Quality improvement of Dutch ICUs from 2009 to 2021: A registry based observational study

PURPOSE

To investigate the development in quality of ICU care over time using the Dutch National Intensive Care Evaluation (NICE) registry.

MATERIALS AND METHODS

We included data from all ICU admissions in the Netherlands from those ICUs that submitted complete data between 2009 and 2021 to the NICE registry. We determined median and interquartile range for eight quality indicators. To evaluate changes over time on the indicators, we performed multilevel regression analyses, once without and once with the COVID-19 years 2020 and 2021 included. Additionally we explored between-ICU heterogeneity by calculating intraclass correlation coefficients (ICC).

RESULTS

705,822 ICU admissions from 55 (65%) ICUs were included in the analyses. ICU length of stay (LOS), duration of mechanical ventilation (MV), readmissions, in-hospital mortality, hypoglycemia, and pressure ulcers decreased significantly between 2009 and 2019 (OR <1). After including the COVID-19 pandemic years, the significant change in MV duration, ICU LOS, and pressure ulcers disappeared. We found an ICC ≤0.07 on the quality indicators for all years, except for pressure ulcers with an ICC of 0.27 for 2009 to 2021.

CONCLUSIONS

Quality of Dutch ICU care based on seven indicators significantly improved from 2009 to 2019 and between-ICU heterogeneity is medium to small, except for pressure ulcers. The COVID-19 pandemic disturbed the trend in quality improvement, but unaltered the between-ICU heterogeneity.

Characteristics and outcome of COVID-19 patients admitted to the ICU: a nationwide cohort study on the comparison between the consecutive stages of the COVID-19 pandemic in the Netherlands, an update

BACKGROUND

Previously, we reported a decreased mortality rate among patients with COVID-19 who were admitted at the ICU during the final upsurge of the second wave (February-June 2021) in the Netherlands. We examined whether this decrease persisted during the third wave and the phases with decreasing incidence of COVID-19 thereafter and brought up to date the information on patient characteristics.

METHODS

Data from the National Intensive Care Evaluation (NICE)-registry of all COVID-19 patients admitted to an ICU in the Netherlands were used. Patient characteristics and rates of in-hospital mortality (the primary outcome) during the consecutive periods after the first wave (periods 2-9, May 25, 2020-January 31, 2023) were compared with those during the first wave (period 1, February-May 24, 2020).

RESULTS

After adjustment for patient characteristics and ICU occupancy rate, the mortality risk during the initial upsurge of the third wave (period 6, October 5, 2021-January, 31, 2022) was similar to that of the first wave (ORadj = 1.01, 95%-CI [0.88-1.16]). The mortality rates thereafter decreased again (e.g., period 9, October 5, 2022-January, 31, 2023: ORadj = 0.52, 95%-CI [0.41-0.66]). Among the SARS-CoV-2 positive patients, there was a huge drop in the proportion of patients with COVID-19 as main reason for ICU admission: from 88.2% during the initial upsurge of the third wave to 51.7%, 37.3%, and 41.9% for the periods thereafter. Restricting the analysis to these patients did not modify the results on mortality.

CONCLUSIONS

The results show variation in mortality rates among critically ill COVID-19 patients across the calendar time periods that is not explained by differences in case-mix and ICU occupancy rates or by varying proportions of patients with COVID-19 as main reason for ICU admission. The consistent increase in mortality during the initial, rising phase of each separate wave might be caused by the increased virulence of the contemporary virus strain and lacking immunity to the new strain, besides unmeasured patient-, treatment- and healthcare system characteristics.

Conservative versus Liberal Oxygenation Targets in Intensive Care Unit Patients (ICONIC): A Randomized Clinical Trial

Rationale: Supplemental oxygen is widely administered to ICU patients, but appropriate oxygenation targets remain unclear. Objectives: This study aimed to determine whether a low-oxygenation strategy would lower 28-day mortality compared with a high-oxygenation strategy. Methods: This randomized multicenter trial included mechanically ventilated ICU patients with an expected ventilation duration of at least 24 hours. Patients were randomized 1:1 to a low-oxygenation (PaO2, 55-80 mm Hg; or oxygen saturation as measured by pulse oximetry, 91-94%) or high-oxygenation (PaO2, 110-150 mm Hg; or oxygen saturation as measured by pulse oximetry, 96-100%) target until ICU discharge or 28 days after randomization, whichever came first. The primary outcome was 28-day mortality. The study was stopped prematurely because of the COVID-19 pandemic when 664 of the planned 1,512 patients were included. Measurements and Main Results: Between November 2018 and November 2021, a total of 664 patients were included in the trial: 335 in the low-oxygenation group and 329 in the high-oxygenation group. The median achieved PaO2 was 75 mm Hg (interquartile range, 70-84) and 115 mm Hg (interquartile range, 100-129) in the low- and high-oxygenation groups, respectively. At Day 28, 129 (38.5%) and 114 (34.7%) patients had died in the low- and high-oxygenation groups, respectively (risk ratio, 1.11; 95% confidence interval, 0.9-1.4; P = 0.30). At least one serious adverse event was reported in 12 (3.6%) and 17 (5.2%) patients in the low- and high-oxygenation groups, respectively. Conclusions: Among mechanically ventilated ICU patients with an expected mechanical ventilation duration of at least 24 hours, using a low-oxygenation strategy did not result in a reduction of 28-day mortality compared with a high-oxygenation strategy. Clinical trial registered with the National Trial Register and the International Clinical Trials Registry Platform (NTR7376).

