[usPropHeader] Error loading user control: The file '/CMSWebParts/WK.HLRP/LNC/LNCProductHeader.ascx' does not exist.

Authors

  1. Roberts, Cindy L.
  2. Meyering, Christopher D.
  3. Zychowicz, Michael E.

Abstract

PURPOSE: Implement and evaluate the effectiveness of the Leg Pain Screening and Referral Tool (LPS&RT) for patients presenting with lower extremity leg pain in an outpatient clinic.

 

SAMPLE: A total of 46 patients diagnosed with tibia stress fractures.

 

METHODS: The study employed a pre-/postintervention design. Retrospective and prospective information was collected from an electronic health record to obtain patient data. The pre- and postintervention groups were compared on the number of patients diagnosed with tibia stress fractures. Provider adherence to the treatments recommended by the algorithm was assessed by chart audits postintervention.

 

RESULTS: There was a significant increase (87.5%) in tibia stress fracture diagnosis, from 16 preintervention to 30 postintervention. Provider adherence to the LPS&RT was 93.3% postintervention. Common treatments were activity restriction, oral medication, and/or specialty referrals.

 

CONCLUSION: The LPS&RT was an effective, uniform measure to standardize the plan of care for tibia stress fractures in one outpatient clinic.

 

Article Content

Stress fractures are a major cause of injury and cost millions of dollars each year in treatment and lost productivity in both the athletic and military population (Nindl, Williams, Deuster, Butler, & Jones, 2013; Ruscio et al., 2010; Rutten, Nolte, Guit, Bouman, & Albers, 2007; Schofer et al., 2010; Yadav, Salgotra, & Banerjee, 2008). In 2010, the total number of soldier limited-duty days due to musculoskeletal injury across all services was estimated at nearly 25 million (Ruscio et al., 2010). An estimated 5%-10% of all sports-related injuries result from stress fractures and, of those stress fractures, approximately 50% occur in the tibia shaft (Philipson & Parker, 2009; Rosenthal & McMillian, 2006). In addition, 5%-10% of the approximate 6.2 million stress fractures demonstrate delayed healing or nonunion (Brand, Brindle, Nyland, Caborn, & Johnson, 1999; Busse, Bhandari, Kulkarni, & Tunks, 2002; Claes & Willie, 2007). The contributing elements are related to extrinsic factors (e.g., an aggressive training regimen without proper body conditioning) and intrinsic factors (e.g., bone anatomy, fitness level, and gender; Philipson & Parker, 2009; Rosenthal & McMillian, 2006).

 

A high number of stress fractures occur in military training programs, basic training posts, military training academies, and specialty training units due to the repetitive high-impact training with weight-bearing activities such as running and marching (Rosenthal & McMillian, 2006). However, the condition has been occurring in nonmilitary populations with increasing frequency since the mid-1900s (Jones, Thacker, Gilchrist, Kimsey, & Sosin, 2002). Given the athletic nature of many active duty members and physically active persons, the possibility of a stress fracture should be considered when evaluating patients with exercise-related musculoskeletal complaints (Rosenthal & McMillian, 2006). Since prompt diagnosis and treatment are crucial in the management of stress fractures, clinicians must have a high index of suspicion and be knowledgeable of lower extremity musculoskeletal diagnoses to make the appropriate decision for care.

 

Medical specialists (e.g., physical therapy, sports medicine, and orthopaedic) are typically booked 2-3 weeks in advance because of the increased workload. As a result, primary care providers (PCPs) who often manage more than one problem find themselves managing most of the clinical care for patients presenting with musculoskeletal injuries. However, a lack of standardized treatment guidelines hinders PCPs from making the appropriate diagnoses and may encourage nonstandard treatments; both behaviors may delay or prolong patient healing.

 

This doctor of nursing practice (DNP) student introduced a screening algorithm for PCPs, whose patients include service members presenting with leg pain, with the intent of standardizing the diagnosis and care of tibia stress fractures in the military population. The intent was to reduce the number of misdiagnosed cases of stress fractures, thereby leading to shorter recovery time for soldiers who have been properly diagnosed with such fractures. The algorithm is intended to be effective in civilian and military populations.

 

Literature Review

Approximately 60% of persons diagnosed with a stress fracture have suffered one in the past (Sanderline & Raspa, 2003). Stress fractures, or overuse bone injuries, occur as a result of repetitive microtrauma to bone that exceeds the intrinsic ability of the bone to repair itself (Sanderline & Raspa, 2003; Yadav et al., 2008). Simply stated, a deconditioned individual (or even a fit athlete) abruptly increases the frequency, duration, and intensity of an activity too rapidly (Patel, Roth, & Kapil, 2011; Yadav et al., 2008). The first report of a stress fracture (named "March" fracture) was diagnosed in the foot of a marching recruit in the Prussian Army of 1855 by Dr. Briethaupt (Rosenthal & McMillian, 2006; Yadav et al., 2008). Since that time, the prevalence of stress fractures has been closely followed as an area of concern for persons in the military service. Among all services (army, air force, navy, and marine), tibia stress fractures accounted for 22.7% of musculoskeletal injuries, and lower extremity injuries accounted for 40.5% of all visits (Ruscio et al., 2010, p. 23, Table 2). The tibia is the most commonly injured bone in the lower extremity (Jones et al., 2002; Patel et al., 2011; Yadav et al., 2008).

