Journal of Pediatric Nursing (2014) 29, 528–535
Increasing Patient Attendance in a Pediatric Obesity Clinic: A Quality Improvement Project Betty Geer DNP, RN, CPNP a,⁎, Renee M. Porter RN, MS, ND b , Matthew Haemer MD, MPH b , Marilyn J. Krajicek EdD, RN, FAAN a a
University of Colorado Anschutz Medical Campus, College of Nursing, Aurora, CO University of Colorado Anschutz Medical Campus, Department of Pediatrics, Section of Nutrition, Aurora, CO
b
Received 18 April 2014; revised 29 August 2014; accepted 5 September 2014
Key words: Childhood obesity; Improve attendance; Follow-up
Research supports intensive lifestyle interventions (N 25 contact hours/six months) to treat childhood obesity. Success requires retention in program. This quality improvement project's purpose was to increase attendance of follow-up patients in a childhood obesity clinic by 10%. A pretest posttest design was used. Three months of baseline data were collected, followed by 52 weeks of intervention data. Data were analyzed using descriptive statistics and Fisher's exact test. Follow-up patient attendance improved significantly from 69% to 81% (z = 1.76, p = .039 (95% CI = 0.2822, 1.0021)). Simple and inexpensive interventions can significantly increase attendance of obese children in follow-up. © 2014 Elsevier Inc. All rights reserved.
LIFESTYLE INTERVENTIONS, EMPLOYING behavioral strategies to modify nutrition and physical activity patterns, are the mainstay of treatment in children who are obese (Whitlock, O’Connor, Williams, Beil, & Lutz, 2010). In a meta-analysis, performed for the U.S. Preventive Services Task Force (USPSTF), Whitlock et al. compared 15 studies for effectiveness of varying intensities of behavioral interventions for pediatric obesity in children ages 4 to 18 years. They found that the effectiveness of lifestyle therapies in reducing BMI is positively associated with the frequency and duration of treatment. In conclusion, they recommended a minimum of 25 contact hours over six months (Whitlock et al., 2010). Contact hours may include individual or multidisciplinary clinic visits, group learning, and individual and group physical activities, all of which are designed to
⁎ Corresponding author: Betty Geer, DNP, RN, CPNP. E-mail address: [email protected]. http://dx.doi.org/10.1016/j.pedn.2014.09.001 0882-5963/© 2014 Elsevier Inc. All rights reserved.
change eating and physical activity behaviors to decrease BMI. Skelton and Beech (2010) recognized that, due to the slow pace of behavioral change, inconsistent participation in treatment would not likely produce long-term health improvement. Therefore, it is imperative for successful treatment of children who are obese, that they consistently attend clinic appointments for lifestyle interventions. Attrition from treatment programs is a major barrier to successful lifestyle intervention for obese children in the United States. In one review, more than 32% of overweight and obese children enrolled in treatment programs failed to complete their courses of treatment (Skelton & Beech, 2010), increasing these children’s risk for morbidity and health related complications. A study published in 2011 by the National Association of Children’s Hospitals and Related Institutions (NACHRI, now Children’s Hospital Association) reported that among 24 hospital-based clinics, patients failed to complete about half of their weight management programs’ follow-up visits (Hampl, Paves, Laubscher, & Eneli, 2011). The average
Increasing Patient Attendance in a Pediatric Obesity Clinic non-attendance rate (no-show or same day cancelation) of follow-up patients was 32.1% (range: 10%–75.7%).
Background and Significance Children whose BMI is greater than the 95th percentile on standard growth charts are considered obese (Centers for Disease Control and Prevention, 2000) and are at increased risk for serious comorbid conditions and chronic diseases, many of which are historically ‘adult’ diseases (Klish, 2014). The American Heart Association has proposed a definition of severe obesity as a BMI greater than 120% of the 95th percentile or absolute BMI ≥ 35 kg/m2, whichever is lower based on age and sex (Kelly et al., 2013). In children with severe obesity, the metabolic and cardiovascular profile is even more adverse than in children who are overweight or obese (Kelly et al., 2013). Childhood obesity is widespread in the United States. Skinner and Skelton (2014) examined the National Health and Nutrition Examination Survey (NHANES) data for 2011–2012 and report that 32.2% of children 2–19 years old were overweight, and 17.3% of children 2–19 years old were obese. While the overall childhood obesity rate has plateaued in recent years, severe obesity in children has increased 300% since 1979 (Skelton, Cook, Auinger, Klein, & Barlow, 2009). A literature search was conducted to identify evidence related to the importance of, barriers to, and methods of increasing patient attendance in childhood obesity treatment. The Cochrane Database, PubMed, and Google Scholar were used to search for articles using the search terms: childhood obesity prevention and treatment, chronic disease management, and patient retention and attrition. Three major reviews were found plus 19 articles, reports and expert opinions. Of these, eight were included in the synthesis of evidence because they reported relevant evidence on effective treatment modalities, barriers to treatment, causes of attrition, and interventions to increase attendance. Findings from a Cochrane Review concluded that a multidisciplinary approach using a family-oriented intervention for childhood obesity is effective, as it addresses the breadth of related causes and influences within the child’s immediate environment (Luttikhuis et al., 2009). Evidence exists for the use of motivational interviewing (MI) to help patients establish goals for lifestyle changes (Schwartz et al., 2007 and Whitlock et al., 2010). MI is also used in obesity treatment as a strategy to support family engagement in treatment and self-management. Self-management has been recognized as the core determinant of weight control in obese children (Dietz, Lee, Wechsler, Malepati, & Sherry, 2007). In order for these treatment modalities in lifestyle interventions to be successful, patients should consistently attend clinic appointments, because more intensive (frequent) interventions have been shown to be more effective in reducing BMI than less intensive interventions (Whitlock et al., 2010). Some studies have been published on barriers to sustained involvement of patients in weight management programs.
529 Skelton and Beech (2010) reviewed 10 studies related to attrition from pediatric weight management programs and found that apparent contributors to attrition included higher severity of obesity, poverty, single-parent households, and behavioral issues. Jelalian et al. (2008) also found high attrition rates among children with more severe obesity, children of obese parents, and children with minority or low income status. These articles indicated that barriers, especially for lower income populations, include parents missing work, children missing school, and transportation or financial limitations. Barlow and Ohlemeyer (2006) reported results of a survey showing differences between family expectations of the treatment plan and the care that was actually delivered in patients who attended fewer than three clinic visits. The most common reason given for non-return to the clinic was, “The program is not what we are looking for,” followed by schedule conflicts, distance from the clinic, and lack of insurance coverage. These findings were supported in the literature reviewed by Skelton and Beech (2010) and in the study by Hampl et al. (2013). Interventions to decrease attrition were discussed in several studies. Hampl et al. (2011) discovered that more successful programs utilized clinic-specific schedulers, reminder phone calls, family involvement in treatment, patient orientation by in-person sessions or written materials, and frequent dietitian visits. These findings concurred with patient feedback received at the weight management clinic (WMC) where this quality improvement project was conducted and suggested potential areas for intervention. The baseline attendance rate in the WMC was approximately 70%, and the non-attendance rate was close to 30% for follow-up patients. Comparatively, nonattendance rates were between 2% and 23% in other outpatient clinics within the hospital.
