Running head: OPEN-ACCESS SCHEDULING

Open-Access Scheduling
Dimple Patel
Arizona State University

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Abstract

A variety of primary health care offices are looking for ways to reduce missed appointments,
increase patient, provider, and staff satisfaction, decrease emergency room visits, and increase
revenue. It is well known that patients miss their appointments for a variety of reasons and when
patients cannot be seen when they want to be or need to be, they become less satisfied. They also
begin to seek care in emergency rooms or urgent care centers, which unnecessarily increases
healthcare spending and does not allow others to be seen. Additionally, when patients do not
show up for their scheduled appointment, office income suffers. Therefore, the purpose of this
paper is to propose an evidence-based practice project to determine how open-access scheduling
(OAS) will affect missed appointments, patient satisfaction, provider satisfaction, staff
satisfaction, revenue, and the use of emergency rooms or urgent cares in a primary health care
setting. In doing this, it will address the overall problem, provide some background information
on the topic, review internal and external evidence surrounding the problem, and will discuss the
overall intervention and results from the proposed intervention.
Keywords: open-access, scheduling, emergency room or department, patient satisfaction, missed
appointments, revenue.

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Open-Access Scheduling

Health care providers are looking for ways to decrease missed appointments (MA),
decrease emergency room visits, increase revenue, and increase patient, provider, and staff
satisfaction scores in their primary care offices. Dating back to the 1990’s, a physician, Dr. Mark
Murray, and Catherine Tantau, a registered nurse, addressed an indirect solution to missed
patient appointments by initiating open-access scheduling (OAS). With the goal of making
patient care more easily available, implementing and evaluating this process took place in the
year 2000 when they published their first study; which has now been recognized as a landmark
piece of work (Grace, 2007). Their goal was to make patient care more easily available by
“Do[ing] today’s work today”(Grace, 2007), and their work has provided numerous benefits for
providers.
Problem Statement
Missed appointments (MA) negatively impact the health care system and are best
described as patients who do not show up or show up late for their scheduled appointment
(Rosario, 2013). Multiple studies have found that MAs are a nation-wide problem and rates
range anywhere from 3% to 80% (Kheirkhah, Feng, Travis, Tavakoli-Tabasi & Sharafkhaneh,
2015). A recent study has indicated that the average no-show rate is now 12.3% (Kuy, 2016).
MAs decrease efficiency, increase worsening of chronic disease, decrease revenue, delay
treatment, prevent other patients from being seen, wastes health care dollars, and wastes
healthcare provider time (Kaplan-Lewis & Percac-Lima, 2013; Miller, Chae, Peterson, & Ko,
2015; Huang & Zuniga, 2012).
Additionally, providers have noticed a decrease in patient satisfaction scores and are
looking for ways to solve the MA problem (Solberg, 2011). This is likely related to poor access

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to healthcare when needed (Fournier, Heale & Rietze, 2012). In 2015, the Commonwealth Fund
in Canada conducted a survey, and found only 41% of patients were able to see their provider on
the same-day or the next day when they were seeking immediate medical attention (Kiran &
O’Brien, 2015). Compounding the problem of MAs, Uscher-Pines, Pines, Kellermann, Gillen,
and Mehrotra (2013) found that 39% of emergency room visits are non-urgent and could have
been managed in the primary care office. This has benknown to increase health care spending
and unnecessary testing, and provide unwarranted treatment (Uscher-Pines et al., 2013).
Therefore, by finding ways to avert MAs, there is the possibility of decreasing emergency room
or urgent care visits, increasing patient satisfaction scores and revenue in the primary care office,
and decreasing overall healthcare expenditures. To solve this, they have found that OAS has
been the solution to decreasing MAs. OAS allows an individual to make an appointment with
their health care provider on the same day or the next day (Fournier, Rainville, Ingram, & Heale,
2015). Thus, these findings lead to the following clinically relevant PICOT question: In a
primary care practice (P), how does open-access appointment scheduling (I) compared to
traditional office scheduling (C) affect office income (outpatient revenue), patient satisfaction,
provider satisfaction, staff satisfaction, emergency room or urgent care visits, and missed
appointment rates (O) over three months (T)?
Background and Significance
Due to the many challenges associated with OAS, many health care offices have
attempted other scheduling systems. Some have been proven more successful than others have
and some are outdated while others are still being used to this day. These include scheduling
reminder systems, over or double booking patients, penalization (Kheirkhah et al., 2015), or
seeing patients on a first-come, first serve basis (Izard, 2005). Some of the common challenges

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associated with OAS include difficulties with implementation, a physician shortage, provider
resistance to changes in scheduling systems, frequent staff changes, and differing schedules
among employees (Rose, Ross & Horwitz, 2011). Solberg (2011) discusses that due to the
constant change in health care and how providers are being paid; OAS is being studied and
reported quiet differently. Flaws in the design and reporting of published studies have been
noted; and that is why many studies that are being published are observational or case studies
(Solberg, 2011). According to Miller (2007), Dr. Murray believes only 20% of primary care
practices are currently using OAS because implementation is challenging – and requires many
changes and planning. Nonetheless, Murray & Tantau have provided various resources to
practices to assist with implementing and facilitating this change (Solberg, 2011). Supporting
the role of primary care is vital as it provides an important service to the public, is cost effective,
and provides continuity of care to patients with acute and chronic conditions in order to reduce
health disparities for all individuals (Agency for Healthcare Research and Quality, 2012). In
2010, there were close to 300,000 providers in the United States providing primary care
including physicians, nurse practitioners and physician assistants (Agency for Healthcare
Research and Quality, 2012).
Several reasons are cited for MAs. Kaplan-Lewis & Percac-Lima (2013) found that MAs
are related to patients forgetting about their scheduled appointments or have received incorrect
information about their appointment, as they may have received an incorrect date or time. In a
survey conducted in the United Kingdom by Neal, Hussain-Fambles, Allgar, Lawlor, &
Dempsey (2005) reasons were found as to why some individuals missed their appointments.
These reasons ranged from difficulty with cancelling their appointment to being hospitalized
(Neal, Hussain-Fambles, Allgar, Lawlor, & Dempsey, 2005). A study in Canada by Mitchell

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(2008) found multiple benefits of using OAS. They not only noticed a decrease in no-show rates,
but they found that patients were happier, physicians and staff felt more confident, and
physicians noticed stability in their income. One study at Kaiser Permanente found that with
using OAS, no-show rates decreased from 20% to 0% (Mitchell, 2008). DuMontier, Rindfleisch,
Pruszynski, & Frey (2013) found that the longer the time lags between when an appointment is
scheduled and when the appointment actually occurs, the less likely they are to show up for their
appointment. Individuals who are underserved, have Medicaid, are Hispanic or African
American, are known to have the highest rates of MAs (Kaplan-Lewis & Percac-Lima, 2013;
Miller et al., 2015; & Homisak, 2013). It is also known that individuals who are uninsured are
more likely to visit the emergency room for care that can easily be provided in a primary care
office, causing undue health care costs (Americans are visiting, 2012; DuMontier et al., 2013).
Cost and lack of money are barriers to MAs. Kheirkhah et al. (2015) found that each
missed appointment costs their practice $196. Moch (2012) found that adding one more patient
to the schedule each day can help increase revenue vastly and that is why some physician
practices charge patients a fee for missing their scheduled appointment. Fournier et al. (2012)
found that a practice in Canada implemented OAS and saw their revenue increase by 7%.
Additionally, Wojciechowski (2012) also found that OAS increased their revenue and allowed
more units to be billed.
Additionally, when patients want to be seen for urgent matters on the same-day and
cannot be seen by their primary care provider, they resort to going to clinics or emergency rooms
(Fournier et al., 2012). Cox (2015) & Murray and Tantau (2000) found that greater patient
satisfaction is achieved when patient’s needs are met on the same day. Cox (2015) states that in
order to keep up with the current millennial culture, much of appointment scheduling needs to

