Patient Demographic and Surgical Factors that Affect Completion of Patient-Reported Outcomes 90 Days and 1 Year After Spine Surgery: Analysis from the Michigan Spine Surgery Improvement Collaborative (MSSIC)

Young or Old Age and Non-White Race Are Associated With Poor Patient-Reported Outcome Measure Response Compliance After Orthopaedic Surgery

Purpose

To investigate orthopaedic patient compliance with patient-reported outcome measures (PROMs) and identify factors that improve response rates.

Methods

Our search strategy comprised a combination of key words and database-specific subject headings for the concepts of orthopaedic surgical procedures, compliance, and PROMs from several research databases from inception to October 11, 2022. Duplicates were removed. A total of 97 studies were included. A table was created for the remaining articles to be appraised and analyzed. The collected data included study characteristics, follow-up/compliance rate, factors that increase/decrease compliance, and type of PROM. Follow-up/compliance rate was determined to be any reported response rate. The range and average used for analysis was based on the highest or lowest number reported in the specific article.

Results

The range of compliance reported was 11.3% to 100%. The overall response rate was 68.6%. The average baseline (preoperative/previsit) response rate was 76.6%. Most studies (77%) had greater than 50% compliance. Intervention/reminder of any type (most commonly phone call or mail) resulted in improved compliance from 44.6% to 70.6%. Young and elderly non-White male patients had the lowest compliance rate. When directly compared, phone call (71.5%) resulted in a greater compliance rate than electronic-based (53.2%) or paper-based (57.6%) surveys.

Conclusions

The response rates for PROMs vary across the orthopaedic literature. Patient-specific factors, such as age (young or old) and race (non-White), may contribute to poor PROM response rate. Reminders and interventions significantly improve PROM response rates.

Clinical Relevance

PROMs are important tools in many aspects of medicine. The data generated from these tools not only provide information about individual patient outcomes but also make hypothesis-driven comparisons possible. Understanding the factors that affect patient compliance with PROMs is vital to our accurate understanding of patient outcomes and the overall advancement of medical care.

Online Patient-Reported Outcome Measure Engagement Is Dependent on Demographics and Locality: Findings From an Observational Cohort

OBJECTIVE

Online patient-reported outcome measures (PROMs) enable remote collection of perceptions of health status, function, and well-being. We aimed to explore patterns of PROM completion in patients with early inflammatory arthritis (EIA) recruited to the National Early Inflammatory Arthritis Audit (NEIAA).

METHODS

NEIAA is an observational cohort study design; we included adults from this cohort with a new diagnosis of EIA from May 2018 to March 2020. The primary outcome was PROM completion at baseline, 3 months, and 12 months. Mixed effects logistic regression and spatial regression models were used to identify associations between demographics (age, gender, ethnicity, deprivation, smoking, and comorbidity), clinical commissioning groups, and PROM completion.

RESULTS

Eleven thousand nine hundred eighty-six patients with EIA were included, of whom 5331 (44.5%) completed at least 1 PROM. Patients from ethnic minority backgrounds were less likely to return a PROM (adjusted odds ratio [aOR] 0.57, 95% CI 0.48-0.66). Greater deprivation (aOR 0.73, 95% CI 0.64-0.83), male gender (aOR 0.86, 95% CI 0.78-0.94), higher comorbidity burden (aOR 0.95, 95% CI 0.91-0.99), and current smoker status (aOR 0.73, 95% CI 0.64-0.82) also reduced odds of PROM completion. Spatial analysis identified 2 regions with high (North of England) and low (Southeast of England) PROM completion.

CONCLUSION

We define key patient characteristics (including ethnicity) that influence PROM engagement using a national clinical audit. We observed an association between locality and PROM completion, with varying response rates across regions of England. Completion rates could benefit from targeted education for these groups.

Response rates in clinical quality registries and databases that collect patient reported outcome measures: a scoping review

BACKGROUND

Patient Reported Outcome Measures (PROMs) are being increasingly introduced in clinical registries, providing a personal perspective on the expectations and impact of treatment. The aim of this study was to describe response rates (RR) to PROMs in clinical registries and databases and to examine the trends over time, and how they change with the registry type, region and disease or condition captured.