Project Aim The purpose of this quality improvement project was to increase the average monthly attendance rate of patients seen for follow-up in a hospital-based pediatric weight management clinic by 10% between April 1, 2012 and April 1, 2013. For simplicity, two groups of follow-up patients were defined: 1) attenders (either kept their appointments or canceled more than one day in advance) and 2) nonattenders (failed to show or canceled the day of appointment). Among the subset of patients who canceled appointments, we expected the interventions to affect the timing of cancelation, such that a greater proportion of patients would cancel and reschedule more than one day prior to scheduled appointments as opposed to canceling the day of the appointment. Interventions aimed at increasing follow-up patients’ attendance align with the hospital’s overall goals of patient satisfaction and growth in patient volume. The project was undertaken to answer the two-fold question: Why are patients failing to show at follow-up appointments, and what can be done to improve attendance?
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Methods Ethical Issues Ethical study design was insured in several ways. Risks to human subjects were minimal, and involve no greater risk than would be encountered in everyday life. Approval for the quality improvement project was obtained from the College of Nursing DNP Bridge Committee at the University of Colorado College of Nursing, to ensure the project was consistent with quality improvement principles. Confidentiality of patients, families, and providers was guarded in accordance with HIPAA guidelines by protecting and de-identifying data.
Sample and Setting The WMC is an outpatient pediatric obesity treatment clinic. It is located in a large freestanding tertiary care children’s hospital located within a large metropolitan area. The interdisciplinary practice includes physicians, nurse practitioners, physician’s assistants, psychologists, dietitians and an exercise physiologist. The WMC referral criteria are: 0–18 years of age, BMI N 95th percentile or BMI above the 85th percentile that is on a rapidly increasing trajectory. Children with special healthcare needs and genetic obesity syndromes (e.g. Prader Willi syndrome) are included in the treatment population. The majority of WMC patients are school age and have severe obesity. The sample and clinic demographics in Figure 1 were the same with the exception of the year of the study: 51% were female, and 48% were Hispanic. See Figure 1 for demographic data (Haemer, Ranade, Baròn, & Krebs, 2013).
Root Cause Analysis The clinical practice flow of the WMC was observed by the primary investigator prior to any formal root cause
WMC Demographics 80% 69%
70% 60% 51%
50%
48% 39%
40% 30%
22%
20% 10% 0% Female
Figure 1
Hispanic
Spanish Language
Private Insurance
Severe Obesity
WMC demographics.Source: Haemer et al. (2013).
analysis, and some specific features were noted. Before and during the project, the WMC utilized a non-clinic-specific hospital-wide scheduling pool and an automated reminder call system that were linked to the electronic health record (EMR). The automated reminder system was programmed to call home phone numbers approximately 2 days prior to appointments. Typical appointment length ranged from 1 to 3 hours. Patients had access to a variety of services and providers, and treatment plans were individualized. The formal analysis of root causes for non-attendance included: • Chronic care assessment (ACIC, Version 3.5., 2000); • Baseline data on clinical indicators: number of no-shows per clinic day, number and timing of cancelations, length of appointments, response to automated reminder calls, patient participation in group classes, and information about whether patients scheduled follow-up appointments; • A patient survey administered to 13 families by phone to elicit reasons why patients did not show for appointments; • Patient contact preference form which also solicited quality improvement suggestions; and • Reports by clinic staff of factors perceived to affect attendance.
The root cause analysis identified several modifiable factors contributing to patient non-attendance that include: (a) forgetting appointment, (b) appointments too far apart, (c) expectations did not match (not what patient expected), and (d) appointments too long.
Interventions Four targeted interventions in the form of Plan-Do-StudyAct (PDSA) cycles began at different points during the project to address aspects of the modifiable factors identified, and each intervention continued to the culmination of the project. The ultimate goal of each intervention was to increase attendance of follow-up patients in the WMC. The principle investigator performed these 4 cycles of quality improvement interventions based upon results of the root cause analysis (Table 1): appointment reminders (PDSA1), follow-up calls (PDSA2), reminder calls to group class participants (PDSA3), and orientation literature (PDSA4).
Data Collection Baseline attendance was recorded from February to April of 2012, and collection of intervention-related data began in mid-April, 2012. Microsoft Excel 2007 was used to collect data, which was de-identified before analysis. Attendance of follow-up patients was tracked in-person in clinic and by review of electronic medical records. Percentages of attendance were calculated by dividing the number of attenders by the number of total follow-up appointments scheduled per clinic session. Modified control charts tracked weekly and average monthly attendance during the project. These charts tracked progress toward the project aim, as all the interventions were
Increasing Patient Attendance in a Pediatric Obesity Clinic Table 1
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Interventions for patient attendance 2012–2013 relative to factors in no-show of patients discovered in the root cause analysis.
Factors in No-Show of Patients
PDSA Interventions
Start Date of PDSA
PDSA1 — appointment reminders Description: personal reminder calls were made one week in advance of appointment. Reminder letters were sent to families unable to be reached by phone. Appointments too far apart PDSA2 — follow-up calls to address questions between visits Description: follow-up calls were made to new patients approximately 3 weeks after initial clinic visits and to returning patients approximately 1 week after follow-up appointments. The foci of these calls were: • troubleshoot difficulties with arranging subsequent appointments • mitigate lack of understanding or difficulties working on goals and recommendations made by clinicians. Problems revealed during these calls were routed to the appropriate staff persons for remediation with expectation of timely follow-up. Forgetting group appointment PDSA3 — reminder calls to group participants Description: reminder calls were made to patients who were scheduled for group sessions occurring weekly for 1 month. These calls were made 1 week in advance of the first session of group, similar to the calls in PDSA1. Letters were sent to those who were not reached by phone or voice mail. Expectations don’t match (clinic was PDSA4 — orientation via literature not what patient expected) Description: a brochure was created that explains what families should expect from the weight management clinic. It was used on the website and in new patient packets (English at the time of intervention), at the 6th grade reading level and using colorful graphics. Forgetting clinic appointment
intended to affect the percentage of attenders and nonattenders among follow-up patients. Figure 2 is a composite chart showing major events and monthly average attendance results in the context of interventions.
