Non-attendance or non-invitation? A case-control study of failed outpatient appointments

Predictors of Specialty Outpatient Palliative Care Utilization Among Persons With Serious Illness

CONTEXT

Outpatient Palliative Care (OPC) benefits persons living with serious illness, yet barriers exist in utilization.

OBJECTIVES

To identify factors associated with OPC clinic utilization.

METHODS

Emergency Medicine Palliative Care Access is a multicenter, randomized control trial comparing two models of palliative care for patients recruited from the Emergency Department (ED): nurse-led telephonic case management and OPC (one visit a month for six months). Patients were aged 50+ with advanced cancer or end-stage organ failure and recruited from 19 EDs. Using a mixed effects hurdle model, we analyzed patient, provider, clinic and healthcare system factors associated with OPC utilization.

RESULTS

Among the 603 patients randomized to OPC, about half (53.6%) of patients attended at least one clinic visit. Those with less than high school education were less likely to attend an initial visit than those with a college degree or higher (aOR 0.44; CI 0.23, 0.85), as were patients who required considerable assistance (aOR 0.45; CI 0.25, 0.82) or had congestive heart failure only (aOR 0.46; CI 0.26, 0.81). Those with higher symptom burden had a higher attendance at the initial visit (aOR 1.05; CI 1.00, 1.10). Reduced follow up visit rates were demonstrated for those of older age (aRR 0.90; CI 0.82, 0.98), female sex (aRR 0.84; CI 0.71, 0.99), and those that were never married (aRR 0.62; CI 0.52, 0.87).

CONCLUSION

Efforts to improve OPC utilization should focus on those with lower education, more functional limitations, older age, female sex, and those with less social support. Trial Registration ClinicalTrials.gov Identifier: NCT03325985.

Development and validation of nonattendance predictive models for scheduled adult outpatient appointments in different medical specialties

INTRODUCTION

Nonattendance is a critical problem that affects health care worldwide. Our aim was to build and validate predictive models of nonattendance in all outpatients appointments, general practitioners, and clinical and surgical specialties.

METHODS

A cohort study of adult patients, who had scheduled outpatient appointments for General Practitioners, Clinical and Surgical specialties, was conducted between January 2015 and December 2016, at the Italian Hospital of Buenos Aires. We evaluated potential predictors grouped in baseline patient characteristics, characteristics of the appointment scheduling process, patient history, characteristics of the appointment, and comorbidities. Patients were divided between those who attended their appointments, and those who did not. We generated predictive models for nonattendance for all appointments and the three subgroups.

RESULTS

Of 2,526,549 appointments included, 703,449 were missed (27.8%). The predictive model for all appointments contains 30 variables, with an area under the ROC (AUROC) curve of 0.71, calibration-in-the-large (CITL) of 0.046, and calibration slope of 1.03 in the validation cohort. For General Practitioners the model has 28 variables (AUROC of 0.72, CITL of 0.053, and calibration slope of 1.01). For clinical subspecialties, the model has 23 variables (AUROC of 0.71, CITL of 0.039, and calibration slope of 1), and for surgical specialties, the model has 22 variables (AUROC of 0.70, CITL of 0.023, and calibration slope of 1.01).

CONCLUSION

We build robust predictive models of nonattendance with adequate precision and calibration for each of the subgroups.

Palliative medicine outpatient clinic 'no-shows': retrospective review

OBJECTIVES

Patients who do not attend outpatient palliative care clinic appointments ('no-shows') may have unmet needs and can impact wait times. We aimed to describe the characteristics and outcomes associated with no-shows.

METHODS

We retrospectively reviewed new no-show referrals to the Princess Margaret Cancer Centre Oncology Palliative Care Clinic (OPCC) in Toronto, Canada, between January 2017 and December 2018, compared with a random selection of patients who attended their first appointment, in a 1:2 ratio. We collected patient information, symptoms, performance status (Eastern Cooperative Oncology Group (ECOG) and outcomes. Univariable and multivariable logistic regression analyses were used to identify significant factors.

RESULTS

Compared with those who attended (n=214), no-shows (n=103), on multivariable analysis, were at higher odds than those who attended of being younger (OR 0.98, 95% CI 0.96 to 1.00, p=0.019), living outside Toronto (OR 2.67, 95% CI 1.54 to 4.62, p<0.001) and having ECOG ≥2 (OR 2.98, 95% CI 1.41 to 6.29, p=0.004). No-shows had a shorter median survival compared with those who attended their first appointment (2.3 vs 8.7 months, p<0.001).

CONCLUSION

Compared with patients who attended, no-shows lived further from the OPCC, were younger, and had a poorer ECOG. Strategies such as virtual visits should be explored to reduce no-shows and enable attendance at OPCCs.

Characterising the nationwide burden and predictors of unkept outpatient appointments in the National Health Service in England: A cohort study using a machine learning approach

BACKGROUND

Unkept outpatient hospital appointments cost the National Health Service £1 billion each year. Given the associated costs and morbidity of unkept appointments, this is an issue requiring urgent attention. We aimed to determine rates of unkept outpatient clinic appointments across hospital trusts in the England. In addition, we aimed to examine the predictors of unkept outpatient clinic appointments across specialties at Imperial College Healthcare NHS Trust (ICHT). Our final aim was to train machine learning models to determine the effectiveness of a potential intervention in reducing unkept appointments.

METHODS AND FINDINGS

UK Hospital Episode Statistics outpatient data from 2016 to 2018 were used for this study. Machine learning models were trained to determine predictors of unkept appointments and their relative importance. These models were gradient boosting machines. In 2017-2018 there were approximately 85 million outpatient appointments, with an unkept appointment rate of 5.7%. Within ICHT, there were almost 1 million appointments, with an unkept appointment rate of 11.2%. Hepatology had the highest rate of unkept appointments (17%), and medical oncology had the lowest (6%). The most important predictors of unkept appointments included the recency (25%) and frequency (13%) of previous unkept appointments and age at appointment (10%). A sensitivity of 0.287 was calculated overall for specialties with at least 10,000 appointments in 2016-2017 (after data cleaning). This suggests that 28.7% of patients who do miss their appointment would be successfully targeted if the top 10% least likely to attend received an intervention. As a result, an intervention targeting the top 10% of likely non-attenders, in the full population of patients, would be able to capture 28.7% of unkept appointments if successful. Study limitations include that some unkept appointments may have been missed from the analysis because recording of unkept appointments is not mandatory in England. Furthermore, results here are based on a single trust in England, hence may not be generalisable to other locations.

CONCLUSIONS

Unkept appointments remain an ongoing concern for healthcare systems internationally. Using machine learning, we can identify those most likely to miss their appointment and implement more targeted interventions to reduce unkept appointment rates.

