Question

Holistic Health Systems (HHS) operates 39 hospital facilities and clinics. The executive team has been reviewing key metrics over the last year and identified a need to improve Point of Service Collections or simply known as POS (pronounced “P-O-S”). POS is a patient payment that is received within 7 days after discharge. Increasing POS is important for HHS because hospitals are 60% less likely to receive payment once the patient leaves the hospital. The cost to collect on the patient’s account continues to go up while the chance of actually collecting payment goes down if there is a delay in collecting the payment after the patient’s discharge. Therefore, it is better to not delay collecting the payment.

Increasing POS reduces Bad Debts, provides a better cash position, reduces expenses, and increases patient satisfaction when conducted properly.

POS is calculated by dividing POS Payments by Total Patient Cash Collected.

HHS has identified the industry median benchmark for POS as 13.6% and the top 10% POS benchmark as 41.4%. HHS’s current POS performance is 35.6% and the executive team has determined that a 5 percentage point increase is needed to stay competitive (target = 40.6%). A Lean Six Sigma team was formed.

POS is a metric that heavily relies on the Patient Access team or PA. PA is responsible for several tasks—patient scheduling, registration, and financial clearance. The “Scheduling” tasks are typically completed by a centralized PA team for multiple hospital facilities. During Scheduling, PA reps receive a doctor’s order for a patient. The order is like a permission slip for specific medical services the doctor deems necessary.

The doctor or even the patient related to the order can call Scheduling to reserve an appointment for the services that correspond to what is written in the order. PA reps need to verify that the order is complete and accurate, coordinate time for services, and provide patients with pre-service instructions. After patient’s information is logged into the scheduling system, it will queue up to the PA registration team to complete the registration process. PA will call the patient and confirm the identity, collect demographics such as address, family, emergency contact, etc. PA registration will also confirm the patient’s health insurance provider(s). PA registration can be completed at a hospital facility or by a centralized team. Lastly, PA Financial Clearance will verify patient health benefits to ensure they exist and to determine if the procedure or service for the patient is covered. If authorization is required, the PA Financial Clearance will request authorization for services from the patient’s health insurance provider. Services performed without authorization lead to rejected claims. Also during PA Financial Clearance, the PA rep will Counsel the patient about their liability (how much their insurance provider says they need to pay for the services) and collect the payment. Any payment received is considered POS since it’s before 7 days post discharge. Financial clearance can also be performed at the hospital facilities or by a centralized team.

Summary patient cash data for HHS’s 39 hospital facilities for a year is presented in Table 1. The table also indicates if the PA team for each facility is centralized or not.

Table 2 provides an overall monthly trend for POS Performance

The team identified the facilities with POS performance above the target and researched the activities they have in place hoping to find commonalities or key drivers.

They are:

 ensure proper patient education on benefits and liability

 ask for payment

 have a financial counseling policy

 reduce number of patients that leave without financial clearance

 have accurate tools to help estimate Patient Liability or Responsibility

 utilize devices that allow patient collections at patient bedside

Holistic Health Systems (HHS) operates 39 hospital facilities and clinics. The executive team has been reviewing key metrics over the last year and identified a need to improve Point of Service Collections or simply known as POS (pronounced “P-O-S”). POS is a patient payment that is received within 7 days after discharge. Increasing POS is important for HHS because hospitals are 60% less likely to receive payment once the patient leaves the hospital. The cost to collect on the patient’s account continues to go up while the chance of actually collecting payment goes down if there is a delay in collecting the payment after the patient’s discharge. Therefore, it is better to not delay collecting the payment.

Increasing POS reduces Bad Debts, provides a better cash position, reduces expenses, and increases patient satisfaction when conducted properly.

POS is calculated by dividing POS Payments by Total Patient Cash Collected.

HHS has identified the industry median benchmark for POS as 13.6% and the top 10% POS benchmark as 41.4%. HHS’s current POS performance is 35.6% and the executive team has determined that a 5 percentage point increase is needed to stay competitive (target = 40.6%). A Lean Six Sigma team was formed.

POS is a metric that heavily relies on the Patient Access team or PA. PA is responsible for several tasks—patient scheduling, registration, and financial clearance. The “Scheduling” tasks are typically completed by a centralized PA team for multiple hospital facilities. During Scheduling, PA reps receive a doctor’s order for a patient. The order is like a permission slip for specific medical services the doctor deems necessary.

The doctor or even the patient related to the order can call Scheduling to reserve an appointment for the services that correspond to what is written in the order. PA reps need to verify that the order is complete and accurate, coordinate time for services, and provide patients with pre-service instructions. After patient’s information is logged into the scheduling system, it will queue up to the PA registration team to complete the registration process. PA will call the patient and confirm the identity, collect demographics such as address, family, emergency contact, etc. PA registration will also confirm the patient’s health insurance provider(s). PA registration can be completed at a hospital facility or by a centralized team. Lastly, PA Financial Clearance will verify patient health benefits to ensure they exist and to determine if the procedure or service for the patient is covered. If authorization is required, the PA Financial Clearance will request authorization for services from the patient’s health insurance provider. Services performed without authorization lead to rejected claims. Also during PA Financial Clearance, the PA rep will Counsel the patient about their liability (how much their insurance provider says they need to pay for the services) and collect the payment. Any payment received is considered POS since it’s before 7 days post discharge. Financial clearance can also be performed at the hospital facilities or by a centralized team.

