Improving laboratory test utilisation at the multihospital Yale New Haven Health System

Managing Resource Utilization Cost of Laboratory Tests for Patients on Chemotherapy in Johns Hopkins Aramco Healthcare

Introduction

Laboratory testing is a fundamental diagnostic and prognostic tool to ensure the quality of healthcare, treatment, and responses. This study aimed to evaluate the cost of laboratory tests performed for patients undergoing chemotherapy treatment in the oncology treatment center at Johns Hopkins Aramco Healthcare in Saudi Arabia. Additionally, we aimed to reduce the cost of unnecessary laboratory tests in a 1-year period.

Methods

This was a quality improvement study with a quasi-experimental design using DMAIC methodology. The intervention strategy involved educating staff about adhering to the British Columbia Cancer Agency (BCCA) guidelines when ordering laboratory tests for chemotherapy patients, then integrating those guidelines into the electronic health record system. Data were collected for 200 randomly selected cases with 10 different chemotherapy protocols before and after the intervention. A paired t test was used to analyze differences in mean cost for all laboratory tests and unnecessary testing before and after the intervention.

Results

A significant cost reduction was achieved for unnecessary laboratory tests (77%, p < 0.01) when following the BCCA guidelines. In addition, the mean cost of all laboratory tests (including necessary and unnecessary) was significantly reduced by 45.5% (p = 0.023).

Conclusion

Lean thinking in clinical practice, realized by integrating a standardized laboratory test guided by BCCA guidelines into the electronic health record, significantly reduced financial costs within 1 year, thereby enhancing efficient resource utilization in the organization. This quality improvement project may serve to increase awareness of further efforts to improve resource utilization for other oncology treatment protocols.

Utility of Investigations, History, and Physical Examination in "Medical Clearance" of Psychiatric Patients: A Meta-Analysis

OBJECTIVE

Few reviews and no meta-analyses have explored the utility of investigations, such as laboratory tests, among patients presenting with psychiatric symptoms, and none has explored the yield of history and physical examination. A meta-analysis of studies exploring the utility of "medical clearance" among adult psychiatric patients was conducted.

METHODS

PubMed, PsycInfo, and Web of Science were systematically searched from inception until February 15, 2021. Primary outcome was detection by investigations (e.g., bloodwork and imaging), history, or physical examination of an illness that caused or aggravated psychiatric symptoms or was comorbid and that resulted in change in the patient's diagnosis or management ("yield"). A mixed-effects meta-analysis with inverse-variance weighting was used to pool results.

RESULTS

Twenty-five cross-sectional studies were included. Pooled yield of investigations was 1.1% (95% confidence interval [CI]=0.5%-2.2%), although yield was relatively higher among disoriented, agitated, or older patients. Yield was higher in the inpatient setting, compared with the emergency room, with similar results by approach (protocolized versus nonprotocolized). Compared with investigations, yield of history and physical examination was higher (15.6%, 95% CI=9.1%-25.6%, and 14.9%, 95% CI=8.1%-25.9%, respectively), with nonsignificant differences by evaluator (psychiatrist versus nonpsychiatrist) for physical examination.

CONCLUSIONS

Investigations were of relatively low yield, especially when weighed against cost and potential harm, and they should not be routinely conducted for patients presenting with primarily psychiatric complaints, although certain subgroups may benefit. History and physical examination, by contrast, should be undertaken for all patients, ideally with participation of the consulting psychiatrist.

An Initiative to Decrease Laboratory Testing in a NICU

BACKGROUND AND OBJECTIVES

Laboratory testing is performed frequently in the NICU. Unnecessary tests can result in increased costs, blood loss, and pain, which can increase the risk of long-term growth and neurodevelopmental impairment. Our aim was to decrease routine screening laboratory testing in all infants admitted to our NICU by 20% over a 24-month period.