Content Validity of Patient-Reported Outcome Measures of Satisfaction With Primary Care for Musculoskeletal Complaints: A Systematic Review

OBJECTIVE

To evaluate the content validity of patient-reported outcome measures (PROMs) used to assess satisfaction in patients with musculoskeletal complaints who are treated in primary care.

DESIGN

Systematic review of clinimetric measurement.

LITERATURE SEARCH

A literature search in MEDLINE, Embase, and CINAHL was undertaken (up to January 2020) to identify studies of the development or evaluation of content validity of a PROM that aimed to assess patient satisfaction.

STUDY SELECTION CRITERIA

A PROM was considered eligible if it aimed to measure satisfaction with care in patients with musculoskeletal complaints. Two independent reviewers performed study selection, quality assessment, and data extraction.

DATA SYNTHESIS

Evaluation of content validity of the included PROMs was performed according to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidance, which includes an evaluation of PROM development, content validity studies, PROM content, and quality of evidence using the modified Grading of Recommendations Assessment, Development and Evaluation (GRADE).

RESULTS

Seven PROMs were identified. Their quality of development was inadequate. No studies evaluating the content validity of the satisfaction PROMs were retrieved. The content validity of the patient satisfaction PROMs was insufficient and supported by very low- quality evidence.

CONCLUSION

In measuring satisfaction among patients with musculoskeletal complaints treated in primary care, none of the identified PROMs had adequate content validity. Future studies should address the relevance, comprehensiveness, and comprehensibility of PROMs used to measure patient satisfaction and emphasize patient involvement during the development of new instruments. J Orthop Sports Phys Ther 2021;51(3):94-102. Epub 12 Nov 2020. doi:10.2519/jospt.2021.9788.

The Impact of the SARS-CoV-2 Outbreak on the Psychological Flexibility and Behaviour of Cancelling Medical Appointments of Italian Patients with Pre-Existing Medical Condition: The "ImpACT-COVID-19 for Patients" Multi-Centre Observational Study

Psychological distress imposed by the SARS-CoV-2 outbreak particularly affects patients with pre-existing medical conditions, and the progression of their diseases. Patients who fail to keep scheduled medical appointments experience a negative impact on care. The aim of this study is to investigate the psychosocial factors contributing to the cancellation of medical appointments during the pandemic by patients with pre-existing health conditions. Data were collected in eleven Italian hospitals during the last week of lockdown, and one month later. In order to assess the emotional impact of the SARS-CoV-2 outbreak and the subject's degree of psychological flexibility, we developed an ad hoc questionnaire (ImpACT), referring to the Acceptance and Commitment Therapy (ACT) model. The Impact of Event Scale-Revised (IES-R), the Depression, Anxiety and Stress Scale (DASS) and the Cognitive Fusion Questionnaire (CFQ) were also used. Pervasive dysfunctional use of experiential avoidance behaviours (used with the function to avoid thought, emotions, sensations), feelings of loneliness and high post-traumatic stress scores were found to correlate with the fear of COVID-19, increasing the likelihood of cancelling medical appointments. Responding promptly to the information and psychological needs of patients who cancel medical appointments can have positive effects in terms of psychological and physical health.

Using machine learning tools to investigate factors associated with trends in 'no-shows' in outpatient appointments

Missed appointments are estimated to cost the UK National Health Service (NHS) approximately £1 billion annually. Research that leads to a fuller understanding of the types of factors influencing spatial and temporal patterns of these so-called "Did-Not-Attends" (DNAs) is therefore timely. This research articulates the results of a study that uses machine learning approaches to investigate whether these factors are consistent across a range of medical specialities. A predictive model was used to determine the risk-increasing and risk-mitigating factors associated with missing appointments, which were then used to assign a risk score to patients on an appointment-by-appointment basis for each speciality. Results show that the best predictors of DNAs include the patient's age, appointment history, and the deprivation rank of their area of residence. Findings have been analysed at both a geographical and medical speciality level, and the factors associated with DNAs have been shown to differ in terms of both importance and association. This research has demonstrated how machine learning techniques have real value in informing future intervention policies related to DNAs that can help reduce the burden on the NHS and improve patient care and well-being.

Patients' reasons for missing scheduled clinic appointments and their solutions at a major urban-based academic medical center

Objective

Patients that do not show up for scheduled clinic appointments affect the quality of healthcare provided. This study aimed to recognize the reasons behind missing scheduled appointments and understand possible solutions from the patient's perspective.

Method

We included 100 patients that attended the outpatient Medicine clinic in January 2020. Selection criteria were based on missing one or more of the scheduled clinic appointments in the last year. The participants answered a questionnaire to clarify the reasons for missing a scheduled clinic appointment and offer suggestions for a solution. The recruiter, in turn, answered several demographical questions.

Results

The study showed a statistically significant difference between the no-show rate in females at 60% compared to males at 40% (P = 0.0023). The no show rate was not significantly affected by the day of the week, time of appointment, or the weather. Forgetting about the appointment was the most common cause (36 subjects). Work-related issues were reported in 17 participants, making it the 2^nd most common cause. Not notified about the appointment, Lack of transportation, childcare-related issues, along with other reasons, were less likely reported (Table 2). 11 out of 36 (30%) subjects suggested a reminder text message in their preferred language; meanwhile, 4 others suggested a weekend clinic.

Conclusion

The patients should be aware of different appointment reminders options and have the freedom to choose a suitable reminder. Patients should be educated about the importance of calling to cancel the appointment since some of the reasons for no show are unpreventable.

Why Patients Miss Scheduled Outpatient Appointments at Urban Academic Residency Clinics: A Qualitative Evaluation

INTRODUCTION

Missed outpatient appointments are a common problem for academic residency clinics, and reducing their rate improves office efficiency, income, and resident education. Identifying specific reasons why some patients miss outpatient appointments may provide insight into developing targeted approaches to reducing their rates. This study sought to find reasons associated with patients' missed appointments at two family medicine residency clinics.

METHODS

The study utilized a qualitative research design involving patients at two urban, university-affiliated family medicine residency outpatient clinics. Twenty-five randomly selected patients who were dismissed from the clinics for missing three or more scheduled appointments during a five-year span (July 2012 to July 2017) were interviewed over the phone about reasons they did not keep their scheduled clinic appointments. The authors, individually and as a group, used an immersion-crystalization approach to analyze the content of the interviews.

RESULTS

Responses from 25 participants (21 females and four males) are presented. Fifty-two percent of patients were Caucasian, 32% Black, 12% Hispanic, and 4% Asian. Five themes emerged from the data analysis as major reasons the patients missed their scheduled outpatient appointments: forgetfulness, transportation issues, personal health issues, family and employer obligations, and other issues, such as anticipated long clinic wait times, bad weather, and financial problems.