METHODS

We conducted a scoping literature review of MEDLINE and EMBASE databases, in addition to Google Scholar and grey literature. All English studies on clinical registries capturing PROMs at one or more time points were included. Follow up time points were defined as follows: baseline (if available), < 1 year, 1 to < 2 years, 2 to < 5 years, 5 to < 10 years and 10 + years. Registries were grouped according to regions of the world and health conditions. Subgroup analyses were conducted to identify trends in RRs over time. These included calculating average RRs, standard deviation and change in RRs according to total follow up time.

RESULTS

The search strategy yielded 1,767 publications. Combined with 20 reports and four websites, a total of 141 sources were used in the data extraction and analysis process. Following the data extraction, 121 registries capturing PROMs were identified. The overall average RR at baseline started at 71% and decreased to 56% at 10 + year at follow up. The highest average baseline RR of 99% was observed in Asian registries and in registries capturing data on chronic conditions (85%). Overall, the average RR declined as follow up time increased.

CONCLUSION

A large variation and downward trend in PROMs RRs was observed in most of the registries identified in our review. Formal recommendations are required for consistent collection, follow up and reporting of PROMs data in a registry setting to improve patient care and clinical practice. Further research studies are needed to determine acceptable RRs for PROMs captured in clinical registries.

The association of patient education level with outcomes after elective lumbar surgery: a Michigan Spine Surgery Improvement Collaborative study

OBJECTIVE

Socioeconomic factors have been shown to impact a host of healthcare-related outcomes. Level of education is a marker of socioeconomic status. This study aimed to investigate the relationship between patient education level and outcomes after elective lumbar surgery and to characterize any education-related disparities.

METHODS

The Michigan Spine Surgery Improvement Collaborative registry was queried for all lumbar spine operations. Primary outcomes included patient satisfaction determined by the North American Spine Society patient satisfaction index, and reaching the minimum clinically important difference of Patient-Reported Outcomes Measurement Information System Physical Function score and return to work up to 2 years after surgery. Multivariate Poisson generalized estimating equation models reported adjusted risk ratios.

RESULTS

A total of 26,229 lumbar spine patients had data available for inclusion in this study. On multivariate generalized estimating equation analysis all comparisons were done versus the high school (HS)/general equivalency development (GED)-level cohort. For North American Spine Society satisfaction scores after surgery the authors observed the following: at 90 days the likelihood of satisfaction significantly decreased by 11% (p < 0.001) among < HS, but increased by 1% (p = 0.52) among college-educated and 3% (p = 0.011) among postcollege-educated cohorts compared to the HS/GED cohort; at 1 year there was a decrease of 9% (p = 0.02) among < HS and increases of 3% (p = 0.02) among college-educated and 9% (p < 0.001) among postcollege-educated patients; and at 2 years, there was an increase of 5% (p = 0.001) among postcollege-educated patients compared to the < HS group. The likelihood of reaching a minimum clinically important difference of Patient-Reported Outcomes Measurement Information System Physical Function score at 90 days increased by 5% (p = 0.005) among college-educated and 9% (p < 0.001) among postcollege-educated cohorts; at 1 year, all comparison cohorts demonstrated significance, with a decrease of 12% (p = 0.007) among < HS, but an increase by 6% (p < 0.001) among college-educated patients and 14% (p < 0.001) among postcollege-educated compared to the HS/GED cohort; at 2 years, there was a significant decrease by 19% (p = 0.003) among the < HS cohort, an increase by 8% (p = 0.001) among the college-educated group, and an increase by 16% (p < 0.001) among the postcollege-educated group. For return to work, a significant increase was demonstrated at 90 days and 1 year when comparing the HS or less group with college or postcollege cohorts.

CONCLUSIONS

This study demonstrated negative associations on all primary outcomes with lower levels of education. This finding suggests a potential disparity linked to education in elective spine surgery.

Electronic health record-integrated approach for collection of patient-reported outcome measures: a retrospective evaluation

Background

The integration of Patient Reported Outcome Measures (PROMs) into clinical care presents many challenges for health systems. PROMs provide quantitative data regarding patient-reported health status. However, the most effective model for collecting PROMs has not been established. Therefore the purpose of this study is to report the development and preliminary evaluation of the standardized collection of PROMs within a department of orthopedic surgery at a large academic health center.

