Dataset Information

Breast cancer diagnosis and treatment wait times in specialized diagnostic units compared with usual care: a population-based study.

ABSTRACT: Background:Breast assessment sites (bass) were developed to provide expedited and coordinated care for patients being evaluated for breast cancer (bca) in Ontario. We compared the diagnostic and treatment intervals for patients diagnosed at a bas and for those diagnosed through a usual care (uc) route. Methods:This population-based, cross-sectional study of patients diagnosed with bca in Ontario during 2007-2015 used linked administrative data. "Diagnostic interval" was the time from the earliest cancer-related health care encounter before diagnosis to diagnosis; "treatment interval" was the time from diagnosis to treatment. Diagnosis at a bas was determined from the patient's biopsy and mammography institutions. Interval lengths for the bas and uc groups were compared using multivariable quantile regression, stratified by detection method. Results:The diagnostic interval was shorter for patients who were bas-diagnosed than for those who were uc-diagnosed, with adjusted median differences of -4.0 days [95% confidence interval (ci): -3.2 days to -4.9 days] for symptomatic patients and -5.4 days (95% ci: -4.7 days to -6.1 days) for screen-detected patients. That association was modified by stage at diagnosis, with larger differences in patients with early-stage cancers. In contrast, the treatment interval was longer in patients who were bas-diagnosed than in those who were uc-diagnosed, with adjusted median differences of 4.2 days (95% ci: 3.8 days to 4.7 days) for symptomatic patients and 4.2 days (95% ci: 3.7 days to 4.8 days) for screen-detected patients. Conclusions:Diagnosis of bca through a bas was associated with a shorter diagnostic interval, but a longer treatment interval. Although efficiencies in the diagnostic interval might help to reduce distress experienced by patients, the longer treatment intervals for patients who are bas-diagnosed remain a cause for concern.

SUBMITTER: Webber C

PROVIDER: S-EPMC7467790 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Breast cancer diagnosis and treatment wait times in specialized diagnostic units compared with usual care: a population-based study.

Webber C C Whitehead M M Eisen A A Holloway C M B CMB Groome P A PA

Current oncology (Toronto, Ont.) 20200801 4

<h4>Background</h4>Breast assessment sites (bass) were developed to provide expedited and coordinated care for patients being evaluated for breast cancer (bca) in Ontario. We compared the diagnostic and treatment intervals for patients diagnosed at a bas and for those diagnosed through a usual care (uc) route.<h4>Methods</h4>This population-based, cross-sectional study of patients diagnosed with bca in Ontario during 2007-2015 used linked administrative data. "Diagnostic interval" was the time f ...[more]

PMID: 32905256

Similar Datasets

Project description:BackgroundTimely coordinated diagnostic assessment following an abnormal screening mammogram reduces patient anxiety and may optimise breast cancer prognosis. Since 1998, the Ontario Breast Screening Program (OBSP) has offered organised assessment through Breast Assessment Centres (BACs). For OBSP women seen at a BAC, an abnormal mammogram is followed by coordinated referrals through the use of navigators for further imaging, biopsy, and surgical consultation as indicated. For OBSP women seen through usual care (UC), further diagnostic imaging is arranged directly from the screening centre and/or through their physician; results must be communicated to the physician who is then responsible for arranging any necessary biopsy and/or surgical consultation. This study aims to evaluate factors associated with diagnostic wait times for women undergoing assessment through BAC and UC.MethodsOf the 2 147 257 women aged 50-69 years screened in the OBSP between 1 January 2002 and 31 December 2009, 155 866 (7.3%) had an abnormal mammogram. A retrospective design identified two concurrent cohorts of women diagnosed with screen-detected breast cancer at a BAC (n=4217; 47%) and UC (n=4827; 53%). Multivariable logistic regression analyses examined associations between wait times and assessment and prognostic characteristics by pathway. A two-sided 5% significance level was used.ResultsScreened women with breast cancer were two times more likely to be diagnosed within 7 weeks when assessed through a BAC vs UC (OR=1.91, 95% CI=1.73-2.10). In addition, compared with UC, women assessed through a BAC were significantly more likely to have their first assessment procedure within 3 weeks of their abnormal mammogram (OR=1.25, 95% CI=1.12-1.39), ⩽3 assessment procedures (OR=1.54, 95% CI=1.41-1.69), ⩽2 assessment visits (OR=1.86, 95% CI=1.70-2.05), and ⩾2 procedures per visit (OR=1.41, 95% CI=1.28-1.55). Women diagnosed through a BAC were also more likely than those in UC to have imaging (OR=1.99, 95% CI=1.44-2.75) or a biopsy (OR=3.69, 95% CI=2.64-5.15) vs consultation only at their first assessment visit, and two times more likely to have a core or FNA biopsy than a surgical biopsy (OR=2.08, 95% CI=1.81-2.40). Having ⩽2 assessment visits was more likely to reduce time to diagnosis for women assessed through a BAC compared with UC (BAC OR=10.58, 95% CI=8.96-12.50; UC OR=4.47, 95% CI=3.94-5.07), as was having ⩽3 assessment procedures (BAC OR=4.97, 95% CI=4.26-5.79; UC OR=2.95, 95% CI=2.61-3.33). Income quintile affected wait times only in women diagnosed in UC, with those in the two highest quintiles more likely to receive a diagnosis in 7 weeks.ConclusionsWomen with screen-detected breast cancer in OBSP were more likely to have shorter wait times if they were diagnosed through organised assessment. This might be as a result of women diagnosed through a BAC having more procedures per visit, procedures scheduled in shorter intervals, and imaging or biopsy on their first visit. Given the significant improvement in timeliness to diagnosis, women with abnormal mammograms should be managed through organised assessment.