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become more flexible and convenient for this population. A seminal report published by the New
England Healthcare Institute (NEHI) in 2007 found that emergency departments in the U.S.
currently waste $38 billion annually and one of the reasons health care costs are so high in
emergency rooms is related to the lack of same day access availability in primary care (NEHI,
2010).
The current method for many primary care offices includes using the traditional method
of scheduling, which allows patients to schedule future appointments (Rose et al., 2011).
Currently at two primary health care clinics in Phoenix, Arizona, providers, medical assistants
and other support staff list various reasons as to why patients do not show up for appointments.
These include lack of transportation, lack of being able to see their preferred provider, lack of
money/financial burden, symptom improvement, holidays, lack of babysitter/daycare services,
location, forgetting about their appointment, or they are finding that their job and providing for
their family is more of a priority than their health. They also believe having decreased access to
care affects patient satisfaction. During one-week in June 2017, a survey was completed at the
clinics asking patients who missed their scheduled appointments why they missed them. A total
of 56 missed appointments occurred during this time frame, and 40 of them provided responses.
The most common reasons included forgetting about their scheduled appointment or forgetting to
call and cancel their scheduled appointment. Between the two health centers and 8 providers,
from September 2016 to December 2016, 15.28% of patients missed their scheduled visits.
During this time, and in the past, these clinics previously used automated system reminders and
have called and reminded patients the day before to confirm their appointment without much
success.
Search Strategy

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An exhaustive search of the literature was completed on this topic. Six different databases
were searched—ABI inform, Academic Search Premier, CINAHL, Cochrane Library, EconLit,
and PubMed. The following are a list of the most common keywords that were searched among
all six databases combined: Open-access, scheduling, emergency room or department, patient
satisfaction, missed appointments, and revenue. Some terms were searched with a hyphen to
yield additional results. MeSH, MAJR, MH terms included appointments and schedules, health
services accessibility/organization and administration, and cost-benefit analysis.
Exclusion criteria included published dates before 2007, studies written in a non-English
language or those that did not include humans. Ancestry searches led to studies published greater
than ten years ago or studies that were not published; therefore, they were inappropriate for this
review. Additionally, commentaries or editor reports were also excluded when looking at the
literature for review since this information did not provide quality evidence.
Due to the lack of external information on the topic at hand, six databases were searched
in depth over the last ten years. The following is a discussion on the databases yielding the most
pertinent evidence to answer the PICOT question.
The Academic Search Premier database (Appendix B) provided an initial yield of
10,487 articles with the keywords same day access or open access. The final yield using same
day or open access or advanced access and appointments and scheduling provided nine results,
which were retained for further review. The Cochrane Library search strategy (Appendix D)
provided an initial yield of 9,792 with the keywords open access or open-access or advancedaccess or advanced access or same-day or same day. When the following key words were used,
appointments and schedules, it provided an initial yield of 9,792. When both sets of these
keywords were combined (open access or open-access or advanced-access or advanced access

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or same-day or same day and appointments and schedules), final yields of 26 articles were found
and retained for further review. The EconLit search strategy (Appendix E) provided an initial
yield of 368 articles with the keywords, open access or same day access or open-access or sameday access. When the keywords, appointments and scheduling were added, it provided an initial
yield of 30 results. When these sets of key words were combined (open access or open-access or
advanced-access or advanced access or same-day or same day and appointments and schedules),
it provided a final yield of one result.
After critical appraisal of 57 studies, ten have been chosen for inclusion in this literature
review (Appendix A, B, C, D, E, F). Those that were included evaluated effects of patient
satisfaction, outpatient revenue (income), MAs and emergency room or urgent care visits with
the use of OAS.
Critical Appraisal and Synthesis of Evidence
Ten studies, as presented in Appendix G, were retained for inclusion in this review,
following a rapid critical appraisal process. The final ten studies included: (1) prospective and
retrospective (PR) quantitative study; (1) PR quantitative cohort study; (1) cross sectional
retrospective study (CSS); (1) anecdotal observations and experience study; (1) discussion, (1)
survey; (1) comparison study with the use of variables; (1) systematic review (SR) of metaanalyses (MTA) in a qualitative study; (1) case study (CS); and (1) multi-level regression model.
Three of these studies were level VI evidence, two studies were a level IV, three studies were a
level VII, one study was a level V, and another study was a level III. These studies were rated
according to the hierarchy of evidence described by Fineout-Overholt (2009). The overall levels
of evidence for these studies are considered low; however, these studies were the best available
evidence based on the inclusion criteria and the PICOT question.

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Due to the limited availability of evidence on OAS, difficulties associated with
implementing OAS, and predominant numbers of longitudinal studies, the strength of the
evidence is difficult to determine. Therefore, the goal of this project is to look at appointments
and schedules in primary care offices, and look for ways to ‘improve the process’ by
implementing OAS so that MAs do not occur, patient satisfaction is achieved, revenue is
increased, and emergency room visits decrease. Most of the studies reported no conflicts or bias
(Appendix G); however, one study, which was a systematic review of meta-analyses, did discuss
some bias (Appendix G). Depending on the bias that is reported, it is likely to weaken the body
of the evidence.
There was moderate homogeneity across the studies. Nine of the studies used OAS as
their intervention (Appendix G & H) and seven of the studies examined the effects of MAs with
the use of this intervention (Appendix G & H). Very few studies looked at patient satisfaction
(3), revenue and cost (3), and emergency room visits (1) (Appendix G & H). Many differences
exist in regards to the study design, as there are not any studies that have the same exact design;
which ultimately affects proposing the best intervention for the project (Appendix H). One study
looked specifically at lead time (which looks at the time difference between when an
appointment is made to when the appointment is scheduled) and found that when appointments
are made closer to the date of the appointment then they are more likely to show up for their
appointment (Appendix G). Additionally, the majority of the studies were done in the United
States or Canada, making this process likely feasible in the United States (Appendix G). Some
heterogeneity exists among these studies as well as the interventions of OAS were implemented
in a variety of settings including primary care, physical therapy/occupational therapy, an

