Does Identifying Provider Expectations Improve Adoption of Patient Reported Outcomes?

Introduction/Purpose: New instruments like the Patient Reported Outcome Information System (PROMIS) minimize the burden to patients and providers addressing significant barriers to adoption. Despite these advances provider adoption remains lackluster. Models of technology adoption suggest adoption is more likely to occur when PRO’s directly improve patient care (performance expectancy) and it’s easy to implement (effort expectancy). Problems with effort expectancy are dealt with by training and improving logistics (i.e. eHR presentation, alerts), where performance expectancy is addressed through research (i.e. validation of thresholds). The purposes of this study were to: 1) evaluate the proportion of orthopedic rehabilitation providers who use PRO’s and how they use them; And, 2) to determine if performance expectancy, effort expectancy or provider burnout are related to provider use

Can Patient Reported Outcomes Guide Therapy Needs in Foot and Ankle Patients?

Introduction/Purpose: The patient acceptable symptom state (PASS) is a validated question establishing if patients activity and symptoms are at a satisfactory low level for pain and function. Surprisingly, ~20% of foot and ankle patients at their initial visit present for care with an acceptable symptom state (i.e. PASS yes). These patients are important to identify to prevent over treatment and avoid excessive cost. It is also unclear what health domains (Pain Interference (PI), Physical Function (PF), or Depression (Dep)) influence a patients judgement of their PASS state (i.e. why they are seeking treatment). The purpose of this analysis is to document the prevalance of PASS state and determine the health domains that discriminate PASS patients and predict PASS state at the initiation of rehabilitation

Can Understanding Provider Expectations Improve Provider Adoption of Patient Reported Outcomes?

Introduction/Purpose: New instruments like the Patient Reported Outcome Information System (PROMIS) minimize the burden to patients and providers addressing significant barriers to adoption. Despite these advances provider adoption remains lackluster. Models of technology adoption suggest adoption is more likely to occur when PRO’s directly improve patient care (performance expectancy) and it’s easy to implement (effort expectancy). Problems with effort expectancy are dealt with by training and improving logistics (i.e. eHR presentation, alerts), where performance expectancy is addressed through research (i.e. validation of thresholds). The purposes of this study were to: 1) evaluate the proportion of orthopedic rehabilitation providers who use PRO’s and how they use them; And, 2) to determine if performance expectancy, effort expectancy or provider burnout are related to provider use

Strategies for Gait Retraining in a Collegiate Runner with Transfemoral Amputation: A Case Report

# Background More than fifty percent of people with limb amputations participate in sports or physical activity following amputation. Athletes with limb amputations may face additional challenges including phantom limb pain (PLP), psychological barriers, prosthetic complications, and gait abnormalities. Prevalence of PLP in the general amputee population is estimated to be as high as 85%. Despite the high prevalence of PLP, there is little research regarding the use of gait training as a treatment for PLP among both the general amputee population and athletes. # Case Description A 20-year old female collegiate track and field athlete presented with phantom knee pain brought on with running. The athlete demonstrated deficits in core and hip strength as well as decreased single leg stability bilaterally. Running gait analysis revealed circumduction with the prosthesis for limb advancement and increased vaulting with push off on the sound (uninvolved) limb. Gait retraining strategies were implemented to address video analysis findings and create a more efficient running gait and address phantom limb pain symptoms. # Outcomes Rehabilitation and gait retraining strategies were effective in improving several clinical and functional outcomes in this case. Significant improvements were noted in PLP, running gait mechanics, and the patient’s psychological and functional status as measured with a standardized outcome tool, the Patient-Reported Outcomes Measurement Information System^®^ (PROMIS^®^). # Discussion Running gait training following amputation could be a crucial component of rehabilitation for athletes in an attempt to lessen pain while running, especially in those experiencing phantom limb pain (PLP). Utilization of a multidisciplinary team in the gait retraining process is recommended. There is a need for further research to determine the effects of running gait retraining for management of PLP in athletes with amputation. # Level of Evidence

Can Understanding Provider Expectations Improve Provider Adoption of Patient Reported Outcomes?

Category: Other Introduction/Purpose: New instruments like the Patient Reported Outcome Information System (PROMIS) minimize the burden to patients and providers addressing significant barriers to adoption. Despite these advances provider adoption remains lackluster. Models of technology adoption suggest adoption is more likely to occur when PRO’s directly improve patient care (performance expectancy) and it’s easy to implement (effort expectancy). Problems with effort expectancy are dealt with by training and improving logistics (i.e. eHR presentation, alerts), where performance expectancy is addressed through research (i.e. validation of thresholds). The purposes of this study were to: 1) evaluate the proportion of orthopedic rehabilitation providers who use PRO’s and how they use them; And, 2) to determine if performance expectancy, effort expectancy or provider burnout are related to provider use. Methods: Fifty rehabilitation providers (physical therapist and athletic trainers) anonymously completed the electronic PRO Adoption Survey. Participants were 23.4±5.8 years old and 54% were female. The purpose of the PRO Adoption Survey is to track adoption across health systems. The first section of the PRO Adoption survey includes whether providers use PRO’s and asks them to detail how they use them (Table 1). A factor analysis supported the use of sets of questions to determine performance expectancy and effort expectancy (Table 1). Performance expectancy captures the health benefits the provider expects to experience. Effort expectancy captures the provider’s expectations of how easy it will be to implement PRO tools. The validated Maslach-2 burnout scale (BO) was included as another a factor that may influence adoption. Proportions and chi square tests were used to describe provider use of PRO’s and its relationship with performance expectancy, effort expectancy, and burnout. Results: The profile of PRO use by rehabilitation professionals is that a majority know about PRO’s (86%) however only 34% utilize PRO’s during clinic visits (Table 1). The most common PRO used is PROMIS (83%), followed by generic measures (41%) and disease specific (29%) measures. Type of use indicated the most common use was to make clinical decisions (71%) with relatively few using it for research (12%). Interestingly, 47% of PRO users review data with patients. The average responses for performance expectancy were 3.9 ± 0.1. The average responses for effort expectancy were 3.2 ± 0.2 or “neutral”. The average BO score was 4.6 ± 1.0. Chi square analysis suggested performance expectancy, effort expectancy, and burn out were not significantly associated with provider use. Conclusion: PROMIS scales are currently available in the electronic medical record(eMR) leading to high use (86%) by current PRO users (34%). High performance expectancy scores (~4/5) and low BO suggest providers can be motivated to use PRO’s. However, providers are neutral (~3/5) on how easy PRO’s would be to implement. Also, lower scores for performance expectancy associated with “aggregate” PRO data (only 54% marked “Agree” for this item) suggests training on specific uses of aggregate data are also indicated. These data detail the real issues providers need addressed to effectively capitalize on the benefits of PRO’s to improve clinical care