Process Measures Process measures associated with either patients’ actual or perceived barriers or operational problems identified by the project team include: 1) length of clinic visit, measured by recording total time patients were in exam rooms and subdivided into time in exam room waiting and time with providers; 2) contact preferences and updated information, collected on a convenience sample of patients using a form in English and Spanish; 3) scheduling of follow-up appointments, determined by review of medical records to verify whether patients actually scheduled recommended follow-up visits; 4) patient questions about goals and recommendations made in their treatment plan, ascertained during follow-up calls; and 5) patients’ difficulties in scheduling follow-up appointments, collected during follow-up calls.
Data Analysis Data were analyzed for both attendance outcome and process measures. The outcome measures of patient attendance were analyzed by Fisher’s exact test using Vasser Stats online software. To reach a power of .8, the sample size for the pre-intervention (n1) and post-intervention (n2) each
April 2012
June 2012
September 2012
January 2013
needed to be at least 313 as calculated using the University of Iowa power calculator. This number was exceeded for n2, but not achieved for n1, because it was not possible to obtain comparable clinic data for a longer pre-intervention period. Process measures of clinic visit length were analyzed using Pearson’s correlation in SPSS version 20 to determine if there was a positive or negative correlation over time. Descriptive data of other process measures were analyzed using frequencies and relative frequencies. These process measures included: ease or difficulty of scheduling, assistance needed after follow-up calls, and contact preferences of patients.
Results Attendance Outcomes The primary outcome was the increase in clinic patient attendance from 69% at baseline (February–April 2012) to an average ≥ 81% that began in May 2012 and was sustained through March 2013 (Figure 2). Over the course of the project, 388 clinic appointments were tracked for attendance and nonattendance. Fisher’s exact test showed a statistically significant decrease in non-attendance from baseline data (38 attenders, 17 non-attenders) to the 11-month intervention period (269 attenders, 64 non-attenders), z = 1.76, p = .039, OR for nonattendance during intervention = 0.53 [95% CI = 0.28, 1.00]. Attendance at group classes was analyzed separately from individual appointments reported above. Attendance at the first
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Figure 2
Chart showing average monthly attendance in context of PDSA cycle introduction.
session of group classes was 30% at baseline (January–August 2012) and averaged 34% during the intervention period (September 2012 to March 2013). Fisher’s exact test was performed to compare the baseline data for attendance at the first session of group classes (50 attenders, 21 non-attenders) to the 7-month intervention period (37 attenders, 19 nonattenders). The result were z = 0.33, p = .369, OR = 1.22 (odds of non-attendance did not significantly differ after the intervention) [95% CI = 0.57, 2.59].
Process Outcomes Descriptive statistics were used to characterize the results of follow-up calls. Calls were made to 248 new and follow-up patients in PDSA2 to ask two basic questions. In response to, “Did you have difficulty scheduling your next appointment?” 175 (71%) patients reported no difficulty. In response to, “Would you like clarification of goals/recommendations made at your last appointment?” 181 (73%) said they did not need any. Thirty-six patients (15%) expressed a need for assistance that required further communication with clinic staff. Data for length of clinic visits were recorded for 313 patient encounters with five providers. Time was tracked from the time a patient arrived in an exam room until leaving the exam room, including time waiting for the provider and time spent with the provider or providers. Maximum, minimum, and average total visit times were charted and displayed in the clinic workroom for 52 weeks. Without additional intervention beyond asking providers to track their time with patients, the average total visit length decreased over a period of 12 months from 128 to 101 minutes. Pearson’s correlation showed little change over time for new and follow-up patients combined (r = − .22, p = .126), but for new patient encoun-
ters, there was a significant decrease in length of time providers spent with patients (r = − .713, p = .007), which reduced total clinic visit time. This decrease could be explained by the Hawthorne effect, as providers became more aware of the goal for less lengthy appointments and more mindful of time spent with patients while participating in tracking this outcome (Shuttleworth, n.d.). There was no observed decrease in time waiting for the providers. One hundred twenty-four (124) parents of patients completed a contact preferences form, in which they could select more than one preferred method of contact. Of these, 72 parents responded with clearly marked preferences. Surveys with ambiguous preferences were excluded. Preferences were tabulated by category: home phone, cell phone, text message, and email. Forty-seven parents preferred text messaging, 42 preferred cell phone, 17 preferred email, and 10 preferred contact by home phone.
Discussion The results of this quality improvement project suggest that relatively inexpensive and simple changes in clinic processes can have a significant impact on increasing attendance of follow-up patients in outpatient obesity clinics. Since an average 12% improvement in attendance was realized shortly after the initiation of personal reminder calls (PDSA1) and before other interventions were introduced, it is reasonable to conclude that the reminder call intervention of PDSA1 accounts for most of the improvement observed in patient attendance. Examples of the effectiveness of phone call interventions are seen in the literature. Hampl et al. (2011) indicated that one of the practices in successful clinics among
Increasing Patient Attendance in a Pediatric Obesity Clinic their group of 24 hospitals was that of making personal reminder phone calls. This intervention has been effective in other venues as well. In the context of increasing vaccination rates in managed care, patients who received a telephone reminder call were more than twice as likely to be vaccinated as control patients (Winston, Mims, & Leatherwood, 2007). However, not all telephone interventions share the same degree of effectiveness. McDonough, Mault, and Burhan (2012) reported mixed results in an abstract describing telephone interventions with asthma patients. The results of interventions PDSA2-PDSA4 were inconclusive regarding their influence in maintaining increased attendance in the WMC. There was no apparent improvement in attendance as a result of the reminder calls by any of the three later interventions: follow-up calls, reminder calls for group classes, and distribution of the new clinic brochure. However, each of these interventions produced beneficial effects of its own. In addition to increasing the frequency of contact between the WMC and the patients, follow-up calls (PDSA2) provided the means to discover and measure problems with appointment scheduling so that corrections could be made. The 15% of patients who requested assistance during follow-up calls received personalized support in areas such as medication advice from medical providers, connection to financial mediators, and coordination of appointments among different specialty clinics. More than half of the patients who were contacted expressed gratitude for the concern shown by the WMC in making these calls. Whether follow-up calls contributed to increasing clinic attendance is unknown, but at least 36 individual patients received additional personalized attention via the follow-up contact. One disadvantage to routine follow-up calls is the additional time commitment by qualified personnel. It was considered desirable that the person making follow-up calls be at least as qualified as an RN due to the nature of questions that patients might ask. Although it did not seem to occur during the timeframe of the intervention, it is conceivable that patients could tire of receiving these calls routinely, potentially rendering them less effective over time. Reminder calls to participants of group classes (PDSA3) did not influence the overall improvement of either attendance for clinic appointments or the first session of group classes. There was great variation in attendance of the first session of group classes each month during the intervention. Both the number of patients called and the number of months were small (46 patients over 7 months). A longer period of intervention could potentially produce more definitive results. In January 2013, an English version of the newly created brochure (PDSA4) was added to new patient packets and sent to new patients in the weeks or days prior to their initial visit. The purpose of this intervention was to explain what patients should expect at the WMC. Since the intervention began late in the project timeline, there was insufficient time after initiation to determine whether the brochure shaped patient expectations, and if so, whether the brochure had any effect on patient attendance in follow-up visits. A patient survey
533 could be used to determine the brochure’s effectiveness. At the conclusion of the project, a Spanish translation of the brochure for the nearly 50% Spanish-speaking population of the WMC was still under development.
