1 Introduction

Patient reported outcome measures (PROMs) are defined by the Federal Drug Administration as “any report of the status of a patient's health condition that comes directly from the patient, without interpretation of the patient's response by a clinician or anyone else.”¹ PROMs have traditionally been used as standardized research tools.^2,3 PROMs are becoming increasingly utilized for quality and patient safety purposes, including addition to CMS value-based payments for hip and knee replacements. These outcomes are subjective, but they avoid observer or clinician bias as they are a direct report from the patient on their own personal health status. PROMs have become highly utilized among orthopedics and its subspecialties, particularly within the field of joint replacement surgery. They are being recognized as an additional measure of evaluation of surgical success that takes patient satisfaction into account.^4,5

In addition to their value as a comparative tool, PROMs may aid clinical care as well. PROMs may increase the chance of identifying postoperative complications earlier.⁶ Identifying complications early may allow surgeons to modify the course of care thus minimizing the progression to more serious adverse outcomes (e.g. revisions, infection). Additionally, collecting this information early on may allow surgeons to optimize patient outcomes by providing more informed pain control and evaluating adherence and progress of physical therapy. This could lead to increased functional outcomes and the ability to minimize narcotic utilization.

PROMs may also facilitate patient provider communication. Survey results allow the physician to be more aware of factors and symptoms that may not have been discussed during the encounter which allows for more comprehensive view of the patient to inform treatment.^2,7 Additionally, PROMs provide the physician with a baseline for symptoms and functionality as well as the ability to systematically track progress over time. These surveys could provide a record to track the gradual benefits and improvements that patients may not have been able to retrospectively appreciate on their own.² Despite these benefits, there is a lack of education and usage of PROMs in clinical practice.^8,9 This may be because many physicians only view PROMs as a reporting tool and may not understand how to interpret or best integrate PROMs into their practice.³

Though factors influencing patient compliance with medical regimens as well as those influencing the physician-patient relationship have been studied, there has been limited assessment of the factors that impact compliance with PROMs. Therefore, the objective of this study is to analyze which patient demographics directly influence completion of PROM surveys preoperatively and postoperatively.

2 Methods

3 Results

3.3

3.3 Outcome data

3.3.1

3.3.1 Completion of baseline PROMs

Univariate analysis showed that patients with a lower ASA score (1 or 2), a BMI <30, hip arthroplasty (reference knee) were more likely to have a baseline HOOS/KOOS completed. Patients with a mental health diagnosis, Parkinson's, diabetes, and those ≥75 years old (reference <60) were less likely to complete a preoperative HOOS/KOOS (Table 1). Alternatively, when compared to people under the age of 60, those between the age of 60–75 were more likely to complete a baseline survey (p < 0.0001). Other variables including sex, opioid abuse, ADHD, legal blindness, and heart failure did not affect compliance for filling out a baseline HOOS/KOOS.

After adjusting for age, sex, ASA score, BMI, hip or TKA, mental health diagnosis, Diabetes, and Parkinson's disease, the multivariable analysis showed age above 60 years increased preoperative PROMs compliance. TKA and an ASA score of 3 or 4 decreased the likelihood of filling out a baseline preoperative PROMs survey (Table 2).

Table 2 Factors Affecting Baseline Compliance. Multivariable analysis adjusted for age, sex, ASA score, BMI, THA vs TKA, mental health diagnosis, diabetes, and Parkinson's disease.

Variable	OR	95 % CI	P-Value
Age: 60–74 vs < 60	1.49	(1.37, 1.62)	<0.0001
Age: ≥75 vs < 60	1.12	(1.02, 1.24)	0.024
Female vs. Male	0.98	(0.92, 1.05)	0.587
ASA score: 3 or 4 vs 1 or 2	0.88	(0.82, 0.95)	0.0006
BMI: ≥30 vs < 30	0.97	(0.91, 1.04)	0.413
TKA vs THA	0.92	(0.86, 0.98)	0.006
Mental Health Diagnosis	0.93	(0.85, 1.02)	0.144
Diabetes	0.95	(0.86, 1.05)	0.317
Parkinson's Disease	0.55	(0.31, 1.00)	0.051

3.3.2

3.3.2 Completion of post-operative PROMs

Continued compliance in filling out follow-up surveys varied between each follow-up point. Univariate analysis showed that at 3 month and 6 month follow up, older age, a BMI <30, females and a 0 day LOS increased survey compliance. The 1-year follow up univariate analysis showed older age, BMI <30, 0 day LOS and THA to increase survey compliance. The 2-year follow up univariate analysis showed that patients aged 60–74, an ASA score of 1 or 2, BMI <30, females, and THA increased compliance.