 

The timing of a stress fracture occurrence after initiation of training is not predictable. Studies indicate that 1%-9% of U.S. military recruits will sustain a stress fracture at 6 weeks of training (Philipson & Parker, 2009; Rosenthal & McMillian, 2006). In contrast, the Israeli Defense Force reports an incidence as high as 31% in its recruit within the first 4 weeks of training (Philipson & Parker, 2009). The high degree of variability is accredited to the U.S. passive surveillance of stress fractures in which an individual must first seek medical treatment. In contrast, the Israeli Defense Force utilizes bone scans as an active surveillance measure to diagnose stress-related injuries-a practice that yields a greater number of positive findings (Rosenthal & McMillian, 2006).

 

Signs and symptoms of musculoskeletal injuries may be underdiagnosed by PCPs (Beattie et al., 2008). Reasons for underdiagnosing musculoskeletal conditions may be related to time constraints, lack of confidence in conducting the assessment, or lack of knowledge in managing the musculoskeletal condition. If treated improperly in the early stages, musculoskeletal injuries can lead to chronic pain and dysfunction. Tibia nonunion fractures have a high occurrence rate and result in significant impairment to daily functioning. In addition, surgical interventions with supplemental bone grafting are complex and costly (Gebauer, Mayr, Orthner, & Ryaby, 2005; Rutten et al., 2007; Schofer et al., 2010). Power, Perruccio, DesMeules, Lagace, and Badley (2006) conducted a study in Canada and concluded that musculoskeletal injuries are the second most common reason for patients visiting a PCP, and such injuries are accountable for costs higher than any other health condition except cardiovascular disease. Despite a high incidence of patient visits for musculoskeletal injuries, only 8% of primary care services were dedicated to management (Flook, 2006). Primary care managers must be equipped to address the need.

 

Part of addressing this need is the use of appropriate diagnostic imaging. Plain film radiographs are characteristically selected as a first-line test to rule out stress fractures. The films are easy to obtain and inexpensive and provide baseline medical information; however, x-ray films are usually negative and unrevealing (Patel et al., 2011; Rosenthal & McMillian, 2006). Therefore, secondary tests such as nuclear medicine bone scans, magnetic resonance imaging (MRI), or computer topography (CT) are often ordered to rule out stress fractures. Bone scans are typically the second choice to diagnose stress fractures because they are inexpensive and extremely sensitive but nonspecific. They are considered a poor monitor for assessing the healing time of stress fractures, however, and could remain positive for up to 1 year or more after initial injury (Yadav et al., 2008). Gaeta and colleagues (2005) conducted a study of 42 patients experiencing tibia pain and determined that the MRI was more specific, sensitive, and accurate (88%, 100%, and 90%, respectively) for early diagnosis of stress fracture and stress injury. Furthermore, an expert panel from the American College of Radiology recommends MRI as the subsequent test when plain radiography is negative, because it provides greater detail of the surrounding tissue (Patel et al., 2011) to determine whether surgical intervention is warranted (Rosenthal & McMillian, 2006). However, in some patients with negative MRI findings, a CT scan appears to be the better choice because it can depict the earliest findings of cortical bone abnormalities (osteopenia; Gaeta et al., 2005).

 

Although stress fractures contribute to severe lower extremity injuries, the differential diagnoses include shin splints, compartment syndrome, nerve entrapment, Achilles rupture, deep vein thrombosis, and cellulitis (Patel et al., 2011). Current treatment guidelines, including initial workup with diagnosis, medications, and radiological imaging, are inconsistent and vary among both PCPs and specialty providers. In addition, treatment protocols differ from provider to provider. Treatment can include rest, ice, elevation, nonsteroidal anti-inflammatory medications, calcium supplements, or shin sleeves; however, many providers report mixed results ranging from no improvement to moderate improvement. In most cases, providers diagnose limb pain as shin splints based only on physical examination rather than on radiological confirmation to the contrary. Because diagnosis is based on the examination alone, conservative treatment measures are usually the norm. Specialty providers may prescribe rest and cessation of all activities. Consequently, there is inconsistency in the treatment regimen among providers and the interdisciplinary departments. Given the gap between the incidence and diagnosis of lower extremity musculoskeletal injuries in the primary care population, a simple screening tool may empower practitioners to accurately identify and treat abnormalities, such as stress fractures (Beattie et al., 2008).

