Investigating the association of alerts from a national mortality surveillance system with subsequent hospital mortality in England: an interrupted time series analysis

Trends in private caregiving cost after implementing a comprehensive nursing service covered by national health insurance: Interrupted time series

BACKGROUND

The Korean government has implemented a comprehensive nursing care service system (CNS) to mitigate the stress faced by caregivers.

OBJECTIVE

This study aimed to assess trends in the estimated average costs of private caregiving and determine the difference in costs between those using CNS and those not using it.

DESIGN

A comparative interrupted time series analysis with a 2-year lag period verified total private caregiving cost trends; biannual differences in costs were evaluated based on using CNS.

PARTICIPANTS

The main unit of analysis was episode. We extracted a total of 6418 episodes of hospitalization in acute care settings that included the use of caregiving services (formal, informal caregiving and CNS).

METHODS

We conducted segmented regression to assess the impact of CNS on total private caregiving costs using data from 2012 to 2018, excluding the years 2015 and 2016 of the Korean Health Panel dataset.

RESULTS

We presented that the immediate mean difference in total private caregiving costs between CNS users and non-users was -444.7 USD two years after the implementation of the CNS policy (95 % CI -714.5 to -174.5, p-value 0.001). Among individuals living in rural areas, two years after the implementation of the CNS policy, there was a significant immediate mean cost difference of -476.9 USD in total private caregiving costs between CNS users and non-users (p-value 0.011). Similarly, for episodes with a Charlson Comorbidity Index (CCI) score of 0 to 1, there was a substantial immediate mean cost difference in total private caregiving costs between CNS users and non-users, amounting to -399.9 USD two years after the CNS policy (p-value 0.008).

CONCLUSIONS

This study evaluated the trend of total private caregiving costs between groups using and not using CNS. After two years of being covered by CNS health insurance, those who utilized CNS paid $433 less for their total private caregiving cost over a 6-month period, compared to those who did not use CNS. The adoption of CNS may be an effective system for relieving the financial burden on inpatients in need of private caregiving services.

TWEETABLE ABSTRACT

Korean Comprehensive Nursing Service reduces private caregiving costs.

Monitoring Hospital Performance with Statistical Process Control After Total Hip and Knee Arthroplasty: A Study to Determine How Much Earlier Worsening Performance Can Be Detected

BACKGROUND

Given the low early revision rate after total hip arthroplasty (THA) and total knee arthroplasty (TKA), hospital performance is typically compared using 3 years of data. The purpose of this study was to assess how much earlier worsening hospital performance in 1-year revision rates after THA and TKA can be detected.

METHODS

All 86,468 THA and 73,077 TKA procedures performed from 2014 to 2016 and recorded in the Dutch Arthroplasty Register were included. Negative outlier hospitals were identified by significantly higher O/E (observed divided by expected) 1-year revision rates in a funnel plot. Monthly Shewhart p-charts (with 2 and 3-sigma control limits) and cumulative sum (CUSUM) charts (with 3.5 and 5 control limits) were constructed to detect a doubling of revisions (odds ratio of 2), generating a signal when the control limit was reached. The median number of months until generation of a first signal for negative outliers and the number of false signals for non-negative outliers were calculated. Sensitivity, specificity, and accuracy were calculated for all charts and control limit settings using outlier status in the funnel plot as the gold standard.

RESULTS

The funnel plot showed that 13 of 97 hospitals had significantly higher O/E 1-year revision rates and were negative outliers for THA and 7 of 98 hospitals had significantly higher O/E 1-year revision rates and were negative outliers for TKA. The Shewhart p-chart with the 3-sigma control limit generated 68 signals (34 false-positive) for THA and 85 signals (63 false-positive) for TKA. The sensitivity for THA and TKA was 92% and 100%, respectively; the specificity was 69% and 51%, respectively; and the accuracy was 72% and 54%, respectively. The CUSUM chart with a 5 control limit generated 18 signals (1 false-positive) for THA and 7 (1 false-positive) for TKA. The sensitivity was 85% and 71% for THA and TKA, respectively; the specificity was 99% for both; and the accuracy was 97% for both. The Shewhart p-chart with a 3-sigma control limit generated the first signal for negative outliers after a median of 10 months (interquartile range [IQR] = 2 to 18) for THA and 13 months (IQR = 5 to 18) for TKA. The CUSUM chart with a 5 control limit generated the first signal after a median of 18 months (IQR = 7 to 22) for THA and 21 months (IQR = 9 to 25) for TKA.

CONCLUSIONS

Monthly monitoring using CUSUM charts with a 5 control limit enables earlier detection of worsening 1-year revision rates with accuracy so that initiatives to improve care can start earlier.

Effect of monitoring surgical outcomes using control charts to reduce major adverse events in patients: cluster randomised trial

OBJECTIVE

To determine the effect of introducing prospective monitoring of outcomes using control charts and regular feedback on indicators to surgical teams on major adverse events in patients.

DESIGN

National, parallel, cluster randomised trial embedding a difference-in-differences analysis.

SETTING

40 surgical departments of hospitals across France.

PARTICIPANTS

155 362 adults who underwent digestive tract surgery. 20 of the surgical departments were randomised to prospective monitoring of outcomes using control charts with regular feedback on indicators (intervention group) and 20 to usual care only (control group).

INTERVENTIONS

Prospective monitoring of outcomes using control charts, provided in sets quarterly, with regular feedback on indicators (intervention hospitals). To facilitate implementation of the programme, study champion partnerships were established at each site, comprising a surgeon and another member of the surgical team (surgeon, anaesthetist, or nurse), and were trained to conduct team meetings, display posters in operating rooms, maintain a logbook, and devise an improvement plan.

