completed (in what type of department/unit); 2) the reason the change was needed; 3) what faculty/staff/patient groups were involved, and 4) the alignment to organizational goals.

UT Health’s Ambulatory Psychiatric Clinic suffers from very high no-show rates (31%). Patient no-shows compromise patient safety, medication compliance, quality of care, employee productivity, employee morale, medical education, revenue generation, and the effective use of emergency and after hour services. The cost of poor quality is significant. With approximately 800 patient appointments per month, a 31% no show rate equates to 248 patients who fail to receive recommended care and 248 appointment slots that are wasted. Because this project aims to increase the percentage of patients who arrive for their scheduled appointment in the psychiatry clinic, the project aligns well with the organization’s clinical, operational, and financial goals.

We started with a target to reduce the patient no-show rate to 20%, and hopefully, share the knowledge gained in this project to improve no-show rates in other departments at UT. Dr. Prashant Gajwani, associate professor and vice chairman of clinical affairs in the Department of Psychiatry and Behavioral Sciences at the UTHealth Medical School and student in the CS&E course, led this project and assembled a team of medical faculty, residents, nursing personnel, and front office staff who were involved at each phase of the project.

Aim Statement (max points 150): Describe the problem that you sought to address.

To improve patient care and efficiency of the UT ambulatory psychiatric clinic by reducing no-show rate to 20%.

Measures of Success: How did you measure the impact of your proposed change?

Retrospective data collection for a one and a half week period took place to establish baseline no-show rate of 31%. At this time, we re-defined operational definitions to ensure common understanding of a “no-show” versus a “cancellation.” We counted the number of no-shows and divided that number by the total number of appointments scheduled to obtain a daily no-show rate. The total number of appointments scheduled included patient arrivals, same day cancellations, and no-shows. Several interventions to reduce no-shows were implemented over a one month period in the month of June. To measure the impact of our interventions, we collected data daily for one week followed by surprise data collections one day per week on an ongoing basis to assess performance.

Use of Quality Tools (max points 250): What quality tools did you use to identify and monitor progress and solve the problem? Provide sample QI tools, such as fishbone diagram or process map.

After completing a basic process map, a team of ambulatory service providers which included residents, medical faculty, therapists, front office staff, and nursing personnel were assembled to develop a detailed cause and effect diagram.

[pic] Using the “causes” listed in the cause and effect diagram session, the group brainstormed and identified several interventions to pilot.

To measure our progress, daily and then weekly data were collected and presented in a control chart (presented on page 5).

Interventions (max points 150 includes points for innovation): What was your overall improvement plan? How did you implement the proposed change? Who was involved in implementing the change? How did you communicate the change to all key stakeholders? What was the timeline for the change? Describe any features you feel were especially innovative.

Intervention Summary:

The improvement plan included several interventions, which were identified through brainstorming and best practices research. While Dr. Prashant Gajwani, the department administrator, Pauline Stapleton, and Priya Khatri (CS&E mentor) decided on the interventions to be administered, most of the brainstorming occurred during the latter half of the cause and effect meeting that included medical faculty, residents, therapists, the department administrator, and the nurse manager.

The first intervention was the introduction of a “personal” appointment reminder call one day in advance of patient appointments. While UTHealth utilizes an automated reminder service that calls patients two days before their appointment, our intervention is a personalized appointment call one day before the appointment. We worked with volunteer services to develop a script and schedule for appointment reminder calls. Each day the department administrator emailed volunteer services an appointment list. The volunteers made the calls and annotated the list to identify which patients confirmed, cancelled, or did not pick up the phone. The updated list was then sent back to the department administrator. In order for this intervention to be effective, the front office staff needed updated patient contact information. Therefore, a complementary front office process change to verify patient contact information at every patient visit was rolled out as well.

In addition to the appointment reminder calls, some educational practices were introduced. Dr. Gajwani coached faculty and residents on the importance of reminding patients to attend follow up appointments. A patient handout detailing cancellation, no show, prescription refills, and urgent call policies was developed as well for distribution to new and follow up patients via email or in person.