CONCLUSIONS

The findings showed there are several logistical, situational, and clinical reasons for patients' missed scheduled outpatient appointments.

Patient Outreaches for Clinical Pharmacy Services: A Population Health Management Program Assessment

BACKGROUND

Pharmacists in ambulatory care can utilize population health approaches to identify patients needing disease management and improve outcomes. However, population health is only effective when identified patients are successfully outreached and show to appointments.

OBJECTIVE

Describe a population health approach utilized by pharmacists in primary care, report outcomes of outreach attempts and scheduled appointments, and determine whether patient and referral characteristics predict no-show appointments.

METHODS

Retrospective cohort study of patients referred for pharmacist management of hypertension or chronic pain through population health between 2013-2016. Outreach attempt and appointments outcomes were collected. Patient and referral characteristics were analyzed to determine whether predictive of no-show appointments using logistic regression.

RESULTS

Of 450 outreach attempts, 250 (56%) patients were not reached, 164 (36%) scheduled appointments, and 36 (8%) were reached but declined an appointment. Of 164 patients with appointments, 71 (43%) no-showed. Patients with higher systolic blood pressure were more likely to no-show (OR: 1.02, 95% CI: 1.00-1.04). Other characteristics were not predictive of no-show appointments.

CONCLUSION

Successful outreach and showed appointments are essential components of successful population health programs. Using multiple outreach modalities and further identifying factors predictive of no-show appointments to refine the current approach may lead to increased efficiency.

Reducing Patient No-Shows: An Initiative at an Integrated Care Teaching Health Center

Background

Patient no-shows impede the effectiveness and efficiency of health care services delivery.

Objective

To evaluate a 2-phase intervention to reduce no-show rates at an integrated care community health center that incorporates a teaching program for osteopathic family medicine residents.

Methods

The Elmont Teaching Health Center (ETHC) is 1 of 5 community-based health centers comprising the Long Island Federally Qualified Health Centers. In August 2015, the ETHC implemented a centerwide No-Show Rates Reduction Initiative divided into an assessment phase and implementation phase. The assessment phase identified reasons most frequently cited by patients for no-shows at the ETHC. The implementation phase, initiated in mid-September, addressed these reasons by focusing on reminder call verification, patient education, personal responses to patient calls, institutional awareness, and integration with multiple departments. To assess the initiative, monthly no-show rates were compared by quarter for 2015 and against rates for the previous year.

Results

We recorded 27,826 appointments with 6147 no-shows in 2014 and 31,696 appointments with 5690 no-shows in 2015. No-show rates in the first 3 quarters of 2015 (range, 18.2%-20.0%) were slightly lower than the rates in 2014 (20.1%-23.4%) and then changed by an increasingly wide margin in the last quarter of 2015 (15.3%), leading to a significant year (2014, 2015) by quarter (Q1, Q2, Q3, Q4) interaction (P=.004). Also, the change observed in Q4 in 2015 differed significantly from Q1 (P=.017), Q2 (P=.004), and Q3 (P=.027) in 2015, while Q1, Q2, and Q3 in 2015 did not significantly differ from one another.

Conclusion

No-show rates were successfully reduced after a 2-phase intervention was implemented at 1 health center within a larger health care organization. Future directions include dismantling the individual components of the intervention, evaluating the role of patient volumes in no-show rates, assessing patient outcomes (eg, costs, health) in integrative care settings that treat underserved populations, and evaluating family medicine residents' training on continuity of care and no-show rates.

Determinants of Clinic Absenteeism: A Novel Method of Examining Distance from Clinic and Transportation

Delayed treatment and non-adherence are associated with inferior prostate cancer (CaP) outcomes. Missed clinic appointments (MA) are one form of non-adherence that may be preventable. We conducted a retrospective cohort study of 1341 scheduled clinic encounters for men referred to an academic urology clinic for evaluation of known or suspected CaP. Driving distance and public transit times were calculated using a Google Distance Matrix API algorithm. Zip code level data regarding socioeconomic status was obtained from the 2013 American Community Survey. Logistic regression multivariate analysis was used to identify MA predictors. Of scheduled clinic encounters, 14% were missed. Public health insurance was associated with MA (Private insurance 10%, Public insurance 19%), (p < 0.01) Calendar month was associated with MA with December showing the highest rate (21.2%) and June the lowest (5.3%) rates. (p = 0.02) Appointments for suspected CaP were more likely to be missed (19.3%) than those for known CaP (10.5%), p < 0.01. Driving distance was inversely associated with rate of MA (CA median 11.8 miles, MA median 10.4 miles, p = 0.04) while public transit times were not (66.7 min for CA, 65.3 min for MA, p = 0.36). Men that missed appointments were from areas with lower household incomes and educational attainment. Patient encounter type, insurance status, and reason for referral remained significantly associated with MA after multivariable adjusted analysis. By computing public transit time to the clinic using a mapping engine, we present a novel way to measure this parameter for studies of urban health care.

Association between age and outpatient clinic arrival time: myth or reality?

BACKGROUND

Non-attendance and late arrivals diminish patient flow in outpatient clinics. On the other hand, patient earliness may also be undesirable. Physicians often experience that older patients are more punctual than younger patients, and often they come excessively early. The aim of this study was to determine whether an association between age and outpatient clinic arrival time could be established or not, i.e. to find out if it is a myth or a reality.

METHODS

Prospective descriptive study performed at a neurological outpatient clinic. Data were collected from all scheduled appointments during an eight-week period. Variables included were age, gender, appointment time, arrival time, no-shows, appointment type, need for assistance and if it was an early or late appointment. Outcomes were unpunctuality (early and late arrivals) and non-attendance.

RESULTS

Of 1353 appointments, non-attendance rate was 9.5 and 5.1% were late arrivals. Median age increased with increased patient earliness (p <  0.001). Younger age (p = 0.007) and new referrals (p = 0.025) were associated with non-attendance.

CONCLUSIONS

The intuition of an association between age and outpatient clinic arrival time was confirmed, thus it is a reality that older patients attend their appointments more frequently and have better punctuality than younger adults. This age effect in outpatient clinics should be considered when developing future simulation models and intervention studies.

Characteristics of patients in a psychiatric follow-up clinic

Out-patient clinics are widely used to asssess and treat patients. In psychiatric practice, out-patient clinics are used both to assess new referrals and follow up existing patients. More than three-quarters of psychiatric out-patient attendances are for follow-up (DHSS, 1984). With modern emphasis on community psychiatry, the role of out-patient clinics may become less prominent and more refined. Very little appears to have been published on the subject of psychiatric follow-up clinics.