3.3.3

3.3.3 Main results

After adjusting for age, sex, THA vs TKA, ASA score, LOS, and BMI- increased age, female sex, and outpatient status were the only statistically significant variables that increased likelihood of continued completion at all follow up points and a BMI ≥30 was associated with decreased compliance at all follow up points (Fig. 1; Table 3). Additionally, patients with an ASA of 1 or 2, a LOS >0 days, males, and those with a BMI ≥30 were less likely to complete a 3-month and 6-month survey. Patients who were female, had outpatient surgery (i.e. LOS <1 day), had THA, or had an ASA Score of 3 or 4 were more likely to complete a PROMs survey at 1 year. Patients who were female, or had THA were statistically more likely to complete a survey at 2 years (Fig. 1; Table 3).

Close

Fig. 1 Predictors of Ongoing Engagement with PROM Surveys. Variables in green indicate increased likelihood of compliance. Variables in red indicate decreased likelihood of compliance. Non-colored variables did not affect follow-up compliance. LOS: Length of stay. ASA: American Society of Anesthesiology. BMI: Body Mass Index. Multivariable regression is demonstrated in Table 3.

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Table 3 Multivariate regression of Predictors of Ongoing Engagement with PROMs Surveys.

Variable	3 Month		6 Month		1 Year		2 Year
	OR	95 % CI	OR	95 % CI	OR	95 % CI	OR	95 % CI
Age 60–74 vs < 60	1.61	(1.40, 1.84)	1.71	(1.48, 1.96)	1.75	(1.56, 1.96)	1.27	(1.12, 1.44)
Age ≥ 75 vs < 60	1.30	(1.11, 1.52)	1.34	(1.14, 1.58)	1.44	(1.25, 1.65)	1.08	(0.93, 1.25)
Male vs Female	0.84	(0.77, 0.93)	0.83	(0.75, 0.91)	0.88	(0.81, 0.95)	0.86	(0.79, 0.94)
ASA score: 3 or 4 vs 1 or 2	1.29	(1.16, 1.44)	1.27	(1.14, 1.42)	1.10	(1.00, 1.21)	0.93	(0.84, 1.03)
BMI ≥ 30 vs < 30	0.36	(0.32, 0.40)	0.35	(0.31, 0.40)	0.88	(0.81, 0.96)	0.85	(0.78, 0.93)
TKA vs THA	1.02	(0.93, 1.13)	1.01	(0.92, 1.11)	0.81	(0.75, 0.88)	0.78	(0.71, 0.85)
LOS: 1–2 days vs0 days	0.30	(0.27, 0.33)	0.31	(0.28, 0.35)	0.30	(0.27, 0.33)	0.84	(0.61, 1.15)
LOS: > 3 days vs 0 days	0.23	(0.20, 0.27)	0.25	(0.22, 0.30)	0.16	(0.14, 0.19)	0.61	(0.44, 0.85)

4 Discussion

As PROMs are increasingly embedded into orthopaedic research, value-based payment structures, and quality, it is important to better understand the factors that influence completion of PROMs and as a result may result in biases in analyses. In addition, incomplete follow-up data and missing demographic data has been noted across the literature and has been shown to adversely affect research. The possibility of comparing bias further demonstrates the importance of improving PROMs compliance.^10–15

We found the overall baseline PROMs compliance to be 34.85 %. In general, patients with characteristics indicative of poorer health were less likely to fill out the baseline PROMs. These factors included older age, THA, and having a higher ASA score. (Table 2). Of note, for postoperative PROMs, our findings were mixed. For example, patients with an ASA of 3 or 4, were more likely to fill out PROMs at 3 and 6 months and 1 year compared to those with an ASA at 1 or 2. However, at 2 years, there was no significant difference based on ASA score. (Table 3). Patients with a BMI ≥30 were less likely than those with a BMI <30 to fill out PROMs surveys at all time points. Finally, with respect to LOS, outpatients were more likely to fill out PROMs at all time points as well. This may be representative of an artifact of our system with respect to sending reminders to patients. With respect to time, completion rates generally declined and then increased, with the lowest compliance rate at 6 months.

