Audit‐based measures of overuse of medical care in Australian hospital practice

Clinical Reasoning Skills Among Second-Phase Medical Students in West Bengal, India: An Exploratory Study

Introduction Proper application of clinical reasoning skills is essential to reduce diagnostic and management errors. Explicit inclusion of training and assessment of clinical reasoning skills is the demand of time. The study intended to measure the clinical reasoning skills of second-phase undergraduate students in a medical college in West Bengal, India, and its distribution across several individual variables. Methods The clinical reasoning skills of 105 undergraduate medical students were assessed in a cross-sectional exploratory study using key feature questions (KFQs) with the partial credit scoring system. Six case vignettes aligned to the core competencies in the subject of pharmacology, pathology, and microbiology were designed and validated by the subject material experts for this purpose. The responses of the participants were collected through Google Forms (Google, Mountain View, CA) after obtaining written informed consent. The scores obtained in all KFQs were added and expressed in percentage of the maximum attainable score. Results The mean (±SD) clinical reasoning score of the participants was 42.5 (±12.6). Only 29.6% of respondents scored ≥ 50. Students with higher subjective economic status (p-value = 0.01) and perceived autonomy (p-value < 0.001) were more likely to have higher clinical reasoning scores. The marks obtained in previous summative examinations were significantly correlated with clinical reasoning scores. Conclusion Average score < 50.0 and inability to score ≥ 50.0 by more than two-thirds of the participants reflected the deficit in the clinical reasoning skills of second-phase MBBS students. The association of clinical reasoning skills with economic status, autonomy, and previous academic performances needs further exploration.

Cutting back on low-value health care practices supports sustainable kidney care

July 2023 marked the hottest month on record, underscoring the urgent need for action on climate change. The imperative to reduce carbon emissions extends to all sectors, including health care, with it being responsible for 5.5% of global emissions. In decarbonizing health care, although much attention has focused on greening health care infrastructure and procurement, less attention has focused on reducing emissions through demand-side management. An important key element of this is reducing low-value care, given that ≈20% of global health care expenditure is considered low value. "Value" in health care, however, is subjective and dependent on how health outcomes are regarded. This review, therefore, examines the 3 main value perspectives specific to health care. Clinical effectiveness defines low-value care as interventions that offer little to no benefit or have a risk of harm exceeding benefits. Cost-effectiveness compares health outcomes versus costs compared with an alternative treatment. In this case, low-value care is care greater than a societal willingness to pay for an additional unit of health (quality-adjusted life year). Last, community perspectives emphasize the value of shared decision-making and patient-centered care. These values sit within broader societal values of ethics and equity. Any reduction in low-value care should, therefore, also consider patient autonomy, societal value perspectives and opportunity costs, and equity. Deimplementing entrenched low-value care practices without unnecessarily compromising ethics and equity will require tailored strategies, education, and transparency.

Cost-effectiveness of a rule-out algorithm of acute myocardial infarction in low-risk patients: emergency primary care versus hospital setting

Aims

Hospital admissions of patients with chest pain considered as low risk for acute coronary syndrome contribute to increased costs and crowding in the emergency departments. This study aims to estimate the cost-effectiveness of assessing these patients in a primary care emergency setting, using the European Society of Cardiology (ESC) 0/1-h algorithm for high-sensitivity cardiac troponin T, compared to routine hospital management.

Methods

A cost-effectiveness analysis was conducted. For the primary care estimates, costs and health care expenditure from the observational OUT-ACS (One-hoUr Troponin in a low-prevalence population of Acute Coronary Syndrome) study were compared with anonymous extracted administrative data on low-risk patients at a large general hospital in Norway. Patients discharged home after the hs-cTnT assessment were defined as low risk in the primary care cohort. In the hospital setting, the low-risk group comprised patients discharged with a non-specific chest pain diagnosis (ICD-10 codes R07.4 and Z03.5). Loss of health related to a potential increase in acute myocardial infarctions the following 30-days was estimated. The primary outcome measure was the costs per quality-adjusted life year (QALY) of applying the ESC 0/1-h algorithm in primary care. The secondary outcomes were health care costs and length of stay in the two settings.

Results

Differences in costs comprise personnel and laboratory costs of applying the algorithm at primary care level (€192) and expenses related to ambulance transports and complete hospital costs for low-risk patients admitted to hospital (€1986). Additional diagnostic procedures were performed in 31.9% (181/567) of the low-risk hospital cohort. The estimated reduction in health care cost when using the 0/1-h algorithm outside of hospital was €1794 per low-risk patient, with a mean decrease in length of stay of 18.9 h. These numbers result in an average per-person QALY gain of 0.0005. Increased QALY and decreased costs indicate that the primary care approach is clearly cost-effective.

Conclusion

Using the ESC 0/1-h algorithm in low-risk patients in emergency primary care appears to be cost-effective compared to standard hospital management, with an extensive reduction in costs and length of stay per patient.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08697-6.

The carbon footprint of hospital diagnostic imaging in Australia

BACKGROUND

Pathology testing and diagnostic imaging together contribute 9% of healthcare's carbon footprint. Whilst the carbon footprint of pathology testing has been undertaken, to date, the carbon footprint of the four most common imaging modalities is unclear.

METHODS

We performed a prospective life cycle assessment at two Australian university-affiliated health services of five imaging modalities: chest X-ray (CXR), mobile chest X-ray (MCXR), computerised tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US). We included scanner electricity use and all consumables and associated waste, including bedding, imaging contrast, and gloves. Analysis was performed using both attributional and consequential life cycle assessment methods. The primary outcome was the greenhouse gas footprint, measured in carbon dioxide equivalent (CO₂e) emissions.