The daily updated Dutch national database on COVID-19 epidemiology, vaccination and sewage surveillance

The Dutch national open database on COVID-19 has been incrementally expanded since its start on 30 April 2020 and now includes datasets on symptoms, tests performed, individual-level positive cases and deaths, cases and deaths among vulnerable populations, settings of transmission, hospital and ICU admissions, SARS-CoV-2 variants, viral loads in sewage, vaccinations and the effective reproduction number. This data is collected by municipal health services, laboratories, hospitals, sewage treatment plants, vaccination providers and citizens and is cleaned, analysed and published, mostly daily, by the National Institute for Public Health and the Environment (RIVM) in the Netherlands, using automated scripts. Because these datasets cover the key aspects of the pandemic and are available at detailed geographical level, they are essential to gain a thorough understanding of the past and current COVID-19 epidemiology in the Netherlands. Future purposes of these datasets include country-level comparative analysis on the effect of non-pharmaceutical interventions against COVID-19 in different contexts, such as different cultural values or levels of socio-economic disparity, and studies on COVID-19 and weather factors.

Assessing the FAIRness of databases on the EHDEN portal: A case study on two Dutch ICU databases

OBJECTIVE

To address the growing need for effective data reuse in health research, healthcare institutions need to make their data Findable, Accessible, Interoperable, and Reusable (FAIR). A prevailing method to model databases for interoperability is the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), developed by the Observational Health Data Sciences and Informatics (OHDSI) initiative. A European repository for OMOP CDM-converted databases called the "European Health Data & Evidence Network (EHDEN) portal" was developed, aiming to make these databases Findable and Accessible. This paper aims to assess the FAIRness of databases on the EHDEN portal.

MATERIALS AND METHODS

Two researchers involved in the OMOP CDM conversion of separate Dutch Intensive Care Unit (ICU) research databases each manually assessed their own database using seventeen metrics. These were defined by the FAIRsFAIR project as a list of minimum requirements for a database to be FAIR. Each metric is given a score from zero to four based on how well the database adheres to the metric. The maximum score for each metric varies from one to four based on the importance of the metric.

RESULTS

Fourteen out of the seventeen metrics were unanimously rated: seven were rated the highest score, one was rated half of the highest score, and five were rated the lowest score. The remaining three metrics were assessed differently for the two use cases. The total scores achieved were 15.5 and 12 out of a maximum of 25.

CONCLUSION

The main omissions in supporting FAIRness were the lack of globally unique identifiers such as Uniform Resource Identifiers (URIs) in the OMOP CDM and the lack of metadata standardization and linkage in the EHDEN portal. By implementing these in future updates, the EHDEN portal can be more FAIR.

Structural under-reporting of informed consent, data handling and sharing, ethical approval, and application of Open Science principles as proxies for study quality conduct in COVID-19 research: a systematic scoping review

BACKGROUND

The COVID-19 pandemic required science to provide answers rapidly to combat the outbreak. Hence, the reproducibility and quality of conducting research may have been threatened, particularly regarding privacy and data protection, in varying ways around the globe. The objective was to investigate aspects of reporting informed consent and data handling as proxies for study quality conduct.

METHODS

A systematic scoping review was performed by searching PubMed and Embase. The search was performed on November 8th, 2020. Studies with hospitalised patients diagnosed with COVID-19 over 18 years old were eligible for inclusion. With a focus on informed consent, data were extracted on the study design, prestudy protocol registration, ethical approval, data anonymisation, data sharing and data transfer as proxies for study quality. For reasons of comparison, data regarding country income level, study location and journal impact factor were also collected.

RESULTS

972 studies were included. 21.3% of studies reported informed consent, 42.6% reported waivers of consent, 31.4% did not report consent information and 4.7% mentioned other types of consent. Informed consent reporting was highest in clinical trials (94.6%) and lowest in retrospective cohort studies (15.0%). The reporting of consent versus no consent did not differ significantly by journal impact factor (p=0.159). 16.8% of studies reported a prestudy protocol registration or design. Ethical approval was described in 90.9% of studies. Information on anonymisation was provided in 17.0% of studies. In 257 multicentre studies, 1.2% reported on data sharing agreements, and none reported on Findable, Accessible, Interoperable and Reusable data principles. 1.2% reported on open data. Consent was most often reported in the Middle East (42.4%) and least often in North America (4.7%). Only one report originated from a low-income country.

DISCUSSION

Informed consent and aspects of data handling and sharing were under-reported in publications concerning COVID-19 and differed between countries, which strains study quality conduct when in dire need of answers.

FAIRifying a Quality Registry Using OMOP CDM: Challenges and Solutions

The need for health data to be internationally Findable, Accessible, Interoperable and Reusable (FAIR) and thereby support integrative analysis with other datasets has become crystal clear in the ongoing pandemic. The Dutch National Intensive Care Evaluation (NICE) quality registry adopted the Observational Medical Outcomes Partnership Common Database Model (OMOP CDM) to achieve a FAIR database. In the process of adopting the OMOP CDM, many modeling, technical, and communication challenges needed to be solved. Through communication with the OMOP CDM implementation community, previously done research and trial-and-error we found solutions that we believe can help other healthcare institutions, especially ICU quality registries, FAIRify their databases.