Project description:Objective: Community addiction treatment agencies have utilized Network for the Improvement of Addiction Treatment (NIATx), a proven implementation strategy, to reduce appointment wait-times. However, its effectiveness at reducing medication access wait-times has not been explored. Thus, we conducted an exploratory analysis to evaluate the impact of the NIATx implementation strategies on reduced wait-times to addiction, psychotropic or both medications for individuals with co-occurring disorders (COD). Methods: In a cluster-randomized waitlist control group design, community addiction treatment agencies (n = 49) were randomized to receive the NIATx strategy (Cohort 1, n = 25) or to a Waitlist control (Cohort 2, n = 24). All agencies had a 12-month active intervention period. The primary outcome was the medication encounter wait-time. A univariate general linear model analysis utilizing a logarithmic (log10) transformation examined medication wait-times improvements. Results: The intent-to-treat analysis for psychotropic medications and both medications (reflecting integrated treatment) showed significant main effects for intervention and time, especially comparing Baseline and Year 1 to Year 2. Conversely, only the main effect for time was significant for addiction medications. Wait-time reductions in Cohort 1 agencies was delayed and occurred in the sustainment phase. Wait-times to a psychotropic, addiction, or both medications encounter declined by 3 days, 4.9 days, and 6.8 days, respectively. For Cohort 2 agencies, reduced wait-times were seen for psychotropic (3.4 days), addiction (6 days), and both medications (4.9 days) during their active implementation period. Same- or next-day medication access also improved. Conclusions: NIATx implementation strategies reduced medication encounter wait-times but timing of agency improvements varied. Despite a significant improvement, a three-week wait-time to receive integrated pharmacological interventions is clinically suboptimal for individuals with a COD in need of immediate intervention. Community addiction treatment agencies should identify barriers and implement changes to improve medication access so that their patients "wait no longer" to receive integrated treatment and medications for their COD.