FINDINGS

Mean CO₂e emissions were 17·5 kg/scan for MRI; 9·2 kg/scan for CT; 0·8 kg/scan for CXR; 0·5 kg/scan for MCXR; and 0·5 kg/scan for US. Emissions from scanners from standby energy were substantial. When expressed as emissions per additional scan (results of consequential analysis) impacts were lower: 1·1 kg/scan for MRI; 1·1 kg/scan for CT; 0·6 kg/scan for CXR; 0·1 kg/scan for MCXR; and 0·1 kg/scan for US, due to emissions from standby power being excluded.

INTERPRETATION

Clinicians and administrators can reduce carbon emissions from diagnostic imaging, firstly by reducing the ordering of unnecessary imaging, or by ordering low-impact imaging (X-ray and US) in place of high-impact MRI and CT when clinically appropriate to do so. Secondly, whenever possible, scanners should be turned off to reduce emissions from standby power. Thirdly, ensuring high utilisation rates for scanners both reduces the time they spend in standby, and apportions the impacts of the reduced standby power of a greater number of scans. This therefore reduces the impact on any individual scan, maximising resource efficiency.

FUNDING

Healthy Urban Environments (HUE) Collaboratory of the Maridulu Budyari Gumal Sydney Partnership for Health, Education, Research and Enterprise MBG SPHERE. The National Health and Medical Research Council (NHMRC) PhD scholarship.

Developing critical thinking skills for delivering optimal care

Healthcare systems across the world are challenged with problems of misdiagnosis, non-beneficial care, unwarranted practice variation and inefficient or unsafe practice. In countering these shortcomings, clinicians must be able to think critically, interpret and assimilate new knowledge, deal with uncertainty and change behaviour in response to compelling new evidence. Three critical thinking skills underpin effective care: clinical reasoning, evidence-informed decision-making and systems thinking. It is important to define these skills explicitly, explain their rationales, describe methods of instruction and provide examples of optimal application. Educational methods for developing and refining these skills must be embedded within all levels of clinician training and continuing professional development.

Pre-hospital One-Hour Troponin in a Low-Prevalence Population of Acute Coronary Syndrome: OUT-ACS study

Objective

The European Society of Cardiology 0/1-hour algorithm for high-sensitivity cardiac troponin T (hs-cTnT) has demonstrated high rule-out safety in large hospital validation cohorts. We aimed to validate the algorithm in a primary care setting, where patients have a lower pretest probability for acute coronary syndrome.

Methods

This prospective, observational, diagnostic study included patients with acute non-specific chest pain admitted to a primary care emergency clinic in Oslo, Norway, from November 2016 to October 2018. hs-cTnT was measured after 0, 1 and 4 hours. The primary outcome measure was the diagnostic performance of the 0/1-hour algorithm, the 90-day incidence of AMI or all-cause death the secondary.

Results

Among 1711 included patients, 61 (3.6%) were diagnosed with AMI. By applying the algorithm, 1311 (76.6%) patients were assigned to the rule-out group. The negative predictive value was 99.9% (95% CI 99.5% to 100.0%), the sensitivity and specificity 98.4% (91.2–100.0) and 79.4% (77.4–81.3), respectively. Sixty-six (3.9%) patients were triaged towards rule-in, where 45 were diagnosed with AMI. The corresponding positive predictive value was 68.2% (58.3–76.7), sensitivity 73.8% (60.9–84.2), and specificity 98.7% (98.1–99.2). Among 334 (19.5%) patients assigned to the observation group in need of further tests, 15 patients had an AMI. The following 90 days, five new patients experienced an AMI and nine patients died, with a low incidence in the rule-out group (0.3%).

Conclusion

The 0/1-hour algorithm for hs-cTnT seems safe, efficient and applicable for an accelerated assessment of patients with non-specific chest pain in a primary care emergency setting.

Trial registration number

NCT02983123.

Appropriateness of admission to rehabilitation: definition of a set of criteria and rules through the application of the Delphi method

BACKGROUND

Controlling inappropriateness of care is an essential issue, especially in rehabilitation medicine. In fact, admitting a patient to a rehabilitation hospital or unit is a complex decision also due to the absence of shared and objective admission criteria.

AIM

The aim was to define clinical admission criteria and rules in rehabilitation medicine.

DESIGN

Survey based on the application of the Delphi method on a sample of rehabilitation medicine experts.

SETTING

Administration of electronic online questionnaires concerning appropriateness of admission to intensive rehabilitation.

POPULATION

Volunteer sample of 53 experts with the following inclusion criteria: being members of the Italian Society of Physical and Rehabilitation Medicine, having practical experience in the research field, agreeing to the confidentiality of the information and being skilled in both rehabilitation and healthcare organization.

METHODS

A three-round Delphi survey was conducted according to international guidelines. The two initial rounds consisted of an electronic online questionnaire while in the third one a report of the results was provided to the participants. The experts had to score their agreement with each item in the questionnaires, based on either a Likert scale or a dichotomous statement. Consensus between the experts was assessed.

RESULTS

A total of 53 health professionals completed the Delphi survey. 19 out of 20 Italian regions were represented. The first round consisted of 8 multiple-choice questions. The second round was designed according to the suggestions provided by the panelists in the previous one and consisted of a twelve items questionnaire. At the end of the survey, seven criteria of appropriateness of admission to rehabilitation were identified and five rules defining an appropriate admission to a rehabilitation facility were elaborated.

CONCLUSIONS

This study represents an attempt to create a worthwhile and reliable tool for a more conscious clinical practice in admission to rehabilitation, based on a set of shared criteria and rules.

CLINICAL REHABILITATION IMPACT

To increase appropriateness of admission to rehabilitation. Improving appropriateness in healthcare delivery must be a primary goal in order to improve healthcare quality, save money and ensure system sustainability.