Comparison of outcome and characteristics between 6343 COVID-19 patients and 2256 other community-acquired viral pneumonia patients admitted to Dutch ICUs

Purpose

Describe the differences in characteristics and outcomes between COVID-19 and other viral pneumonia patients admitted to Dutch ICUs.

Materials and methods

Data from the National-Intensive-Care-Evaluation-registry of COVID-19 patients admitted between February 15th and January 1th 2021 and other viral pneumonia patients admitted between January 1st 2017 and January 1st 2020 were used. Patients' characteristics, the unadjusted, and adjusted in-hospital mortality were compared.

Results

6343 COVID-19 and 2256 other viral pneumonia patients from 79 ICUs were included. The COVID-19 patients included more male (71.3 vs 49.8%), had a higher Body-Mass-Index (28.1 vs 25.5), less comorbidities (42.2 vs 72.7%), and a prolonged hospital length of stay (19 vs 9 days). The COVID-19 patients had a significantly higher crude in-hospital mortality rate (Odds ratio (OR) = 1.80), after adjustment for patient characteristics and ICU occupancy rate the OR was respectively 3.62 and 3.58.

Conclusion

Higher mortality among COVID-19 patients could not be explained by patient characteristics and higher ICU occupancy rates, indicating that COVID-19 is more severe compared to other viral pneumonia. Our findings confirm earlier warnings of a high need of ICU capacity and high mortality rates among relatively healthy COVID-19 patients as this may lead to a higher mental workload for the staff.

Number of intensivists per bed is associated with efficiency of Dutch intensive care units

PURPOSE

To measure efficiency in Intensive Care Units (ICUs) and to determine which organizational factors are associated with ICU efficiency, taking confounding factors into account.

MATERIALS AND METHODS

We used data of all consecutive admissions to Dutch ICUs between January 1, 2016 and January 1, 2019 and recorded ICU organizational factors. We calculated efficiency for each ICU by averaging the Standardized Mortality Ratio (SMR) and Standardized Resource Use (SRU) and examined the relationship between various organizational factors and ICU efficiency. We thereby compared the results of linear regression models before and after covariate adjustment using propensity scores.

RESULTS

We included 164,399 admissions from 83 ICUs. ICU efficiency ranged from 0.51-1.42 (average 0.99, 0.15 SD). The unadjusted model as well as the propensity score adjusted model showed a significant association between the ratio of employed intensivists per ICU bed and ICU efficiency. Other organizational factors had no statistically significant association with ICU efficiency after adjustment.

CONCLUSIONS

We found marked variability in efficiency in Dutch ICUs. After applying covariate adjustment using propensity scores, we identified one organizational factor, ratio intensivists per bed, having an association with ICU efficiency.

Outcomes of Intensive Care Patients Older Than 90 Years: An 11-Year National Observational Study

BACKGROUND/OBJECTIVES

Many intensive care unit (ICU) physicians are reluctant to admit patients aged 90 years and older, although evidence to support these decisions is scarce. Although the body of evidence on outcomes of patients aged 80 years and older is growing, it does not include patients aged 90 years and older. The aim of this study was to compare the short- and long-term mortality of ICU patients aged 90 years and older in the Netherlands with ICU patients aged 80 to 90 years, that is, octogenarians.

DESIGN

Multicenter national cohort study over an 11-year period (2008-2018), using data of the National Intensive Care Evaluation (NICE) registry and the Dutch insurance claims registry.

SETTING

All 82 ICUs in the Netherlands.

PARTICIPANTS

All patients aged 80 years and older at the time of ICU admission.

MEASUREMENTS

A total of 104,754 patients aged 80 years and older, of whom 9,495 (9%) were 90 years and older, were admitted to Dutch ICUs during the study period.

RESULTS

ICU mortality of the patients aged 90 years and older was lower (13.8% vs 16.1%; P < .001) and hospital mortality was similar (26.1% vs 25.7%; P = .41) compared with octogenarians. After 3 months, mortality was higher for the patients aged 90 years and older (43.1% vs 33.7%; P < .001) and after 1-year mortality was 55.0% vs 42.7%; P < .001.

CONCLUSION

In the Netherlands, mortality rates of patients aged 90 years and older admitted to the ICU are not as disappointing as often assumed. They have a lower ICU mortality and a similar hospital mortality compared with octogenarians. Nevertheless, their longer term mortality is higher compared with octogenarians. However, almost 3 of 4 patients leave the hospital alive, and almost half of the patients aged 90 years and older are still alive 1 year after their ICU admission. J Am Geriatr Soc 68:1842-1846, 2020.

Mortality prediction by SOFA score in ICU-patients after cardiac surgery; comparison with traditional prognostic-models

Background

There are many prognostic models and scoring systems in use to predict mortality in ICU patients. The only general ICU scoring system developed and validated for patients after cardiac surgery is the APACHE-IV model. This is, however, a labor-intensive scoring system requiring a lot of data and could therefore be prone to error. The SOFA score on the other hand is a simpler system, has been widely used in ICUs and could be a good alternative.

The goal of the study was to compare the SOFA score with the APACHE-IV and other ICU prediction models.

Methods

We investigated, in a large cohort of cardiac surgery patients admitted to Dutch ICUs, how well the SOFA score from the first 24 h after admission, predict hospital and ICU mortality in comparison with other recalibrated general ICU scoring systems. Measures of discrimination, accuracy, and calibration (area under the receiver operating characteristic curve (AUC), Brier score, R², and Ĉ-statistic) were calculated using bootstrapping. The cohort consisted of 36,632 Patients from the Dutch National Intensive Care Evaluation (NICE) registry having had a cardiac surgery procedure for which ICU admission was necessary between January 1st, 2006 and June 31st, 2018.

