The impact of a text messaging service on orthopaedic clinic Did Not Attend rates

Factors Influencing Compliance to Follow-up Visits in Orthopaedic Surgery

BACKGROUND

Orthopaedic procedures require postoperative follow-up to maximize recovery. Missed appointments and noncompliance can result in complications and increased healthcare costs. This study investigates the relationship between patient postoperative visit attendance and the distance traveled to receive care.

MATERIALS AND METHODS

A retrospective review of all surgeries performed by a single orthopaedic surgeon in 2019 at level 1 trauma center in a midsized city serving a largely rural population was completed. We excluded patients who underwent another subsequent procedure. Distance to care and time traveled were determined by the patient's address and the clinic address using Google Maps Application Programming Interface. Other variables that may affect attendance at follow-up visits were also collected. Univariate and multivariate logistic regression was done with purposeful selection.

RESULTS

We identified 518 patients of whom 32 (6%) did not attend their first scheduled follow-up appointment. An additional 47 (10%) did not attend their second follow-up. In total, 79 patients (15%) did not attend one of their appointments. Younger age, male sex, Black or African American race, self-pay, Medicaid insurance, accident insurance, and increased distance were individual predictors of missing an appointment. In the final multivariate logistic regression model, male sex (OR 1.74), Black or African American race (OR 2.78), self-pay (OR 3.12), Medicaid (OR 3.05), and traveling more than 70 miles to clinic (OR 2.02) markedly predicted missing an appointment, while workers' compensation (OR 0.23) predicted attendance.

DISCUSSION

Several nonmodifiable patient factors predict patient noncompliance in attending orthopaedic postoperative visits. When patients are considered at high risk of being lost to follow-up, there may be an opportunity to implement interventions to improve follow-up rate and patient outcomes, minimize patient costs, and maximize profitability for the hospital.

Follow-up non-attendance after long-bone fractures in a low-resource setting: a prospective study of predictors and interventions to increase attendance rates

BACKGROUND

While the majority of traumatic injuries occur in low- and middle-income countries, the published literature comes chiefly from high-income countries due to poor follow-up. Clinical and radiographic post-surgical trauma follow-up is essential to high-quality research and objective monitoring for healing and/or complications. This study aimed to identify the predictors of follow-up non-attendance in a low-resource setting and investigate the extent to which interventional efforts based on mobile phone technology (MPT) and home visits improved the follow-up rates for fractures treated with SIGN nails.

METHODS

This was a prospective study of 594 patients with long-bone fractures. Socio-demographic (e.g. age, gender, marital status, education level, etc.) and clinical (e.g. fracture type, concomitant injuries, comorbidity, etc.) data were collected on each patient. Before discharge, the importance of follow-up was explained to patients and their relations. They were encouraged to attend even if they felt well. Their residential addresses and telephone numbers were validated and securely stored. Patients who missed their appointments were contacted by phone. Those who failed to honour 2 or 3 rescheduled appointments were visited in their home. The patients were divided into those who returned for the primarily scheduled follow-up without prompting (volition group) and those who did not come (non-attenders). Univariate analyses and binary logistic regression were conducted to determine the significant predictors of non-attendance.

RESULTS

The proportion of patients in the volition group reduced from 96.1% at 6 weeks to 53.0% at 12 weeks and 39.2% at 6 months. However, interventional efforts increased these values to 98.5%, 92.5%, and 72.4% respectively. Walking unaided before the primarily scheduled 12-week appointment was the major reason for not attending the follow-up. Education, occupation, post-operative length of hospital stay (PLOS) and infection were significantly associated with non-attendance but younger age, long distances from the hospital, being separated or divorced, difficulty paying the in-patient care bill, closed fracture, having no (or a non-limb) concomitant injury, achieving painless weight bearing ≤ 6 weeks post-operatively and needing no additional surgery were independent predictors of non-attendance.