MAIN OUTCOME MEASURES

The primary outcome was a composite of major adverse events (inpatient death, intensive care stay, reoperation, and severe complications) within 30 days after surgery. Changes in surgical outcomes were compared before and after implementation of the programme between intervention and control hospitals, with adjustment for patient mix and clustering.

RESULTS

75 047 patients were analysed in the intervention hospitals (37 579 before and 37 468 after programme implementation) versus 80 315 in the control hospitals (41 548 and 38 767). After introduction of the control chart, the absolute risk of a major adverse event was reduced by 0.9% (95% confidence interval 0.4% to 1.4%) in intervention compared with control hospitals, corresponding to 114 patients (70 to 280) who needed to receive the intervention to prevent one major adverse event. A significant decrease in major adverse events (adjusted ratio of odds ratios 0.89, 95% confidence interval 0.83 to 0.96), patient death (0.84, 0.71 to 0.99), and intensive care stay (0.85, 0.76 to 0.94) was found in intervention compared with control hospitals. The same trend was observed for reoperation (0.91, 0.82 to 1.00), whereas severe complications remained unchanged (0.96, 0.87 to 1.07). Among the intervention hospitals, the effect size was proportional to the degree of control chart implementation witnessed. Highly compliant hospitals experienced a more important reduction in major adverse events (0.84, 0.77 to 0.92), patient death (0.78, 0.63 to 0.97), intensive care stay (0.76, 0.67 to 0.87), and reoperation (0.84, 0.74 to 0.96).

CONCLUSIONS

The implementation of control charts with feedback on indicators to surgical teams was associated with concomitant reductions in major adverse events in patients. Understanding variations in surgical outcomes and how to provide safe surgery is imperative for improvements.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02569450.

A framework to support risk assessment in hospitals

Quality problem or issue

A number of challenges have been identified with current risk assessment practice in hospitals, including: a lack of consultation with a sufficiently wide group of stakeholders; a lack of consistency and transparency; and insufficient risk assessment guidance. Consequently, risk assessment may not be fully effective as a means to ensure safety.

Initial assessment

We used a V system developmental model, in conjunction with mixed methods, including interviews and document analysis to identify user needs and requirements.

Choice of solution

One way to address current challenges is through providing good guidance on the fundamental aspects of risk assessment. We designed a risk assessment framework, comprising: a risk assessment model that depicts the main risk assessment steps; risk assessment explanation cards that provide prompts to help apply each step; and a risk assessment form that helps to systematize the risk assessment and document the findings.

Implementation

We conducted multiple group discussions to pilot the framework through the use of a representative scenario and used our findings for the user evaluation.

Evaluation

User evaluation was conducted with 10 participants through interviews and showed promising results.

Lessons learned

While the framework was recommended for use in practice, it was also proposed that it be adopted as a training tool. With its use in risk assessment, we anticipate that risk assessments would lead to more effective decisions being made and more appropriate actions being taken to minimize risks. Consequently, the quality and safety of care delivered could be improved.

What is the relationship between mortality alerts and other indicators of quality of care? A national cross-sectional study

Objectives

To assess whether mortality alerts, triggered by sustained higher than expected hospital mortality, are associated with other potential indicators of hospital quality relating to factors of hospital structure, clinical process and patient outcomes.

Methods

Cross-sectional study of National Health Service hospital trusts in England (2011–2013) using publicly available hospital measures reflecting organizational structure (mean acute bed occupancy, nurse/bed ratio, training satisfaction and proportion of trusts with low National Health Service Litigation Authority risk assessment or in financial deficit); process (mean proportion of eligible patients who receive percutaneous coronary intervention within 90 minutes) and outcomes (mean patient satisfaction scores, summary measures of hospital mortality and proportion of patients harmed). Mortality alerts were based on hospital administrative data.

Results

Mortality alerts were associated with structural indicators and outcome indicators of quality. There was insufficient data to detect an association between mortality alerts and the process indicator.

Conclusions

Mortality alerts appear to reflect aspects of quality within an English hospital setting, suggesting that there may be value in a mortality alerting system in highlighting poor hospital quality.

National hospital mortality surveillance system: a descriptive analysis

OBJECTIVE

To provide a description of the Imperial College Mortality Surveillance System and subsequent investigations by the Care Quality Commission (CQC) in National Health Service (NHS) hospitals receiving mortality alerts.

BACKGROUND

The mortality surveillance system has generated monthly mortality alerts since 2007, on 122 individual diagnosis and surgical procedure groups, using routinely collected hospital administrative data for all English acute NHS hospital trusts. The CQC, the English national regulator, is notified of each alert. This study describes the findings of CQC investigations of alerting trusts.

METHODS

We carried out (1) a descriptive analysis of alerts (2007-2016) and (2) an audit of CQC investigations in a subset of alerts (2011-2013).

RESULTS

Between April 2007 and October 2016, 860 alerts were generated and 76% (654 alerts) were sent to trusts. Alert volumes varied over time (range: 40-101). Septicaemia (except in labour) was the most commonly alerting group (11.5% alerts sent). We reviewed CQC communications in a subset of 204 alerts from 96 trusts. The CQC investigated 75% (154/204) of alerts. In 90% of these pursued alerts, trusts returned evidence of local case note reviews (140/154). These reviews found areas of care that could be improved in 69% (106/154) of alerts. In 25% (38/154) trusts considered that identified failings in care could have impacted on patient outcomes. The CQC investigations resulted in full trust action plans in 77% (118/154) of all pursued alerts.

CONCLUSION

The mortality surveillance system has generated a large number of alerts since 2007. Quality of care problems were found in 69% of alerts with CQC investigations, and one in four trusts reported that failings in care may have an impact on patient outcomes. Identifying whether mortality alerts are the most efficient means to highlight areas of substandard care will require further investigation.