Results

Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM₂₄-II - models to predict hospital mortality was good with an AUC of respectively: 0.809, 0.851, 0.830, 0.850, 0.801. Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM₂₄-II - models to predict ICU mortality was slightly better with AUCs of respectively: 0.809, 0.906, 0.892, 0.919, 0.862. Calibration of the models was generally poor.

Conclusion

Although the SOFA score had a good discriminatory power for hospital- and ICU mortality the discriminatory power of the APACHE-IV and SAPS-II was better. The SOFA score should not be preferred as mortality prediction model above traditional prognostic ICU-models.

The influence of clinical variables on the risk of developing chronic conditions in ICU survivors

PURPOSE

To assess the association of clinical variables and the development of specified chronic conditions in ICU survivors.

MATERIALS AND METHODS

A retrospective cohort study, combining a national health insurance claims database and a national quality registry for ICUs. Claims data from 2012 to 2014 were combined with clinical data of patients admitted to an ICU during 2013. To assess the association of clinical variables (ICU length of stay, mechanical ventilation, acute physiology score, reason for ICU admission, mean arterial pressure score and glucose score) and the development of chronic conditions (i.e. heart diseases, COPD or asthma, Diabetes mellitus type II, depression and kidney diseases), logistic regression was used.

RESULTS

49,004 ICU patients were included. ICU length of stay was associated with the development of heart diseases, asthma or COPD and depression. The reason for ICU admission was an important risk factor for the development of all chronic conditions with adjusted ORs ranging from 2.05 (CI 1.56; 2.69) for kidney diseases to 5.14 (CI 3.99; 6.62) for depression.

CONCLUSIONS

Clinical variables, especially the reason for ICU admission, are associated with the development of chronic conditions after ICU discharge. Therefore, these clinical variables should be considered when organizing follow-up care for ICU survivors.

Dutch ICU survivors have more consultations with general practitioners before and after ICU admission compared to a matched control group from the general population

Background

General Practitioners (GPs) play a key role in the healthcare trajectory of patients. If the patient experiences problems that are typically non-life-threatening, such as the symptoms of post-intensive-care syndrome, the GP will be the first healthcare professional they consult. The primary aim of this study is to gain insight in the frequency of GP consultations during the year before hospital admission and the year after discharge for ICU survivors and a matched control group from the general population. The secondary aim of this study is to gain insight into differences between subgroups of the ICU population with respect to the frequency of GP consultations.

Methods

We conducted a retrospective cohort study, combining a national health insurance claims database and a national quality registry for ICUs. Clinical data of patients admitted to an ICU in 2013 were enriched with claims data from the years 2012, 2013 and 2014. Poisson regression was used to assess the differences in frequency of GP consultations between the ICU population and the control group.

Results

ICU patients have more consultations with GPs during the year before and after admission than individuals in the control group. In the last four weeks before admission, ICU patients have 3.58 (CI 3.37; 3.80) times more GP consultations than the control group, and during the first four weeks after discharge they have 4.98 (CI 4.74; 5.23) times more GP consultations. In the year after hospital discharge ICU survivors have an increased GP consultation rate compared to the year before their hospital admission.

Conclusions

Close to hospital admission and shortly after hospital discharge, the frequency of GP consultations substantially increases in the population of ICU survivors. Even a year after hospital discharge, ICU survivors have increased GP consultation rates. Therefore, GPs should be well informed about the problems ICU patients suffer after discharge, in order to provide suitable follow-up care.

The healthcare costs of intoxicated patients who survive ICU admission are higher than non-intoxicated ICU patients: a retrospective study combining healthcare insurance data and data from a Dutch national quality registry

Background

The aim of this study was to describe the healthcare costs of intoxicated ICU patients in the year before and the year after ICU admission, and to compare their healthcare costs with non-intoxicated ICU patients and a population based control group.

Methods

We conducted a retrospective cohort study, combining a national health insurance claims database and a national quality registry database for ICUs. Claims data in the timeframe 2012 until 2014 were combined with the clinical data of patients who had been admitted to an ICU during 2013. Three study populations were compared and matched according to socioeconomic status, type of admission, age and gender: an “ICU population”, an “intoxication population” and a “control population” (who had never been on the ICU).

Results

2591 individual “intoxicated ICU patients” were compared to 2577 general “ICU patients” and 2591 patients from the “control population”. The median and interquartile ranges (IQR) healthcare costs per day alive for the “intoxicated ICU patients” were higher during the year before ICU admission (€20.3 (IQR €3.6–€76.4)) and the year after ICU admission (€23.9 (IQR €5.1–€82.4)) compared to the ICU population (€6.1 (IQR €0.9–€29.3) and €13.6 (IQR €3.3–€54.9) respectively) and a general control population (€1.1 (IQR €0.3–€4.6) and €1.1 (IQR €0.4–€4.9) respectively). The healthcare associated costs in intoxicated ICU patients were correlated with the number of chronic conditions present prior ICU admission (p < 0.0001).

Conclusions

Intoxicated patients admitted to the ICU had in the year before and after ICU admission much higher median healthcare costs per day alive compared to other ICU patients and a general population control group. Healthcare costs are greatly influenced by the number of psychiatric and other chronic conditions of these intoxicated patients.