CONCLUSIONS

Our study sheds light on the predictors of follow-up non-attendance and demonstrates how interventional efforts improved attendance rates in a low-resource setting. In addition, efforts that better the socio-economic status of people such as more-encompassing health insurance coverage and greater work flexibility can improve the follow-up attendance rates.

Causes, impacts and possible mitigation of non-attendance of appointments within the National Health Service: a literature review

PURPOSE

Missed appointments within the National Health Service (NHS) are a drain on resources, associated with not only considerable time and cost implications, but also sub-optimal health outcomes. This literature review aims to explore non-attendance within the NHS in relation to causes, impacts and possible mitigation of negative effects of missed appointments.

DESIGN/METHODOLOGY/APPROACH

MEDLINE, CINAHL Plus and PubMed were searched with a date range of 2016-2021. Databases were searched for peer-reviewed articles published in English addressing non-attendance of adults within the NHS. Studies were excluded if they were theoretical papers, dissertations or research concerning patients aged under 18. A total of 21 articles met the inclusion criteria and were selected for analysis.

FINDINGS

The results indicate a significant association of non-attendance and poor health outcomes. Patients from a lower socioeconomic status, adults aged over 85 and those with multiple co-morbidities are more likely to miss appointments. The most commonly reported patient-centred reasons for failing to attend were forgetfulness, transportation difficulties, and family commitments. Practice-specific reasons were cited as inefficiencies of the appointment booking system, failure of traditional reminders and inconvenient timings. Interventions included text reminder services, the inclusion of costs within reminders and enhanced patient involvement with the booking process.

ORIGINALITY/VALUE

Non-attendance is complex, and to secure maximum attendance, targeted interventions are required by healthcare facilities to ensure patient needs are met. The adaption of scheduling systems and healthcare services can assist in reducing DNA rates.

Hello, can you hear me? Orthopaedic clinic telephone consultations in the COVID-19 era- a patient and clinician perspective

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has resulted in seismic changes in healthcare delivery. As a result of this, hospital footfall required to be reduced due to increased risk of transmission of infection. To ensure patients can safely access healthcare, we introduced orthopaedic clinic telephone consultations in our busy district general hospital.

AIM

To investigate patients' and clinicians' perspective of telephone consultations during COVID-19, and whether this method of consultation could be a viable option in the post- pandemic future.

METHODS

This is a single centre, prospective study conducted in a busy National Health Service district general hospital. In May 2020, 100 non- consecutive adult patients were contacted by independent investigators within 48 h of their orthopaedic clinic telephone consultation to complete a telephone satisfaction questionnaire. The questions assessed satisfaction regarding various aspects of the consultation including overall satisfaction and willingness to use this approach long term. Satisfaction and perspective of 25 clinicians conducting these telephone consultations was also assessed via an online survey tool.

RESULTS

93% of patients were overall satisfied with telephone consultations and 79% were willing to continue this method of consultation post- pandemic. Patients found telephone consultations to reduce personal cost and inconvenience associated with attending a hospital appointment. 72% of clinicians reported overall satisfaction with this service and 80% agreed that telephone consultations should be used in the future. The majority found it less laborious in time and administration in comparison to face to face consultations. Patients and clinicians expressed their desire for video consultations as a method of further improving their experience with remote consultations.

CONCLUSION

Our study has shown that telephone consultations are a safe and rapid method of adaptation to the COVID-19 pandemic, achieving the aim of reducing hospital footfall. This method of consultation has resulted in immense clinician and patient satisfaction. Our findings suggest that this tool has benefits in post pandemic healthcare delivery. It has also highlighted that telephone consultations can act as a steppingstone to the introduction of the more complex platform of video consulting.

Secondary Impact of Social Media via Text Message Screening for Type 2 Diabetes Risk in Kuwait: Survey Study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is an international problem of alarming epidemic proportions. T2DM can develop due to multiple factors, and it usually begins with prediabetes. Fortunately, this disease can be prevented by following a healthy lifestyle. However, many health care systems fail to properly educate the public on disease prevention and to offer support in embracing behavioral interventions to prevent diabetes. SMS messaging has been combined with cost-effective ways to reach out to the population at risk for medical comorbidities. To our knowledge, the use of nationwide SMS messaging in the Middle East as a screening tool to identify individuals who might be at risk of developing T2DM has not been reported in the literature.