Younger patients were less likely to fill out PROMs at all time points. It was initially hypothesized that patients over the age of 65 may be less likely to complete PROMs due to technology disconnect or difficulty understanding the survey.^16–18 Additionally prior studies in total joint arthroplasty patients have demonstrated lower completion rates with older age.¹⁶ On contrary, we found that patients younger than 60 were less likely to complete follow-up PROMs at across all postoperative timepoints. This may be because of their better recovery and therefore shift of life focus. This may also be because older patients have been found to have increased health literacy relative to younger patients which may increase their willingness and ability to complete PROMs.¹⁹

However, this trend of increased compliance with age is not uniform in the literature as a study by Sutton et al. saw that patients on Medicare had lower rates of follow-up compliance compared to the rest of their cohort, but higher rates of preoperative compliance. These Medicare patients had an average age of 72.9 years where the rest of their cohort had an average age of 57.0 years.²⁰The inconsistency of the effect of age across these studies indicates that another factor linked to age may be at play. Additionally, studies have demonstrated that older patients are able to use technology without much difficulty.^21,22 Regardless, given the findings in this study, it may be beneficial to provide additional education to patients under the age of 60 about the importance of PROMs and long-term follow up.

Patients with a mental health diagnosis were also significantly less likely to fill out baseline PROMs. Given the diversity of conditions and symptoms under the umbrella of mental health disorders, it is difficult to surmise what the driving force of this result is. For example, it is reasonable to suggest that mental health diagnosis may affect motivation to complete optional tasks (i.e. PROMs). Further analysis within this cohort may be indicated in future studies.²³

In our study, patients who underwent TKA had a lower compliance rate relative to THA. This finding is consistent with a similar study conducted by Patel et al., which also looked to identify specific patient or provider characteristics that relate to low reporting of patient-reported outcomes using the California Joint Replacement Registry.²⁴ This study identified multiple patient demographic factors that correlated with low completion rates of these questionnaires including age, race, ASA score, preoperative comorbidities, and type of surgery (TKA vs THA).²⁴ The study also observed a similar decline to ours in response rate at subsequent time points.

Survey delivery method is another important consideration for increasing PROMs compliance. A study investigating factors that affected compliance of PROMs after spine surgery using the Michigan Spine Surgery Improvement Collaborative found that age, race, employment status, and zip-code based income affected PROMs compliance rates.²⁵ However, this study had preoperative compliance rates of over 70 %. This may be due to the fact that in addition to a web-based survey, this group also sent PROMs via mail. One study found that sending reminder emails increased compliance rates, but this was limited by access to email as well as the technological knowledge to be able to navigate these websites on their own.²⁶

An additional barrier to compliance is the resources needed to assist patients in filling the surveys out. Some studies noted that lack of dedicated personnel for these efforts, and therefore lack of ownership of PROMs initiatives lead to decreased perceptions of importance and prioritization.^2,3 Funds for third-party survey platforms are also barriers to PROMs distribution and increasing compliance rates. Therefore, it is important for hospitals and payers to recognize the benefits and costs of PROMs registries to support the investment into resources to implement more robust patient-feedback programs.

Our data and similar studies show there are many patient and hospital factors contributing to PROMs compliance.^9,24,25,27 Compliance is likely driven by a complex interplay between patient motivation, and, accessibility. This complexity speaks to the inconsistency of trends observed in the literature regarding compliance's correlation with various demographic factors. In fact, some studies have not been able to identify correlations between compliance and demographic factors³³. However, it is important to identify these trends within the population being surveyed, in order to adjust and facilitate the continued delivery of PROMs for any population of interest.

5 Conclusions

This study captures a unique cohort of patients and examines the factors that contribute to compliance in filling out PROMs. The barriers to increased compliance are multifactorial and may include patient demographics including age, comorbidities, and race. These data will help to inform methods for improving PROM completion rates as well as understanding and addressing biases in sample collection.

CRediT authorship contribution statement

Samantha J. Simon: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization. Andrew R. Grant: Conceptualization, Methodology, Validation, Writing – review & editing, Visualization. Ruijia Niu: Conceptualization, Methodology, Validation, Writing – review & editing. Sade Olatunbosun: Conceptualization, Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – review & editing. Carl T. Talmo: Conceptualization, Validation, Writing – review & editing. Brian L. Hollenbeck: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing – review & editing, Visualization, Supervision, Project administration, All authors have read and approved the final submitted manuscript.

Patient's consent

The work described has been carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans. All procedures were performed in compliance with relevant laws and institutional guidelines. Informed consent was obtained for all patients.

Ethics statement

The work described has been carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans. All procedures were performed in compliance with relevant laws and institutional guidelines. This work was deemed to be exempt from IRB Approval by the New England Baptist Hospital IRB.

Funding

There is no external funding source for this study.