Electronic supplementary material

The online version of this article (10.1186/s12873-019-0224-7) contains supplementary material, which is available to authorized users.

Healthcare-related costs in very elderly intensive care patients

INTRODUCTION

The long-term outcome of "very old intensive care unit patients" (VOPs; ≥ 80 years) is often disappointing. Little is known about the healthcare costs of these VOPs in comparison to younger ICU patients and the very elderly in the general population not admitted to the ICU.

METHODS

Data from a national health insurance claims database and a national quality registry for ICUs were combined. Costs of VOPs admitted to the ICU in 2013 were compared with costs of younger ICU patients (two groups, respectively 18-65 and 65-80 years old) and a matched control group of very elderly subjects who were not admitted to the ICU. We compared median costs and median costs per day alive in the year before ICU admission (2012), the year of ICU admission (2013) and the year after ICU admission (2014).

RESULTS

A total of 9272 VOPs were included and compared to three equally sized study groups. Median costs for VOPs in 2012, 2013 and 2014 (€5944, €35,653 and €12,565) are higher compared to the ICU 18-65 population (€3022, €30,223 and €5052, all p < 0.001) and the very elderly control population (€3590, €4238 and €4723, all p < 0.001). Compared to the ICU 65-80 population, costs of VOPs are higher in the year before and after ICU admission (€4323 and €6750, both p < 0.001), but not in the year of ICU admission (€34,448, p = 0.950). The median healthcare costs per day alive in the year before, the year of and the year after ICU admission are all higher for VOPs than for the other groups (p < 0.001).

CONCLUSIONS

VOPs required more healthcare resources in the year before, the year of and the year after ICU admission compared to younger ICU patients and the very elderly control population, except compared to the ICU 65-80 population in the year of ICU admission. Healthcare costs per day alive, however, are substantially higher for VOPs than for all other study groups in all three studied years.

Lessons learnt during the implementation of a web-based triage tool for Dutch intensive care follow-up clinics

OBJECTIVES

Screening for symptoms of postintensive care syndrome is based on a long list of questionnaires, filled out by the intensive care unit (ICU) survivor and manually reviewed by the health professional. This is an inefficient and time-consuming process. The aim of this study was to evaluate the feasibility of a web-based triage tool and to compare the outcomes from web-based questionnaires to those from paper-based questionnaires.

DESIGN

A mixed-methods study.

SETTING

Nine Dutch ICU follow-up clinics.

PARTICIPANTS

221 ICU survivors and 14 health professionals.

INTERVENTIONS

A web-based triage tool was implemented by nine ICU follow-up clinics. End users, that is, health professionals were interviewed in order to evaluate the feasibility of the triage tool. ICU survivors were invited to fill out web-based questionnaires 3 months after hospital discharge.

PRIMARY OUTCOMES

Outcomes of the questionnaires were merged with clinical data from a national quality registry to assess the differences in outcomes between paper-based and web-based questionnaires.

RESULTS

221 ICU survivors received an invitation to fill out questionnaires, 93 (42.1%) survivors did not respond to the invitation. Respondents to the web-based questionnaires (n=54) were significantly younger and had a significantly longer ICU stay than those who preferred the paper-based questionnaires (n=74). The prevalence of mental, physical and nutritional problems was high, although comparable between the groups. Health professionals' interviews revealed that the software was complex to use (n=8) and although emailing survivors is very convenient, not all survivors have an email address (n=7).

CONCLUSIONS

Web-based screening software has major benefits compared with paper-based screening. However, implementation has shown to be rather difficult and there are important barriers to consider. Although different in age, the health status is comparable between the users of the web-based questionnaire and paper-based questionnaire.

Reported burden on informal caregivers of ICU survivors: a literature review

BACKGROUND

Critical illness and the problems faced after ICU discharge do not only affect the patient, it also negatively impacts patients' informal caregivers. There is no review which summarizes all types of burden reported in informal caregivers of ICU survivors. It is important that the burdens these informal caregivers suffer are systematically assessed so the caregivers can receive the professional care they need. We aimed to provide a complete overview of the types of burdens reported in informal caregivers of adult ICU survivors, to make recommendations on which burdens should be assessed in this population, and which tools should be used to assess them.

METHOD

We performed a systematic search in PubMed and CINAHL from database inception until June 2014. All articles reporting on burdens in informal caregivers of adult ICU survivors were included. Two independent reviewers used a standardized form to extract characteristics of informal caregivers, types of burdens and instruments used to assess these burdens. The quality of the included studies was assessed using the Newcastle-Ottawa and the PEDro scales.

RESULTS

The search yielded 2704 articles, of which we included 28 in our review. The most commonly reported outcomes were psychosocial burden. Six months after ICU discharge, the prevalence of anxiety was between 15% and 24%, depression between 4.7% and 36.4% and post-traumatic stress disorder (PTSD) between 35% and 57.1%. Loss of employment, financial burden, lifestyle interference and low health-related quality of life (HRQoL) were also frequently reported. The most commonly used tools were the Hospital Anxiety and Depression Scale (HADS), Centre for Epidemiological Studies-Depression questionnaire, and Impact of Event Scale (IES). The quality of observational studies was low and of randomized studies moderate to fair.