OBJECTIVE

The primary aim of this study was to assess the feasibility of conducting a series of SMS messaging campaigns directed at random smartphone users in Kuwait for the detection and prevention of T2DM. It was predicted that 1% of those receiving the text message would find it relevant and participate in the study. The secondary aim of this study was to assess the incidence of participation of those who were forwarded the initial text message by family members and friends.

METHODS

In this study, 5 separate text message screening campaigns were launched inviting recipients to answer 6 questions to determine the risk of developing T2DM. If subjects agreed to participate, a link to the prediabetes screening test devised by the Centers for Disease Control and Prevention was automatically transmitted to their mobile devices. Those identified as high risk were invited to participate in a diabetes prevention program.

RESULTS

A total of 180,000 SMSs were sent to approximately 6% of the adult population in Kuwait. Of these, 0.14% (260/180,000) of the individuals who received the SMS agreed to participate, of whom 58.8% (153/260) completed the screening. Surprisingly, additional surveys were completed by 367 individuals who were invited via circulated SMS messages forwarded by family members and friends. Altogether, 23.3% (121/520) qualified and agreed to participate in a diabetes prevention program. The majority of those who chose to participate in the prevention program were overweight, aged 45-65 years, and reported being less physically active than those who chose not to participate (χ²₂=42.1, P<.001).

CONCLUSIONS

Although health care screening via text messaging was found to have limited effectiveness by itself, it exhibited increased reach through shared second-party social media messaging. Despite the fact a subpopulation at possible risk of developing T2DM could be reached via text messaging, most responders were informed about the screening campaign by family and friends. Future research should be designed to tap into the benefits of social media use in health risk campaigns.

Electronic Patient Portal Use in Orthopaedic Surgery Is Associated with Disparities, Improved Satisfaction, and Lower No-Show Rates

BACKGROUND

Electronic patient portal (EPP) use has been associated with a number of benefits in the internal medicine setting. Few studies have examined the disparities in and the benefits of EPP utilization among surgical patients. The purposes of this study were to examine factors associated with EPP use among patients undergoing an orthopaedic surgical procedure and to determine if EPP use is associated with improved outcomes or satisfaction after orthopaedic surgical procedures.

METHODS

We queried all patients undergoing an orthopaedic surgical procedure from May 2015 to December 2018 at 2 academic medical centers in an integrated hospital system. Patient demographic characteristics, operative characteristics, satisfaction scores, and patient-reported outcome measures (PROMs) were collected. Multivariable logistic regression was used to identify disparities in EPP use. Adjusted logistic and linear regressions were then used to assess the association between EPP use and the various outcome metrics while controlling for confounders identified in the previous analysis.

RESULTS

Numerous demographic factors were independently associated with EPP use among patients undergoing an orthopaedic surgical procedure, including English speakers compared with non-English speakers (odds ratio [OR], 2.37 [95% confidence interval (CI), 2.01 to 2.79]); African-American or black race (OR, 0.42 [95% CI, 0.36 to 0.48]) and Hispanic race (OR, 0.52 [95% CI, 0.44 to 0.61]) compared with white race; college education compared with high school education (OR, 2.30 [95% CI, 2.12 to 2.49]); and a surgical procedure for orthopaedic trauma compared with that for the hand or upper extremity (OR, 0.51 [95% CI, 0.45 to 0.58]) (p < 0.001 for all), among others. EPP use was independently associated with the increased likelihood of completing a PROM (OR, 1.57 [95% CI, 1.45 to 1.7]) and a satisfaction survey (OR, 2.38 [95% CI, 2.17 to 2.61]) and improved overall patient satisfaction (mean difference, 2.61 points [95% CI, 1.79 to 3.43 points]) (p < 0.001 for all). Finally, EPP use was independently associated with lower mean no-show rates (6.8% [95% CI, 6.4% to 7.2%] compared with 9.3% [95% CI, 8.9% to 9.7%]). The lower no-show rate for EPP users corresponded to an estimated $218,225 in savings for our institution within the first postoperative year.