Additional Beneficial Outcomes Data collected during the improvement process resulted in some unexpected benefits and provided information that was useful in both short term and future interventions. Contact Preferences The contact preferences reported by patients revealed a disparity between patient preferences and the current system for automated reminders, which calls home phones only. These findings will be used to guide changes in contact methods between the WMC and patients. Text messaging, email, and social media are preferred methods of contact of many people, including the patients at the WMC. Thielst (2011), summarized the multitude of clinical and business benefits of using social media in healthcare. Due to the size of the organization of which the WMC is a part, a systemic switch to include this kind of contact would require substantial system-wide changes. The currently available electronic chart portal for patients (EPIC’s MyChartTM) is a step in that direction, but was not provided in Spanish and is presently infrequently utilized in this clinic’s patient population. Increased utilization of MyChart could be useful in improving communication with families. Appointment Length In recording length of appointments, individual provider’s statistics were tracked to observe differences among providers for patients’ visit time for both new patient and follow-up visits. These data were reported to the WMC staff and used to inform changes in utilization and scheduling patterns in the WMC. Scheduling Gap While tracking which patients scheduled their recommended follow-up appointments, a gap in scheduling was discovered. Many patients had been advised to attend group classes as their next ‘appointment,’ and did not understand the need to schedule individual clinic follow-up appointments after the group classes. Based on this discovery, the WMC’s protocol was altered so that these patients would schedule their clinic follow-up at the same time as they arranged for their group classes, facilitating continuity of care. Cost Benefits One of the side benefits of increasing patient attendance is its effect on the WMC’s financial status by revenue generation. Hampl et al. (2013) summarize the findings of several authors and point out that “attrition decreases the cost-effectiveness of an already expensive and poorly reimbursed intervention” (p.1). For example, when one
534 new patient fails to show for an appointment, the loss of clinical charges is approximately $700, per the 80th percentile benchmark for an 80 minute clinic visit (FAIR Health Consumer Cost Lookup, 2014).1 Even with clinic charges from follow-up patients being somewhat lower, the cumulative economic impact of 30% non-attendance of both new and follow-up patients can be substantial.
Limitations The quality improvement project had some limitations. The findings of quality improvement projects are not considered to be generalizable, because there are no randomization, no control group, and no control of the numerous factors that might influence patient behavior. Although the results of the Fisher’s exact test show the increase in attendance of follow-up patients was not likely due to chance, there remains the possibility that external factors may have influenced the results. Time was a limitation, as some additional possible interventions were never pursued. Due to time constraints, one potential evidence-based intervention that was not pursued was creation of audio/video media to orient patients to the WMC. Media presentations have been shown to be effective for patient education according to Armstrong, Idriss, and Kim (2010). Finally, the progress made in increasing patient attendance for follow-up appointments may be lost or may diminish if the WMC does not continue to apply the methods employed in the project. In order to sustain the progress made in improving patient attendance, a transition plan was established to distribute the intervention work among the WMC staff and volunteers until additional staff could be hired to perform these interventions.
Conclusions Results of the project will be useful to both patients and the WMC. Per Luttikhuis et al. (2009), patients will benefit because increased attendance is linked to reduced BMI and improved health outcomes. The WMC will benefit by means of increased revenue and schedule efficiency. Similar clinics may use the project findings to generate improvement in their own settings by adaptation and expansion of our methods. Future quality improvement for increasing patient attendance in this and other settings should focus on finding more efficient and effective methods to engage patients before, during, and between appointments. These methods may
1 Research for this cost estimate is based upon healthcare charge data compiled and maintained by FAIR Health, Inc. This benchmark reflects the professional charges only and does not include facility charges, which would be in addition to the $700 for the sample cited. Authors are solely responsible for the research, opinions and conclusions reflected in this article.
B. Geer et al. include modifying current appointment reminder systems, patient orientations, and utilizing social media.
Acknowledgments Funding: No external funding was solicited or received for the performance of this quality improvement project. Incidental expenses of the project, such as office supplies, were paid for by the principal investigator or provided inkind by Children’s Hospital Colorado. Presentations: DNP Capstone presentation, May 14, 2013 at University of Colorado College of Nursing Anschutz Medical Campus.
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Increasing Patient Attendance in a Pediatric Obesity Clinic Luttikhuis, H., Baur, L., Jansen, H., Shrewsbury, V., O’Malley, C., Stolk, R., et al. (2009). Interventions for treating obesity in children. Cochrane Database of Systematic Reviews, 2009, 1–197, http://dx.doi.org/10.1002/ 14651858.CD001872.pub2. McDonough, B. J., Mault, S., & Burhan, H. (2012). Reducing non-attendance at a difficult asthma clinic—are phone calls futile? [Poster session]. Thorax, 67, A187–A188, http://dx.doi.org/10.1136/thoraxjnl-2012202678.372. Schwartz, R. P., Hamre, R., Dietz, W. H., Wasserman, R. C., Slora, E. J., Myers, E. F., et al. (2007). Office-based motivational interviewing to prevent childhood obesity. Archives of Pediatric and Adolescent Medicine, 161, 495–501, http://dx.doi.org/10.1001/archpedi.161.5.495. Shuttleworth, M., (no date). Hawthorne effect. Explorable [website]. Retrieved from https://explorable.com/hawthorne-effect. Skelton, J. A., & Beech, B. M. (2010). Attrition in paediatric weight management: a review of the literature and new directions. Obesity Review, 12, e273–e281, http://dx.doi.org/10.1111/j.1467-789X.2010. 00803.x.