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ophthalmology clinic, and veteran clinics (Appendix G). Similarly, one study used model
formulations to determine the effects of OAS on MAs (Appendix G).
For the majority of the studies, the independent variable included a form of OAS
(Appendix H). The dependent variables varied among the studies, but the majority discussed
MAs (Appendix H). Other dependent variables included patient satisfaction (3), emergency room
visits (1), revenue or costs (3), wait time (4), and lead time (1) (Appendix H). A variety of tools
and measurements were used among the studies. One study used time to third appointment
available where empirical data was collected overtime and with the use of t tests, and found a
statistically significant reduction in MAs (P<0.0001) (Appendix G). Another study interviewed
clinical staff and used open-ended surveys to determine if a multi-method intervention including
OAS would reduce MAs. Chi-squared tests were used to determine the no-show rate and found a
significant reduction in the number of MAs in the total patient population (P<0.001) in the office
and in the individuals that miss appointments the most (P<0.001) (Appendix G). One study
looked at patient satisfaction through observations and statements or comments made by the
patients, providers and staff. No source of data analysis was used; however through these
observations and statements, they found patients were more satisfied with this method as more
than 85% of patients were able to schedule appointments on the same day or the next day and
were also able to reduce office costs (Appendix G). Another study obtained data from a
computerized scheduling database and examined the correlation between keeping appointments
when an appointment is made closer to the actual appointment date. Z-tests were used to
determine this comparison and found that faculty physicians and resident physicians, had a
significant reduction in MAs (P<0.001). They also found that when patient’s appointments are
scheduled more than two weeks from their scheduled appointment, they are more likely to miss it

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(Appendix G). In another study, the office scheduling system was used to determine the rates of
MAs and a survey was sent out to 100 randomly selected patients at the office to determine their
satisfaction with the new system. The data analysis they used to report their findings was not
reported; however, found that their patients were more satisfied (93%), as were the physicians,
and they noticed a reduction in MAs (Appendix G).
One study used a scheduling manager, and their military health system management
analysis and reporting tool along with an army provider level satisfaction survey to determine
patient satisfaction with patients in an army setting. A panel time series analysis with general
estimating equations was used to analyze the data, which concluded that patients were more
satisfied with OAS (Appendix G). Similarly, another study used a nonlinear integer program
with model formulations using equations to determine whether the OAS system is preferred over
the traditional scheduling system in reducing MAs by using marginal analyses (Appendix G).
One study performed a systematic review of meta-analyses regarding all the literature out there
about OAS and their findings, and found that in the majority of studies done, open-access does
reduce the number of MAs (Appendix G). The measurement tool(s) and data analysis used was
not discussed in depth for any of the studies in this review (Appendix G). Additionally, one study
used the Pittsburgh Veteran Engineering Resource Center and Office of Systems Redesign
Group, a scheduling system to determine the number of missed appointments in their office
where they provided physical and occupational therapy for patients (Appendix G). The data
analysis they used was not reported; however, their findings found that the number of missed
appointments reduced significantly with the implementation of OAS as it went from 20% to 10%
and they found that their office revenue increased as well (Appendix G). Lastly, another study
used the area resource file, the Charlson Index, and the Deyo-Quann approach to determine

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whether OAS reduces emergency room visits (Appendix G). They used a one-way ANOVA to
analyze their findings and found that when access to primary care is improved, it can reduce
emergency room visits for non-emergent and primary care treatable events (Appendix G). Thus,
it can be concluded that not all of the studies have one instrument or tool, or analysis tool that
works best when determining the benefits of OAS. Nonetheless, all of these studies support the
PICO question.
Conclusion
Implementation of OAS has provided many benefits for primary care offices. It has been
shown to decrease MAs, increase patient satisfaction, increase revenue, and decrease emergency
room and/or urgent care use (Appendix H). Additionally, one study found that when
appointments are made closer to the actual appointment time, they are more likely to show up for
their appointment (Appendix G). Thus, literature indicates with OAS, patients are more satisfied,
an increase in revenue is seen and fewer patients seek emergency room care for non-emergent
care; all of which yield more positive effects in scheduling compared to the traditional method
(Appendix I).
Purpose and Rationale
Since MAs cause negative health care outcomes, interventions aimed at improving MA
rates are needed. Implementation of an OAS system has shown to increase patient satisfaction,
decrease MAs, decrease office costs, and decrease emergency room and/or urgent care visits in
primary care offices (Agency for Healthcare Research and Quality, 2015; Institute for Healthcare
Improvement, n.d.). The purpose of this paper is to review and critically appraise the literature
surrounding the effects of OAS on MAs, revenue, patient satisfaction, and emergency room
and/or urgent care visits.

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Contribution of Theory

The chosen theoretical framework is the theory of planned behavior (Appendix I). This
framework allows one to believe a certain behavior change will provide certain outcomes
through subjective evaluation of the risks and benefits associated with that outcome (Boston
University, 2016). In this case, the benefits, challenges, and risks associated with the
implementation of OAS were evaluated and found that much of the evidence is subjective
through pilot or case studies (Boston University, 2016). In order for a behavioral change to
occur, motivation and the ability to change are needed to make the change (Boston University,
2016). This theory has six different elements: 1) attitude, 2) behavioral intention, 3) subjective
norms, 4) social norms, 5) perceived power, and 6) perceived behavioral control (Boston
University, 2016) (Appendix I). Overall, these elements look at whether individual are in favor
or not of the projected change, and the motivation of individuals (Boston University, 2016). This
framework evaluates whether or not people approve of what is coming, how the group at large
feels about the change versus individually, certain factors that may hinder the change, and
looking at each person’s perception regarding the difficulty or ease that may be associated with
the project change (Boston University, 2016). All of these elements are important when trying to
implement something new that requires all members of the team to be on board in order for it to
be successful (Boston University, 2016). Additionally, the behaviors of the individuals must be
evaluated in trying to understand reasons for MAs and decreased patient satisfaction, which can
help us better understand why there are more emergency room visits and decreased revenue.
EBP Model
The Ottawa Model of Research was the chosen model to guide the development of a
potential evidence based practice project. This theory provides a specific process that lends itself

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to effectively implement a new process in a system. The first step involves assessing the barriers
and support available; therefore, one must understand the current barriers that exist and why
there is a need to implement a certain change and then one must determine if there is adequate
support to implement the process (Sudsawad, 2016). Then the interventions must be monitored
before one is able to evaluate the outcomes of the intervention. This model has six key elements:
1) evidence-based innovation, 2) potential adopters; 3) the practice environment; 4)
implementation of interventions; 5) adoption of the innovation; 6) outcomes resulting from
implementation of the innovation (Sudsawad, 2016). (Appendix J). Primarily, one must find a
need, determine what change needs to occur in a setting, and if evaluate internal and external
evidence on the problem or need (Sudsawad, 2016). Then, internal evidence must be found
through stakeholders, employees, staff, etc. and data must be gathered regarding attitudes,
concerns, knowledge, etc. currently exists within the facility, and current and former practice
changes that have occurred (Sudsawad, 2016). Then other factors that may contribute to the
practice change must occur by looking at the culture, patients, structure, finances, etc.
(Sudsawad, 2016). Then one is able to determine ways to effectively implement the strategy,
adopt it and then find the outcomes of the study (Sudsawad, 2016). Initially, a need at a primary
care clinic in Southwestern United States was identified and internal data regarding the matter
was gathered. Then an exhaustive search of the literature was completed in regards to OAS so
that the intervention may be implemented effectively based on the data that currently exists and
so that statistically significant data can be found. This model was chosen specifically for this
project as it has been known to be highly effective and highly feasible in multiple studies and
guides many evidence-based practice models (Sudsawad, 2016).
Project Methods