 

The Innovation

The proposed innovation for this DNP quality improvement project was the implementation of the Leg Pain Screening and Referral Tool (LPS&RT) to provide consistent diagnosis and treatment at a military outpatient clinic. The LPS&RT was created under the direction of the Medical Command Chief of Staff's Strategic Performance Action Plan (U.S. Army Medical Department Office of Quality Management, 2008) and approved by the Army's Quality Management (U.S. Army Medical Department Army Medicine, 2008) as a tool to identify and treat lower extremity leg pain as well as bridge the gap between knowledge and quality of care. The LPS&RT consists of five elements:

 

1. Red Flags: Identifies traumatic clinical presentations that warrant an immediate x-ray and/or STAT orthopaedic consultation.

 

2. Close Monitoring: Acute leg pain injuries that warrant further evaluation and/or ASAP orthopaedic consultation.

 

3. Conservative Management: Management guidance for acute leg pain to include follow-up appointments and clinical presentation that may warrant consultation with a specialty provider (e.g., physical therapy, sports medicine, or orthopaedics).

 

4. Profiles: Categorizes two types (A or B) of limited-duty assignments and defines the restrictions and required equipment (if warranted).

 

5. RICE: Defines the acronym and provides time and duration of treatments.

 

 

Purpose (or Objective)

The purpose of the LPS&RT was to arm PCPs with a point-of-care decision support tool for prompt diagnosis and treatment, as well as guidance on when to refer leg pain injuries. The main focus of the project was tibia stress fractures, but other differential diagnoses must be considered and ruled out. According to the U.S. Army Medical Department Army Medicine (2008), algorithms quickly guide a patient along the appropriate treatment path of a specific diagnosis, thereby expediting care and speeding up the recovery period for athletes.

 

Aim of the Innovation

The aim of this project was twofold: (1) assess the impact of the proposed intervention on clinical outcome in the outpatient clinic setting, as demonstrated by an increase in the diagnosis of tibia stress fractures, and (2) assess the provider's adherence to a leg pain algorithm to assist with identifying tibia stress fractures. More specifically, the clinical goal was to increase proper diagnoses of tibia stress fractures by at least 50% after the new algorithm was implemented. The compliance goal, based on algorithm fidelity, was to have providers adhere to the treatment recommendations of the algorithm at least 90% of the time.

 

Description of Innovation

The LPS&RT was self-explanatory and very easy to use. Large, colorful, laminated posters of the algorithm were posted in each provider's examination room for easy access. In addition, providers were given a pocket size copy of the algorithm to carry. One consideration, when implementing the tool, was to ensure that the military acronyms were defined for nonmilitary outpatient clinics in order for PCPs to maximize usage. Therefore, a legend was added to the bottom half of the original algorithm (see Figure 1).

  
Figure 1 - Click to enlarge in new windowFigure 1. Screen and referral tools (SRTs): Traumatic and acute leg pain. Courtesy of the U.S. Army Medical Department Office of Quality Management and the U.S. Army Medical Department Army Medicine (

The Organization

The practice setting was Mark A. Connelly Health Clinic, an outlying clinic of Dwight D. Eisenhower Army Medical Center at Fort Gordon, Georgia. Fort Gordon remains one of the Army's largest training and doctrine command sites for military members in trainee status for the Army, Air Force, and Navy personnel in the Reserves, National Guard, and active duty. Connelly Clinic serves approximately 7,000 men and women monthly in addition to maintaining service members and civilian employees' ability to deploy oversees. At the time of the study, the clinic was staffed with 56 employees, of whom 42 were directly assigned under this DNP student's supervision. Assigned staff members included 14 PCPs, comprising 12 mid-level providers, one medical doctor, and one doctor of osteopathy. Staff members also included three registered nurses, seven licensed practical nurses, six certified nursing assistants, five medics, and eight medical clerks.

 

Other services embedded within the clinic, and of importance to this study, are physical therapy with two physiotherapists and two physical therapy assistants, and two specialty providers, a sports medicine physician, and an orthopaedic physician assistant (PA). Therefore, the cost of innovation implementation was minimal because many of the key requirements were already in place. Two teams, each consisting of six PCPs, one practical nurse, and three nursing assistants, took part in the intervention. The nursing personnel were responsible for screening the patient to verify patient personal health information (e.g., name and date of birth), obtain vital signs, assess pain level, obtain the patient's reason for visit, and review current medications to include charting of the information, prior to the clinician's arrival into the examination room. Patient appointments were scheduled to last 15-20 minutes each.

 

Preparing for the Innovation

Recognizing the strength in synergy, the implementation of this quality improvement innovation required a multidisciplinary approach. A team of PCPs, a sports medicine physician, an orthopaedic PA, physical therapists, nurses, a health systems specialist, and board-certified radiologists were crucial to the successful outcome of this project. The sports medicine physician was an early adopter and champion of the project. He assisted this DNP student with coordination of staff. The orthopaedic PA also assisted by providing guidance on musculoskeletal injuries from a surgical standpoint. Physical therapists assisted by demonstrating proper body mechanics for home exercises prescribed by PCPs for patients awaiting an appointment. Radiologists validated the number of positive tests for stress fractures, shin splints, or stress reactions ordered by the provider. The health systems specialist retrieved all medical records assigned the International Classification Diseases (ICD) codes of 733.93 (tibia stress fractures) and 719.46 (lower extremity pain), 729.5 (limb pain), and 849.5 (shin splint/leg strain).