535 Skelton, J. A., Cook, S. R., Auinger, P., Klein, J. D., & Barlow, S. E. (2009). Prevalence and trends of severe obesity among US children and adolescents. Academic Pediatrics, 9, 322–329, http://dx.doi.org/10. 1016/j.acap.2009.04.005. Skinner, A. C., & Skelton, J. A. (2014). Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA, Pediatrics, 168, 561–566. Thielst, C. B. (2011). Social media: ubiquitous community and patient engagement. Frontiers of Health Service Management, 28, 3–14 (Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22256506). Whitlock, E. P., O’Connor, E. A., Williams, S. B., Beil, T. L., & Lutz, K. W. (2010). Effectiveness of weight management interventions in children: a targeted systematic review for the USPSTF. Pediatrics, 125, e396–418, http://dx.doi.org/10.1542/peds.2009-1955. Winston, C. A., Mims, A. D., & Leatherwood, K. A. (2007). Increasing pneumococcal vaccination in managed care through telephone outreach. American Journal of Managed Care, 13, 581–588 (Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17927463).
Increasing Patient Attendance in a Pediatric Obesity Clinic: A Quality Improvement Project Betty Geer DNP, RN, CPNP a,⁎, Renee M. Porter RN, MS, ND b , Matthew Haemer MD, MPH b , Marilyn J. Krajicek EdD, RN, FAAN a a
University of Colorado Anschutz Medical Campus, College of Nursing, Aurora, CO University of Colorado Anschutz Medical Campus, Department of Pediatrics, Section of Nutrition, Aurora, CO
b
Received 18 April 2014; revised 29 August 2014; accepted 5 September 2014
Key words: Childhood obesity; Improve attendance; Follow-up
Research supports intensive lifestyle interventions (N 25 contact hours/six months) to treat childhood obesity. Success requires retention in program. This quality improvement project's purpose was to increase attendance of follow-up patients in a childhood obesity clinic by 10%. A pretest posttest design was used. Three months of baseline data were collected, followed by 52 weeks of intervention data. Data were analyzed using descriptive statistics and Fisher's exact test. Follow-up patient attendance improved significantly from 69% to 81% (z = 1.76, p = .039 (95% CI = 0.2822, 1.0021)). Simple and inexpensive interventions can significantly increase attendance of obese children in follow-up. © 2014 Elsevier Inc. All rights reserved.
LIFESTYLE INTERVENTIONS, EMPLOYING behavioral strategies to modify nutrition and physical activity patterns, are the mainstay of treatment in children who are obese (Whitlock, O’Connor, Williams, Beil, & Lutz, 2010). In a meta-analysis, performed for the U.S. Preventive Services Task Force (USPSTF), Whitlock et al. compared 15 studies for effectiveness of varying intensities of behavioral interventions for pediatric obesity in children ages 4 to 18 years. They found that the effectiveness of lifestyle therapies in reducing BMI is positively associated with the frequency and duration of treatment. In conclusion, they recommended a minimum of 25 contact hours over six months (Whitlock et al., 2010). Contact hours may include individual or multidisciplinary clinic visits, group learning, and individual and group physical activities, all of which are designed to
⁎ Corresponding author: Betty Geer, DNP, RN, CPNP. E-mail address: [email protected]. http://dx.doi.org/10.1016/j.pedn.2014.09.001 0882-5963/© 2014 Elsevier Inc. All rights reserved.
change eating and physical activity behaviors to decrease BMI. Skelton and Beech (2010) recognized that, due to the slow pace of behavioral change, inconsistent participation in treatment would not likely produce long-term health improvement. Therefore, it is imperative for successful treatment of children who are obese, that they consistently attend clinic appointments for lifestyle interventions. Attrition from treatment programs is a major barrier to successful lifestyle intervention for obese children in the United States. In one review, more than 32% of overweight and obese children enrolled in treatment programs failed to complete their courses of treatment (Skelton & Beech, 2010), increasing these children’s risk for morbidity and health related complications. A study published in 2011 by the National Association of Children’s Hospitals and Related Institutions (NACHRI, now Children’s Hospital Association) reported that among 24 hospital-based clinics, patients failed to complete about half of their weight management programs’ follow-up visits (Hampl, Paves, Laubscher, & Eneli, 2011). The average
Increasing Patient Attendance in a Pediatric Obesity Clinic non-attendance rate (no-show or same day cancelation) of follow-up patients was 32.1% (range: 10%–75.7%).
Background and Significance Children whose BMI is greater than the 95th percentile on standard growth charts are considered obese (Centers for Disease Control and Prevention, 2000) and are at increased risk for serious comorbid conditions and chronic diseases, many of which are historically ‘adult’ diseases (Klish, 2014). The American Heart Association has proposed a definition of severe obesity as a BMI greater than 120% of the 95th percentile or absolute BMI ≥ 35 kg/m2, whichever is lower based on age and sex (Kelly et al., 2013). In children with severe obesity, the metabolic and cardiovascular profile is even more adverse than in children who are overweight or obese (Kelly et al., 2013). Childhood obesity is widespread in the United States. Skinner and Skelton (2014) examined the National Health and Nutrition Examination Survey (NHANES) data for 2011–2012 and report that 32.2% of children 2–19 years old were overweight, and 17.3% of children 2–19 years old were obese. While the overall childhood obesity rate has plateaued in recent years, severe obesity in children has increased 300% since 1979 (Skelton, Cook, Auinger, Klein, & Barlow, 2009). A literature search was conducted to identify evidence related to the importance of, barriers to, and methods of increasing patient attendance in childhood obesity treatment. The Cochrane Database, PubMed, and Google Scholar were used to search for articles using the search terms: childhood obesity prevention and treatment, chronic disease management, and patient retention and attrition. Three major reviews were found plus 19 articles, reports and expert opinions. Of these, eight were included in the synthesis of evidence because they reported relevant evidence on effective treatment modalities, barriers to treatment, causes of attrition, and interventions to increase attendance. Findings from a Cochrane Review concluded that a multidisciplinary approach using a family-oriented intervention for childhood obesity is effective, as it addresses the breadth of related causes and influences within the child’s immediate environment (Luttikhuis et al., 2009). Evidence exists for the use of motivational interviewing (MI) to help patients establish goals for lifestyle changes (Schwartz et al., 2007 and Whitlock et al., 2010). MI is also used in obesity treatment as a strategy to support family engagement in treatment and self-management. Self-management has been recognized as the core determinant of weight control in obese children (Dietz, Lee, Wechsler, Malepati, & Sherry, 2007). In order for these treatment modalities in lifestyle interventions to be successful, patients should consistently attend clinic appointments, because more intensive (frequent) interventions have been shown to be more effective in reducing BMI than less intensive interventions (Whitlock et al., 2010). Some studies have been published on barriers to sustained involvement of patients in weight management programs.