CONCLUSIONS

This study identified significant disparities in EPP use among patients undergoing an orthopaedic surgical procedure. Given that EPP use was independently associated with lower no-show rates and improved patient satisfaction among patients undergoing an orthopaedic procedure, efforts to reduce these disparities are warranted.

CLINICAL RELEVANCE

EPPs are increasingly being used by health-care systems to improve communication between providers and patients; however, providers should be aware of and strive to eliminate disparities in EPP utilization among orthopaedic patients. Within orthopaedic surgery, EPPs are associated with a number of benefits, including lower no-show rates and increased patient satisfaction.

Patient-Centric Scheduling With the Implementation of Health Information Technology to Improve the Patient Experience and Access to Care: Retrospective Case-Control Analysis

Background

Cancellations and rescheduling of doctor’s appointments are common. An automated rescheduling system has the potential to facilitate the rescheduling process so that newly opened slots are promptly filled by patients who need and can take the slot. Building on an existing online patient portal, a large health care system adopted an automated rescheduling system, Fast Pass, that sends out an earlier appointment offer to patients via email or SMS text messaging and allows patients to reschedule their appointment through the online portal.

Objective

We examined the uptake of Fast Pass at its early stage of implementation. We assessed program features and patient and visit characteristics associated with higher levels of Fast Pass utilization and the association between Fast Pass use and no-show and cancellation rates.

Methods

This study was a retrospective analysis of Fast Pass offers sent between July and December 2018. Multivariable logistic regression was used to assess the independent contribution of program, patient, and visit characteristics on the likelihood of accepting an offer. We then assessed the appointment outcome (completion, cancellation, or no-show) of Fast Pass offered appointments compared to appointments with the same patient and visit characteristics, but without an offer.

Results

Of 177,311 Fast Pass offers sent, 14,717 (8.3%) were accepted. Overall, there was a 1.3 percentage point (38%) reduction in no-show rates among Fast Pass accepted appointments compared to other appointments with matching characteristics (P<.001). The offers were more likely to be accepted if they were sent in the evening (versus early morning), the first (versus repeated) offer for the same appointment, for a slot 1-31 days ahead (versus same-day), for later in a day (versus before 10am), for a primary care (versus specialty) visit, sent via SMS text messaging (versus email only), for an appointment made through the online patient portal (versus via phone call or in-person), or for younger adults aged 18-49 years (versus those aged 65 years or older; all at P<.001). Factors negatively associated with offer acceptance were a higher number of comorbidities (P=.02) and visits scheduled for chronic conditions (versus acute conditions only; P=.002).

Conclusions

An automated rescheduling system can improve patients’ access by reducing wait times for an appointment, with an added benefit of reducing no-shows by serving as a reminder of an upcoming appointment. Future modifications, such as increasing the adoption of SMS text messaging offers and targeting older adults or patients with complex conditions, may make the system more patient-centered and help promote wider utilization.

Using text message reminders in health care services: A narrative literature review

INTRODUCTION

Despite the extensive use of mHealth behavior change interventions, questions remain about the use of technology-based reminders in delivering health care services. Text messaging, or short message service (SMS), is one reminder method that has been extensively researched. Most SMS-reminder research is distributed across a range of health care outcomes. The aim of this article is to systematically review the aggregate impact of these reminders on overall health care outcomes.

METHODS

A systematic literature review was conducted and yielded 2316 articles. Studies were included if they used SMS reminders to support patient health care outcomes. Study methodology was aligned with the PRISMA guidelines for systematic reviews.

RESULTS

Following screening, 162 articles met inclusion criteria. Of these studies, 93 investigated medical compliance reminders and 56 investigated appointment reminders. The review found that nearly all the SMS-reminder studies helped improve patient medical compliance and appointment reminders. Additionally, researchers reported numerous benefits from using SMS reminders, including ease of use, relative inexpensiveness, and rapid and automated message delivery. Minimal risks were reported and most participants found the reminders to be acceptable.

