The diverse implant landscape, the rising and disparate costs of implants in public healthcare institutions (PHIs), and the limited application of health technology assessment (HTA) impede fair and sustainable implant subsidies in Singapore. This study described the Agency for Care Effectiveness (ACE) Implant Subsidy List (ISL) methodology and the key enablers for supporting government subsidy of clinically effective and cost-effective implants in Singapore.

A multi-tiered implant grouping scheme on the ISL was established by adapting overseas implant classifications, consulting clinicians, and conducting HTA evaluations, with subsidy extensions at the product group tier. Implants within a product group share similar biomechanical actions and patient outcomes and are subject to the same clinical criteria and pricing requirement. Implants on the ISL must be approved by the regulatory authority. Patients who meet the clinical criteria for ISL implants are eligible for subsidy. ACE conducted value-based pricing (VBP) and partnered with the public healthcare supply chain agency to harmonize PHI implant prices. The ISL is updated three times per year.

Implants listed on the ISL were deemed clinically and cost effective. Underpinned by HTA principles, the implant grouping scheme promoted parsimonious classification, while allowing the creation of new product groups for implants offering superior benefits for patients. Reasonable prices set for the product groups aided affordability and cost sustainability. The ISL clinical criteria and standardized implant identifiers encouraged the appropriate use of subsidized implants and facilitated implementation. By ISL implementation in December 2023, ACE assessed 42,165 implants and listed 22,689 ISL implants spanning 143 product groups. Industry can apply for ISL listing three times per year, which keeps the ISL updated and relevant.

The ISL adopts a fit-for-purpose methodology to standardize implant classifications, enable scalable application of HTA, drive appropriate use of subsidized implants, and bring cost sustainability to the government subsidy of implants in Singapore. A strategic partnership with the public healthcare supply chain agency to concurrently establish national procurement contracts reduced disparate implant prices in PHIs and provided greater leverage for better implant prices.

The field of healthcare epidemiology is increasingly focused on identifying, characterizing, and addressing social determinants of health (SDOH) to address inequities in healthcare quality. To identify evidence gaps, we examined recent systematic reviews examining the association of race, ethnicity, and SDOH with inpatient quality measures.

We searched Medline via OVID for English language systematic reviews from 2010 to 2022 addressing race, ethnicity, or SDOH domains and inpatient quality measures in adults using specific topic questions. We imported all citations to Covidence (www.covidence.org, Veritas Health Innovation) and removed duplicates. Two blinded reviewers assessed all articles for inclusion in 2 phases: title/abstract, then full-text review. Discrepancies were resolved by a third reviewer.

Of 472 systematic reviews identified, 39 were included. Of these, 23 examined all-cause mortality; 6 examined 30-day readmission rates; 4 examined length of stay, 4 examined falls, 2 examined surgical site infections (SSIs) and one review examined risk of venous thromboembolism. The most evaluated SDOH measures were sex (n = 9), income and/or employment status (n = 9), age (n = 6), race and ethnicity (n = 6), and education (n = 5). No systematic reviews assessed medication use errors or healthcare-associated infections. We found very limited assessment of other SDOH measures such as economic stability, neighborhood, and health system access.

A limited number of systematic reviews have examined the association of race, ethnicity and SDOH measures with inpatient quality measures, and existing reviews highlight wide variability in reporting. Future systematic evaluations of SDOH measures are needed to better understand the relationships with inpatient quality measures.

Many factors have been associated with the risk of toxigenic C. difficile diarrhea (TCdD). This study derived and internally validated a multivariate model for estimating the risk of TCdD in patients with diarrhea using readily available clinical factors.

A random sample of 3,050 symptomatic emergency department or hospitalized patients undergoing testing for toxigenic C. difficile at a single teaching hospital between 2014 and 2018 was created. Unformed stool samples positive for both glutamate dehydrogenase antigen by enzyme immunoassay and tcdB gene by polymerase chain reaction were classified as TCdD positive. The TCdD Model was created using logistic regression and was modified to the TCdD Risk Score to facilitate its use.

8.1% of patients were TCdD positive. TCdD risk increased with abdominal pain (adjusted odds ratio 1.3; 95% CI, 1.0–1.8), previous C. difficile diarrhea (2.5, 1.1–6.1), and prior antibiotic exposure, especially when sampled in the emergency department (4.2, 2.5–7.0) versus the hospital (1.7, 1.3–2.3). TCdD risk also increased when testing occurred earlier during the hospitalization encounter, when age and white cell count increased concurrently, and with decreased eosinophil count. In internal validation, the TCdD Model had moderate discrimination (optimism-corrected C-statistic 0.65, 0.62–0.68) and good calibration (optimism-corrected Integrated Calibration Index [ICI] 0.017, 0.001–0.022). Performance decreased slightly for the TCdD Risk Score (C-statistic 0.63, 0.62–0.63; ICI 0.038, 0.004–0.038).

