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Six Sigma Project to Reduce Waiting Time

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  • #25597

    Jose Ramon
    Participant

    Hello.  My name is Jose.  I am performing a project to reduce waiting time in a Clinic. In my project I am in the improve phase of the DMAIC.  I am not sure what to do to improve the waiting time.  I perdormed a DOE to analyzed the Xs and the responses Ys.  DOE is not use to reduce waiting time but in this stage of the project what do you suggest to use ?.  I have the data from Monday to Friday with the actual setting of staff.  Please recommend me what do do to solve this problem out ?
    Thanks a lot

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    #61849

    Mikel
    Member

    Queueing theory

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    #61850

    Medic
    Participant

    Jose,
    I agree with Stan. You should tale a look at Process Model – you can obtain a free demo copy. Contact the seller … they are very helpful, unlike Simul8 and some others.
    By the way, you should use a dynamic DOE to optimise a clinic because you can’t keep the input at a constant level. It’s a bit like the steering wheel on a car – you need to be able to adjust the set-up according to the variety presenting in the clinic.
    Cheers,
    Medic

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    #61852

    melvin
    Participant

    Stay with DMAIC structure but shelve the DOE for now and use Lean tools…  Don’t get me wrong, I’m an old-school MBB, but for this type of project I use the Lean toolkit more than heavy stats.
    First – Go and walk the process (the gemba) yourself.  Value Stream Map the process looking at pt flow and data flows and vet it with the workers.  Look for bottlenecks in the process, batching (always bad), unbalanced steps in the flow.  Identify the 7 wastes (muda) by talking with the front-line folks and get them involved in continuous improvement event (Kaizen)…
     

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    #61855

    RDogg
    Participant

    If you want to reduce wait times in a Clinic, look up Advanced Access on the web.  Queuing theory is great, but often in clinics one needs only to look at demand and capacity matching on a daily basis (i.e. if demand for appointments on Monday is 15 and on Friday its 4, why schedule 10 slots on each day etc.).
    Process Model may be useful, but if you have some scheduling data and knowledge of what true demand is, it’s overkill.

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    #61857

    melvin
    Participant

    If you used DMAIC, then the results of your Analyze phase should have provided you with signficant factors that become the focus of improvement for the Improve phase. What factors were significantly related to clinic wait time?

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    #61859

    Sea
    Participant

    Bob (5th Feb) provides great advice. In getting the process map together I would also suggest drawing a Spaghetti Chart of the movement and staff and patients … and then look at the reason for the movements.
    In addition, segment the patient types if possible and analyse the time required to manage each type. You could also segment the staff and analyse how much time each type spends with the patient types.
    With all this information (and having walked the floor) there may be very obvious lay-out and preparation / change-over issues that you can address.

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    #61860

    Wayne Smith
    Member

    A common “Advanced Access” Lean approach to this uses a measurement method referred to as “Time to Third Next Available Appointment”.
    In our evaluation of how providers might measure their ability to meet Patient Appointment Demand; “Time to Third Next Available Appointment” is a metric that can be used to evaluate how a department is performing in response to Patient Volume Changes or the effects of Staffing Variation. I like it because it’s a metric based on Patient Satisfaction, and statistics are used instead of the “feelings” of management or others.
    Referred to as “Advanced Access” in the Health Care world, the formula for “Time to Third Next Available Appointment” is used to measure the patient’s ability to receive care from the provider of their choice, at the time they choose, regardless of the reason for their visit; an indicator of how long a patient waits to be seen. It is defined as “the number of days it takes a new patient to get the third next available appointment time”, (which can be less than 1) for each clinic and/or department. This measure does not differentiate between “new” and “established” patients. Also, office visits include acute as well as routine follow-up appointments.
    NUMERATOR (encounter or point in time)

    Average number of days to the third next available appointment (a continuously variable statement) requires periodic sampling at a given time interval or event trigger. In some cases the receptionist simply makes note, at the same time every day, of when the third next appointment time is available. Multiple daily samples are more accurate with sample averages feeding a daily Grand Average.
    DENOMINATOR (provider)
    Providers within a clinic and/or department (see the related “Denominator Inclusions/Exclusions” below)
     