Improving out-patient attendance using postal appointment reminders

Previous studies have demonstrated high rates of non-attendance among new referrals to psychiatric out-patient clinics. Consistent factors which distinguish non-attenders have not been shown. Forgetting an appointment contributes towards non-attendance and offers potential for its reduction. The effect of sending patients an appointment reminder three working days prior to the appointment date was examined. The rate of attendance of those sent a reminder improved significantly.

Psychiatric out-patient services: origins and future

Psychiatric out-patient services originated in the early-20th century to enable triage of new referrals to the asylum in order to differentiate between treatable and untreatable cases. They evolved to provide community follow-up of patients discharged from hospital and assessment of those newly referred to psychiatric services. Non-attendance at out-patient appointments represents an enormous waste of clinical and administrative resources and has potentially serious clinical implications for those who are most psychiatrically unwell. The place of out-patient clinics in modern community mental health services is explored with reference to the reasons for, and clinical and cost implications of, missed appointments. An alternative model is described that incorporates recent UK government guidance on the roles and implementation of community mental health teams, liaison with primary care and new roles for consultant psychiatrists.

Influence of a Nurse Practitioner on Non-Attendance Rate for Barium Enema

Non-attendance for barium enema investigation wastes resources, prolongs waiting times and delays diagnosis of colorectal carcinoma. In an inner-city hospital with a previous non-attendance rate of over 20% for barium enema we investigated the value of systematic personal contact with a nurse practitioner at the time of booking. We compared two groups of patients, all of whom received an explanation of the procedure from the referring clinician. Patients referred from the colorectal clinic were accompanied by the colorectal nurse practitioner to the radiology department for booking, an appointment being sent later by mail. The nurse practitioner reiterated the details of the procedure, provided supplementary information, confirmed the patient's contact details and provided a telephone number in case further information or assistance was needed. Patients referred from the gastroenterology clinic were managed as previously, making their own way to the radiology department and receiving supplementary information only on request.

The patients referred from the two clinics were closely similar; however, the non-attendance rate for the intervention (colorectal) clinic was 4/157 (2.5%) compared with 17/110 (15.5%) for the comparison clinic (P < 0.001). A year previously the non-attendance rates in these clinics had been 23% and 20%, respectively.

These results indicate that personal contact, with supplementary information, can substantially reduce the non-attendance rate for barium enema.

Risk factors for negative experiences during psychotherapy

BACKGROUND

It is estimated that between 3% and 15% of patients have a negative experience of psychotherapy, but little is understood about this.

AIMS

The aim of this study was to investigate the factors associated with patients' negative therapy experiences.

METHOD

The data comprised 185 patient and 304 therapist questionnaires, 20 patient and 20 therapist interviews. Patients reported on an unhelpful or harmful experience of therapy, and therapists on a therapy where they thought the patient they were working with had a poor or harmful experience. These were transcribed and analysed using thematic analysis.

RESULTS

There was a Lack of fit between Patient needs, Therapist skills, and Service structures. This could result in Fault Lines, a tension between Safety and containment and Power and control. This tension led to Strain and Poor Engagement, which led to Consequences following the negative therapy experience.

CONCLUSIONS

Patients require clear information, choice, involvement in decision-making, explicit contracting and clarity about sessions and progress. Opportunities for patient feedback should be the norm, where the therapist and service are vigilant for signs of deterioration and solutions considered. Clinical and methodological significance of this article: Estimates of "unwanted effects," including long-lasting effects, of psychotherapy have ranged from 3% to 15%. Few empirical studies have been conducted in this area. This study aimed to address this gap and provide clinicians with a model of risk factors for negative therapy effects. The findings of this study indicate the importance of providing patients with a supportive service structure that offers clear information, choice and involvement in decision-making. Explicit contracting at the beginning of therapy and clarity about sessions and progress are also important in managing patient expectations throughout. Opportunities for patient feedback should be provided.

An Audit of Occupational Therapy Outpatient Attendance

An audit of occupational therapy outpatient appointments over a 3-year period demonstrated improved attendance for first appointments in neuropsychiatry when new referral procedures were followed. A substantial number of patients, however, continued to drop out of therapy. The results are discussed in relation to findings of other studies. Speed of referral and personal contact were found to be important factors in reducing non-attendance. Further changes are proposed in an attempt to reduce the number of patients dropping out of therapy, illustrating how audit is a continuous process.

Effect of team training on improving MRI study completion rates and no-show rates

PURPOSE

Magnetic resonance imaging (MRI) is a high-cost imaging modality, and an optimized encounter ideally provides high-quality care, patient satisfaction, and capacity utilization. Our purpose was to assess the effectiveness of team training and its impact on patient show-up and completion rates for their MRI examinations.

MATERIALS AND METHODS

A total of 97,712 patient visits from three tertiary academic medical centers over 1-year intervals were evaluated, totaling 49,733 visits at baseline and 47,979 after training. Each center's MRI team received team training skill training including advanced communication and team training techniques training. This training included onsite instruction including case simulation with scenarios requiring appropriate behavioral and communicative interventions. Orientation and training also utilized customized online tools and proctoring. The study completion rate and patient show-up rate during consecutive year-long intervals before and after team training were compared to assess its effectiveness. Two-sided chi-square tests for proportions using were applied at a 0.05 significance level.

RESULTS

Despite differing no-show rates (5-22.2%) and study incompletion rates (0.7-3.7%) at the three academic centers, the combined patients' data showed significant (P < 0.0001) improvement in the patients' no-show rates (combined decreases from 11.2% to 8.7%) and incompletion rates (combined decreases from 2.3% to 1.4%).

CONCLUSION

Our preliminary results suggest training of the imaging team can improve the no-show and incompletion rates of the MRI service, positively affecting throughput and utilization. Team training can be readily implemented and may help address the needs of the current cost-conscious and consumer-sensitive healthcare environment. J. MAGN. RESON. IMAGING 2016;44:1040-1047.

Who did not appear? First dental visit absences in secondary care in a major Brazilian city: a cross-sectional study

The study sought to identify possible factors associated with non-attendance at first dental appointments scheduled in 2011 of users living in Belo Horizonte, Minas Gerais, who were referred from primary care to different dental specialties in secondary care within the public health services of the city. A cross-sectional study was conducted based on research in secondary data bases of the public health regulatory system. The dependent variable was "no shows" for scheduled appointments, and the independent variables were age, time on the waiting list, gender, health district, and the specialty to which the individual was referred. Among the 6,428 first dental visits scheduled for 2011 in the specialties selected for analysis, 32.9 % were not performed due to the absence of the user. Bivariate analysis revealed a statistically significant association between non-attendance of the user and the five independent variables. Young adults, male, and resident in given districts who were referred to the specialties of surgery and endodontics and who waited longer on the waiting list exhibited a higher frequency of no-shows.