METHODS

We designed and implemented a multifaceted quality improvement project using the Institute for Healthcare Improvement's Model for Improvement. Baseline data were reviewed and analyzed to prioritize order of interventions. The primary outcome measure was number of laboratory tests performed per 1000 patient days. Secondary outcome measures included number of blood glucose and serum bilirubin tests per 1000 patient days, blood volume removed per 1000 patient days, and cost. Extreme laboratory values were tracked and reviewed as balancing measures. Statistical process control charts were used to track measures over time.

RESULTS

Over a 24-month period, we achieved a 26.8% decrease in laboratory tests performed per 1000 patient days (∽51 000 fewer tests). We observed significant decreases in all secondary measures, including a decrease of almost 8 L of blood drawn and a savings of $258 000. No extreme laboratory values were deemed attributable to the interventions. Improvement was sustained for an additional 7 months.

CONCLUSIONS

Targeted interventions, including guideline development, dashboard creation and distribution, electronic medical record optimization, and expansion of noninvasive and point-of-care testing resulted in a significant and sustained reduction in laboratory testing without notable adverse effects.

[Laboratory testing in intensive care medicine]

Despite the tremendous technological developments in medicine, careful history-taking and clinical examination remain the cornerstones of diagnostics. Numerous laboratory tests are ordered in intensive care and emergency medicine. The rate of overutilization of these tests during initial patient admission is almost 50%. Patient history may be frequently insufficient for conducting targeted laboratory testing, and concern about not overlooking a pathology also contributes to laboratory test overutilization. On the other hand, laboratory test profiles are frequently defined a priori to simplify the management process. However, these profiles are commonly based on symptoms rather than on a suspected diagnosis. Several laboratory variables are outside the normal range in critically ill patients. However, normal ranges are defined on the basis of data from healthy subjects, and these do not allow for a clear distinction between stress adaptation and clinically relevant changes that require correction. Pathophysiological changes due to the acute injury in critically ill patients and the reaction of the organism to the injury or even to the treatment itself can lead to changes in laboratory values. Untargeted laboratory tests contribute to iatrogenic anemia and increased costs. The results of such tests are either hardly noticed or, in the worst case, lead to further unnecessary diagnostic steps and unjustified therapeutic measures. Point-of-care laboratory tests, including blood gas analysis, blood count, serum electrolytes, and lactate, to assess the patient's homeostatic state and laboratory data for the relevant critical care scores are uniformly required. Beyond that, every laboratory test should be chosen wisely based on a concrete clinical question.

Reference Laboratory Testing for Neurologic Disorders

Laboratory testing plays a critical role in the diagnosis and monitoring of patients with neurologic disorders. Although common tests are often performed in a central hospital laboratory, an increasing number of essential but esoteric tests are performed at reference laboratories or other outside health care facilities. In this article, we analyze recent trends in neurologic disease testing within the overall context of reference laboratory testing and discuss strategies to facilitate the provision of high-quality, cost-effective laboratory services.

Collaborative AI and Laboratory Medicine integration in precision cardiovascular medicine

Artificial Intelligence (AI) is a broad term that combines computation with sophisticated mathematical models and in turn allows the development of complex algorithms which are capable to simulate human intelligence such as problem solving and learning. It is devised to promote a significant paradigm shift in the most diverse areas of medical knowledge. On the other hand, Cardiology is a vast field dealing with diseases relating to the heart, the circulatory system, and includes coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions. AI has emerged as a promising tool in cardiovascular medicine which is aimed in augmenting the effectiveness of the cardiologist and to extend better quality to patients. It has the ability to support decision‑making and improve diagnostic and prognostic performance. Attempt has also been made to explore novel genotypes and phenotypes in existing cardiovascular diseases, improve the quality of patient care, to enablecost-effectiveness with reducereadmissionand mortality rates. Our review addresses the integration of AI and laboratory medicine as an accelerator of personalization care associated with the precision and the need of value creation services in cardiovascular medicine.