 

The team was provided three methods of training-seminars, videos, and web-based training modules-over 3 months at Connelly Health Clinic. Three 30-minute seminars facilitated tool introduction to include pertinent differential diagnoses associated with leg pain, treatment and referral guidance, and hands-on demonstration of home exercises. However, the emphasis was on identifying and treating tibia stress fractures. PowerPoint presentations of each lecture were e-mailed to staff and several videos demonstrating a proper musculoskeletal examination for lower extremity injury were an available option as well. In addition, self-paced training was conducted by team members via Web-based modules previously approved by our facility for musculoskeletal injuries. Upon written request, the Army's Quality Management (U.S. Army Medical Department Army Medicine, 2008) provided 35 notebooks titled Screening and Referral Tools for Musculoskeletal Injuries (e.g., back, shoulder, knees). Also, with a submitted request, this DNP student produced 20 poster board-size and 20 pocket-size laminated algorithms from the Media and Distribution Department at Eisenhower Army Medical Center.

 

Team members met once a week for 15-20 minutes the first month, then bimonthly the second month, and finally monthly for 2 months to discuss concerns and provide input on how the algorithm was enhancing or disturbing their daily work flow with patients. This time enabled PCPs to offer suggestions on process improvement. Thursday afternoon had already been set aside for mandatory and routine training in each department of this facility. Hence, it was the identified training day for this DNP student project.

 

Methods

Study Design

The project was a pre-/postintervention design. Retrospective and prospective information was collected from an electronic health record to obtain patient data. Retrospective data were retrieved from January 1, 2012, to March 30, 2012, to establish baseline values prior to implementation of the innovation. The innovation was implemented and monitored from August 1, 2012, until December 31, 2012.

 

Sample

The health systems specialist compiled a list of 18,280 patients whose record showed a visit for the previously listed four ICD-9 codes. A selected PCP from the clinic de-identified the data (with the exception of diagnosis, age, and gender) and submitted the list to the DNP student for review to ensure that the patients met inclusion criteria. The initial goal was to get at least 150 participants aged 17 to 24 years diagnosed with one of the four ICD-9 codes during implementation; however, because of time constraints and the project's primary interest in patients with tibia stress fractures, only subjects with tibia stress fractures (733.93) as one of their diagnoses was included in the data analysis. As a result, the single inclusion criteria created a smaller sample of 46, which was determined to be adequate for the descriptive and nonparametric analyses performed on the data.

 

Data Collection

Data were retrieved from the electronic health records by the health systems specialist assigned to the Managed Care Division at Eisenhower Army Medical Center. An identified PCP assigned to Connelly Clinic and the DNP student had full access to the patient's protected health information. The purpose was to review the assessment and plan section of each chart collected postimplementation to determine whether the PCP adhered to the recommended diagnostic and treatment guidelines of the LPS&RT (i.e., consider x-ray, bone scan, crutches, profile days).

 

The integrity of the data was maintained and stored at a password-protected document created by the health systems specialist. To safeguard patient information, charts were assigned a random registration number created by the facility, and demographic information was excluded to protect the patient's identity with the exception of their age and gender. Following the 5-month intervention period, the information was accessible only to the principal investigator, the DNP student, and the statistician who assisted with analysis of the data.

 

Ethical Considerations

The quality improvement project was reviewed and approved by the institutional review board at two independent facilities as a systematic investigation and a nonresearch venture. The data were collected anonymously and held 24 months before destroying it. The execution of the leg pain screening tool was incorporated into routine care for patients presenting with leg pain; hence, informed consent was given verbally by the participant without supplemental documentation being required to conduct this project.

 

Data Analysis

Preliminary analysis of data included descriptive statistics for continuous data, such as age, and frequency counts for categorical data, such as gender. Regarding the compliance outcome, a manual count was conducted and records showing that PCPs adhered to the algorithm were given credit. For diagnosis of tibia stress fractures, a percentage change was calculated by comparing raw frequency count of the number of preintervention diagnoses to postintervention diagnoses. For percentage increase, the following equation was used: subtracting the number of patients diagnosed with tibia stress fractures prior to algorithm implementation from the number of patients diagnosed postimplementation, then dividing by the number of patients diagnosed preintervention to determine whether there was an increase or a decrease in the number of patients diagnosed with a tibia stress fracture. To compare diagnosis at pre- and postimplementation by gender, Fisher's exact test was conducted using IBM SPSS version 19 grad pack (IBM, Chicago, IL).