TCdD risk can be predicted using readily available clinical risk factors with modest accuracy.

Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

The 2014 US National Strategy for Combating Antibiotic-Resistant Bacteria (CARB) aimed to reduce inappropriate inpatient antibiotic use by 20% for monitored conditions, such as community-acquired pneumonia (CAP), by 2020. We evaluated annual trends in length of therapy (LOT) in adults hospitalized with uncomplicated CAP from 2013 through 2020.

We conducted a retrospective cohort study among adults with a primary diagnosis of bacterial or unspecified pneumonia using International Classification of Diseases Ninth and Tenth Revision codes in MarketScan and the Centers for Medicare & Medicaid Services databases. We included patients with length of stay (LOS) of 2–10 days, discharged home with self-care, and not rehospitalized in the 3 days following discharge. We estimated inpatient LOT based on LOS from the PINC AI Healthcare Database. The total LOT was calculated by summing estimated inpatient LOT and actual postdischarge LOT. We examined trends from 2013 to 2020 in patients with total LOT >7 days, which was considered an indicator of likely excessive LOT.

There were 44,976 and 400,928 uncomplicated CAP hospitalizations among patients aged 18–64 years and ≥65 years, respectively. From 2013 to 2020, the proportion of patients with total LOT >7 days decreased by 25% (68% to 51%) among patients aged 18–64 years and by 27% (68%–50%) among patients aged ≥65 years.

Although likely excessive LOT for uncomplicated CAP patients decreased since 2013, the proportion of patients treated with LOT >7 days still exceeded 50% in 2020. Antibiotic stewardship programs should continue to pursue interventions to reduce likely excessive LOT for common infections.

Despite the impact of inappropriate prescribing on antibiotic resistance, data on surgical antibiotic prophylaxis in sub-Saharan Africa are limited. In this study, we evaluated antibiotic use and consumption in surgical prophylaxis in 4 hospitals located in 2 geographic regions of Sierra Leone.

We used a prospective cohort design to collect data from surgical patients aged 18 years or older between February and October 2021. Data were analyzed using Stata version 16 software.

Of the 753 surgical patients, 439 (58.3%) were females, and 723 (96%) had received at least 1 dose of antibiotics. Only 410 (54.4%) patients had indications for surgical antibiotic prophylaxis consistent with local guidelines. Factors associated with preoperative antibiotic prophylaxis were the type of surgery, wound class, and consistency of surgical antibiotic prophylaxis with local guidelines. Postoperatively, type of surgery, wound class, and consistency of antibiotic use with local guidelines were important factors associated with antibiotic use. Of the 2,482 doses administered, 1,410 (56.8%) were given postoperatively. Preoperative and intraoperative antibiotic use was reported in 645 (26%) and 427 (17.2%) cases, respectively. The most commonly used antibiotic was ceftriaxone 949 (38.2%) with a consumption of 41.6 defined daily doses (DDD) per 100 bed days. Overall, antibiotic consumption was 117.9 DDD per 100 bed days. The Access antibiotics had 72.7 DDD per 100 bed days (61.7%).

We report a high rate of antibiotic consumption for surgical prophylaxis, most of which was not based on local guidelines. To address this growing threat, urgent action is needed to reduce irrational antibiotic prescribing for surgical prophylaxis.

The coronavirus disease 2019 pandemic caused substantial changes to healthcare delivery and antibiotic prescribing beginning in March 2020. To assess pandemic impact on Clostridioides difficile infection (CDI) rates, we described patients and trends in facility-level incidence, testing rates, and percent positivity during 2019–2020 in a large cohort of US hospitals.

We estimated and compared rates of community-onset CDI (CO-CDI) per 10,000 discharges, hospital-onset CDI (HO-CDI) per 10,000 patient days, and C. difficile testing rates per 10,000 discharges in 2019 and 2020. We calculated percent positivity as the number of inpatients diagnosed with CDI over the total number of discharges with a test for C. difficile. We used an interrupted time series (ITS) design with negative binomial and logistic regression models to describe level and trend changes in rates and percent positivity before and after March 2020.

In pairwise comparisons, overall CO-CDI rates decreased from 20.0 to 15.8 between 2019 and 2020 (P < .0001). HO-CDI rates did not change. Using ITS, we detected decreasing monthly trends in CO-CDI (−1% per month, P = .0036) and HO-CDI incidence (−1% per month, P < .0001) during the baseline period, prior to the COVID-19 pandemic declaration. We detected no change in monthly trends for CO-CDI or HO-CDI incidence or percent positivity after March 2020 compared with the baseline period.

