Dataset Information

Appointment scheduling and cost in first opinion small animal practice.

ABSTRACT: Approximately half of first opinion, small animal consultations exceed their allocated time and there's a growing call in the UK for longer consults. The aim of this study was to investigate and describe allocated appointment length in first opinion, small animal practice in the UK. Almost half (49.8%) of consults were scheduled for 15 min, with a further 39.4% scheduled for 10 min. Nearly all participants (97.1%) reported flexibility when booking appointments, scheduling longer appointments for conditions predicted to require more time. However, the majority (68.1%) reported no additional cost charged to the client for a longer consult. Furthermore, 54.7% of the survey respondents offered nurse appointments free of charge. A restructured approach to consult scheduling for both Veterinary Surgeon and Registered Veterinary Nurse (RVN) consultations could help to improve workforce wellbeing, utilise the vast knowledge and skill sets of RVNs and improve financial metrics.

SUBMITTER: Corah L

PROVIDER: S-EPMC6820084 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Appointment scheduling and cost in first opinion small animal practice.

Corah Louise L Lambert Alison A Cobb Kate K Mossop Liz L

Heliyon 20191024 10

Approximately half of first opinion, small animal consultations exceed their allocated time and there's a growing call in the UK for longer consults. The aim of this study was to investigate and describe allocated appointment length in first opinion, small animal practice in the UK. Almost half (49.8%) of consults were scheduled for 15 min, with a further 39.4% scheduled for 10 min. Nearly all participants (97.1%) reported flexibility when booking appointments, scheduling longer appointments for ...[more]

PMID: 31687484

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Project description:BackgroundCost-sharing in health insurance plans creates incentives for patients to shop for lower prices, but it is unknown what price information patients can obtain when scheduling office visits.ObjectiveTo determine whether new patients can obtain price information for a primary care visit and identify variation across insurance types, offices, and geographic areas.DesignSimulated patient methodology in which trained interviewers posed as non-elderly adults seeking new patient primary care appointments. Caller insurance type (employer-sponsored insurance [ESI], Marketplace, or uninsured) and plan were experimentally manipulated. Callers who were offered a visit asked for price information. Unadjusted means and regression-adjusted differences by insurance, office types, and geography were calculated.ParticipantsCalls to a representative sample of primary care offices in ten states in 2014: Arkansas, Georgia, Iowa, Illinois, Massachusetts, Montana, New Jersey, Oregon, Pennsylvania, and Texas (N?=?7865).Main measuresCallers recorded whether they were able to obtain a price. If not, they recorded whether they were referred to other sources for price information.Key resultsOverall, 61.8% of callers with ESI were able to obtain a price, versus 89.2% of uninsured and 47.3% of Marketplace callers (P?<?0.001 for differences). Price information was also more readily available in small offices and in counties with high uninsured rates. Among callers not receiving a price, 72.1% of callers with ESI were referred to other sources (billing office or insurance company), versus 25.8% of uninsured and 50.9% of Marketplace callers (P?<?0.001). A small fraction of insured callers were told their visit would be free. If not free, mean visit prices ranged from $157 for uninsured to $165 for ESI (P?<?0.05). Prices were significantly lower at federally qualified health centers (FQHCs), smaller offices, and in counties with high uninsured and low-income rates.ConclusionsPrice information is often unavailable for privately insured patients seeking primary care visits at the time a visit is scheduled.

Project description:BackgroundIntegrated dental services within the Health System, particularly at primary health care, are crucial to reverse the current impact of oral diseases, which are among the most prevalent diseases worldwide. However, the use of dental services is determined by complex phenomena related to the individual, the environment and practices in which care is offered. Therefore, factors associated with dental appointments scheduling can affect positively or negatively the use of dental services. The aim of the present study was to evaluate the indicators for dental appointment scheduling in Primary Health Care (PHC).MethodsThe present is a cross-sectional analytical study that used data from the external assessment of the third cycle of the National Program for Improving Access and Quality in Primary Care (PMAQ-AB), carried out between 2017 and 2018, in Brazil. The final sample consisted of 85,231 patients and 22,475 Oral Health teams (OHTs). The outcome variable was the fact that the user sought for a dental appointment at the Primary Health Care Unit. A multilevel analysis was carried out to verify the association between individual variables (related to users) and contextual variables (related to the OHTs) in relation to the outcome.ResultsOnly 58.1% of the users interviewed at these Primary Health Care Units seek the available dental care. The variables with the greatest effect on the outcome were the patient's age up to 42 years old (OR = 2.03, 95% CI: 1.96-2.10), at individual level, and 'oral health teams that assisted no more than a single family health team (FHT)' (OR = 1.29, 95% CI: 1.23-1.36) at contextual level. Other variables were also associated with the outcome, but with a smaller effect size.ConclusionIn conclusion, users' age and work process of OHT were indicators for dental appointment scheduling. Our results suggest that when OHT put the National Oral Health Policy guidelines into practice, by assisting only one FHT, the chance for PHC users seeking dental appointments is higher than OHTs that assist more than one FHT. Regarding age, patients aged up to 42 years are more likely to seek an appointment with a dentist.

Project description:BackgroundEvery week, radiotherapy centers face the complex task of scheduling hundreds of treatment sessions amongst the available linear accelerators. With the increase in cancer patient numbers, manually creating a feasible and efficient schedule has shown to be a difficult, time-consuming task. Although operations research models have been increasingly reported upon to optimize patient care logistics, there is almost no scientific evidence of implementation in practice.MethodsA mathematical operations research model was adapted to generate radiotherapy treatment schedules in two Dutch centers. The model was iteratively adjusted to fulfill the technical and medical constraints of each center until a valid model was attained. Patient data was collected for the planning horizon of one week, and the feasibility of the obtained schedules was verified by the staff of each center. The resulting optimized solutions are compared with the ones manually developed in practice.ResultsThe weekly schedule was improved in both centers by decreasing the average standard deviation between sessions' starting times from 103.0 to 50.4 minutes (51%) in one center, and the number of gaps in the schedule from 18 to 5 (72%) in the other. The number of patients requiring linac switching between sessions has also decreased from 71 to 0 patients in one center, and from 43 to 2 in the other. The automated process required 5 minutes and 1.5 hours of computation time to find an optimal weekly patient schedule, respectively, as opposed to approximately 1.5 days when performed manually for both centers.ConclusionsThe practical application of a theoretical operations research model for radiotherapy treatment scheduling has provided radiotherapy planners a feasible, high-quality schedule in an automated way. Iterative model adaptations performed in small steps, early engagement of stakeholders, and constant communication proved to facilitate the implementation of operations research models into clinical practice.

Dataset Information

Appointment scheduling and cost in first opinion small animal practice.

Publications

Appointment scheduling and cost in first opinion small animal practice.

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