CONCLUSIONS

Informal caregivers of ICU survivors suffer a substantial variety of burdens. Although the quality of the included studies was poor, there is evidence that burden in the psychosocial field is most prevalent. We suggest screening informal caregivers of ICU survivors for anxiety, depression, PTSD, and HRQoL using respectively the HADS, IES and Short Form 36 and recommend a follow-up period of at least 6 months.

Trends in practice of blood glucose control in critically ill patients in the Netherlands

BACKGROUND

Publication of the Normoglycemia in Intensive Care Evaluation and Survival Using Glucose Algorithm Regulation (NICE-SUGAR) trial in 2009 and several observational studies caused a change in the recommendations for blood glucose control in intensive care patients. We evaluated local trends in blood glucose control in intensive care units in the Netherlands before and after the publication of the NICE-SUGAR trial and the revised Surviving Sepsis Campaign (SSC) guidelines in 2012.

METHODS

Survey focusing on the timing of changes in thresholds in local guidelines for blood glucose control and interrupted time-series analysis of patients admitted to seven intensive care units in the Netherlands from September 2008 through July 2014. Statistical process control was used to visualise and analyse trends in metrics for blood glucose control in association with the moment changes became effective.

RESULTS

Overall, the mean blood glucose level increased and the median percentage of blood glucose levels within the normoglycaemic range and in the hypoglycaemic range decreased, while the relative proportion of hyperglycaemic measurements increased. Changes in metrics were notable after publication of the NICE-SUGAR trial and the SSC guidelines but more frequent after changes in local guidelines; some changes seemed to appear independent of changes in local guidelines.

CONCLUSION

Local guidelines for blood glucose practice have changed in intensive care units in the Netherlands since the publication of the NICE-SUGAR trial and the revised SSC guidelines. Trends in the metrics for blood glucose control suggest new, higher target ranges for blood glucose control.

Recommendations for intensive care follow-up clinics; report from a survey and conference of Dutch intensive cares

BACKGROUND

With the increasing awareness of postintensive care syndrome and the unbridled development of post-ICU clinics in the Netherlands, guidelines for ICU after care are needed. The purpose of this study was to develop recommendations for the set-up of post-ICU clinics.

METHODS

Recommendations regarding the design of post-ICU clinics were formulated based on a survey among Dutch ICUs and the available literature. Subsequently, in a round table conference stakeholders discussed and voted on a final approval of the recommendations.

RESULTS

The response rate of our survey was 70% (57 of 82), 40% of the respondents provided ICU after care. Twenty-one people from 16 ICUs participated in the round table conference. Only two studies are available with information on organization and effectiveness of post-ICU clinics. It is recommended to invite patients who are mechanically ventilated for more than 2 days at a post-ICU clinic between 6 and 12 weeks after hospital discharge and screen for physical, psychological and cognitive impairments by using validated electronic patient-reported questionnaires. The set-up of a national registry for benchmarking and research purposes is suggested.

CONCLUSION

This study recommends how to organize post-ICU clinics based on literature and expert opinion. The implementation of the recommendations will facilitate the set-up of post-ICU clinics, research on effectiveness of post-ICU clinics and benchmarking of quality of ICU care.

Outcomes of intensive care unit admissions after elective cancer surgery

BACKGROUND

Postoperative care for major elective cancer surgery is frequently provided on the Intensive Care Unit (ICU).

OBJECTIVE

To analyze the characteristics and outcome of patients after ICU admission following elective surgery for different cancer diagnoses.

METHODS

We analyzed all ICU admissions following elective cancer surgery in the Netherlands collected in the National Intensive Care Evaluation registry between January 2007 and January 2012.

RESULTS

28,973 patients (9.0% of all ICU admissions; 40% female) were admitted to the ICU after elective cancer surgery. Of these admissions 77% were planned; in 23% of cases the decision for ICU admission was made during or directly after surgery. The most frequent malignancies were colorectal cancer (25.6%), lung cancer (18.5%) and tumors of the central nervous system (14.3%). Mechanical ventilation was necessary in 24.8% of all patients, most frequently after surgery for esophageal (62.5%) and head and neck cancer (50.2%); 20.7% of patients were treated with vasopressors in the acute postoperative phase, in particular after surgery for esophageal cancer (41.8%). The median length of stay on the ICU was 0.9 days (interquartile ranges [IQR] 0.8-1.5); surgery for esophageal cancer was associated with the longest ICU length of stay (median 2.0 days) with the largest variation (IQR 1.0-4.8 days). ICU mortality was 1.4%; surgery for gastrointestinal cancer was associated with the highest ICU mortality (colorectal cancer 2.2%, pancreatico-cholangiocarcinoma 2.0%).

CONCLUSION

Elective cancer surgery represents a significant part of all ICU admissions, with a short length of stay and low mortality.

Outcomes of cancer patients after unplanned admission to general intensive care units

BACKGROUND

Acute admission to an intensive care unit (ICU) of cancer patients is considered with increasing frequency due to a better life expectancy and more aggressive therapies. The aim of this study was to determine the characteristics and outcomes of cancer patients with unplanned admissions to general ICUs, and to compare these with outcomes of critically ill patients without cancer.

MATERIAL AND METHODS

All unplanned ICU admissions in the Netherlands collected in the National Intensive Care Evaluation registry between January 2007 and January 2011 were analyzed.