While there was a slight downward trajectory in CDI trends prior to March 2020, no significant change in CDI trends occurred during the COVID-19 pandemic despite changes in infection control practices, antibiotic use, and healthcare delivery.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Contrasting the well-described effects of early intervention (EI) services for youth-onset psychosis, the potential benefits of the intervention for adult-onset psychosis are uncertain. This paper aims to examine the effectiveness of EI on functioning and symptomatic improvement in adult-onset psychosis, and the optimal duration of the intervention.

360 psychosis patients aged 26–55 years were randomized to receive either standard care (SC, n = 120), or case management for two (2-year EI, n = 120) or 4 years (4-year EI, n = 120) in a 4-year rater-masked, parallel-group, superiority, randomized controlled trial of treatment effectiveness (Clinicaltrials.gov: NCT00919620). Primary (i.e. social and occupational functioning) and secondary outcomes (i.e. positive and negative symptoms, and quality of life) were assessed at baseline, 6-month, and yearly for 4 years.

Compared with SC, patients with 4-year EI had better Role Functioning Scale (RFS) immediate [interaction estimate = 0.008, 95% confidence interval (CI) = 0.001–0.014, p = 0.02] and extended social network (interaction estimate = 0.011, 95% CI = 0.004–0.018, p = 0.003) scores. Specifically, these improvements were observed in the first 2 years. Compared with the 2-year EI group, the 4-year EI group had better RFS total (p = 0.01), immediate (p = 0.01), and extended social network (p = 0.05) scores at the fourth year. Meanwhile, the 4-year (p = 0.02) and 2-year EI (p = 0.004) group had less severe symptoms than the SC group at the first year.

Specialized EI treatment for psychosis patients aged 26–55 should be provided for at least the initial 2 years of illness. Further treatment up to 4 years confers little benefits in this age range over the course of the study.

To determine the impact of an inpatient stewardship intervention targeting fluoroquinolone use on inpatient and postdischarge Clostridioides difficile infection (CDI).

We used an interrupted time series study design to evaluate the rate of hospital-onset CDI (HO-CDI), postdischarge CDI (PD-CDI) within 12 weeks, and inpatient fluoroquinolone use from 2 years prior to 1 year after a stewardship intervention.

An academic healthcare system with 4 hospitals.

All inpatients hospitalized between January 2017 and September 2020, excluding those discharged from locations caring for oncology, bone marrow transplant, or solid-organ transplant patients.

Introduction of electronic order sets designed to reduce inpatient fluoroquinolone prescribing.

Among 163,117 admissions, there were 683 cases of HO-CDI and 1,104 cases of PD-CDI. In the context of a 2% month-to-month decline starting in the preintervention period (P < .01), we observed a reduction in fluoroquinolone days of therapy per 1,000 patient days of 21% after the intervention (level change, P < .05). HO-CDI rates were stable throughout the study period. In contrast, we also detected a change in the trend of PD-CDI rates from a stable monthly rate in the preintervention period to a monthly decrease of 2.5% in the postintervention period (P < .01).

Our systemwide intervention reduced inpatient fluoroquinolone use immediately, but not HO-CDI. However, a downward trend in PD-CDI occurred. Relying on outcome measures limited to the inpatient setting may not reflect the full impact of inpatient stewardship efforts.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in shortages of personal protective equipment (PPE), underscoring the urgent need for simple, efficient, and inexpensive methods to decontaminate masks and respirators exposed to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). We hypothesized that methylene blue (MB) photochemical treatment, which has various clinical applications, could decontaminate PPE contaminated with coronavirus.

The 2 arms of the study included (1) PPE inoculation with coronaviruses followed by MB with light (MBL) decontamination treatment and (2) PPE treatment with MBL for 5 cycles of decontamination to determine maintenance of PPE performance.

MBL treatment was used to inactivate coronaviruses on 3 N95 filtering facepiece respirator (FFR) and 2 medical mask models. We inoculated FFR and medical mask materials with 3 coronaviruses, including SARS-CoV-2, and we treated them with 10 µM MB and exposed them to 50,000 lux of white light or 12,500 lux of red light for 30 minutes. In parallel, integrity was assessed after 5 cycles of decontamination using multiple US and international test methods, and the process was compared with the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method.

Overall, MBL robustly and consistently inactivated all 3 coronaviruses with 99.8% to >99.9% virus inactivation across all FFRs and medical masks tested. FFR and medical mask integrity was maintained after 5 cycles of MBL treatment, whereas 1 FFR model failed after 5 cycles of VHP+O3.

MBL treatment decontaminated respirators and masks by inactivating 3 tested coronaviruses without compromising integrity through 5 cycles of decontamination. MBL decontamination is effective, is low cost, and does not require specialized equipment, making it applicable in low- to high-resource settings.