529 Skelton and Beech (2010) reviewed 10 studies related to attrition from pediatric weight management programs and found that apparent contributors to attrition included higher severity of obesity, poverty, single-parent households, and behavioral issues. Jelalian et al. (2008) also found high attrition rates among children with more severe obesity, children of obese parents, and children with minority or low income status. These articles indicated that barriers, especially for lower income populations, include parents missing work, children missing school, and transportation or financial limitations. Barlow and Ohlemeyer (2006) reported results of a survey showing differences between family expectations of the treatment plan and the care that was actually delivered in patients who attended fewer than three clinic visits. The most common reason given for non-return to the clinic was, “The program is not what we are looking for,” followed by schedule conflicts, distance from the clinic, and lack of insurance coverage. These findings were supported in the literature reviewed by Skelton and Beech (2010) and in the study by Hampl et al. (2013). Interventions to decrease attrition were discussed in several studies. Hampl et al. (2011) discovered that more successful programs utilized clinic-specific schedulers, reminder phone calls, family involvement in treatment, patient orientation by in-person sessions or written materials, and frequent dietitian visits. These findings concurred with patient feedback received at the weight management clinic (WMC) where this quality improvement project was conducted and suggested potential areas for intervention. The baseline attendance rate in the WMC was approximately 70%, and the non-attendance rate was close to 30% for follow-up patients. Comparatively, nonattendance rates were between 2% and 23% in other outpatient clinics within the hospital.
Project Aim The purpose of this quality improvement project was to increase the average monthly attendance rate of patients seen for follow-up in a hospital-based pediatric weight management clinic by 10% between April 1, 2012 and April 1, 2013. For simplicity, two groups of follow-up patients were defined: 1) attenders (either kept their appointments or canceled more than one day in advance) and 2) nonattenders (failed to show or canceled the day of appointment). Among the subset of patients who canceled appointments, we expected the interventions to affect the timing of cancelation, such that a greater proportion of patients would cancel and reschedule more than one day prior to scheduled appointments as opposed to canceling the day of the appointment. Interventions aimed at increasing follow-up patients’ attendance align with the hospital’s overall goals of patient satisfaction and growth in patient volume. The project was undertaken to answer the two-fold question: Why are patients failing to show at follow-up appointments, and what can be done to improve attendance?
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Methods Ethical Issues Ethical study design was insured in several ways. Risks to human subjects were minimal, and involve no greater risk than would be encountered in everyday life. Approval for the quality improvement project was obtained from the College of Nursing DNP Bridge Committee at the University of Colorado College of Nursing, to ensure the project was consistent with quality improvement principles. Confidentiality of patients, families, and providers was guarded in accordance with HIPAA guidelines by protecting and de-identifying data.
Sample and Setting The WMC is an outpatient pediatric obesity treatment clinic. It is located in a large freestanding tertiary care children’s hospital located within a large metropolitan area. The interdisciplinary practice includes physicians, nurse practitioners, physician’s assistants, psychologists, dietitians and an exercise physiologist. The WMC referral criteria are: 0–18 years of age, BMI N 95th percentile or BMI above the 85th percentile that is on a rapidly increasing trajectory. Children with special healthcare needs and genetic obesity syndromes (e.g. Prader Willi syndrome) are included in the treatment population. The majority of WMC patients are school age and have severe obesity. The sample and clinic demographics in Figure 1 were the same with the exception of the year of the study: 51% were female, and 48% were Hispanic. See Figure 1 for demographic data (Haemer, Ranade, Baròn, & Krebs, 2013).
Root Cause Analysis The clinical practice flow of the WMC was observed by the primary investigator prior to any formal root cause
WMC Demographics 80% 69%
70% 60% 51%
50%
48% 39%
40% 30%
22%
20% 10% 0% Female
Figure 1
Hispanic
Spanish Language
Private Insurance
Severe Obesity
WMC demographics.Source: Haemer et al. (2013).
analysis, and some specific features were noted. Before and during the project, the WMC utilized a non-clinic-specific hospital-wide scheduling pool and an automated reminder call system that were linked to the electronic health record (EMR). The automated reminder system was programmed to call home phone numbers approximately 2 days prior to appointments. Typical appointment length ranged from 1 to 3 hours. Patients had access to a variety of services and providers, and treatment plans were individualized. The formal analysis of root causes for non-attendance included: • Chronic care assessment (ACIC, Version 3.5., 2000); • Baseline data on clinical indicators: number of no-shows per clinic day, number and timing of cancelations, length of appointments, response to automated reminder calls, patient participation in group classes, and information about whether patients scheduled follow-up appointments; • A patient survey administered to 13 families by phone to elicit reasons why patients did not show for appointments; • Patient contact preference form which also solicited quality improvement suggestions; and • Reports by clinic staff of factors perceived to affect attendance.
The root cause analysis identified several modifiable factors contributing to patient non-attendance that include: (a) forgetting appointment, (b) appointments too far apart, (c) expectations did not match (not what patient expected), and (d) appointments too long.
Interventions Four targeted interventions in the form of Plan-Do-StudyAct (PDSA) cycles began at different points during the project to address aspects of the modifiable factors identified, and each intervention continued to the culmination of the project. The ultimate goal of each intervention was to increase attendance of follow-up patients in the WMC. The principle investigator performed these 4 cycles of quality improvement interventions based upon results of the root cause analysis (Table 1): appointment reminders (PDSA1), follow-up calls (PDSA2), reminder calls to group class participants (PDSA3), and orientation literature (PDSA4).
Data Collection Baseline attendance was recorded from February to April of 2012, and collection of intervention-related data began in mid-April, 2012. Microsoft Excel 2007 was used to collect data, which was de-identified before analysis. Attendance of follow-up patients was tracked in-person in clinic and by review of electronic medical records. Percentages of attendance were calculated by dividing the number of attenders by the number of total follow-up appointments scheduled per clinic session. Modified control charts tracked weekly and average monthly attendance during the project. These charts tracked progress toward the project aim, as all the interventions were
Increasing Patient Attendance in a Pediatric Obesity Clinic Table 1
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Interventions for patient attendance 2012–2013 relative to factors in no-show of patients discovered in the root cause analysis.
Factors in No-Show of Patients
PDSA Interventions
Start Date of PDSA
PDSA1 — appointment reminders Description: personal reminder calls were made one week in advance of appointment. Reminder letters were sent to families unable to be reached by phone. Appointments too far apart PDSA2 — follow-up calls to address questions between visits Description: follow-up calls were made to new patients approximately 3 weeks after initial clinic visits and to returning patients approximately 1 week after follow-up appointments. The foci of these calls were: • troubleshoot difficulties with arranging subsequent appointments • mitigate lack of understanding or difficulties working on goals and recommendations made by clinicians. Problems revealed during these calls were routed to the appropriate staff persons for remediation with expectation of timely follow-up. Forgetting group appointment PDSA3 — reminder calls to group participants Description: reminder calls were made to patients who were scheduled for group sessions occurring weekly for 1 month. These calls were made 1 week in advance of the first session of group, similar to the calls in PDSA1. Letters were sent to those who were not reached by phone or voice mail. Expectations don’t match (clinic was PDSA4 — orientation via literature not what patient expected) Description: a brochure was created that explains what families should expect from the weight management clinic. It was used on the website and in new patient packets (English at the time of intervention), at the 6th grade reading level and using colorful graphics. Forgetting clinic appointment
intended to affect the percentage of attenders and nonattenders among follow-up patients. Figure 2 is a composite chart showing major events and monthly average attendance results in the context of interventions.
