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PATIENT FLOW: FOLLOW – UP REPORT

PATIENT FLOW: FOLLOW – UP REPORT. Agoncillo , Asperas , Cosalan , Tanbonliong ASMIP 2009. BACKGROUND. SIGNIFICANCE OF THE STUDY. Assess and evaluate the current patient flow system being employed Identify weak and strong points of the system

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PATIENT FLOW: FOLLOW – UP REPORT

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  1. PATIENT FLOW: FOLLOW – UP REPORT Agoncillo, Asperas, Cosalan, Tanbonliong ASMIP 2009

  2. BACKGROUND

  3. SIGNIFICANCE OF THE STUDY • Assess and evaluate the current patient flow system being employed • Identify weak and strong points of the system • Provide tools and recommendations to keep the operations of the center as efficient as possible

  4. SCOPE AND LIMITATIONS • Study is based on changes made by a previous study conducted last year focused on patient flow and waiting times • Statistical data from June 2008 to May 2009

  5. OBJECTIVES General Objective This follow-up study seeks to evaluate the current operation system of American Eye Center in terms of waiting lines and patient flow.

  6. Specific Objectives • Determine and compare current and previous statistical trends on patient volume according to: • Time interval in a day • Day of the week • Age group • Chart type

  7. Evaluate the general flow of patients in the clinic on light and heavy days within the period after the initial study on operations management • Assess the utilization of examination rooms and relate it to patient volume and turnover from optometrist to ophthalmologist

  8. Assess the recommendations from the previous study • Provide recommendations that will improve the waiting lines and patient flow

  9. STATISTICAL TRENDS: TIME INTERVAL IN A DAY Average Patient Volume by Time Interval per Weekday

  10. Current Patient Volume by Time Interval per Workday There is a peak of incoming patients around 9am to 11am that later on decline s during lunch hour and later on peaks again at 1pm. This is unlike the previous study which shows a steady decrease in the number of incoming patients as the day progresses.

  11. Patient Volume by Time Interval per Month

  12. Current Patient Volume by Time Interval per Month Similar to the previous chart on Time Interval per Workday, the table on Time Interval per Month shows a similar trend. There is an increase in patient volume in the morning, a decrease during lunchtime, and again an increase after lunch at around 1pm Back to objectives

  13. STATISTICAL TRENDS: DAY OF THE WEEK

  14. Average Patient Volume by Weekday There has been an increase on the average number of patients this year as compared to last year. The trend on the busiest and slowest days of the week remain the same however with Saturday as having the most number of patients and Wednesday having the least. The trend may be due to the schedule of surgeries and consultations that are have a specific schedule in the week and the presence or absence of the physicians. Back to objectives

  15. STATISTICAL TRENDS: AGE GROUPPatient Volume by Age Group per Month Majority of patients come from the 19 – 59 age group. Patients from the 60 and above age group are the next most numerous since the clinic offers procedures to repair cataracts

  16. Patient Volume by Age Group per Day of the Week There has been a noted decrease in patients from the 19 – 59 age group and an increase in the 60 and above age group this year. This increase in the number of senior citizens may be due to the increasing popularity of cataract treatment services provided for by the clinic Back to objectives

  17. STATISTICAL TRENDS: CHART TYPE Patient Volume by Chart Type per Month It is seen from the chart and table that majority of patients go to the clinic for follow – up sessions. This is understandable since patients that undergo surgeries must return to the clinic repetitively for Observation.

  18. Patient Volume by Chart Type per Weekday Saturday is considered the busiest day despite the shorter working time and lack of surgeries thus the day is mostly devoted to follow – up and consultations. Back to objectives

  19. GENERAL FLOW

  20. PATIENT DATA PROCESSING AT FRONT DESK A marked decrease in the processing time was observed from 3 min and 2 seconds last year to 16 seconds this year. This drastic decrease is attributed to the SmartQ system that is being implemented. Although this system was already in effect last year, it was still very new. Thus, the staff may have still been unfamiliar with the system last year and this year are already very familiar and used to it.

  21. TURNOVER FROM CHART BOX TO OPTOMETRIST Current Study This shows the time it takes for the charts to be picked up by the optometrists. There is an increase in duration at around 11:30am and reached its peak at 1:00pm. The initial increase may be attributed To the surge of patients that came in During the morning while the second Increase may be due to the decrease in Number of optometrists since most Of them have their lunch at this time. The current study shows a decrease in duration as the day progresses unlike the previous study that shows the steady increase in duration until the clinic closes. Previous Study

  22. GENERAL SCREENINGS Automated Refractometry Corneal Topography Air Puff Tonometry Specular Microscopy

  23. OPTOMETRIST ROOM USE The results for optometrist room use last year compared to this year is very similar. The results show a room use that ranges from 1min to 15 min with an average of around 6 min. The optometrists use the room to perform numerous tests to the patient and explains procedures which accounts for the long room use time.

  24. TURNOVER FROM OPTOMETRIST TO OPHTHALMOLOGIST The patient waiting for a room to be available or for the doctor to finish with his preceding patients There is a significant decrease in waiting time which means that there is a more efficient usage of rooms.

  25. OPTHALMOLOGIST ROOM USE Ophthalmologists usually perform less tests than optometrists The maximum time may be attributed to consultations that patients and their family may have with the doctors thus resulting to a maximum time similar to that of the Optometrists There is no significant difference in last year’s time from this year’s time. Back to objectives

  26. ROOM UTILITY

  27. CATARACT SURGERY DAY: MAY 26 Cataract surgery days are usually on Tuesdays and Thursdays. The average duration is 8min with the shortest time of 5min and the longest time of 43 min showing a large range. This long time may be due to elderly patients who consult long with physicians due to their cataract surgeries.

  28. DURATION OF USE BY TIME INTERVAL PER EXAM ROOM: May 26

  29. LASIK SURGERY DAY: May 29 LASIK surgeries are scheduled every Monday and Friday. There is an average waiting time of 9min with the shortest time being 7min and the Longest time being 14min. The smaller range in the results is indicative that there are more patients in the working group than in the elderly and children group since the working group are usually the ones who opt for LASIK surgery.

  30. DURATION OF USE BY TIME INTERVAL PER EXAM ROOM: May 26

  31. ROOM UTILITY ON A SATURDAY: May 30 Saturday is the busiest day of the week of the clinic. Most of the cases here are follow – up consultations and there is an increased number of pediatric aged patients during Saturday. The average time is 8min with a range of 3min being the shortest time and 24min as the longest time. According to interviews, the long time may be attributed to pediatric patients who are sometimes difficult to perform tests to.

  32. DURATION OF USE BY TIME INTERVAL PER EXAM ROOM: May 30

  33. AVERAGE ROOM VACANCY IN 1 DAY Significant decrease in time of room vacancy this year compared to last year which means that there is a more efficient usage of rooms and they are not left empty. Therefore there is also a decrease in the turnover time Of patients from optometrists to opthalmologists.

  34. CONCLUSION • Statistical trends on patient volume • Peaks before and after lunch • Saturday contains the highest volume of patients • Majority of patients are of working age (19 – 59) • Majority of patients are in the clinic for follow-up (FF)

  35. Comparison of current and previous study • Increase in total number of patients • Increase in GC: 661 – 794 • Increase in FF: 1956 – 1689 • Increase in LS: 132 – 162 • Increase in SX: 221 – 231 • Change in trend according to time interval • Previous study • Linear decline in patient volume • Current study • Two peaks in patient volume (before and after lunch)

  36. Same trend according to workday • Tuesday, Friday and Saturday = most number of patients • Same distribution according to age group • Majority of patients from 19 – 59 age group • Increase in percentage of patients from the 60 and above group • Evaluate the general flow of patients in the clinic on light and heavy days within the period after the initial study on operations management

  37. Decrease in the processing time • From 3:02 to 0:16 • Increase in turnover duration from chart to opto at 11:30am • Charts started to pile up due to increase in patient volume • Peak at 1:00pm due to a decrease in the number of optometrists • No significant change in general screening, opto and ophtha room use • Decrease in turnover from opto to ophtha

  38. Assess the utilization of examination rooms and relate it to patient volume and turnover time from optometrist to ophthalmologist • Same trend • Increase in utilization • More efficient, less periods of vacancy • Decrease turnover time from opto to optha • Increase in number of patients served per hour

  39. Identify changes in the operation system and relate these to the current patient flow and waiting time • Charts from the box have numbers that are being followed • More efficient use of exam rooms • Generally, no change in the system; changes in the efficiency of people in the system (encoding, chart prioritization, room assignment and use)

  40. RECOMMENDATIONS • Adhere to an appointment based institution • Scheduled breaks of optometrists • Maintain a standard cut-off time • Lessen incoming late patients and limit the quota • Hiring more personnel or training more employees to help with record keeping and retrieval of files • Investment in machines • Automation of files

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