    DENOMINATOR INCLUSIONS/EXCLUSIONS
    InclusionsThis measure applies to providers* within a reported clinic and/or department**
    *Providers:
    ·         All providers are included. Full-time and part-time providers are included, regardless of the number of hours s/he practices per week.
    ·         Providers who truly job share are counted as one provider (i.e., they share one schedule, and/or they work separate day and share coverage of one practice).
    ·         When measuring a care team, each member of the care team is counted separately (i.e., MD, NP, PA).
    ·         If a provider is practicing in a specialty other than the one in which s/he is board certified, the provider should be included in the specialty in which s/he is practicing.
    ·         For providers practicing at more than 1 location, measure days to third next available for only the provider’s primary location as long as the provider is at that location 51%+ of their time.
    ·         Locums are included in the measure only if they are assigned to a specific site for an extended period of time (greater than 4 weeks) and provide continuity care to a panel of patients.
    ·         Mid-Level providers are included in the measure (NP, PA, CNM).
    ·         Mid-Level providers should have continuity practice and their own schedule available to see patients.
    **Departments:
    ·         Primary Care
    o        General Internal Medicine
    o        Family Practice
    o        Pediatrics with the focus on generalists, not specialists
    o        Med/Peds (physicians who see both adults and children)
    o        Specialty Care
    o        Obstetrics
    o        Physical exam = New OB visit
    Exclusions
    ·         Exclude clinicians who do not practice for an extended period of time (greater than 4 weeks) due to maternity leave, sabbatical, family medical leave.
    ·         Mid-Level providers who function only as an “extender,” overflow to another practice, or urgent care should not be included.
     
     
     
     

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    #61862

    Dr. Gibson
    Participant

    When you performed the cause and effect diagram/matrix or fishbone diagram in the analyze phase, you should have identified the cause of “increased wait time”. Once that was identified, make sure that you collect data on the (x’s) to ensure that it is the true problem or a big enough problem to put improvements in place.
    Do hypothesis testing based on the type of data that you have. Based on the true cause of wait time, you might want to re-structure how the process is. It could be a scheduling issue,  doctors issue, staffing/resource issues. Figure out what the real reason is and re-do the process or look at other avenues that would improve patient wait time. 

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    #61864

    Roger Noble
    Member

    I am doing a similar project for our 22 hospitals and their Outpatient Clinics. My approach differs slightly from each of the approaches recommended so far. I’m forming this project as an MBB DMAIC study. Why? it’s not going to find a solution necessarily. Instead, it’s going to identify all the potential factors downstream that will increase a patient’s wait time. Ex: re-imaging in Xray due to rework, patient awaiting transport to a specialty consult, handsoff shift change for patients still in the Exam process. You get the picture. What we are going to do is identify all the factors then identify the acuity of their impact on the wait times. We will then break these factors down into Black Belt/Green Belt level projects to focus on just one of the factors each. In other words, you will have multiple improvement projects going on at the same time that will impact Wait Times.
    Why this approach? Some times a project appears narrow in scope: high wait times. In actuality, the factors impacting that outcome are actually too broad in scope. Thus, you need to break it down into managable improvement chunks. Thus, Wait Times has become a Six Sigma Improvement Initiative comprised of many Improvement projects.

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    #61868

    Tyler Smith
    Member

    Developing an electronic messaging system that allows patients to contact providers for simple prescription refills, questions on conditions and appointment settings is also useful.
    Staff can “triage” the messages so that MD mailboxes are not full. The system saves phone calls and the need for verbal exchanges between staff and MD, both of which are significant time consumers.
    Patient satisfaction improves not only because many like the convenience of electronic communication, but also because staff can spend more time helping people sign in, communicating when there is a delay, etc.
     

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    #61873

    mullally
    Participant

    These discussions are so important.  Canada, Japan, UK and many others are facing resource issues and the easiest most inexpensive way to reduce waits is through Lean and Six Sigma.  I have another blog at http://www.waittimes.blogspot.com discussing this.  Our office has been using both lean and six sigma for 7 years.  I attribute 10-20% change across the board in efficiency due to six sigma projects.  Good discussions.  Ian.

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    #61882

    Ian Furst
    Participant

    Sorry Jose – just read the original blog,
    There are several concrete things you can do but queue theory isn’t one of them.  Try using block booking to break up you’re patient population — you will likely find that some groups are “over-serviced” and others “under-serviced”.  I’ve got an article on this at http://www.waittimes.blogspot.com  Once you’ve got the populations defined and there wait times measured you should be able to make adjustments to you’re schedule to get them in quickly.  Assuming that you’re wait time is not 0 for any population use Little’s Law which basically says that you’re wait time = number in the queue/average completion rate.  If you have 200 people in the queue and you see 20 per day you’re wait is 10 days (this breaks down if the queue empties).  There are other techniques but they won’t have the same bang-for-the-buck.  That being said you can decrease the variation in wait times (improves efficiency), value-map processes from the patients’s perspective (e.g. first call to discharge), six-sigma processes to prevent repeated clinic visits.  These are the big ones.  Email if you need more specifics.  Ian.

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