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Ethics
There were no known or foreseeable risks or discomforts related to participation in the
project other than those that are associated with everyday types of activity. Completion of the
survey was voluntary with minimal time required (approximately five minutes). Responses to the
survey remained confidential and were identified only by a number that was not be connected by
a name or any other personal identifying information. The pre-assigned ID number on the
questionnaire was the same number on the survey for each participant. The ID numbers were not
linked or coded to any other data sources or participants in any way. The data was only shared
with the clinics, any patients who wished to receive project results, and for project dissemination.
If the patient, provider or staff member was unwilling to participate, there was no harm or
penalty, and they were not treated any differently as a patient, provider, or staff member by the
clinic/facility.
Setting, Culture, Leadership, & Participants
The project was completed at two federally qualified health centers in Phoenix, Arizona.
These facilities primarily care for the Hispanic population providing primary care, preventative
services, family planning, obstetric care and a variety of other services. The project consisted of
surveying patients that were being cared for at the clinic and also providers and staff. Providers
were either physicians or nurse practitioners, and staff members were medical assistants, lab
technicians, promoters, medical assistant supervisors, or front desk staff. Leadership team that
was involved with assistance of gathering data or implementation of the project included the
chief medical officers, chief administrative officer, and the chief financial officer.
Team Collaboration

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Prior to implementation of the project, meetings with the assistant medical officer and the
chief administrative officer were held discussing the problem, and the best scheduling method to
implement at the facility given internal and external evidence available. Thereafter, an
educational session was held discussing the issue and training regarding what to expect was also
provided to the providers and staff at both clinics. The training included an educational
information session reviewing what OAS is and discussing the positive effects OAS can have on
patient satisfaction, revenue, MAs, and emergency room and/or urgent care use.
Intervention
Due to the lack of external information available on this topic, six databases were
searched in depth from 2006-2016 discussing OAS. As a result, after reviewing and analyzing
findings found in literature, an OAS method was implemented at both facilities beginning in
September 2017. One provider at each clinic in the afternoons (from 1300-1600) did not have
any pre-scheduled patients. Patients that were scheduled for these days were only allowed to
make an appointment the same-day or the day before. These providers also accepted same-day
walk-ins. The surveys were given only to patients who benefited from using the new scheduling
system, and were voluntary. Surveys were also provided to all providers and staff members at the
clinic, and were voluntary for them as well.
Outcome Measures, Data Collection, Analysis Plan, and Proposed Budget
Patient satisfaction, provider satisfaction and staff satisfaction was measured using a fivepoint Likert scale (Brown, 2010) to determine satisfaction with the new vs. the old scheduling
system. The likelihood of using an emergency room or urgent care was measured using a
dichotomous scale. In order to determine revenue gain or loss, the electronic medical record
(EMR) system, eClinicalWorks provided us with total revenue for any time frame that was

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needed. The revenue from September 2016 to December 2016 was compared to the revenue
from September 2017 to December 2017. Missed appointments were measured using a data
collection plan/chart audit as well. In order to determine the number of missed appointments, the
Institute for Healthcare Improvement (2017) recommends using a data collection plan by
calculating the number of missed appointments in a month (numerator) and dividing it by the
total number of scheduled appointments in a month (denominator). Then when you multiply this
number by 100, you will receive a percentage; which will give you the total number of missed
appointments. However, this will need to be compared to a time frame prior to implementation in
order to determine the effect of OAS on missed appointments.
A dichotomous scale has shown to have only high levels of reliability without much
mention to levels of high validity (Byrne, Allen, Dove, Watt, & Nathan, 2008); however, the
likert scale has been known to have high levels of validity and reliability, especially when a fivepoint scale is used like it was in this project compared to the four-point scale (Osteras,
Gulbrandsen, Garratt, Benth, Dahl, Natvig, & Brage, 2008). Although both of these scales were
used, they were adapted to suit the purpose of this project since there was a lack of
data/information/tools available for use with reliability and validity available to related to this
intervention. Missed appointments were measured using a chart audit. Chart audits are
commonly used and help us by providing information on office systems (Agency for Healthcare
Research and Quality, 2013a). Chart audits also allow us to collect, analyze and report data in an
attempt to improve quality and performance (Agency for Healthcare Research and Quality,
2013b).
For the patients, providers and staff, a survey was provided to them asking them nonidentifiable demographic data. The patients were asked to discuss their satisfaction with the old

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scheduling system compared to the new scheduling system (These questions were asked using
the five-point Likert scale). They were also asked to discuss their likelihood of visiting an
emergency room or urgent care, given that they were able to make an appointment to see a
provider on the same day or the next day (This question was asked using the dichotomous scale).
Providers and staff were asked to discuss their satisfaction with the old scheduling system
compared to the new scheduling system as well. Additionally, for data collection, a chart audit
was used to compile data found in the charts regarding missed appointments during the time of
implementation and one-year prior during the same time frame. The same way, revenue was
measured, through comparison of income made after the implementation of the project and
compared to the year prior during the same time frame.
In order to measure patient, provider, and staff satisfaction, the Wilcoxon test was used.
Findings regarding missed appointment rates and revenue were also evaluated through pre/post
comparisons. Similarly, a percentage was provided discussing the likelihood of patients using
emergency room or urgent care services given that they were able to see a provider on the same
day. The overall proposed budget for this project was $4,161.79.
Outcomes/Project Results/Impact
Patients
A total of 58 patients with or without dependents completed the demographic and/or
satisfaction survey. The average age of the patient was 39.73 years (13.88). The number of years
ranged from 20 to 70. The average age of the dependent was 16.78 years (19.17), and the number
of years ranged from 1 to 53. The majority of the patients were female (71%, n=42), while the
others were male (22%, n=13), and the remaining did not include their gender. Majority of the
patients were also Hispanic (80%, n=47), and did not have insurance (64%, n=38), and were

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established patients at the facility (71%, n-42). Additionally, the majority of the patients also
reported that they have never missed or forgotten to cancel their scheduled appointment (66%,
n=39). Demographic data on the dependents was also gathered and found that the majority of the
dependents were of male gender (9%, n=5), were Hispanic (15%, n=9), did not have insurance
(7%, n=4), were an established patient (15%, n=9), and reported that they did not miss a
scheduled appointment in the past (15%, n=9). Prior to the new scheduling change, 36 (72%) of
the patients reported being very satisfied or extremely satisfied with the old scheduling system,
and 52 (96%) of the patients reported being very satisfied or extremely satisfied with the new
scheduling system). Similarly, nine (18%) of the patients reported being either not at all or
slightly satisfied with the old scheduling system; where as none of the patients reported being not
at all or slightly satisfied with the new scheduling system.
Providers
A total of seven providers completed the demographic and/or satisfaction portion of the
survey. The providers were all females. The sample consisted of 5 (71%) Caucasian and 2 (29%)
Hispanic providers. The provider specialty consists of 6 (86%) providers specializing in family
care and 1 (14%) in adult-geriatrics. The sample consisted of 4 (57%) nurse practitioners, and 2
(29%) physicians. The average number of years of provider experience is 2.21 (1.35). The
number of years ranges from 1 to 4 years. The average length of time for each provider at the
clinic is 1.70 (1.40) years. The number of years ranged from two months to four years. Prior to
the new scheduling change, 2 (34%) the providers reported being either slightly satisfied or very
satisfied with the old scheduling system. Four (67%) of the providers reported being moderately
satisfied with the old scheduling system (three of them were nurse practitioners, and one of them
was a physician). None reported being extremely satisfied or not at all satisfied. Similarly, none