DISCUSSION

Text messages appear to be an effective reminder mechanism to promote improved patient appointment and medical compliance. Reminders should continue to be evaluated and improved to determine the most effective timing and frequency of messages for improving outcomes.

Impact of Delayed Time to Advanced Imaging on Missed Appointments Across Different Demographic and Socioeconomic Factors

PURPOSE

The aim of this study was to investigate the impact of wait days (WDs) on missed outpatient MRI appointments across different demographic and socioeconomic factors.

METHODS

An institutional review board-approved retrospective study was conducted among adult patients scheduled for outpatient MRI during a 12-month period. Scheduling data and demographic information were obtained. Imaging missed appointments were defined as missed scheduled imaging encounters. WDs were defined as the number of days from study order to appointment. Multivariate logistic regression was applied to assess the contribution of race and socioeconomic factors to missed appointments. Linear regression was performed to assess the relationship between missed appointment rates and WDs stratified by race, income, and patient insurance groups with analysis of covariance statistics.

RESULTS

A total of 42,727 patients met the inclusion criteria. Mean WDs were 7.95 days. Multivariate regression showed increased odds ratio for missed appointments for patients with increased WDs (7-21 days: odds ratio [OR], 1.39; >21 days: OR, 1.77), African American patients (OR, 1.71), Hispanic patients (OR, 1.30), patients with noncommercial insurance (OR, 2.00-2.55), and those with imaging performed at the main hospital campus (OR, 1.51). Missed appointment rate linearly increased with WDs, with analysis of covariance revealing underrepresented minorities and Medicaid insurance as significant effect modifiers.

CONCLUSIONS

Increased WDs for advanced imaging significantly increases the likelihood of missed appointments. This effect is most pronounced among underrepresented minorities and patients with lower socioeconomic status. Efforts to reduce WDs may improve equity in access to and utilization of advanced diagnostic imaging for all patients.

Factors Associated With Missed Appointments at an Academic Pain Treatment Center: A Prospective Year-Long Longitudinal Study

BACKGROUND

Interventional pain treatment centers represent an integral part of interdisciplinary care. Barriers to effective treatment include access to care and financial issues related to pain clinic operations. To address these challenges, specialty clinics have taken steps to identify and remedy missed clinic appointments. However, no prospective study has sought to identify factors associated with pain clinic "no-shows."

METHODS

We performed a prospective, longitudinal year-long study in an inner-city, academic pain clinic in which patients scheduled for office visits and procedures were categorized as to whether they showed up or did not show up for their scheduled appointment without cancelling the day before. Twenty demographic (age, employment status), clinical (eg, diagnosis, duration of pain), and environmental (season, time and day of appointment) variables were assessed for their association with missing an appointment. The logistic regression model predicting no-shows was internally validated with crossvalidation and bootstrapping methods. A predictive nomogram was developed to display effect size of predictors for no-shows.

RESULTS

No-show data were collected on 5134 patients out of 5209 total appointments for a capture rate of 98.6%. The overall no-show rate was 24.6% and was higher in individuals who were young (<65 years), single, of ethnic minority background, received Medicare/Medicaid, had a primary diagnosis of low back pain or headaches, were seen on a day with rain or snow or for an initial consult, and had at least 1 previous pain provider. Model discrimination (area under curve) was 0.738 (99% confidence interval, 0.70-0.85). A minimum threshold of 350 points on the nomogram predicted greater than 55% risk of no-shows.

CONCLUSIONS

We found a high no-show rate, which was associated with predictable and unpredictable (eg, snow) factors. Steps to reduce the no-show rate are discussed. To maximize access to care, operation managers should consider a regression model that accounts for patient-level risk of predictable no-shows. Knowing the patient level, no-show rate can potentially help to optimize the schedule programming by staggering low- versus high-probability no-shows.