RESULTS AND CONCLUSION

Of the 140,154 patients with unplanned ICU admission 10.9% had a malignancy. Medical cancer patients were more severely ill on ICU admission in comparison with medical non-cancer patients, as reflected by higher needs for mechanical ventilation (50.8% vs. 46.4%, p < 0.001) and vasopressors within 24 hours after admission (41.5% vs. 33.0%, p < 0.001), higher Acute Physiology and Chronic Health Evaluation (APACHE) IV scores (88.1 vs. 67.5, p < 0.001) and a longer ICU stay (5.1 vs. 4.6 days, p < 0.001). In contrast, surgical cancer patients only displayed a modestly higher APACHE IV score on admission when compared with non-cancer surgical patients, whereas the other afore mentioned parameters were lower in the surgical cancer patients group. In-hospital mortality was almost twice as high in medical cancer patients (40.6%) as in medical patients without cancer (23.7%). In-hospital mortality of surgical cancer patients (17.4%) was slightly higher than in patients without cancer (14.6%). These data indicate that unplanned ICU admission is associated with a high mortality in patients with cancer when admitted for medical reasons.

A usability evaluation of a SNOMED CT based compositional interface terminology for intensive care

OBJECTIVE

To evaluate the usability of a large compositional interface terminology based on SNOMED CT and the terminology application for registration of the reasons for intensive care admission in a Patient Data Management System.

DESIGN

Observational study with user-based usability evaluations before and 3 months after the system was implemented and routinely used.

MEASUREMENTS

Usability was defined by five aspects: effectiveness, efficiency, learnability, overall user satisfaction, and experienced usability problems. Qualitative (the Think-Aloud user testing method) and quantitative (the System Usability Scale questionnaire and Time-on-Task analyses) methods were used to examine these usability aspects.

RESULTS

The results of the evaluation study revealed that the usability of the interface terminology fell short (SUS scores before and after implementation of 47.2 out of 100 and 37.5 respectively out of 100). The qualitative measurements revealed a high number (n=35) of distinct usability problems, leading to ineffective and inefficient registration of reasons for admission. The effectiveness and efficiency of the system did not change over time. About 14% (n=5) of the revealed usability problems were related to the terminology content based on SNOMED CT, while the remaining 86% (n=30) was related to the terminology application. The problems related to the terminology content were more severe than the problems related to the terminology application.

CONCLUSIONS

This study provides a detailed insight into how clinicians interact with a controlled compositional terminology through a terminology application. The extensiveness, complexity of the hierarchy, and the language usage of an interface terminology are defining for its usability. Carefully crafted domain-specific subsets and a well-designed terminology application are needed to facilitate the use of a complex compositional interface terminology based on SNOMED CT.

The role of standardized data and terminological systems in computerized clinical decision support systems: literature review and survey

INTRODUCTION

Clinical decision support systems (CDSSs) should be seamlessly integrated with existing clinical information systems to enable automatic provision of advice at the time and place where decisions are made. It has been suggested that a lack of agreed data standards frequently hampers this integration. We performed a literature review to investigate whether CDSSs used standardized (i.e. coded or numerical) data and which terminological systems have been used to code data. We also investigated whether a lack of standardized data was considered an impediment for CDSS implementation.

METHODS

Articles reporting an evaluation of a CDSS that provided a computerized advice based on patient-specific data items were identified based on a former literature review on CDSS and on CDSS studies identified in AMIA's 'Year in Review'. Authors of these articles were contacted to check and complete the extracted data. A questionnaire among the authors of included studies was used to determine the obstacles in CDSS implementation.

RESULTS

We identified 77 articles published between 1995 and 2008. Twenty-two percent of the evaluated CDSSs used only numerical data. Fifty one percent of the CDSSs that used coded data applied an international terminology. The most frequently used international terminology were the ICD (International Classification of Diseases), used in 68% of the cases and LOINC (Logical Observation Identifiers Names and Codes) in 12% of the cases. More than half of the authors experienced barriers in CDSS implementation. In most cases these barriers were related to the lack of electronically available standardized data required to invoke or activate the CDSS.

CONCLUSION

Many CDSSs applied different terminological systems to code data. This diversity hampers the possibility of sharing and reasoning with data within different systems. The results of the survey confirm the hypothesis that data standardization is a critical success factor for CDSS development.

Construction of an interface terminology on SNOMED CT. Generic approach and its application in intensive care

OBJECTIVE

To provide a generic approach for developing a domain-specific interface terminology on SNOMED CT and to apply this approach to the domain of intensive care.

METHODS

The process of developing an interface terminology on SNOMED CT can be regarded as six sequential phases: domain analysis, mapping from the domain concepts to SNOMED CT concepts, creating the SNOMED CT subset guided by the mapping, extending the subset with non-covered concepts, constraining the subset by removing irrelevant content, and deploying the subset in a terminology server.

RESULTS

The APACHE IV classification, a standard in the intensive care with 445 diagnostic categories, served as the starting point for designing the interface terminology. The majority (89.2%) of the diagnostic categories from APACHE IV could be mapped to SNOMED CT concepts and for the remaining concepts a partial match was identified. The resulting initial set of mapped concepts consisted of 404 SNOMED CT concepts. This set could be extended to 83,125 concepts if all taxonomic children of these concepts were included. Also including all concepts that are referred to in the definition of other concepts lead to a subset of 233,782 concepts. An evaluation of the interface terminology should reveal what level of detail in the subset is suitable for the intensive care domain and whether parts need further constraining. In the final phase, the interface terminology is implemented in the intensive care in a locally developed terminology server to collect the reasons for intensive care admission.

CONCLUSIONS

We provide a structure for the process of identifying a domain-specific interface terminology on SNOMED CT. We use this approach to design an interface terminology on SNOMED CT for the intensive care domain. This work is of value for other researchers who intend to build a domain-specific interface terminology on SNOMED CT.

Using SNOMED CT to identify a crossmap between two classification systems: a comparison with an expert-based and a data-driven strategy

A crossmap between successive versions of classification systems is necessary to maintain the continuity of health care documentation. A reference terminology can serve as an intermediary to support this task. Within this study we evaluated the use of SNOMED CT to create a crossmap between two versions of an intensive care classification system. Firstly, the SNOMED CT crossmap was compared with an expert-based and a data-driven crossmap. Next, the influence of these crossmap strategies on the health care outcome was evaluated. For 50% of the analyzed cases, the three mapping strategies resulted in the same crossmaps. In other cases, there was an overlap between the SNOMED CT crossmaps and the crossmaps provided by one of the two other strategies. Differences in the crossmap results had however no significant influence on the health care outcomes. SNOMED CT can be used as an intermediary to solve the problem of crossmapping between versions of classification systems.

Development and application of a framework for maintenance of medical terminological systems

OBJECTIVE

Terminological Systems (TSs) need to be maintained in order to sustain their utility. This paper describes a study aiming at the standardization of the maintenance processes of medical TSs by capturing the criteria for the management of the maintenance processes into a framework. Furthermore, this paper describes application of the framework, which sheds light on the current practice of TS maintenance.

DESIGN

Observational study.

MEASUREMENTS

By means of a literature study, criteria for the maintenance of TSs were obtained and categorized into a framework. The current practice of TS maintenance was explored by a survey among organizations that maintain a TS. Results were stratified by the size of the TS being maintained.

RESULTS

From Sixty-three relevant articles, criteria for the maintenance processes of TSs were extracted and organized into four components. The primary component "Execution" concerns the core activities of the maintenance process. The other three components "Process management," "Change specifications," and "Editing tools" support the core activities of the component "Execution." The survey had a response rate of 40% (37 of 93). The answers reflect the large variation in the number of criteria that are satisfied for the participating organizations. Overall, maintenance of larger TSs seems to satisfy more criteria.

CONCLUSIONS

The framework is an important step towards standardization of the maintenance of medical TSs and can be used to eliminate shortcomings in this process. Surveying the current practice showed that there is ample room to improve the maintenance processes of medical TSs, especially for the smaller TSs.

The impact of different prognostic models and their customization on institutional comparison of intensive care units

OBJECTIVES

To evaluate the influence of choice of a prognostic model and the effect of customization of these models on league tables (i.e., rank-order listing) in which intensive care units (ICUs) are ranked by standardized mortality ratios using Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, and Mortality Probability Model II (MPM24II).

DESIGN

Retrospective analysis of prospectively collected data on ICU admissions.

SETTING

Forty Dutch ICUs.

PATIENTS

A data set from a national registry of 86,427 patients from January 2002 to October 2006.

INTERVENTIONS

The league tables associated with the different models were compared to evaluate their agreement. Bootstrapping was used to quantify the uncertainty in the ranks for ICUs. First, for each ICU the median rank and its 95% confidence interval were identified for each model. Then, for a given pair of models, for each ICU the median difference in rank and its associated 95% confidence interval were computed. A difference in rank for an ICU for a given pair of models was considered relevant if it was statistically significant and if one of the models would categorize this ICU as a performance outlier (excellent performer or very poor performer) while the other did not.

MEASUREMENTS AND MAIN RESULTS

For 20 ICUs, there was a significant difference in rank (2-19 positions) between one or more pairs of models. Three ICUs were rated as performance outliers by one of the models, while the other excluded this possibility with 95% certainty. Furthermore, for ten ICUs, one or more pairs of models classified these ICUs as performance outliers while the other model did not do so with certainty. Regarding the agreement between the original models and their customized versions, in all cases the median change in rank was three positions or less and the models fully agreed with respect to which ICUs should be classified as performance outliers.

CONCLUSIONS

Institutional comparison based on case-mix adjusted league tables is sensitive to the choice of prognostic model but not to customization of these models. League tables should always display the uncertainty associated with institutional ranks.

Cross-mapping APACHE IV "reasons for intensive care admission" classification to SNOMED CT

The APACHE IV classification is used to capture diagnostic information for calculation of mortality risks in intensive care (IC). The lack of structured and formal definitions for concepts in APACHE IV classification as in any classification results in shortcomings when scaling up for re-use. The use of SNOMED CT as a reference terminology can address these shortcomings. However, all of SNOMED CT contains large amounts of information that is irrelevant for IC. By building an interface terminology (IfT) based on SNOMED CT and APACHE IV, it is possible to isolate the IC users from the complexity of SNOMED CT while enabling standardized data registration. Within this study, a mapping is realized from the APACHE IV classification to SNOMED CT. The results of the mapping will be used to identify a relevant SNOMED CT subset for the development of an IC-specific IfT. The vast majority of the diagnostic categories in APACHE IV could be mapped to one or more SNOMED CT concepts (83.8%) and for the remaining concept a partial match was identified (16%). The good mapping results will provide a SNOMED CT subset sufficient for developing an IC-specific IfT. Finally, lessons learned in this study are valuable for other researchers who intend to realize a mapping from a classification to SNOMED CT.