 

Results

Clinical Outcome of Diagnosing Tibia Stress Fractures

Of the 46 patients diagnosed with tibia stress fractures, 16 occurred during the preimplementation and 30 occurred during postimplementation. As a result, there was an 87.5% increase in identifying tibia stress fractures after project implementation. Stress fractures were bilateral (n = 12) in 26.1% of cases. Radiographs were taken in 100% of cases at the time of presentation but were abnormal (n = 2) in only 4.3%. Bone scans routinely confirmed diagnosis of positive stress fractures of the tibia (n = 43) in 93.5% of cases but were normal in 2.2%. Magnetic resonance images (n = 2) were taken only in 4.3% in individuals presenting with lower leg extremity pain but were abnormal in only one. A CT scan was never offered as a diagnostic option.

 

Age and Gender

In the sample of 46 patients, 24 women and 22 men were diagnosed with tibia stress fractures (see Figure 2). All patients were between the ages of 18 and 30 years, with the exception of one male (age = 34 years) and one female (age = 49 years). The average age for men was 21.87 years at preimplementation and 20.57 years at postimplementation. For women, the average age was 21.38 years at preimplementation and 21.81 years at postimplementation (see Figure 3). Although there were more women than men with diagnosed tibia stress fractures at the postimplementation compared with preimplementation, Fisher's exact test revealed that this was a nonsignificant difference (p > .05).

  
Figure 2 - Click to enlarge in new windowFigure 2. Summary of tibia stress facture diagnosis by gender.
 
Figure 3 - Click to enlarge in new windowFigure 3. Average age by gender.

Providers' Compliance to Protocol

The project goal was to increase providers' compliance to the algorithm by at least 90%. Only records that followed the proposed algorithm were given credit as compliant (yes/no). Of the 30 patients diagnosed with tibia stress fractures during the implementation period, the provider adhered to the algorithm on 28; hence, the compliance rate was 93.3%.

 

Discussion

Over the course of the implementation of this algorithm, a total of 18,280 patients presented to the clinic, with complaints of lower extremity leg pain under the four previously identified ICD-9 codes (see Figure 4). However, the single inclusion criteria of a diagnosis of a tibia stress fracture (733.93) led to a smaller sample than originally projected. This DNP student only used the 46 participants who fit the criteria in order to minimize the confounding variables that could affect the findings.

  
Figure 4 - Click to enlarge in new windowFigure 4. Frequency of

Running was the most common sport at the time of injury; however, patients admitted to actively engaging in ruck marching/hiking and increased and repetitive strenuous calisthenics (i.e., jumping jacks, obstacle course training, sprints) over a short period of time. The duration of the offending activity and week of training was not obtained. Time to diagnosis varied among patients. This was based in part on compliance with appointments (i.e., radiology department, follow-up, specialty referrals). It is believed that proper diagnoses and treatment guidance provided by the LPS&RT resulted in fewer stress fractures, but an increase in the other diagnoses (e.g., limb pain, shin splints, and lower extremity pain; see Figure 4).

 

Diagnosis of tibia stress fracture was based on (1) clinical presentation of point tenderness to the tibia compartment, with/without acute trauma, aggravated by repetitive weight-bearing activities and relieved with rest, and (2) a confirmatory (+) radiograph and/or bone scan at the same site as the clinical presentation. Patients were diagnosed from 5 to 21 days after their initial appointment. Bone scan was the single most useful diagnostic aid. However, healing was assessed using plain films or magnetic resonance images.

 

Conservative management with specialty referral was satisfactory in the majority of cases due to the athletic nature of the individual. Specialists utilized were physical therapy 100% (n = 46), sports medicine 2.2% (n = 1), and orthopaedic 15.2% (n = 7). Orthopaedic referrals were reserved for Grade III or complicated/nonhealing Grade II fractures. Surgical intervention by an orthopaedic physician was considered in one case for a nonossifying fibroma on the lateral tibial metaphysis that coexisted with a posteromedial tibia stress fracture, but waived for observation and conservative management. The lesion is usually a benign, developmental defect, classically located in the distal femur, proximal and distal tibia, and fibula, but can occur about the knee and coexist with a stress fracture (Hod et al., 2007; Grove & Robbins, n.d.). Military recruits (mean age = 19.4 years) undergoing bone scan for suspected stress fracture might have incidental findings of a nonossifying fibroma which require further evaluation (Hod et al., 2007). Most lesions heal spontaneous with conservative management and/or immobilization by casting. Surgical intervention (e.g., curettage and bone grafting) is reserved for persistent symptoms and structurally compromising location of the lesion (Grove & Robbins, n.d.; Orthopaedic Institute for Children, n.d.).