Summary patient cash data for HHS’s 39 hospital facilities for a year is presented in Table 1. The table also indicates if the PA team for each facility is centralized or not.

Table 2 provides an overall monthly trend for POS Performance

The team identified the facilities with POS performance above the target and researched the activities they have in place hoping to find commonalities or key drivers.

They are:

 ensure proper patient education on benefits and liability

 ask for payment

 have a financial counseling policy

 reduce number of patients that leave without financial clearance

 have accurate tools to help estimate Patient Liability or Responsibility

 utilize devices that allow patient collections at patient bedside

Table 1: 2015 POS by Facility Facility POS Payments | All Patient Payments | POS% | Centralized Teams 015 $1,301,746 $2,964,730 $625,428 $849,646 076 3,348,748 $6,854,164 1,709,452 2,141,211 LAK CGH 37% 9,710,312 6,062,173 241 2,250,807 GSM $2,621,784 $1,713,107 5,936,564 $1,215,112 SMH Yes PGH 5,395,09 41% $1,311,286 $2,997,636 3,611,438 7,494,091 WBO 26% Yes $2,358,653 8,133,287 5,286,184 BAR $1457,038 236 $1,076,377 $2,145,483 $2,428,480 $2,253,084 2,979,026 5,249,186 7,833,806 7,080,683 739,024 7,262,268 $13,946,130 357 $4,624,894 6,929,016 446,048 9,134,398 $4,378,487 9,188,848 3,939,240 503 $4,971,199 7,850,558 999,804 $10,909,840 IND 41% 31% 32% $2,455,353 $3,486,532 534,470 $2,416,085 $2,182,243 GBH BMC 25% FRH HNM LPX NMC PMC PPH 31% 45% $3,379,727 $1,946,885 $2,885,804 $1,969,620 31% SES SFH $1,940,017 $3,254,250 3,051,755 $2,658,292 $1,606,482 $1,297,858 No 41% 44% SRM 24% $5,225, 755 25% No

Read case study then answer the following questions

Exercise 1 Process Stability Using the data given in Table 2, determine if the POS performance is stable using a control chart.
Explain why you used the type of control chart you selected.

Exercise 2 Scope Opportunity Using the data given in Table 1, how would you scope the focus area of the project?

Exercise 3 Testing a Theory Use the data from Table 1 and conduct a hypothesis test to determine if centralized teams impact POS collections.

Exercise 4 Solution Categories Based on the information provided what could be affinity categories for the key drivers that impact POS performance?

Answer 1

Answer:

the control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation).

Control charts for variable data are used in pairs. The top chart monitors the average, or the centering of the distribution of data from the process. The bottom chart monitors the range, or the width of the distribution. If your data were shots in target practice, the average is where the shots are clustering, and the range is how tightly they are clustered. Control charts for attribute data are used singly.

When to Use a Control Chart

• When controlling ongoing processes by finding and correcting problems as they occur.
• When predicting the expected range of outcomes from a process.
• When determining whether a process is stable (in statistical control).
• When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process).
• When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

Template

See a sample control chart and create your own with the control chart template (Excel, 973 KB).*

Control Chart Basic Procedure

0 1 2 3 4 5 67 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Time

Figure 1 Control Chart: Out-of-Control Signals

1. Choose the appropriate control chart for your data.
2. Determine the appropriate time period for collecting and plotting data.
3. Collect data, construct your chart and analyze the data.
4. Look for “out-of-control signals” on the control chart. When one is identified, mark it on the chart and investigate the cause. Document how you investigated, what you learned, the cause and how it was corrected.

   Out-of-control signals

   • A single point outside the control limits. In Figure 1, point sixteen is above the UCL (upper control limit).
   • Two out of three successive points are on the same side of the centerline and farther than 2 σ from it. In Figure 1, point 4 sends that signal.
   • Four out of five successive points are on the same side of the centerline and farther than 1 σ from it. In Figure 1, point 11 sends that signal.
   • A run of eight in a row are on the same side of the centerline. Or 10 out of 11, 12 out of 14 or 16 out of 20. In Figure 1, point 21 is eighth in a row above the centerline.
   • Obvious consistent or persistent patterns that suggest something unusual about your data and your process.
5. Continue to plot data as they are generated. As each new data point is plotted, check for new out-of-control signals.
6. When you start a new control chart, the process may be out of control. If so, the control limits calculated from the first 20 points are conditional limits. When you have at least 20 sequential points from a period when the process is operating in control, recalculate control limits