Stress and Depression in Relation to Functional Health Behaviors in African American Patients with Systemic Lupus Erythematosus

OBJECTIVE

While increased psychological distress in SLE has been clinically and empirically reported, the relationship between emotional distress, treatment adherence, and disease activity are complex and even more unclear in African American lupus patients. In an effort to elucidate this phenomenon in these patients, this exploratory study aimed to investigate relationships between stress, depression, and various health behaviors in this group.

METHODS

Thirty patients invited to participate in this study were African American systemic lupus erythematosus (SLE) patients attending rheumatology clinics at the Medical University of South Carolina (MUSC). This study was part of a larger interventional pilot study, the Balancing Lupus Experiences with Stress Strategies (BLESS) study, that included a comprehensive battery of psychosocial, quality of life, and behavior change measures.

RESULTS

When looking at the association between anxiety/stress and functionality, levels of reported stress had strong effects upon functionality, especially between health distress and functionality. When looking at the association between depressive symptoms and functionality, depressive symptoms had moderate effects upon social/role limitations and nights spent in the hospital.

CONCLUSION

Not only did the larger pilot project demonstrate significant reductions in stress and depression as a result of workshop participation; this nested study also showed that those improvements were positively associated with improved health behaviors. These results could have implications for developing interventions to improve disease experience and quality of life in SLE patients with stress and depression.

Can valid and practical risk-prediction or casemix adjustment models, including adjustment for comorbidity, be generated from English hospital administrative data (Hospital Episode Statistics)? A national observational study

Background

NHS hospitals collect a wealth of administrative data covering accident and emergency (A&E) department attendances, inpatient and day case activity, and outpatient appointments. Such data are increasingly being used to compare units and services, but adjusting for risk is difficult.

Objectives

To derive robust risk-adjustment models for various patient groups, including those admitted for heart failure (HF), acute myocardial infarction, colorectal and orthopaedic surgery, and outcomes adjusting for available patient factors such as comorbidity, using England’s Hospital Episode Statistics (HES) data. To assess if more sophisticated statistical methods based on machine learning such as artificial neural networks (ANNs) outperform traditional logistic regression (LR) for risk prediction. To update and assess for the NHS the Charlson index for comorbidity. To assess the usefulness of outpatient data for these models.

Main outcome measures

Mortality, readmission, return to theatre, outpatient non-attendance. For HF patients we considered various readmission measures such as diagnosis-specific and total within a year.

Methods

We systematically reviewed studies comparing two or more comorbidity indices. Logistic regression, ANNs, support vector machines and random forests were compared for mortality and readmission. Models were assessed using discrimination and calibration statistics. Competing risks proportional hazards regression and various count models were used for future admissions and bed-days.

Results

Our systematic review and empirical analysis suggested that for general purposes comorbidity is currently best described by the set of 30 Elixhauser comorbidities plus dementia. Model discrimination was often high for mortality and poor, or at best moderate, for other outcomes, for examplec = 0.62 for readmission andc = 0.73 for death following stroke. Calibration was often good for procedure groups but poorer for diagnosis groups, with overprediction of low risk a common cause. The machine learning methods we investigated offered little beyond LR for their greater complexity and implementation difficulties. For HF, some patient-level predictors differed by primary diagnosis of readmission but not by length of follow-up. Prior non-attendance at outpatient appointments was a useful, strong predictor of readmission. Hospital-level readmission rates for HF did not correlate with readmission rates for non-HF; hospital performance on national audit process measures largely correlated only with HF readmission rates.

Conclusions

Many practical risk-prediction or casemix adjustment models can be generated from HES data using LR, though an extra step is often required for accurate calibration. Including outpatient data in readmission models is useful. The three machine learning methods we assessed added little with these data. Readmission rates for HF patients should be divided by diagnosis on readmission when used for quality improvement.

Future work

As HES data continue to develop and improve in scope and accuracy, they can be used more, for instance A&E records. The return to theatre metric appears promising and could be extended to other index procedures and specialties. While our data did not warrant the testing of a larger number of machine learning methods, databases augmented with physiological and pathology information, for example, might benefit from methods such as boosted trees. Finally, one could apply the HF readmissions analysis to other chronic conditions.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

A longitudinal linear model of patient characteristics to predict failure to attend an inner-city chronic pain clinic

Patients often fail to attend appointments in chronic pain clinics for unknown reasons. We hypothesized that certain patient characteristics predict failure to attend scheduled appointments, pointing to systematic barriers to accessing chronic pain services for certain underserved populations. We collected retrospective data from a longitudinal observational cohort of patients at an academic pain clinic in Newark, New Jersey. To examine the effect of demographic factors on appointment status, we fit a marginal logistic regression using generalized estimating equations with exchangeable correlation. A total of 1,394 patients with 3,488 total encounters between January 1, 2006, and December 31, 2009, were included. Spanish spoken as a primary language (alternatively Hispanic or other race) and living between 5 and 10 miles from the clinic were associated with reduced odds of arriving for an appointment; making an appointment for a particular complaint such as cancer pain or back pain, an interventional pain procedure scheduled in connection with the appointment, unemployed status, and continuity of care (as measured by office visit number) were associated with increased odds of arriving. Spanish spoken as a primary language and distance to the pain clinic predicted failure to attend a scheduled appointment in our cohort. If these constitute systematic barriers to access, they may be amenable to targeted interventions.

PERSPECTIVE

We identified certain patient characteristics, specifically Spanish spoken as a primary language and geographic distance from the clinic, that predict failure to attend an inner-city chronic pain clinic. These identified barriers to accessing chronic pain services may be modifiable by simple cost-effective interventions.

Dropout revisited: patient- and therapist-initiated discontinuation of psychotherapy as a function of organizational instability

OBJECTIVE

To explore the association between the stability or instability of services' organizational structure and patient- and therapist-initiated discontinuation of therapy in routine mental health.

METHOD

Three groups, comprising altogether 750 cases in routine mental health care in eight different clinics, were included: cases with patient-initiated discontinuation, therapist-initiated discontinuation, and patients remaining in treatment. Multilevel multinomial regression was used to estimate three models: An initial, unconditional intercept-only model, another one including patient variables, and a final model with significant patient and therapist variables including the organizational stability of the therapists' clinic.

RESULTS

High between-therapist variability was noted. Odds ratios and significance tests indicated a strong association of organizational instability with patient-initiated premature termination in particular.

CONCLUSIONS

The question of how organizational factors influence the treatment results needs further research. Future studies have to be designed in ways that permit clinically meaningful subdivision of the patients' and the therapists' decisions for premature termination.

Predictors of non-response and non-compliance in African American lupus patients: Findings from the Balancing Lupus Experiences with Stress Strategies (BLESS) Study

Arthritis self-management education has demonstrated significant improvements in health distress, self-reported global health, and activity limitation, with trends toward improvement in self efficacy and mental stress management. Consequently, numerous national agencies have recommended arthritis self-management education to complement medical care. Despite these recommendations, arthritis self-management education has reached only a limited number of people. Compliance is also a persistent problem in standardized programs. As part of the Balancing Lupus Experiences with Stress Strategies (BLESS) Study, a validated psychosocial stress intervention was piloted among a cohort of African American lupus patients participating in an SLE database project at the Medical University of South Carolina (MUSC). Recruitment attempts were made with the 330 database participants who met eligibility requirements for the study. While enrollment was limited to 30 participants (n=15 controls and n=15 intervention), two of the participants assigned to the intervention group did not attend any intervention sessions and several participants did not complete post-intervention questionnaires. Therefore, data were analyzed on 30 participants at baseline, 25 (n=13 controls and n=12 intervention) at post-intervention, and 22 (n=12 controls and n=10 intervention) at four months post-intervention. In an effort to characterize those who fully participated in the study and those who were non-compliant or non-responsive to recruitment attempts, we obtained descriptive data from African-American Lupus patients participating in the SLE Clinic Database Project. This information can be used to develop and refine future intervention activities.

Weekday affects attendance rate for medical appointments: large-scale data analysis and implications

The financial cost of missed appointments is so great that even a small percentage reduction in Did Not Attend (DNA) rate could save significant sums of money. Previous studies have identified many factors that predict DNA rate, including patient age, gender, and transport options. However, it is not obvious how healthcare providers can use this information to improve attendance, as such factors are not under their control. One factor that is under administrative control is appointment scheduling. Here we asked whether DNA rate could be reduced by altering scheduling policy. In Study 1, we examined attendance records for 4,538,294 outpatient hospital appointments across Scotland between January 1st 2008 and December 31st 2010. DNA rate was highest for Mondays (11%), lowest for Fridays (9.7%), and decreased monotonically over the week (Monday-Friday comparison [χ²(1, N  = 1,585,545)  = 722.33, p<0.0001]; Relative Risk Reduction 11.8%). This weekly decline was present for male and female patient groups of all ages, but was steeper for younger age groups. In Study 2, we examined attendance records for 10,895 appointments at a single GP clinic in Glasgow. Here again, DNA rate was highest for Mondays (6.2%), lowest for Fridays (4.2%), and decreased monotonically over the week (Monday-Friday comparison [χ²(1, N  = 4767)  = 9.20, p<0.01]; Relative Risk Reduction 32.3%). In two very different settings, appointments at the beginning of the week were more likely to be missed than appointments at the end of the week. We suggest that DNA rate could be significantly reduced by preferentially loading appointments onto high-attendance days.

Failure of Fracture Patients to Attend Their Out Patient Appointments

The failure to attend outpatient clinics is a chronic problem throughout the NHS. Previous studies have compared individual specialties. Trauma has received little attention. The average NHS-wide figure for non-attendance in outpatient clinics nationally is often quoted at 12%.1 there is considerable variation in the rate of non-attendance and studies have reported this as ranging from 5% to 34%.

Defaulters among lung cancer patients in a suburban district in a developing country

INTRODUCTION

This study was carried out to determine the prevalence, patient's characteristic and reasons for defaulting follow-up and treatment among patients with lung cancer.

METHODS

Patients with histologically confirmed lung cancer were recruited. Patient's detailed demographic data, occupation, socioeconomic status, and educational level of both the patients and their children were recorded. Defaulters were classified as either intermittent or persistent defaulters. By using Chi-square test, defaulter status was compared with various demographic and disease characteristic factors. The reasons for default were determined.

RESULTS

Ninety five patients were recruited. Among them, 81.1% patients were males; 66.3% were Malays. The mean age (SD) was 60 ± 10.5 years. About 46.3% of the patients had Eastern Cooperation Oncology Group (ECOG) functional status 0/1 and 96.8% of the patients presented with advanced stage (Stage 3b or 4). Overall, 20 patients (21.1%) were defaulters (35.0% intermittent defaulters; 65.0% persistent defaulters). Among the intermittent defaulters, 8 patients defaulted once and one patient defaulted 3 times. Among the 20 defaulters, only 2 (10%) patients turned up for the second follow-up appointment after telephone reminder. Two main reasons for default were 'too ill to come' (38.5.5%) and logistic difficulties (23.1%). No correlation was found between patient education, children education, income, ECOG status, stage of the disease, race, and gender with the defaulter rate.

CONCLUSION

Defaulter rate among lung cancer patients was 21.1%. Children education level is the only significant factor associated with the defaulter rate.

The effect of appointment rescheduling on monitoring interval and patient attendance in the glaucoma outpatient clinic

AIM

To assess the effect of appointment rescheduling on monitoring intervals and patient attendance in the glaucoma clinic.

METHODS

A retrospective review of 100 consecutive patients was conducted. Patients were categorised into groups based on risk of progressive visual loss. The monitoring interval requested by the clinician was compared with the interval recommended by national guidelines. One hundred consecutive patients who had had their appointment rescheduled were also examined to assess the effect of appointment rescheduling on the actual monitoring interval. Patient non-attendance rates and attendances at the emergency department were also examined.

RESULTS

After excluding patients with secondary glaucoma, glaucoma suspects, and those with short-term factors affecting monitoring interval, 54 patients with chronic open-angle glaucoma (COAG) were included. Forty-eight (89%) of patients had a monitoring interval requested in accordance with national guidelines (2 had longer intervals by 1-2 months and 4 had shorter time intervals). The monitoring interval was not influenced by disease severity (Kruskal-Wallis test, P=0.16), but was significantly shorter if the intraocular pressure was above target (P<0.0001) or the patient showed structural or functional progression (P<0.0001). Hospital-initiated appointment rescheduling led to significant lengthening of monitoring interval. The mean difference between intended and actual monitoring interval was 5.6 months. Eight percent (8/100) of patients with rescheduled appointments did not attend compared with 15% (39/265) without rescheduled appointments.

CONCLUSION

Clinical staff are selecting appropriate monitoring intervals for patients with COAG; however, hospital-initiated rescheduling of appointments is a major challenge to appropriate follow-up.

Missed appointments in resident continuity clinic: patient characteristics and health care outcomes

BACKGROUND

Frequent missed patient appointments in resident continuity clinic is a well-documented problem, but whether rates of missed appointments are disproportionate to standard academic practice, what patient factors contribute to these differences, and health care outcomes of patients who frequently miss appointments are unclear.

METHODS

The overall population for the study was composed of patients in an academic internal medicine continuity clinic with 5 or more office visits between January 2006 and December 2008. We randomly selected 325 patients seen by resident physicians and 325 patients cared for by faculty. Multivariate linear regression was used to examine the relationship between patient factors and missed appointments. Health outcomes were compared between patients with frequent missed appointments and the remainder of the study sample, using Cox regression analysis.

RESULTS

Resident patients demonstrated significantly higher rates of missed appointments than faculty patients, but this difference was explained by patient factors. Factors associated with more missed appointments included use of a medical interpreter, Medicaid insurance, more frequent emergency department visits, less time impanelled in the practice, and lower proportion of office visits with the primary care provider. Patients with frequent missed appointments were less likely to be up to date with preventive health services and more likely to have poorly controlled blood pressure and diabetes.

CONCLUSIONS

We found that the disproportionate frequency of missed appointments in resident continuity clinic is explained by patient factors and practice discontinuity, and that patients with frequent missed appointments demonstrated worse health care outcomes.

Engagement and early termination of contact with a community-based early intervention service for personality disorder in young adults

BACKGROUND

Few studies have examined factors associated with continuity of care in a community-based early intervention service for personality disorder in patients aged 16-25.

AIMS

To estimate the probability of dropping out of care in patients attending an early intervention service for personality disorder and identify patient characteristics associated with those who drop out, are discharged or continue using the service.

METHOD

A 24-month cohort of first-contact patients attending the early intervention service was followed up for 12 months to identify drop-outs, discharges and those still using the service.

RESULTS

One hundred eighty-three first contact patients were referred/self-referred during the study timescale. After 12-month follow-up, 83 (45%) were discharged, 39 (21%) still using the service and 61 (33%) dropped out. Drop out was most likely among patients aged 21-25, from higher socio-economic groups and highest during months 3-5 of service use. No discharges occurred until at least 3 months into the service, with a peak at 6-8 months.

CONCLUSIONS

Although sharing many factors predicting increased levels of drop-out, the rate of drop-out among young adults aged between 16-25 attending an early intervention service for personality disorder was equivalent to that experienced by services for adults with a long history of personality disorder diagnosis. Concerns exist, however, concerning increased rates of drop-out among patients reporting a greater number of difficulties, reporting a common mental health or substance abuse problem, and during months 3-5 of service use. Implications of the results for future service developments are discussed.

Disengagement from mental health services. A literature review

This paper reviews the literature on disengagement from mental health services examining how the terms engagement and disengagement are defined, what proportion of patients disengage from services, and what sociodemographic variables predict disengagement. Both engagement and disengagement appear to be poorly conceptualised, with a lack of consensus on accepted and agreed definitions. Rates of disengagement from mental health services vary from 4 to 46%, depending on the study setting, service type and definition of engagement used. Sociodemographic and clinical predictors of disengagement also vary, with only a few consistent findings, suggesting that such associations are complex and multifaceted. Most commonly reported associations of disengagement appear to be with sociodemographic variables including young age, ethnicity and deprivation; clinical variables such as lack of insight, substance misuse and forensic history; and service level variables such as availability of assertive outreach provision. Given the importance of continuity of care in serious mental disorders, there is a need for a consensual, validated and reliable measure of engagement which can be used to explore associations between patient, illness and service related variables and can inform service provision for difficult to reach patients.

Nonattendance in a dermatology clinic--a large sample analysis

BACKGROUND

Previous studies have described factors determining non-attendance at dermatology appointments in small sample sizes.

OBJECTIVE

To perform an analysis of factors associated with non-attendance in a dermatology clinic in a larger sample.

METHODS

Factors determining non-attendance were examined in 52 604 consecutive first-time visits to a dermatology clinic over a period of 44 months.

RESULTS

Non-attendance proportion was 27.6%. Among children, non-attendance was associated with waiting for an appointment < 7 days [odds ratio (OR), 1.44], Bedouin sector (OR, 1.30), rural Jewish sector (OR, 0.45) and the treating physician. Among adults, non-attendance was associated with female gender (OR, 1.08), age < 55 years (OR, 1.65), waiting time for an appointment < 7 days (OR, 1.44), timing of the appointment between 1 and 4 pm (OR, 1.13), Bedouin sector (OR, 1.63), rural Jewish sector (OR, 0.46) and the treating physician.

CONCLUSION

Non-attendance is common among Bedouins, adult female patients and young adults and is more likely as waiting times become longer. Strategies to reduce non-attendance are needed.

Inequality of use of cancer genetics services by members of breast, ovarian and colorectal cancer families in South East Scotland

Some studies have found a deficiency of male, younger and more socially deprived individuals amongst referrals to and/or attendees at cancer genetics clinics. We investigated this inequality of use of genetics services from data on 4,178 Scottish patients with a family history of breast and/or ovarian cancer (BOC) or colorectal cancer (CRC) referred from 2000--2006. Some 98% BOC and 60% CRC referrals were female. Median age of female referrals was greater in the CRC than the BOC group (45.3 vs. 38.7 years, P < 0.001). Both groups of referrals were less socially deprived than the general population (P < 0.001) and the CRC less deprived than the BOC group (P < 0.001). Some 88% patients attended the first appointment offered. Attendance was greater in the CRC group (P < 0.001) and in older patients (P < 0.001) and in the BOC group was highly significantly lower in more socially deprived patients (P < 0.001). Male relatives may feel counselling is less relevant and relatives of both sexes may delay counselling until approaching the age of onset of cancer in a relative. We suggest that medical professionals and the general public may have more knowledge about the genetics of BOC than of CRC. Thus relatives in CRC families seeking counselling are likely to be those with access to more information. The lower attendance amongst more deprived relatives in BOC families may result from poor understanding of the reason for referral. These findings confirm the need to provide male, younger and more socially deprived relatives with more helpful information on cancer genetics.

Reduction and management of no-shows by family medicine residency practice exemplars

PURPOSE

We wanted to describe the methods used by family medicine residency practices with low no-show rates (rate exemplars) and those able to keep visit rates high despite no-shows (management exemplars).

METHODS

Program directors of US family medicine residency programs were asked to respond to a survey questionnaire. Telephone interviews were conducted with the administrators of rate exemplars (no-show rates of 10% or less) and management exemplars (average of 8 to 10 patient visits per half-day plus high administrator satisfaction with no-show management strategies).

RESULTS

Directors of 14 rate and 8 management exemplars, identified from among the 141 practices (31.5%) that returned the initial survey instrument, were interviewed and subsequently resurveyed. All of the rate exemplars used multiple strategies, including patient education, patient reminders, patient sanctions, and some degree of open-access scheduling. Practices that managed no-shows well encouraged walk-ins and work-ins and overbooked resident schedules either equally or based upon individual no-show rates. Practice exemplars of both types were highly committed to addressing the no-shows problem and were diligent about following their policies and procedures regarding no-shows.

CONCLUSION

Some family medicine residency practices are able to achieve low no-show rates or keep them from affecting practice volume. Those that do use combinations of well-established methods.

Health provider factors associated with nonattendance in pediatric dermatology ambulatory patients

Nonattendance for dermatology appointments disrupts the management of medical delivery and leads to inefficient allocation of resources and lost revenue. The factors that determine nonattendance in pediatric dermatology patients have not been well documented. We investigated health provider factors for nonattendance in pediatric dermatology patients. We assessed the effects of waiting time for an appointment and the timing of the appointment (during the day, week, and year) on nonattendance proportions during a 1 year period. Chi-squared tests were used to analyze statistically significant differences of categorical variables. Logistic regression was used for multivariate analyses. A total of 1696 children visits were included in the study. The overall rate of nonattendance at the dermatology clinic was 30.5%. Nonattendance was 29.7% during the periods between 8 a.m. to 1 p.m. and 3 p.m. to 7 p.m. and 40.7% during the periods between 1 p.m. to 3 p.m. and 7 p.m. to 8 p.m. (p = 0.013). Nonattendance was 21.1% when the waiting time for an appointment was short (1-7 days), 32.5% when it was intermediate (8-14 days) and 43.5% when the wait time was long (15 days and above) (p-value < 0.001). A multivariate logistic regression model demonstrated that the hour of the day and the waiting time for an appointment were significantly associated with nonattendance (p value = 0.009, p value < 0.001, respectively). We conclude that in children attending a dermatology clinic, health provider factors that determine nonattendance include the waiting time for an appointment and the hour of the appointment within the day.

Understanding reasons for asthma outpatient (non)-attendance and exploring the role of telephone and e-consulting in facilitating access to care: exploratory qualitative study

OBJECTIVE

To understand factors influencing patients' decisions to attend for outpatient follow up consultations for asthma and to explore patients' attitudes to telephone and email consultations in facilitating access to asthma care.

DESIGN

Exploratory qualitative study using in depth interviews.

SETTING

Hospital outpatient clinic in West London.

PARTICIPANTS

Nineteen patients with moderate to severe asthma (12 "attenders" and 7 "non-attenders").

RESULTS

Patients' main reasons for attending were the wish to improve control over asthma symptoms and a concern not to jeopardise the valued relationship with their doctor. Memory lapses, poor health, and disillusionment with the structure of outpatient care were important factors implicated in non-attendance. The patients were generally sceptical about the suggestion that greater opportunity for telephone consulting might improve access to care. They expressed concerns about the difficulties in effectively communicating through non-face to face media and were worried that clinicians would not be in a position to perform an adequate physical examination over the telephone. Email and text messaging were viewed as potentially useful for sending appointment reminders and sharing clinical information but were not considered to be acceptable alternatives to the face to face clinic encounter.

CONCLUSIONS

Memory lapses, impaired mobility due to poor health, and frustration with outpatient clinic organisation resulting in long waiting times and discontinuity of care are factors that deter patients from attending for hospital asthma assessments. The idea of telephone review assessments was viewed with scepticism by most study subjects. Particular attention should be given to explaining to patients the benefits of telephone consultations, and to seeking their views as to whether they would like to try them out before replacing face to face consultations with them. Email and text messaging may have a role in issuing reminders about imminent appointments.

Health Provider Determinants of Nonattendance in Pediatric Otolaryngology Patients

INTRODUCTION

Nonattendance for otolaryngology appointments disrupts the management of medical care and leads to ineffective use of resources. The determinants of nonattendance in pediatric otolaryngology patients have not been well documented.

OBJECTIVES

To investigate health provider determinants of nonattendance in pediatric otolaryngology patients.

STUDY DESIGN

We assessed the effects of waiting time for an appointment and the timing of the appointment (during the day, week, and year) on nonattendance proportions during a 1 year period. Chi square tests were used to analyze statistically significant differences of categorical variables. Logistic regression was used for multivariate analyses.

RESULTS

A total of 2,628 pediatric visits were included in the study. The overall proportion of nonattendance at the pediatric otolaryngology clinic was 33.0%. Nonattendance proportions were 32.7% between 7 AM and 9 AM; 28.3% between 9 AM and 2 PM, and 36.5% between 2 PM and 8 PM (P < .001). The proportion of nonattendance was 24.1% when there was a short waiting time for an appointment (0-7 days), and 36.3% when there was an intermediate waiting time (7-15 days), and 36.6% when there was a long waiting time (15 days and above)(P < .001, P < .012, respectively). CONCLUSIVE: Health provider determinants of nonattendance in pediatric otolaryngology clinic appointments include the waiting time for an appointment and the hour of the appointment within the day.

Predictors of failed attendances in a multi-specialty outpatient centre using electronic databases

Background

Failure to keep outpatient medical appointments results in inefficiencies and costs. The objective of this study is to show the factors in an existing electronic database that affect failed appointments and to develop a predictive probability model to increase the effectiveness of interventions.

Methods

A retrospective study was conducted on outpatient clinic attendances at Tan Tock Seng Hospital, Singapore from 2000 to 2004. 22864 patients were randomly sampled for analysis. The outcome measure was failed outpatient appointments according to each patient's latest appointment.

Results

Failures comprised of 21% of all appointments and 39% when using the patients' latest appointment. Using odds ratios from the mutliple logistic regression analysis, age group (0.75 to 0.84 for groups above 40 years compared to below 20 years), race (1.48 for Malays, 1.61 for Indians compared to Chinese), days from scheduling to appointment (2.38 for more than 21 days compared to less than 7 days), previous failed appointments (1.79 for more than 60% failures and 4.38 for no previous appointments, compared with less than 20% failures), provision of cell phone number (0.10 for providing numbers compared to otherwise) and distance from hospital (1.14 for more than 14 km compared to less than 6 km) were significantly associated with failed appointments. The predicted probability model's diagnostic accuracy to predict failures is more than 80%.

Conclusion

A few key variables have shown to adequately account for and predict failed appointments using existing electronic databases. These can be used to develop integrative technological solutions in the outpatient clinic.