 

Nonsteroidal anti-inflammatory drugs and Tylenol (acetaminophen) were prescribed equally for pain, but calcium and vitamin D supplements were prescribed in only 45% of the cases. The role of nonsteroidal anti-inflammatory drugs in the management of stress injuries is unclear. Some animal studies have shown that nonsteroidal anti-inflammatory drugs may delay healing in subjects with traumatic fractures (Wheeler & Batt, 2005). In contrast, there are inconsistent results (e.g., no difference, delayed healing, and increased risk of nonunion) documenting the effect of nonsteroidal anti-inflammatory drugs on stress fracture healing in human subjects. Therefore, Wheeler and Batt (2005) recommend short-term use in patients with proven stress fracture, until conclusive evidence is produced. In regard to supplementation with calcium and vitamin D, both are safe, well-tolerated, and found to significantly reduce the risk of stress fracture in recruits despite the negative effects of several lifestyle factors (Lappe et al., 2008).

 

Stress fractures can occur in each gender and at various fitness levels (i.e., well-trained vs. casual athletes) equally. In addition, as mentioned earlier, the contributing elements are related to extrinsic and intrinsic factors (Philipson & Parker, 2009). Yet, women's incidence of stress fractures is twice as high as that of men undergoing the same entry-level military training at a rate of 5%-12% (Beck et al., 2000; Jones, Bovee, Harris, & Cowan, 1993). For this project, the incidence of tibia stress fractures was 8% higher in female trainees (n = 24) than in their male counterparts (n = 22). The increased risk for women was possibly attributed to anatomical/physiological (e.g., differences in gait, more slender bones, a wide pelvis, genu valgum, tibia torsion, increased hip external rotation, and greater percentage of body fat loading), endocrine (e.g., body somatotype, menstrual irregularities), or lower initial physical fitness (Brukner & Bennell, 1997; Bennell, Matheson, Meeuwisse, & Brukner, 1999; Martin, 1991). However, the major risk factor for women is the female athlete triad.

 

The female athlete triad denotes an interconnected problem consisting of amenorrhea (absence of menses), disordered eating (e.g., binging or purging), and osteoporosis (low bone density; Pepper, Akuthota, & McCarty, 2006). It is considered a potentially lethal combination of medical disorders. Likewise, women are typically underweight and undernourished and may have hormonal/endocrine deficiencies and narrow bone width. In recent studies, "both chronic under nutrition and acute dietary energy restrictions have been found to be accompanied by reduced bone formation" (Pepper et al., 2006, p. 3). In some instances, the damage may be irreversible after a certain age (Drinkwater, Nilson, Ott, & Chesnut et al., 1986; Nattiv & Armsey, 1997; Rigotti, Neer, Skates, Herzog, & Nussbaum, 1991). During patient screening, data were collected on weight, last menstrual period, and contraceptive type, but the data were not analyzed. In contrast, participants were not questioned about disordered eating, menstrual irregularities, and duration of contraceptive and hormonal/endocrine issues.

 

Strengths

This innovation fit current organizational patient population and capabilities. It was moderately compatible to the Department of Defense strategic plan to improve and maintain a fit-force. Likewise, the screening tool was well-suited with the existing clinical practice guidelines. In addition, algorithms reduce inappropriate variations in clinical practice, improve outcomes, and reduce costs by reducing or eliminating ineffective practices (Fountoulakis et al., 2005; Mistler, Mellman, & Drake, 2009). Participants perceived a relative advantage or benefit of the innovation to stay actively engaged in training. Providers' compliance was based upon their willingness to use the algorithm.

 

Specialists and PCPs collaborated and provided feedback and input on how best to implement the LPS&RT for lower leg injuries. Also, a previous implementation of a similar quality improvement program on hip pain was successful, as evidenced by a fidelity compliance of greater than 94% at year 4. As a result, PCPs commented that the LPS&RT was very similar and easy to follow. Routine meetings provided an opportunity to share new knowledge with staff. In addition, routine meetings provided members and staff with statistical information on incidence rates and associated costs of musculoskeletal injuries, which helped illustrate the significance of the problem and garner project support.

 

Limitations

The innovation was implemented in an outpatient clinic on a military installation. Because of time constraints, this study was not random (site or sample) and the sample size was small but adequate. Likewise, the sample was presumed healthy, active, and otherwise in a good physical condition, which is not true of all patients with musculoskeletal injuries in other settings. Furthermore, this DNP student did not obtain what week of training the recruit/patient was in, how long the individual had been training before entering active duty, and what the individual's level of physical condition was prior to injury. Primary care providers' adherence to the algorithm was assessed; however, feedback to determine their satisfaction with the algorithm was not obtained. Finally, the cost and number of missed workdays were mentioned but not assessed.

 

Recommendations

In future studies, this DNP student has four recommendations. First, civilian outpatient clinics with a specific population (e.g., athletic program) should be included in the evaluation to obtain a larger sample with patients of varying fitness levels. Second, a patient questionnaire should be created to obtain past medical information to include level of fitness prior to injury. Third, a provider satisfaction questionnaire should be created to obtain measurable feedback on innovation implementation. Finally, a cost analysis and/or the number of missed workdays should be calculated pre- and postintervention to determine the financial gains/loss of implementing this algorithm.

 

Conclusion

The objective of this study was to introduce a screening algorithm for PCPs whose patients include service members presenting with leg pain with the intent of standardizing the diagnosis and care of tibia stress fractures in the military population. Tibia stress fractures have financial and human consequences in military and civilian sectors. Many clinicians in the primary care setting lack sufficient training to include the "competency, skills and confidence to manage musculoskeletal disorders in their daily practice" (Akesson, Dreinhofer, & Woolfe, 2003, p., 678). The LPS&RT was shown to be beneficial for diagnosing and treating tibia stress fractures at a military treatment facility. With access to the entire population of interest, implementation of this algorithm increased the diagnosis of tibia stress fractures (p = .34 using a chi-square test with Yates' correction), making it clinically meaningful but not statistically significant. Such an increase in tibia stress fractures would be associated with a significant decrease in morbidity and financial costs. Complete bone health depends on mechanical, hormonal, nutritional, and genetic factors, but the guidance provided can be useful to other military treatment facilities and can ultimately become the standard of care for military and civilian populations across the country.

 

References

 

Akesson K., Dreinhofer K. E., Woolf A. D. (2003). Improved education in musculoskeletal conditions is necessary for all doctors. Bulletin of the World Health Organization, 81(9), 677-683. [Context Link]

 

Beattie K. A., Bobba R., Bayoumi I., Chan D., Schabort I., Boulos P., Cividino A. (2008). Validation of the GALS musculoskeletal screening exam for use in primary care: A pilot study. BMC Musculoskeletal Disorders, 9(115), 1-8. doi:10.1186/1471-2474-9-115. [Context Link]

 

Beck T. J., Ruff C. B., Shaffer R. A., Betsinger K., Trone D. W., Brodine S. K. (2000). Stress fracture in military recruits: Gender differences in muscle and bone susceptibility factors. Bone, 27, 437-444. [Context Link]

 

Bennell K., Matheson G., Meeuwisse W., Brukner P. (1999). Risk factors for stress fractures. Sports Medicine, 28, 91-122. [Context Link]

 

Brand J. C., Brindle T., Nyland J., Caborn D. N., Johnson D. L. (1999). Does pulse low intensity ultrasound allow early return to normal activities when treating stress fractures? A review of one tarsal navicular and eight tibia stress fractures. The Iowa Orthopaedic Journal, 19, 26-30. [Context Link]

 

Brukner P., Bennell K. (1997). Stress fractures in female athletes: Diagnosis, management and rehabilitation. Sports Medicine, 24, 419-429. [Context Link]

 

Busse J. W., Bhandari M., Kulkarni A. V., Tunks E. (2002). The effect of low-intensity pulsed ultrasound therapy on time to fracture healing: A meta-analysis. Canadian Medical Association Journal, 166(4), 437-441. [Context Link]

 

Claes L., Willie B. (2007). The enhancement of bone regeneration by ultrasound. Progress in Biophysics and Molecular Biology, 93, 384-398. [Context Link]

 

Drinkwater B. L., Nilson K., Ott S., Chesnut C. H. III (1986). BMD after resumption of menses in amenorrheic athletes. JAMA, 256, 380-382. [Context Link]

 

Flook N. W. (2006). Primary care physicians and musculoskeletal disorders: The challenges increase. The Journal of Rheumatology, 33(1), 4-5. [Context Link]

 

Fountoulakis K. N., Vieta E., Sanchez-Moreno J., Kaprinis S. G., Goikolea J. M., Kaprinis G. S. (2005). Treatment guidelines for bipolar disorder: A critical review. Journal of Affect Disorders, 86(1), 1-10. [Context Link]

 

Gaeta M., Minutoli F., Scribano E., Ascenti G., Vinci S., Bruschetta D., Magaudda L., Blandino A. (2005). CT and MR imaging findings in athletes with early tibial stress injuries: comparison with bone scintigraphy findings and emphasis on cortical abnormalities Radiology, 235(2), 553-561. doi:10.1148/radiol.2352040406 [Context Link]

 

Gebauer D., Mayr E., Orthner E., Ryaby J. P. (2005). Low-intensity pulsed ultrasound: Effects on nonunions. Ultrasound Medicine Biology; 31, 1391-1402. [Context Link]

 

Grove J., Robbins C. (n.d.). Nonossifying fibroma: A literature review and case study. Retrieved from http://www.kent.edu/cpm/academics/resources/upload/nonossifying-fibroma.pdf[Context Link]

 

Hod N., Levi Y., Fire G., Cohen I., Ayash D., Somekh M., Horne T. (2007). Scintigraphic characteristics of non-ossifying fibroma in military recruits undergoing bone scintigraphy for suspected stress fractures and lower limb pains. Nuclear Medicine Communications, 28(1), 25-33. [Context Link]

 

Jones B. H., Bovee M. W., Harris J. M. III, Cowan D. N. (1993). Intrinsic risk factors for exercise-related injuries among male and female Army trainees. American Journal of Sports Medicine, 21, 705-710. [Context Link]

 