20

OPEN-ACCESSSCHEDULING
of the providers reported being not at all or slightly satisfied with the new scheduling system. In
fact, 6 (86%) of the providers reported being either very satisfied or extremely satisfied with the
new scheduling system. The number of years of experience and the number of years at the
facility did not make a difference. One (14%) reported being moderately satisfied with the new
scheduling system. The providers that had 1 year of experience or less were moderately satisfied
or very satisfied (3) with the old scheduling system. However, with implementation of the new
scheduling system they were very satisfied (3). The providers (1) with 2 years of experience
were slightly satisfied with the old scheduling system, and were extremely satisfied with new
scheduling system (1). The providers with 4 years of experience were moderately satisfied (1),
and were very satisfied (2) with the old scheduling system.
Staff
A total of 14 staff members completed the demographic and/or satisfaction portion of the
survey. The staff members were all Hispanic females. The majority of the staff members
reported that they either always (43%) or sometimes (43%) schedule patients for appointments.
Only 2 (14%) staff members reported that they never schedule patient appointments. The
majority of the staff members were either medical assistants (36%) or front office schedulers
(36%). The remaining staff members were medical assistant supervisors, medical assistant and
promotors, or a medical assistant and lab technician (29%). Majority of the staff had about 1 year
of experience (29%), and 2 (14%) of the staff members had eight years of experience in their
role, and both of these individuals also reported that they were not at all satisfied with the old
scheduling system. The years of experience at the facility had similar results to overall number of
years of experience. Each of these members reported that they were moderately satisfied or very
satisfied with the new scheduling system. The individuals with 9 years and 10 years of

21

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experience both reported being extremely satisfied with the new scheduling system, and also
reported being not at all satisfied with the old scheduling system. None of the staff members
reported that they were very or extremely satisfied with the old scheduling system; however, 10
(71%) of the staff members reported either being very or extremely satisfied with the new
scheduling system, (43% of these individuals were either medical assistants or front office
schedulers).
Statistical/Clinical Significance
Patients
When analyzing results, a Wilcoxon test was conducted to examine whether patients
were more satisfied with the old scheduling system or the new scheduling system. The results
indicated a significant increase in patient satisfaction, z=-3.49, P<.01. The mean of the ranks in
favor of satisfaction of the old scheduling system was 3.87 (1.42), while the mean of the ranks in
favor of the new scheduling system was 4.63 (.56) on a scale of 1-5.
Providers
A Wilcoxon test was conducted to examine whether providers were more satisfied with
the old scheduling system or the new scheduling system. The results indicated a significant
increase in provider satisfaction, z=-1.89, P= .06 (P<0.10) The mean of the ranks in favor of
satisfaction of the old scheduling system was 3 (.63), while the mean of the ranks in favor of the
new scheduling system was 4 (.58) on a scale of 1-5.
Staff
A Wilcoxon test was conducted to examine whether staff were more satisfied with the old
scheduling system or the new scheduling system. The results indicated a significant increase in
staff satisfaction, z=-2.852, P= .004 (P<.005) The mean of the ranks in favor of satisfaction of

22

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23

the old scheduling system was 2 (.88), while the mean of the ranks in favor of the new
scheduling system was 3.79 (.98) on a scale of 1-5.
Missed Appointments
Overall the MA rate did decrease, which indicated clinical significance, but was not
statistically significant. From September 2016 to December 2016, the MA rate was 15.28%.
During this three-month period, a total of 4,314 patients were seen at the two clinics among eight
different providers. In September 2017 to December 2017, the MA rate was 14.76%. During this
three-month period, a total of 5,191 patients were seen at the two clinics among eight different
providers. Overall, 877 more patients were seen over a three-month period, and findings resulted
in a 0.52% decrease in missed appointment rates.
Revenue
When comparing the three months, in 2016 to 2017, a 41% increase in revenue was noted
during the implementation period of this project.
Emergency Room/Urgent Care Visits
When patients were asked about the likelihood of using an emergency room or urgent
care, 88% (N=37) and 90% (N=38) reported that they were less likely to use these services given
that they were able to see a provider on the same day with the implementation of this project,
respectively.
Discussion
Overall, the patient, provider, and staff satisfaction results indicated statistically
significant values indicating that they were more satisfied with the new scheduling system,
which allowed patients the option to make an appointment and see a provider on the same day or
the next day. This new scheduling system is known as OAS. Similarly, results also indicated

OPEN-ACCESSSCHEDULING
clinically significant results in regards to patients being less likely to visit the emergency room or
urgent care, given they were able to see a provider on the same day. After implementation of this
study, an outcome that was not measured, but proven to be clinically significant was that the
facility saw 877 more patients during the three-month period when this project was being
implemented. Multiple factors also hindered this factor, but surprisingly did not limit the results.
For example, in September 2017, the facility moved from seeing patients every 15 minutes to
every 20 minutes. This meant that they went from seeing a maximum of 12 patients in the
afternoons to 9 patients. Similarly, other factors also played a role in possibly decreasing the
number of patients that scheduled appointments or missed their appointment time such as certain
laws that were passed, and other political environmental limitations. On the contrary, we know
that this did not impact the facilities negatively, as it provided a clinically significant increase in
revenue, and a clinically significant decrease in missed appointments. Other factors that may
have limited results included a language barrier in filling out the surveys, even though the patient
surveys were translated and provided to patients in both languages, English and Spanish.
Similarly, not having a valid or reliable measurable instrument or tool could have also hindered
overall findings of the project. Furthermore, the chief financial officer (CFO) at the facility does
not believe the revenue results to be fully accurate. In July of 2016 (data was compared starting
in September 2016), the organization went from an old electronic medical record to a new
electronic medical record system, and as a result of this change, the CFO believes that the
providers were not billing appropriately. However, after speaking to some of the providers at the
facilities, they do not believe that to be fully accurate, and many report they did bill
appropriately, even during the transition of the new scheduling system. Nonetheless, if they did
not bill appropriately, the increase in revenue most likely did increase since more patients were

24

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25

seen during the time frame of the project, and no decreases in the number of missed
appointments were noted.
Alternatively, the minimal exclusion criteria (that was not based on a specific diagnosis,
chronic condition, age, etc.) led to a larger sample size. All patients who were impacted by the
new scheduling system were provided the opportunity to fill out the survey, which resulted in a
diverse group of individuals who provided their feedback regarding the scheduling system.
Similarly, the short questionnaire and survey most likely inclined more individuals to participate,
and gathering of data required minimal time. Statistically significant results were also noted over
a short period of time, which provided to be the greatest benefit especially since OAS was not
fully implemented clinic-wide. In fact, it only involved one provider at each clinic, and only in
the afternoons, leaving at least six providers available for other scheduled appointments, and
leaving the same-day providers available for scheduled appointments in the morning.
This project can be implemented in any practice setting that requires patients to be seen
for acute matters, primarily in primary care settings. The lack of literature indicates that
difficulties exist in implementation of this project; however, the positive findings discussed
above should provide one with relief and motivation for implementation into their practice,
especially if missed appointments are negatively impacting the workplace.
Conclusion
Although further work is required regarding this type of scheduling system,
implementation of OAS has provided many benefits for primary care offices, and has shown to
be transferrable in any setting. This type of scheduling system has great potential in increasing
revenue and seeing more patients. It has also shown to increase patient, provider, and staff
satisfaction whilst potentially decreasing urgent care and emergency room visits. Furthermore, it

OPEN-ACCESSSCHEDULING
has shown to decrease rates of missed appointments as well. Thus, given the wide-range of
positive effects OAS has shown in this project, implementation is highly recommended.

26

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27
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35
Appendix A
Search Strategy 1

ABI/Inform

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36
Appendix B
Search Strategy 2

Academic Search Premier

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37
Appendix C
Search Strategy 3

CINAHL

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39
Appendix D
Search Strategy 4

Cochrane

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41
Appendix E
Search Strategy 5

EconLit

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42
Appendix F
Search Strategy 6

PubMed

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47
Appendix G

Table 1
Evaluation Table
Citation
Theory/
Conceptual
Framework

Cameron et al.
(2010)
Adoption of
OAS in an
academic
family practice
Country:
Canada
No funding
discussed
No conflicts or
biases
recognized

Inferred to be
the queuing
theory

Design/ Method
(Grounded
Theory,
phenomenology,
Narrative…)
Design:
Prospective and
retrospective
Quantitative
Study
Method:
Collection of
empirical data
Purpose: In order
to reduce WTs
and reduce
missed appts by
implementing
OASS.

Sample/ Setting
(describe)

Pre-I # of PTS
seen: 21,838
Post-I # of PTS
seen: 21819
Demo:
NRep

Major
Variables
studied &
their
Definitions
IV: OAS
DV1:
TTTA/WT
DV2: NS/MA
DV3: PV

Setting: 2-site
academic
practice in
Halifax, NS
Exclusion:
None
Attrition: NREP

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization

TTAA

t tests
(to determine
significance
between the
two time
periods)

TTAA: 

Level: VI

BI: 13.7days
AI: 3.6days
(P<.0001)
NS: 
BI: 3.3%
AI: 1.89%
(P<.001)
Pt Volume:
Unchanged
(P<0.1%)
Statistically
significant
reduction in NS,
even though
numbers were
already low

Strengths:
LR and NI.
Weaknesses: TTAA
results entered
manually; however by
the same person
Multiple changes of
clerical staff during trial
Differences in how NS
were entered into system
Conclusion: OAS
resulted in  WT

and

NS.
Feasibility: Useful
in practice due to
the many successful
findings, LC;
however difficulty

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING

48
with implementation

Citation

Theory/
Conceptual
Framework

DuMontier et
al. (2013)

Inferred to be
the wider
social system,
health care
utilization
theory, theory
of planned
behavior, and
the
transtheoretical
model.

A multimethod
intervention to
reduce NS in
an urban
residence clinic
Country: USA

Design/ Method

Design:
Prospective and
retrospective
quantitative
cohort study
Method: Mixedmethod with the
collection of
empirical data
and open-ended

Sample/ Setting

Demo:
TPS:
N=8974; F5079
(57%)
AfAm=1856
(21%)
26-44=3006
(34%)
M=2132 (24%)
CS:

Major
Variables
studied &
their
Definitions
IV: OAS

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization

Interview clinical
staff

Chi-square
tests ( to
determine NS
rate and
number of
active pts
before and
after the
interventions)
Significance
level of

NS total
population:
BI: 10%
AI:
7.06%
(P<0.001)
=6,086 more
appts

Level: IV

DV1: NS
Open-ended survey
(in-person or
telephone)
Wisconsin
Department of
Family Medicine’s
Clinical Data

NS cohort:
BI: 33.26%

Strengths: provider and
staff commitment
Persistence over time
rather than short-term
measures
No changes in the # of
active patients seen
Clinic has been present
in same community for

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
interviews
No funding
discussed

Purpose: If the
use of MM – an
educational
program focused
on the NS cohort,
modified method
of DB and
modified AA can
help decrease the
NSR.

No conflicts or
biases
recognized

49
n=141; F 114
(81%)
AfAm=98
(70%)
26-44=57 (40%)
M= 108 (77%)

Warehouse – EPIC
EMR

0.05% was
assumed for
all tests.

AI:
17.71%
(P<0.001)
=6,086 more
appts

Setting: WFMC,
a residency TC
of the
UWFMRP
Exclusion:
None

40years
Spanish-speaking
faculty
LR and NI
Weaknesses: Assessed
the effects of multiple
interventions making it
difficulty to determine
the effects of each
Unable to see if patients
went to other health
systems, UC or ED’s
Provider turnover
Mixed providers and NS
rate

Attrition: NREP
Conclusion: Significant
decrease in NS noted

Citation

Theory/
Conceptual
Framework

Fournier et al.
(2015)

Inferred to be a
process model
(quality
implementation

Implementation

Design/ Method

Design:
Discussion
Purpose: To

Sample/ Setting

Demo: NREP
due to type of
design

Major
Variables
studied &
their
Definitions
IV1: AAS
DV1: PS

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

Observation or
statements/comments
made by patients,
providers, staff.

NRep

Through
observation and
statements made
by various

Feasibility:
Recommended due to
the in NS rates, WT
and TTAA.
Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization
Level: VII
Strengths: costs, LR
and NI

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
of an AA
scheduling
system in
primary
healthcare: One
clinics
experience.

framework)

Country:
Canada

discuss the
experience
associated with
implementation
of AAS – in an
effort to decrease
WT for primary
healthcare by
increasing
efficiency.

50
Setting: NP led
clinic

members of the
team, the
following
findings were
found: 
PS as indicated
from positive
feedback
from patients
regarding new
scheduling
system. >85%
were able to
schedule
appointments on
the SD or ND.

Exclusion:
NREP
Attrition: NREP

No funding
discussed
No conflicts or
biases
recognized

AAS allowed providers
to provide care in a
timely manner,
increasing patientprovider rapport and pt
satisfaction
Weaknesses: Must
determine if
accessibility or
efficiency is the focus of
implementation of AAS
Mindful of new patients
that are enrolled
Only implemented in 1
NP clinic
Unmet client
expectations
Team flexibility
Triage calls and skill
building
Conclusion: PS,
ER visits, walk-ins.

Citation

Theory/
Conceptual
Framework

Design/ Method

Sample/ Setting

Major
Variables
studied &

Measurement/
Instrumentation
(focus group, 1:1,

Data
Analysis
(stats used)

Findings/
Results/Themes

Feasibility: Due to
numerous + effects of
AAS, likely
recommended
Level/Quality of
Evidence; Decision for
practice/ application to

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
McMullen et
al. (2015)
Lead time for
appt and the
no-show rate in
an
ophthalmology
clinic
Country: USA
No funding
discussed
No conflicts or
biases
recognized

Lead time
model and
NSR model

Design: Crosssectional
retrospective
quantitative study
Purpose: If there
is a correlational
difference with
no-show rates if
appts are
scheduled in
advance versus
closer to the appt
time

51
Demo:
Total appt
sample:
N=46,655
nr=14066
nf=32589
Setting:
UOVEC
Exclusion:
None discussed.
Attrition: NREP

their
Definitions
DV1: NS
DV2: LT
(time from
scheduled
appt to actual
appt
IV: NRep

researcher(s)
Data obtained from
computerized
scheduling database
at UOVEC

practice/Generalization
Z-test
(comparison
of
proportions
test)