Process Measures Process measures associated with either patients’ actual or perceived barriers or operational problems identified by the project team include: 1) length of clinic visit, measured by recording total time patients were in exam rooms and subdivided into time in exam room waiting and time with providers; 2) contact preferences and updated information, collected on a convenience sample of patients using a form in English and Spanish; 3) scheduling of follow-up appointments, determined by review of medical records to verify whether patients actually scheduled recommended follow-up visits; 4) patient questions about goals and recommendations made in their treatment plan, ascertained during follow-up calls; and 5) patients’ difficulties in scheduling follow-up appointments, collected during follow-up calls.
Data Analysis Data were analyzed for both attendance outcome and process measures. The outcome measures of patient attendance were analyzed by Fisher’s exact test using Vasser Stats online software. To reach a power of .8, the sample size for the pre-intervention (n1) and post-intervention (n2) each
April 2012
June 2012
September 2012
January 2013
needed to be at least 313 as calculated using the University of Iowa power calculator. This number was exceeded for n2, but not achieved for n1, because it was not possible to obtain comparable clinic data for a longer pre-intervention period. Process measures of clinic visit length were analyzed using Pearson’s correlation in SPSS version 20 to determine if there was a positive or negative correlation over time. Descriptive data of other process measures were analyzed using frequencies and relative frequencies. These process measures included: ease or difficulty of scheduling, assistance needed after follow-up calls, and contact preferences of patients.
Results Attendance Outcomes The primary outcome was the increase in clinic patient attendance from 69% at baseline (February–April 2012) to an average ≥ 81% that began in May 2012 and was sustained through March 2013 (Figure 2). Over the course of the project, 388 clinic appointments were tracked for attendance and nonattendance. Fisher’s exact test showed a statistically significant decrease in non-attendance from baseline data (38 attenders, 17 non-attenders) to the 11-month intervention period (269 attenders, 64 non-attenders), z = 1.76, p = .039, OR for nonattendance during intervention = 0.53 [95% CI = 0.28, 1.00]. Attendance at group classes was analyzed separately from individual appointments reported above. Attendance at the first
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Figure 2
Chart showing average monthly attendance in context of PDSA cycle introduction.
session of group classes was 30% at baseline (January–August 2012) and averaged 34% during the intervention period (September 2012 to March 2013). Fisher’s exact test was performed to compare the baseline data for attendance at the first session of group classes (50 attenders, 21 non-attenders) to the 7-month intervention period (37 attenders, 19 nonattenders). The result were z = 0.33, p = .369, OR = 1.22 (odds of non-attendance did not significantly differ after the intervention) [95% CI = 0.57, 2.59].
Process Outcomes Descriptive statistics were used to characterize the results of follow-up calls. Calls were made to 248 new and follow-up patients in PDSA2 to ask two basic questions. In response to, “Did you have difficulty scheduling your next appointment?” 175 (71%) patients reported no difficulty. In response to, “Would you like clarification of goals/recommendations made at your last appointment?” 181 (73%) said they did not need any. Thirty-six patients (15%) expressed a need for assistance that required further communication with clinic staff. Data for length of clinic visits were recorded for 313 patient encounters with five providers. Time was tracked from the time a patient arrived in an exam room until leaving the exam room, including time waiting for the provider and time spent with the provider or providers. Maximum, minimum, and average total visit times were charted and displayed in the clinic workroom for 52 weeks. Without additional intervention beyond asking providers to track their time with patients, the average total visit length decreased over a period of 12 months from 128 to 101 minutes. Pearson’s correlation showed little change over time for new and follow-up patients combined (r = − .22, p = .126), but for new patient encoun-
ters, there was a significant decrease in length of time providers spent with patients (r = − .713, p = .007), which reduced total clinic visit time. This decrease could be explained by the Hawthorne effect, as providers became more aware of the goal for less lengthy appointments and more mindful of time spent with patients while participating in tracking this outcome (Shuttleworth, n.d.). There was no observed decrease in time waiting for the providers. One hundred twenty-four (124) parents of patients completed a contact preferences form, in which they could select more than one preferred method of contact. Of these, 72 parents responded with clearly marked preferences. Surveys with ambiguous preferences were excluded. Preferences were tabulated by category: home phone, cell phone, text message, and email. Forty-seven parents preferred text messaging, 42 preferred cell phone, 17 preferred email, and 10 preferred contact by home phone.
Discussion The results of this quality improvement project suggest that relatively inexpensive and simple changes in clinic processes can have a significant impact on increasing attendance of follow-up patients in outpatient obesity clinics. Since an average 12% improvement in attendance was realized shortly after the initiation of personal reminder calls (PDSA1) and before other interventions were introduced, it is reasonable to conclude that the reminder call intervention of PDSA1 accounts for most of the improvement observed in patient attendance. Examples of the effectiveness of phone call interventions are seen in the literature. Hampl et al. (2011) indicated that one of the practices in successful clinics among
Increasing Patient Attendance in a Pediatric Obesity Clinic their group of 24 hospitals was that of making personal reminder phone calls. This intervention has been effective in other venues as well. In the context of increasing vaccination rates in managed care, patients who received a telephone reminder call were more than twice as likely to be vaccinated as control patients (Winston, Mims, & Leatherwood, 2007). However, not all telephone interventions share the same degree of effectiveness. McDonough, Mault, and Burhan (2012) reported mixed results in an abstract describing telephone interventions with asthma patients. The results of interventions PDSA2-PDSA4 were inconclusive regarding their influence in maintaining increased attendance in the WMC. There was no apparent improvement in attendance as a result of the reminder calls by any of the three later interventions: follow-up calls, reminder calls for group classes, and distribution of the new clinic brochure. However, each of these interventions produced beneficial effects of its own. In addition to increasing the frequency of contact between the WMC and the patients, follow-up calls (PDSA2) provided the means to discover and measure problems with appointment scheduling so that corrections could be made. The 15% of patients who requested assistance during follow-up calls received personalized support in areas such as medication advice from medical providers, connection to financial mediators, and coordination of appointments among different specialty clinics. More than half of the patients who were contacted expressed gratitude for the concern shown by the WMC in making these calls. Whether follow-up calls contributed to increasing clinic attendance is unknown, but at least 36 individual patients received additional personalized attention via the follow-up contact. One disadvantage to routine follow-up calls is the additional time commitment by qualified personnel. It was considered desirable that the person making follow-up calls be at least as qualified as an RN due to the nature of questions that patients might ask. Although it did not seem to occur during the timeframe of the intervention, it is conceivable that patients could tire of receiving these calls routinely, potentially rendering them less effective over time. Reminder calls to participants of group classes (PDSA3) did not influence the overall improvement of either attendance for clinic appointments or the first session of group classes. There was great variation in attendance of the first session of group classes each month during the intervention. Both the number of patients called and the number of months were small (46 patients over 7 months). A longer period of intervention could potentially produce more definitive results. In January 2013, an English version of the newly created brochure (PDSA4) was added to new patient packets and sent to new patients in the weeks or days prior to their initial visit. The purpose of this intervention was to explain what patients should expect at the WMC. Since the intervention began late in the project timeline, there was insufficient time after initiation to determine whether the brochure shaped patient expectations, and if so, whether the brochure had any effect on patient attendance in follow-up visits. A patient survey
533 could be used to determine the brochure’s effectiveness. At the conclusion of the project, a Spanish translation of the brochure for the nearly 50% Spanish-speaking population of the WMC was still under development.