Jones B. H., Thacker S. B., Gitchrist J., Kimsey C. D., Sosin D. M. (2002). Prevention of lower extremity stress fractures in athletes and soldiers: A systematic review. Epidemiology Reviews, 24(2), 228-247. [Context Link]

 

Lappe J., Cullen D., Haynatzki G., Recker R., Ahlf R., Thompson K. (2008). Calcium and vitamin D supplementation decreases incidences of stress fractures in female Navy recruits. Journal of Bone and Mineral Research, 23(5), 741-749. [Context Link]

 

Martin R. (1991). Determinants of the mechanical properties of bones. Journal of Biomechanics, 24(Suppl. 1), 79-88. [Context Link]

 

Mistler L. A., Mellman T. A., Drake R. E. (2009). A pilot study of an algorithm to reduce antipsychotic polypharmacy. Quality and Safety in Health Care, 18(1), 55-58. [Context Link]

 

Nattiv A., Armsey T. D. (1997). Stress injury to bone in the female athlete. Clinical Sports Medicine, 16, 197-224. [Context Link]

 

Nindl B. C, Williams T. J., Deuster P. A., Butler N. L., Jones B. H. (2013, October-December). Strategies for optimizing military physical readiness and preventing musculoskeletal injuries in the 21st century. The United States Army Medical Department Journal. Retrieved from http://www.cs.amedd.army.mil/amedd_journal.aspx[Context Link]

 

Orthopaedic Institute for Children. (n.d.). Non-ossifying fibroma. Retrieved from http://www.orthohospital.org/sites/default/files/non-ossifying%20fibromas%20OH.p[Context Link]

 

Patel D. S., Roth M., Kapil N. (2011). Stress fractures: Diagnosis, treatment, and prevention. American Family Physician, 83(1), 39-46.

 

Pepper M., Akuthota V., McCarty E. C. (2006). The pathophysiology of stress fractures. Clinics in Sports Medicine, 25, 1-16. [Context Link]

 

Philipson M. R., Parker P. J. (2009). Stress fractures. Orthopaedics and Trauma, 23(2), 137-143. [Context Link]

 

Power J. D., Perruccio A. V., DesMeules M., Lagace C., Badley E. M. (2006). Ambulatory physician care for musculoskeletal disorders in Canada. The Journal of Rheumatology, 33(1), 133-139. [Context Link]

 

Rigotti N. A., Neer R. M., Skates S. J., Herzog D. B., Nussbaum S. R. (1991). The clinical course of osteoporosis in anorexia nervosa. A longitudinal study of cortical bone mass. JAMA, 265, 1133-1138. [Context Link]

 

Rosenthal M. D., McMillian D. J. (2006). Comprehensive evaluation and management of stress fractures in military trainees. In DeKoning B. L. (Ed.), Recruit medicine (pp. 175-202). San Diego, CA: Government Printing Office. Retrieved from http://www.bordeninstitute.army.mil/published_volumes/recruit_medicine/RM-ch11.p[Context Link]

 

Ruscio B. A., Jones B. H., Bullock S. H., Burnham B. R., Canham-Chervak M., Rennix C. P., Smith J. W. (2010). A process to identify military injury prevention priorities based on injury type and limited duty days. American Journal of Preventive Medicine, 38(1S), S19-S33. [Context Link]

 

Rutten S., Nolte P. A., Guit G. L., Bouman D. E., Albers G. H. (2007). Use of low-intensity pulsed ultrasound for posttraumatic nonunions of the tibia: A review of patients treated in the Netherlands. Journal of Trauma, 62(4), 902-908. [Context Link]

 

Sanderline B. W., Raspa R. F. (2003). Common stress fractures. American Family Physician, 68, 1527-1532. [Context Link]

 

Schofer M.D., Block J.E., Aigner J., Schmelz A. (2010). Improved healing response in delayed unions of the tibia with low-intensity pulsed ultrasound: result of a randomized sham-controlled trial. Biomedical Central Musculoskeletal Disorders, 11, 229-235. [Context Link]

 

U.S. Army Medical Department Army Medicine. (2008). Screening and referral tools. Retrieved from http://www.armymedicine.army.mil/r2d/20080813-prrnr-screeningtools.html[Context Link]

 

U.S. Army Medical Department Office of Quality Management. (2008). Screening and referral tools: Traumatic and acute leg pain. Retrieved from https://www.qmo.amedd.army.mil/srts/WebAcuteLeg.pdf[Context Link]

 

Wheeler P., Batt M. E. (2005). Do non-steroidal anti-inflammatory drugs adversely affect stress fracture healing? A short review. British Journal of Sports Medicine, 39(2), 65-69. [Context Link]

 

Yadav Y. K., Salgotra K. R., Banerjee A. (2008). Role of ultrasound therapy in the healing of tibia stress fractures. Medical Journal Armed Forces India, 64(3), 234-236. [Context Link]

 

For more than 50 additional continuing nursing education activities on orthopaedic topics and 34 activities on quality improvement topics, go to http://nursingcenter.com/ce.