At 6mo
likelihood of
appt kept forFaculty: 58.8%
Residents:
41.1%
NS rate:
Faculty: 21.7%
Residents: 6.6%
(P<0.001)
Lead time of 02wks, NS rate
forFaculty: 9.1%
Residents: 2.4%
Would notice a
60% in NS

for resident
clinic if all
pts were
scheduled 0-2
weeks out

Level: VI
Strengths: LR, NI
Weaknesses:
Cross-sectional study
Did not assess shortterm appt scheduling
strategy
PS and CO was not
measured
Use of RS was not used
to determine f/u rates.
Did not assess reason
for longer time to appt.
Did not determine the
reason in NS rate
between faculty and
residents
Did not assess impact of
current telephone
reminders that were in
place on NS rate.
Conclusion:
NS when LT
Feasibility:
SD or AA will NS
rates according to
predictive models;

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING

52
therefore, likely to be
feasible in practice

Citation

Theory/
Conceptual
Framework

Design/ Method/

Sample/ Setting

Mitchell (2008)

Inferred to be
the queuing
theory

Design/method:
Anecdotal
observations and
experience

Demo:
NREP due to
type of study

Same-day
booking –
success in a
Canadian
family practice
Country:
Canada
No funding
discussed
No conflicts or
biases
recognized

Purpose:
Providing access
to appts in a
timely manner so
that patient care
can be improved

Setting: A
family practice
in Halifax, NS.
Exclusion:
None
Attrition: NREP

Major
Variables
studied &
their
Definitions
IV: same-day
booking
DV1: NS
DV2: PS

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization

Scheduling of daily
appointments,
clearing back log,
and log calls to
determine number of
appts and follow up
appts.
Over 1 wk pd,
surveys to 100 pts at
random was given
regarding the new
scheduling system

NRep

Eliminate WT

Level: VII

 NS
PS (93% of

pts satisfied
with system)

Strengths: Observation
of positive results, LR
and NI
Weaknesses: May be
difficult to implement
AAS if there is a large
portion of chronic care
and elderly pts, but this
did not seem to be a
problem for the pts in
this clinic.
Baseline and post
implementation data are
not available since it
was an informal study
Conclusion: Experience
in implementing SD
booking provided PS,

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING

53
and physician
satisfaction, NS,
stable income and
unchanged physician
burden
Feasibility: Likely to be
feasible due to positive
outcomes observed,
unknown if findings
were statistically
significant or not.

Citation

Theory/
Conceptual
Framework

Design/ Method

Sample/ Setting

Major
Variables
studied &
their
Definitions

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
Richter et al.
(2017)
Does the
proportion of
same-day and
24-hour appts
impact PS?

Inferred to be a
process model
(quality
implementation
framework)

Design: Survey
Purpose: To
determine if there
is a relationship
between PS and
OAS with OP
facilities

Country: USA
No funding
discussed

Setting:
Outpatient
facilities in the
MHS
Exclusion:
None

No conflicts or
biases
recognized

Citation

54
Demo:
N=32,364,957
encounters and
surveys in 32
facilities from
7/13-5/15

Attrition: NREP

Theory/
Conceptual
Framework

Design/ Method

Sample/ Setting

IV1: SDA
IV2: 24-hour
appts
DV1: PS –
able to see
provider when
needed
DV2: PSO
CV1: Patient
perception of
health
CV2: Age
CV3: Gender
(all male)
C4: Size (total
encounters)

Major
Variables
studied &
their
Definitions

Schedule manager
managed schedules
MHS Management
Analysis and
Reporting Tool (M2)
-ad hoc query tool
that manages and
oversees healthcare
operations

Panel timeseries
analysis with
GEE to look
at the various
observations
in each
sample

Significant
association with
PS with SDA
compared to
appointments
24-hours ago.

Strengths:
LR aind NI
3.9million army
beneficiaries –
substantial population
Weaknesses:
Only army facilities
Unable to test for
causality

(APLSS)
-a provider-level
satisfaction tool

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Level: VI

Conclusion: Armyfacilities specifically
should implement sameday access

Data
Analysis
(stats used)

Findings/
Results/Themes

Feasibility: Strongly
suggest SDA and PS
with this – especially in
army facilities
Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
Robinson et al.
(2010)
A comparison
of traditional
and openaccess policies
for appt
scheduling
Country:
NREP
No funding
discussed
No conflicts or
biases
recognized

Traditional
scheduling
policy
Open-access
policy
Inferred to be a
process model
(quality
implementation
framework)

Design:
Comparison
study with the
use of variables
Method: Model
formulations
using equations
Purpose: To
determine
whether or not
OAS will be
better than the TS
in WT, doctor’s
IT, and the
doctors OT.
Thus, looking at
which ScSy will
effect costs in the
office and in
which system is
preferred under
different
conditions

55
Demo: NRep

IV1: OAS
IV2: TS

Setting: NRep
Exclusion:
NRep
Attrition: NRep

DV1: NS
probability

Nonlinear integer
program

Marginal
analyses

NS

Level: III
Strengths:
LR and NI
First paper to compare
traditional and OAS
under respective sources
of variability’s
Weaknesses: Fails to
look at other possible
variabilities
Conclusion: if NS>5%,
OAS is preferred
Feasibility: OAS is
preferred over
traditional appt
scheduling

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
Rose et al.
(2011)
AA scheduling
outcomes: A
systematic
review
Country: USA
and UK
Funding:
CTSA Grant
from NCRR;
however no
biases present
from funding
agency since
they did not
have a role in
the design and
conduct of the
study
Bias: 2
reviewers
independently
assessed risk
for bias using
the CEPOCG
Risk of Bias
criteria.

Inferred to be a
process model
(quality
implementation
framework)

56

Design: A
systematic
review of metaanalyses
described in a
qualitative
method

Demo:
N= 28 studies
n=24 distinct
studies that
provided
different
interventions

Purpose: To
determine how
implementing
AA scheduling
affect patient,
physician, and
practice
outcomes

(24)
implementations
(1) RCT
(6) concurrent
control group
(21) pre/post
studies
(22) USA
(6) UK
(24)
implementations
TTAA(8)
NSR(11)
PSO(4)
PSA (4)
CC (9)
HCU(2)
Setting:
Multiple:
Teaching

IV: AAS
DV1: NS

NRep

NRep

NS: 11 studies
had NS rate
from 116-43%,
and reduced NS
rate from -24%0 in at least 5
studies.

Level: V
Strengths:
Systematic review
LC, NI, LR
Weaknesses: lack of
follow-up and effects on
CO
Articles were not all
randomized
One study included
contamination and
crossover bias
Some studies had selfselected intervention
groups
Other practice initiatives
with AA
Conclusion: AA
decrease WT and NS
rates
LR and NI
Specifically,  in

reducing TTAA.
Feasibility: Very likely
to be feasible due to the
multiple number of
studies that have shown
positive affects of OAS

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
-(1) substantial
contamination
and crossover
bias
(6)implemented
other practice
initiatives
concurrently
with AA
-all others
included selfselected
intervention
groups
-publication
bias

57
practices (6)
NHS (5)
CHC (2)
VA (3)
USM (1)
Varied (1)
HS with SO (1)
NW of
neighborhood
HC (1)
MSMG (1)
HMO (1)
NRep (1)
Exclusion:
Conference
abstracts,
commentaries,
editorials, and
narratives not
written in
scientific
format.