Additional Beneficial Outcomes Data collected during the improvement process resulted in some unexpected benefits and provided information that was useful in both short term and future interventions. Contact Preferences The contact preferences reported by patients revealed a disparity between patient preferences and the current system for automated reminders, which calls home phones only. These findings will be used to guide changes in contact methods between the WMC and patients. Text messaging, email, and social media are preferred methods of contact of many people, including the patients at the WMC. Thielst (2011), summarized the multitude of clinical and business benefits of using social media in healthcare. Due to the size of the organization of which the WMC is a part, a systemic switch to include this kind of contact would require substantial system-wide changes. The currently available electronic chart portal for patients (EPIC’s MyChartTM) is a step in that direction, but was not provided in Spanish and is presently infrequently utilized in this clinic’s patient population. Increased utilization of MyChart could be useful in improving communication with families. Appointment Length In recording length of appointments, individual provider’s statistics were tracked to observe differences among providers for patients’ visit time for both new patient and follow-up visits. These data were reported to the WMC staff and used to inform changes in utilization and scheduling patterns in the WMC. Scheduling Gap While tracking which patients scheduled their recommended follow-up appointments, a gap in scheduling was discovered. Many patients had been advised to attend group classes as their next ‘appointment,’ and did not understand the need to schedule individual clinic follow-up appointments after the group classes. Based on this discovery, the WMC’s protocol was altered so that these patients would schedule their clinic follow-up at the same time as they arranged for their group classes, facilitating continuity of care. Cost Benefits One of the side benefits of increasing patient attendance is its effect on the WMC’s financial status by revenue generation. Hampl et al. (2013) summarize the findings of several authors and point out that “attrition decreases the cost-effectiveness of an already expensive and poorly reimbursed intervention” (p.1). For example, when one
534 new patient fails to show for an appointment, the loss of clinical charges is approximately $700, per the 80th percentile benchmark for an 80 minute clinic visit (FAIR Health Consumer Cost Lookup, 2014).1 Even with clinic charges from follow-up patients being somewhat lower, the cumulative economic impact of 30% non-attendance of both new and follow-up patients can be substantial.
Limitations The quality improvement project had some limitations. The findings of quality improvement projects are not considered to be generalizable, because there are no randomization, no control group, and no control of the numerous factors that might influence patient behavior. Although the results of the Fisher’s exact test show the increase in attendance of follow-up patients was not likely due to chance, there remains the possibility that external factors may have influenced the results. Time was a limitation, as some additional possible interventions were never pursued. Due to time constraints, one potential evidence-based intervention that was not pursued was creation of audio/video media to orient patients to the WMC. Media presentations have been shown to be effective for patient education according to Armstrong, Idriss, and Kim (2010). Finally, the progress made in increasing patient attendance for follow-up appointments may be lost or may diminish if the WMC does not continue to apply the methods employed in the project. In order to sustain the progress made in improving patient attendance, a transition plan was established to distribute the intervention work among the WMC staff and volunteers until additional staff could be hired to perform these interventions.
Conclusions Results of the project will be useful to both patients and the WMC. Per Luttikhuis et al. (2009), patients will benefit because increased attendance is linked to reduced BMI and improved health outcomes. The WMC will benefit by means of increased revenue and schedule efficiency. Similar clinics may use the project findings to generate improvement in their own settings by adaptation and expansion of our methods. Future quality improvement for increasing patient attendance in this and other settings should focus on finding more efficient and effective methods to engage patients before, during, and between appointments. These methods may
1 Research for this cost estimate is based upon healthcare charge data compiled and maintained by FAIR Health, Inc. This benchmark reflects the professional charges only and does not include facility charges, which would be in addition to the $700 for the sample cited. Authors are solely responsible for the research, opinions and conclusions reflected in this article.
B. Geer et al. include modifying current appointment reminder systems, patient orientations, and utilizing social media.
Acknowledgments Funding: No external funding was solicited or received for the performance of this quality improvement project. Incidental expenses of the project, such as office supplies, were paid for by the principal investigator or provided inkind by Children’s Hospital Colorado. Presentations: DNP Capstone presentation, May 14, 2013 at University of Colorado College of Nursing Anschutz Medical Campus.
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535 Skelton, J. A., Cook, S. R., Auinger, P., Klein, J. D., & Barlow, S. E. (2009). Prevalence and trends of severe obesity among US children and adolescents. Academic Pediatrics, 9, 322–329, http://dx.doi.org/10. 1016/j.acap.2009.04.005. Skinner, A. C., & Skelton, J. A. (2014). Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA, Pediatrics, 168, 561–566. Thielst, C. B. (2011). Social media: ubiquitous community and patient engagement. Frontiers of Health Service Management, 28, 3–14 (Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22256506). Whitlock, E. P., O’Connor, E. A., Williams, S. B., Beil, T. L., & Lutz, K. W. (2010). Effectiveness of weight management interventions in children: a targeted systematic review for the USPSTF. Pediatrics, 125, e396–418, http://dx.doi.org/10.1542/peds.2009-1955. Winston, C. A., Mims, A. D., & Leatherwood, K. A. (2007). Increasing pneumococcal vaccination in managed care through telephone outreach. American Journal of Managed Care, 13, 581–588 (Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17927463).