Project description:BackgroundDepression and anxiety frequently coexist with chronic musculoskeletal pain and can negatively impact patients' responses to standard orthopedic treatments. Nevertheless, mental health is not routinely addressed in the orthopedic care setting. If effective, a digital mental health intervention may be a feasible and scalable method of addressing mental health in an orthopedic setting.ObjectiveWe aimed to compare 2-month changes in mental and physical health between orthopedic patients who received a digital mental health intervention in addition to usual orthopedic care, those who received usual orthopedic care only (without a specific mental health intervention), and those who received in-person care with a psychologist as part of their orthopedic treatment plan.MethodsIn this single-center retrospective cohort study involving ancillary analysis of a pilot feasibility study, 2-month self-reported health changes were compared between a cohort of orthopedic patients who received access to a digital mental health intervention (Wysa) and 2 convenience sample comparison cohorts (patients who received usual orthopedic care without a specific mental health intervention and patients who received in-person care with a psychologist as part of their orthopedic treatment plan). All patients were 18 years or older and reported elevated symptoms of depression or anxiety at an orthopedic clinic visit (Patient-Reported Outcomes Measurement Information System [PROMIS] Depression or Anxiety score ≥55). The digital intervention was a multi-component mobile app that used chatbot technology and text-based access to human counselors to provide cognitive behavioral therapy, mindfulness training, and sleep tools, among other features, with an emphasis on behavioral activation and pain acceptance. Outcomes of interest were between-cohort differences in the 2-month longitudinal changes in PROMIS Depression and Anxiety scores (primary outcomes) and PROMIS Pain Interference and Physical Function scores (secondary outcomes).ResultsAmong 153 patients (mean age 55, SD 15 years; 128 [83.7%] female; 51 patients per cohort), patients who received the digital mental health intervention showed clinically meaningful improvements at the 2-month follow-up for all PROMIS measures (mean longitudinal improvement 2.8-3.7 points; P≤.02). After controlling for age and BMI, the improvements in PROMIS Depression, Pain Interference, and Physical Function were meaningfully greater than longitudinal changes shown by patients who received usual orthopedic care (mean between-group difference 2.6-4.8 points; P≤.04). Improvements in PROMIS Physical Function were also meaningfully greater than longitudinal changes shown by patients who received in-person psychological counseling (mean between-group difference 2.4 points; P=.04).ConclusionsPatients who received a digital mental health intervention as part of orthopedic care reported greater 2-month mean improvements in depression, pain interference, and physical function than patients who received usual orthopedic care. They also reported a greater mean improvement in physical function and comparable improvements in depression, anxiety, and pain interference compared with orthopedic patients who received in-person psychological counseling.

Project description:ImportanceTimely access to medical care is an important determinant of health and well-being. The US Congress passed the Veterans Access, Choice, and Accountability Act in 2014 and the VA MISSION (Maintaining Systems and Strengthening Integrated Outside Networks) Act in 2018, both of which allow veterans to access care from community-based clinicians, but geographic variation in appointment wait times after the passage of these acts have not been studied.ObjectiveTo describe geographic variation in wait times experienced by veterans for primary care, mental health, and other specialties.Design, setting, and participantsThis is a cross-sectional study using data from the Veterans Health Administration (VHA) Corporate Data Warehouse. Participants include veterans who sought medical care from January 1, 2018, to June 30, 2021. Data analysis was performed from February to June 2022.ExposuresReferral to either VHA or community-based clinicians.Main outcomes and measuresTotal appointment wait times (in days) for 3 care categories: primary care, mental health, and all other specialties. VHA medical centers are organized into regions called Veterans Integrated Services Networks (VISNs); wait times were aggregated to the VISN level.ResultsThe final sample included 22 632 918 million appointments for 4 846 892 unique veterans (77.3% male; mean [SD] age, 61.6 [15.5] years). Among non-VHA appointments, mean (SD) VISN-level appointment wait times were 38.9 (8.2) days for primary care, 43.9 (9.0) days for mental health, and 41.9 (5.9) days for all other specialties. Among VHA appointments, mean (SD) VISN-level appointment wait times were 29.0 (5.5) days for primary care, 33.6 (4.6) days for mental health, and 35.4 (2.7) days for all other specialties. There was substantial geographic variation in appointment wait times. Among non-VHA appointments, VISN-level appointment wait times ranged from 25.4 to 52.4 days for primary care, from 29.3 to 65.7 days for mental health, and from 34.7 to 54.8 days for all other specialties. Among VHA appointments, wait times ranged from 22.4 to 43.4 days for primary care, from 24.7 to 42.0 days for mental health, and from 30.3 to 41.9 days for all other specialties. There was a correlation between wait times across care categories and setting (VHA vs community care).Conclusions and relevanceThis cross-sectional study found substantial variation in wait times across care type and geography, and VHA wait times in a majority of VISNs were lower than those for community-based clinicians, even after controlling for differences in specialty mix. These findings suggest that liberalized access to community care under the Veterans Access, Choice, and Accountability Act and the VA MISSION Act may not result in lower wait times within these regions.

Dataset Information

Breast cancer diagnosis and treatment wait times in specialized diagnostic units compared with usual care: a population-based study.

Publications

Breast cancer diagnosis and treatment wait times in specialized diagnostic units compared with usual care: a population-based study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets