Predicting no-shows in paediatric orthopaedic clinics.

BACKGROUND: Clinic 'no shows' (NS) can be a burden on the healthcare system, and efforts to minimise them can reduce lost revenue and improve patient care. Leveraging a large data set via the electronic health record (EHR) has not been previously attempted to identify 'high risk' groups in paediatric orthopaedics. OBJECTIVE: To use discrete data captured by the EHR system to identify predictors of non-attendance at paediatric orthopaedic outpatient appointments. METHODS: Appointments from January 2014 to March 2016 were included. Variables included appointment status, age, gender, type of visit, payor type (government vs private insurance), distance of residence to clinic, region of residence, clinic location, clinic type, and appointment day of the week, hour and month. Classification and regression trees (CART) were constructed to identify predictors of NS. RESULTS: 131 512 encounters were included, 15 543 of which were in the NS group (11.8%). CART identified three predictive covariates for NS: days in between scheduling and appointment, insurance type, and specific orthopaedic clinic type. The combination of covariates provided predictability of NS: if they had ≤38.5 days of waiting for appointment and had private insurance, the NS rate was 7.8% (the best result), compared with waiting >38.5 days for either a fracture or sports clinic, which had an NS rate of 29.3% (OR=4.9). CONCLUSION: Payor type and duration between scheduling and appointment may predict non-attendance at outpatient paediatric orthopaedic appointments. Although these findings allow for predicting and interventions for at-risk groups, even the best performing NS group occurred 7.8% of the time, highlighting the complexity of the NS phenomenon.

Patient non-attendance at urgent referral appointments for suspected cancer and its links to cancer diagnosis and one year mortality: A cohort study of patients referred on the Two Week Wait pathway.

BACKGROUND: The 'Two Week Wait' policy aims to ensure patients with suspected cancer are seen within two weeks of referral. However, patient non-attendance can result in this target being missed. This study aimed to identify predictors of non-attendance; and analyse the relationship between attendance and outcomes including cancer diagnosis and early mortality. METHODS: A cohort study of 109,433 adults registered at 105 general practices, referred to a cancer centre within a large NHS hospital trust (April 2009 to December 2016) on the 'Two Week Wait' pathway. RESULTS: 5673 (5.2%) patients did not attend. Non-attendance was largely predicted by patient factors (younger and older age, male gender, greater deprivation, suspected cancer site, earlier year of referral, greater distance to the hospital) over practice factors (greater deprivation, lower Quality and Outcomes Framework score, lower cancer conversion rate, lower cancer detection rate). 10,360 (9.6%) patients were diagnosed with cancer within six months of referral (9.8% attending patients, 5.6% non-attending patients). Among these patients, 2029 (19.6%) died within 12 months of diagnosis: early mortality risk was 31.3% in non-attenders and 19.2% in attending patients. CONCLUSIONS: Non-attendance at urgent referral appointments for suspected cancer involves a minority of patients but happens in predictable groups. Cancer diagnosis was less likely in non-attending patients but these patients had worse early mortality outcomes than attending patients. The study findings have implications for cancer services and policy.

Sexual health clinic attendance and non-attendance in Britain: findings from the third National Survey of Sexual Attitudes and Lifestyles (Natsal-3).

OBJECTIVES: In Britain, sexual health clinics (SHCs) are the most common location for STI diagnosis but many people with STI risk behaviours do not attend. We estimate prevalence of SHC attendance and how this varies by sociodemographic and behavioural factors (including unsafe sex) and describe hypothetical service preferences for those reporting unsafe sex. METHODS: Complex survey analyses of data from Britain's third National Survey of Sexual Attitudes and Lifestyles, a probability survey of 15 162 people aged 16-74 years, undertaken 2010-2012. RESULTS: Overall, recent attendance (past year) was highest among those aged 16-24 years (16.6% men, 22.4% women), decreasing with age (<1.5% among those 45-74 years). Approximately 15% of sexually-active 16-74 year olds (n=1002 men; n=1253 women) reported 'unsafe sex' (condomless first sex with a new partner and/or ≥2 partners and no condom use, past year); >75% of these had not attended a SHC (past year). However, of non-attenders aged 16-44 years, 18.7% of men and 39.0% of women reported chlamydia testing (past year) with testing highest in women aged <25 years. Of those aged 16-44 years reporting unsafe sex, the majority who reported previous SHC attendance would seek STI care there, whereas the majority who had not would use general practice. CONCLUSION: While most reporting unsafe sex had not attended a SHC, many, particularly younger women, had tested for chlamydia suggesting engagement with sexual health services more broadly. Effective, diverse service provision is needed to engage those at-risk and ensure that they can attend services appropriate to their needs.

Targeted Reminder Phone Calls to Patients at High Risk of No-Show for Primary Care Appointment: A Randomized Trial.

BACKGROUND: No-shows, or missed appointments, are a problem for many medical practices. They result in fragmented care and reduce access for all patients. OBJECTIVE: To determine whether telephone reminder calls targeted to patients at high risk of no-show can reduce no-show rates. DESIGN: Single-center randomized controlled trial. PARTICIPANTS: A total of 2247 primary care patients in a hospital-based primary care clinic at high risk of no-show (>15 % risk) for their appointment in 7 days. INTERVENTION: Seven days prior to their appointment, intervention arm patients were placed in a calling queue to receive a reminder phone call from a patient service coordinator. Coordinators were trained to engage patients in concrete planning. All patients received an automated phone call (usual care). MAIN MEASURES: Primary outcome was no-show rate. Secondary outcomes included arrival rate, cancellation rate, reschedule rate, time to cancellation, and change in revenue. KEY RESULTS: The no-show rate in the intervention arm (22.8 %) was significantly lower (absolute risk difference -6.4 %, p < 0.01, 95 % CI [-9.8 to -3.0 %]) than that in the control arm (29.2 %). Arrival, cancellation, and reschedule rates did not differ significantly. In the intervention arm, rescheduling and cancellations occurred further in advance of the appointment (mean difference, 0.35 days; 95 % CI [0.07-0.64]; p = 0.01). Reimbursement did not differ significantly. CONCLUSIONS: A phone call 7 days prior to an appointment led to a significant reduction in no-shows and increased reimbursement among patients at high risk of no-show. The use of targeted interventions may be of interest to practices taking on increased accountability for population health.

Impact of Urine Drug Screening on No Shows and Dropouts among Chronic Pain Patients: A Propensity-Matched Cohort Study.

BACKGROUND: The last 2 decades have seen a substantial increase in both the prescription of opioids for managing chronic pain, and an increase in opioid-related deaths in the US. Urine drug screening (UDS) is the de facto monitoring tool aimed at detecting and deterring opioid misuse. OBJECTIVE: We study whether administering UDS on pain patients influences post-screening behavior of no-shows and dropouts. STUDY DESIGN: Observational cohort study of electronic medical records. SETTING: Single urban academic pain-clinic. METHODS: A retrospective cohort comparison of patients receiving UDS versus those not receiving UDS was conducted on the entire sample as well as in the propensity score-matched samples in which matching was based on age, gender, pain-score, procedure-scheduled, systolic and diastolic blood pressure (BP), pulse, temperature, physician ID, year of visit, psychology referral, and opioid prescription in the first visit. In addition, we conducted within-subjects logistic-regression to study no-shows and non-proportional hazards survival modeling to study dropout. RESULTS: Analyses of 4,448 clinic visits by 723 pain patients indicated that UDS exposure in the first visit is associated with increased risk of no-show in the second visit (OR = 2.73, P < .0001); no-show rate was 10.24% for those without UDS compared to 23.75% for those with a UDS. Among those tested, the no-show rate was higher for those testing positive for illicit substances (34.57%) than for those testing negative (21.74%). These findings were replicated in 8 different propensity-score matched subsamples aimed at addressing potential non-random selection, as well as in within-subject analysis accounting for individual-level no-show propensity. Non-proportional hazards survival analysis shows that risk of dropout increased by 100.3% with every additional UDS (HR 95% CI: 1.54 to 2.61). LIMITATIONS: Retrospective design, non-randomized sample, single-setting. CONCLUSIONS: The results indicate that UDS is associated with increased no-shows and dropout from clinic subject to limitations of observational studies such as selection bias and confound by unobserved variables. These results serve as a call for additional prospective randomized studies to understand the impact of UDS, and where the patients might go when they dropout from the clinic.