During the cause and effect diagram session, some residents and physicians indicated that no shows could be attributed to low patient satisfaction and long wait times. To better understand patient satisfaction, a short survey was developed and administered for two weeks. The survey indicated that patients for the most part are satisfied with the service they receive, but that some would prefer shorter wait times. While improving customer service is a continuous process, one intervention developed to ameliorate patient concerns during long waits was hourly RN rounding in the waiting room to keep track of patients and assuage their concerns.

Communication:

Dr. Gajwani took responsibility for updating clinical staff, medical faculty, residents, and nursing regarding process analysis and interventions. The department administrator kept the front office informed, and Priya Khatri kept UT Physicians’ COO aware of upcoming changes and performance.

As interventions were rolled out, Priya analyzed and shared performance data with all stakeholders. If the no-show rate increased, Priya immediately sent an email to Dr. Gajwani, the department administrator, and volunteer coordinator to problem solve.

Timeline:

Process changes were slowly implemented in the month of June. Although solutions were identified at the beginning of June, finalizing action plans took some time. The first changes, patient appointment calls and the collection of up-to-date patient contact information began on June 20th, and nurse rounding in the waiting room began the following week. The group is awaiting legal review of the new patient information handout, which should be ready for distribution by the end of August.

Results (max points 250): Include all results, using control charts, graphs or tables as appropriate.

The no-show rate in the Psychiatric Clinic decreased from 31% to 12%. The average number of no-shows per day decreased, and the standard deviation of the number of no-shows per day decreased as well.

Please see performance data and control chart below:

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Revenue Enhancement /Cost Avoidance / Generalizability (max points 200): What is the revenue enhancement /cost avoidance and/or savings for your project? Did you implement this project in multiple sites after determining that your change was successful?

A decrease in patient no-shows equates to an increase in the number of patients seen. With an average patient charge of $163 year to date and a collection rate of approximately 53%, each additional patient seen contributes $86 to the bottom line. With the intervention in place, we saw the average no-shows per day fall from 19.3 to 5.2. The increase in patients seen results in an additional $1,200 in charges collected over one day. Over one week, the increase in charges collected would be $6,000, and over an entire year the increase amounts to over $300,000. Not only did the project interventions increase charges collected, but it enabled better utilization of medical and office staff.

CS&E mentor, Priya Khatri, and CS&E professor, Dr. Eric Thomas, have begun discussions to implement the project in General Medicine, Pediatrics and any other ambulatory service line with high no-show rates. We hope to perform some analysis and inform and gain buy-in from key stakeholders in the month of August and roll out interventions in September. UT Physicians’ COO, Andrew Casas, has expressed interest in spreading the success of this project to other clinics at UTP.

Conclusions and Next Steps: Describe your conclusions drawn from this project and any recommendations for future work. How does this project align with organizational goals? Describe, as applicable, how you plan to move ahead with this project.

Overall, this project proves to UTP that no-shows can be reduced with concentrated effort and positive teamwork. The effectiveness of personalized appointment reminder calls cannot be overlooked, and the psychiatry department agreed to hard wire this process change by assigning responsibility for making these calls to one of its own staff members.

The project aligns with many organizational goals. First, reduced no-shows represent an increase in the number of patients receiving treatment in a timely manner, and this increase translates to an increase in charges collected. Furthermore, as an academic institution, the number of patients that medical students, residents, and faculty see influences their educational experience and research aspirations. High no-shows result in less opportunity for resident learning and research.

As mentioned before, news of the project’s success has spread throughout UTP, and the COO has agreed to spread the project to other departments over the next few months. After achieving positive results in other departments with reduced no-show rates, we will consider more sophisticated management engineering interventions such as the design of appointment scheduling algorithms that leverage predicted no-show and cancellation rates to “overbook” and maximize the number of patients seen.

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PROJECT NAME: Reducing No-Show rates in Ambulatory Psychiatric Clinic

Institution: University of Texas Health Science Center

Primary Author: Dr. Prashant Gajwani

Secondary Author: Rachna (Priya) Khatri, MBA, MPH

Project Category: Patient Centered Care

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