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Development and Evaluation of a Novel Survey Tool Assessing Inpatient Consult Service Performance.

ABSTRACT: Subspecialty consultation in inpatient medicine is increasing, and enhancing performance of consultation services may have a broad-reaching impact. Multisource feedback is an important tool in assessing competence and improving performance. A mechanism for primary team resident feedback on performance of consult services has not been described.We developed and evaluated an instrument designed to assess internal medicine (IM) subspecialty inpatient consult service performance. We hypothesized that the instrument would be feasible to administer and provide important information to fellowship directors.The instrument was administered in 2015 and 2016 at a single academic center. All IM residents were invited to evaluate 10 IM subspecialty consult services on 4 items and an overall satisfaction rating. The instrument allowed for free-text feedback to fellows. Program directors completed another survey assessing the impact of the consult service evaluation.A total of 113 residents responded (47 in 2015 and 66 in 2016, for a combined response rate of 35%). Each of the 4 items measured (communication, professionalism, teaching, and pushback) correlated significantly with the overall satisfaction rating in univariate and multivariate analyses. There were no differences in ratings across postgraduate year or year of administration. There was considerable variation in ratings among the services evaluated. The 7 program directors who provided feedback found the survey useful and made programmatic changes following evaluation implementation.A primary team resident evaluation of inpatient medicine subspecialty consult services is feasible, provides valuable information, and is associated with changes in consult service structure and curricula.

SUBMITTER: Miloslavsky EM

PROVIDER: S-EPMC5734333 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Development and Evaluation of a Novel Survey Tool Assessing Inpatient Consult Service Performance.

Miloslavsky Eli M EM Chang Yuchiao Y

Journal of graduate medical education 20171201 6

<h4>Background</h4>Subspecialty consultation in inpatient medicine is increasing, and enhancing performance of consultation services may have a broad-reaching impact. Multisource feedback is an important tool in assessing competence and improving performance. A mechanism for primary team resident feedback on performance of consult services has not been described.<h4>Objective</h4>We developed and evaluated an instrument designed to assess internal medicine (IM) subspecialty inpatient consult ser ...[more]

PMID: 29270268

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Project description:BackgroundIndividuals on the autism spectrum face significant disparities in health and physicians often report difficulties in providing care to autistic patients. In order to improve the quality of care autistic individuals receive, it is important to identify the barriers that physicians experience in providing care so that these may be addressed. This paper reports the initial development and preliminary evaluation of a physician-report 'Barriers to Providing Healthcare' measurement tool.MethodAn established taxonomy of healthcare barriers for autistic individuals informed the initial draft of a 22-item measurement tool. This measurement tool was distributed to physicians working in various healthcare specialties and settings. Exploratory factor analysis (EFA) was conducted to determine the construct validity of the tool; discriminant validity between, and internal consistency of, the resultant factors were assessed. Multiple regressions were used to explore variables potentially associated with barriers endorsed by physicians.ResultsA total of 203 physicians were included in the analyses. The EFA resulted in a 17-item tool with three distinct factors which explained 37.6% of the variance: 1) Patient-related barriers (Cronbach's α = 0.83; e.g., the patient's reactivity to the healthcare environment); 2) Healthcare provider (HCP)/family-related barriers (Cronbach's α = 0.81; e.g., a lack of providers willing to work with autistic patients); and 3) System-related barriers (Cronbach's α = 0.84; e.g., there is a lack of support for patients and families). Discriminant validity between the factors was adequate (r < .8). The barriers that were most frequently endorsed as occurring 'often' or 'very often' included a lack of support for patients and families (endorsed by 79.9% of physicians); communication difficulties (73.4%); and a lack of coordination between services (69.9%). The regression analyses identified no significant associated variables.ConclusionA preliminary version of a novel physician-report tool to assess barriers to providing care to autistic patients has been developed although further validation work is required. The use of this tool will help physicians to identify issues specific to different medical specialities and healthcare settings. This information may help identify the supports physicians require to recognise and implement the required accommodations. Future research which elucidates barriers to healthcare provision for autistic patients is required to support systemic change in healthcare so as to improve care experiences and health outcomes for people on the autism spectrum.

Project description:Introduction:Genetic-guided selection of non-oncologic medications is not commonly practiced in general, and at University of California, San Francisco (UCSF) Health, specifically. Understanding the unique position of clinicians with respect to clinical pharmacogenetics (PG) at a specific institution or practice is fundamental for implementing a successful PG consult service. Objectives:To assess clinicians' current practices, needs, and interests with respect to clinical PG at UCSF Health, a large tertiary academic medical center. Methods:A list of 42 target medications with clinical PG recommendations was complied. Clinical specialties that routinely used the target medications were identified. A 12-question survey focused on practice of PG for target medications was developed. Pharmacists and physicians were surveyed anonymously in several clinical specialties. Survey results were analyzed using descriptive statistics. Results:Of the 396 clinicians surveyed, 76 physicians and 59 pharmacists participated, resulting in 27% and 50% average response rates, respectively. The current use of PG in clinical practice for physicians and pharmacists was 29% and 32%, respectively, however this number varied across clinical specialties from 0% to 80%. Of clinicians whom reported they do not currently apply PG, 63% of physicians and 54% of pharmacists expressed interest in integrating PG. However, the level of interest varied from 20% to 100% across specialties. Of the respondents, 64% of physicians and 56% of pharmacists elected to provide contact information to investigators to further discuss their interest related to clinical PG. Conclusions:While PG is not uniformly practiced at UCSF Health, there is considerable interest in utilizing PG by the respondents. Our approach was successful at identifying clinicians and services interested in PG for specific drug-gene pairs. This work has set a foundation for next steps to advance PG integration at UCSF Health. Clinicians can adopt our approach as preliminary work to build a clinical PG program at their institutions.

Project description:BackgroundRemoval of total joint arthroplasty from the inpatient-only list has created significant confusion regarding which patients qualify for an inpatient designation. The purpose of this study is to develop and validate a novel predictive tool for assessing who will be an outpatient vs inpatient after total knee arthroplasty (TKA).MethodsA cohort of Medicare patients undergoing primary TKA between January 2018 and September 2019 were retrospectively reviewed. Baseline demographics and patient characteristics were obtained, and their distributions for outpatient (less than 2 midnights) and inpatient stay were assessed. Subsequently, a XGBoost machine learning model was trained using 80% of the TKA patients, and the remaining 20% of patients were involved in testing the model's performance in terms of accuracy and the average area under the receive operating characteristic curve.ResultsEight hundred ninety-nine Medicare patients underwent TKA at our institution between January 2018 and September 2019. Of which, 625 patients had outpatients stays, and 274 qualified for inpatient designation. Significant associations were demonstrated between inpatient visits and the following factors: higher body mass index, increased age, better functional scores, multidimensional fatigue inventory, Charlson Comorbidity Index, American Society of Anesthesiologists score, female gender, cardiac history, and the Revised Cardiac Risk Index. The XGBoost model for predicting an inpatient or outpatient stay was 63.3% accurate, with area under the receive operating characteristic curve of 68.8%.ConclusionsUsing readily available key baseline characteristics, functional scores, and comorbidities, this machine-learning model accurately predicts the probability of an "outpatient" vs "inpatient" stay after TKA in the Medicare population. body mass index, age, VR12 functional scores, and multidimensional fatigue inventory scores had the highest influence on this predictive model.

Dataset Information

Development and Evaluation of a Novel Survey Tool Assessing Inpatient Consult Service Performance.

Publications

Development and Evaluation of a Novel Survey Tool Assessing Inpatient Consult Service Performance.

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