No conflicts
recognized

Citation

Theory/
Conceptual
Framework

Wojciechowski
(2012)

Urgent care
model

Design/ Method

Design: Case
Study

Attrition: NREP
Sample/ Setting

Demo:
NRep

Major
Variables
studied &
their
Definitions
IV: OAS

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization

PVERC and Office
of Systems Redesign

NRep

NS reduced
from 20% to

Level: VII

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING

58
DV1: NS

Open access
scheduling
Country: USA
No funding
discussed
No conflicts or
biases
recognized

Citation

Theory/
Conceptual
Framework

Yoon et al.
(2015)

Inferred to be a
process model
quality
implementation
framework)

The
relationship
between sameday access and
continuity in
primary care
and emergency
department

Comparative
quantification
of health risks

Method: Mixedmethod with the
collection of
empirical data
and open-ended
interviews

Setting: PTH
services at the
VA PHS

Purpose: To
determine if
implementing
OAS will help
decrease NS

Attrition: NREP

Design/ Method

Design: Multilevel regression
model

Purpose: To
determine how
ED visits for
health conditions
were related to
SD access and

Group used flow
simulations with
computer models to
schedule patients

10%
Efficiency,
revenue, 
downtime
Saving 8days
over 6-month
period

Exclusion:
None

Strengths: Initially
determined reasons NS
were occurring. LR, NI
and LC
Weaknesses: Study
regarding PT/OccT
Pilot program
Conclusion: Reduction
of NS noted with OAS
implementation

Sample/ Setting

Demo: PC
clinics (22)
within
(3) VHA
medical systems
Setting: VHA
medical systems
in Southern CA
Exclusion:

Major
Variables
studied &
their
Definitions
IV1: Cliniclevel
measures of
access
IV2: PCont
FY2010FY2012
IV3: health
status
IV4: pt factors

Measurement/
Instrumentation
(focus group, 1:1,
researcher(s)

Data
Analysis
(stats used)

Findings/
Results/Themes

ICD-9 codes
Area Resource File
(ARF)
Charlson Index –
Deyo-Quan approach

One-way
ANOVA
Significance
level of
P<0.01

10%

access
to same-day
care
decreased
non-emergent
visits by 7%
(P<0.001)
 in EC but
PC treatable

Feasibility: Most likely
to be successful in a
clinical practice
Level/Quality of
Evidence; Decision for
practice/ application to
practice/Generalization
Level: IV
Strengths: SD access in
PC related to fewer ED
visits for all-cause, nonemergent and PC
treatable visits.
Weaknesses:
Veteran clinic study
only

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING
visits
Country: USA
Funding: VA
however, no
bias is
indicated by
the VA as they
did not have a
role in this
study.
No conflicts or
biases
recognized

CC in PC offices.

59
Less frequent
use of PC
Deceased
between 20092012
Attrition: NREP

DV1: non-EC
DV2:
Treatable EPC
DV3:
Preventable
ED care
DV4: Nonpreventable
ED care

visits also
noted

No information on ED
visits from non-VHA
providers covered by
non-VHA services
Measures of access was
not validated in study
Data on study practices
regarding whether they
were practicing based on
NCQA guidelines or not
was not measured
Possibility that this
study may not be
generalizable to outside
of a VHA system since
VHA is highly
integrated with a
national EMR.
Conclusion:
Improvements in PC
access can  ED visits
for non-emergent and
PC treatable events
Feasibility: Since this
study is consistent with
prior veteran and nonveteran clinics, it is
likely to be successful in
multiple clinics.

AA-advanced access; AAS-appointment access scheduling; AfAm-African American; appt-appointment; appts-appointments; AR-attrition rate; BP-blood pressure; CA-California; CC-continuity of care; CS-cohort sample;
CEPOCG-cochrane effective practice and organization of care group; CG-control group; CHC-community health center; CV-control variable; DB-double booking; Demo-demographics; DM-demographics; DV-dependent
variable; EC-emergent care; ED-emergency department; EPC-emergent and primary care; F-female; FY-fiscal year; HC-health centers; HCU-healthcare utilization; HMO-health maintenance organization; HS-health
systems; IT-idle time; IV- independent variable; IG-intervention group; LC=lipid control; LD-length of day; LDT-lead time; LR-low risk; LT- length of time; M-medicaid; MA-missed appointments; MM-multiple
methods; MHS-military health systems; MSMG-multispecialty medical group; N-number of studies; n- number of participants; N/A-not applicable; NCRR- national center for research resources; NF- number of faculty
participants; NHS-national health service practices; NI-non invasive; NP-nurse practitioner; NR-number of resident participants; NRep-not reported; NS-no shows; NW-network; NSR-no show rate; OA-open access; OASopen access scheduling; OASS-open access scheduling system; OP-outpatient; OT-overtime; PC-primary care; PCont-provider continuity; PHS- Pittsburgh healthcare system; PM-physician morale; Post-I-post intervention
Pre-I-pre intervention; PS-patient satisfaction; PSA-patient satisfaction appointments; PSO-patient satisfaction overall; Psych-psychiatric; PT-patient; PTH-physical therapy; PTS-patients; PVERC-Pittsburgh Veteran
Engineering Resource Center; RCT-randomized control trial; s-satisfaction; ScSy- scheduling system; SD-same day; SDA-same day appointments; SO-small office; SS-staff satisfaction; TC-teaching clinic; TMgmt-time
management; TS-traditional schedule; TTAA-time to third appointment available; TPS-total patient population; UK-united kingdom, USA-United States of America, USM-united states military; UVOEC-university of
Virginia outpatient eye clinic; UWFMRP-university of Wisconsin family medicine residence clinic; VA-veteran affairs; VHA-Veteran health administration; WC-working conditions; WFMC-wingra family medical center;
WL-workload.

OPEN-ACCESSSCHEDULING

60
Appendix H

Table 2
Synthesis Table
Author

Cameron

Fournier

McMullen

Mitchell

Richter

Robinson

Rose

Wojciechow
ski

Yoon

Year
Setting/Po
pulation

DuMontie
r

2010
Academic
practice

2013
Residency
teaching
clinic

2015
NP led
clinic

2015
UOVEC

2008
Family
practice

2010
N/A

2011
Variety

PR
quantitative
cohort study

Discussion

IV

VII

CSS
retrospectiv
e study

Anecdotal
observation
s and
experience

Comparison
study with
the use of
variables

SR of MTA
in a
qualitative
study

2012
Physical
therapy and
occupational
therapy in VA
setting

2015
VHA
medical
system

PR
quantitative
study

2017
Outpatien
t facilities
in military
health
system

V

VII

X

X

X

X

X







Design

Study
Level
IV
OAS
DV

PS
NS/MA
ER/UC
visits
Revenue/C
osts
Wait time
Lead time

VI



VII

VI

X

X

X










VI

Survey



CS

Multilevel
regressio
n model
IV
X


unchanged

costs




revenue






CS-case study; CSS-cross sectional; DV-dependent variable; ER-emergency room; IV-independent variable; MA-missed appointments; MTA-meta analyses; NP-nurse practitioner, NS-no shows; OAS-open access
scheduling; PR-prospective and retrospective; PS-patient satisfaction; SR-systematic review; UC-urgent care; UVOEC-university of Virginia outpatient eye clinic; VA-veteran affairs; VHA-veteran health administration

OPEN-ACCESSSCHEDULING

61
Appendix I

Theory of Planned Behavior

OPEN-ACCESSSCHEDULING

62
Appendix J

Ottawa Model of Research