Methods

We utilized the Users’ Guide to Integrating Patient-Reported Outcomes in Electronic Health Records by Gensheimer et al., 2018 as a framework to describe the development of PROMs collection initiative. We framed our initiative by operationalizing the three aspects of PROM collection development: Planning, Selection, and Engagement. Next, we performed a preliminary evaluation of our initiative by assessing the response rate of patients completing PROMs (no. of PROMs completed/no. of PROMs administered) across the entire department (18 clinics), ambulatory clinics only (14 clinics), and hospital-based clinics only (4 clinics). Lastly, we reported on the mean response rates for the top 5 and bottom 5 orthopaedic providers to describe the variability across providers.

Results

We described the development of a fully-integrated, population health based implementation strategy leveraging the existing resources of our local EHR to maximize clinical utility of PROMs and routine collection. We collected a large volume of PROMs over a 13 month period (n = 10,951) across 18 clinical sites, 7 clinical specialties and over 100 providers. The response rates varied across the department, ranging from 29 to 42%, depending on active status for the portal to the electronic health record (MyChart). The highest single provider mean response rate was 52%, and the lowest provider rate was 13%. Rates were similar between hospital-based (26%) and ambulatory clinics (29%).

Conclusions

We found that our standardized PROMs collection initiative, informed by Gensheimer et al., achieved scope and scale, but faced challenges in achieving a high response rate commensurate with existing literature. However, most studies reported a targeted recruitment strategy within a narrow clinical population. Further research is needed to elucidate the trade-off between scalability and response rates in PROM collection initiatives.

Predictors of patient dissatisfaction at 1 and 2 years after lumbar surgery

OBJECTIVE

As compensation transitions from a fee-for-service to pay-for-performance healthcare model, providers must prioritize patient-centered experiences. Here, the authors' primary aim was to identify predictors of patient dissatisfaction at 1 and 2 years after lumbar surgery.

METHODS

The Michigan Spine Surgery Improvement Collaborative (MSSIC) was queried for all lumbar operations at the 1- and 2-year follow-ups. Predictors of patients' postoperative contentment were identified per the North American Spine Surgery (NASS) Patient Satisfaction Index, wherein satisfied patients were assigned a score of 1 ("the treatment met my expectations") or 2 ("I did not improve as much as I had hoped, but I would undergo the same treatment for the same outcome") and unsatisfied patients were assigned a score of 3 ("I did not improve as much as I had hoped, and I would not undergo the same treatment for the same outcome") or 4 ("I am the same or worse than before treatment"). Multivariable Poisson generalized estimating equation models were used to report adjusted risk ratios (RRadj).

RESULTS

Among 5390 patients with a 1-year follow-up, 22% reported dissatisfaction postoperatively. Dissatisfaction was predicted by higher body mass index (RRadj =1.07, p < 0.001), African American race compared to white (RRadj = 1.51, p < 0.001), education level less than high school graduation compared to a high school diploma or equivalent (RRadj = 1.25, p = 0.008), smoking (RRadj = 1.34, p < 0.001), daily preoperative opioid use > 6 months (RRadj = 1.22, p < 0.001), depression (RRadj = 1.31, p < 0.001), symptom duration > 1 year (RRadj = 1.32, p < 0.001), previous spine surgery (RRadj = 1.32, p < 0.001), and higher baseline numeric rating scale (NRS)-back pain score (RRadj = 1.04, p = 0.002). Conversely, an education level higher than high school graduation, independent ambulation (RRadj = 0.90, p = 0.039), higher baseline NRS-leg pain score (RRadj = 0.97, p = 0.013), and fusion surgery (RRadj = 0.88, p = 0.014) decreased dissatisfaction.Among 2776 patients with a 2-year follow-up, 22% reported dissatisfaction postoperatively. Dissatisfaction was predicted by a non-white race, current smoking (RRadj = 1.26, p = 0.004), depression (RRadj = 1.34, p < 0.001), symptom duration > 1 year (RRadj = 1.47, p < 0.001), previous spine surgery (RRadj = 1.28, p < 0.001), and higher baseline NRS-back pain score (RRadj = 1.06, p = 0.003). Conversely, at least some college education (RRadj = 0.87, p = 0.035) decreased the risk of dissatisfaction.

CONCLUSIONS

Both comorbid conditions and socioeconomic circumstances must be considered in counseling patients on postoperative expectations. After race, symptom duration was the strongest predictor of dissatisfaction; thus, patient-centered measures must be prioritized. These findings should serve as a tool for surgeons to identify at-risk populations that may need more attention regarding effective communication and additional preoperative counseling to address potential barriers unique to their situation.