Effects of Checklists in Surgical Care - a Study on Complications, Death and Quality of Patient Administrative Data
|The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.|
|ClinicalTrials.gov Identifier: NCT01872195|
Recruitment Status : Completed
First Posted : June 7, 2013
Last Update Posted : June 11, 2015
|First Submitted Date ICMJE||May 24, 2013|
|First Posted Date ICMJE||June 7, 2013|
|Last Update Posted Date||June 11, 2015|
|Study Start Date ICMJE||June 2013|
|Actual Primary Completion Date||March 2015 (Final data collection date for primary outcome measure)|
|Current Primary Outcome Measures ICMJE
||Number of patients with complications or death, as a measure of checklist use [ Time Frame: One year ]
Register number of patients with defined complications or peri- or postoperative death before and after checklist implementation.
|Original Primary Outcome Measures ICMJE||Same as current|
|Change History||Complete list of historical versions of study NCT01872195 on ClinicalTrials.gov Archive Site|
|Current Secondary Outcome Measures ICMJE
||Discrepancies between patient information on complications registered as ICD-10 codes and information on complications documented in the actual electronic patient journal [ Time Frame: One year ]
Registration of ICD-10 codes on complications and complications documented in the actual electronic patient journal will be registered separately and then compared as to discrepancies between these. This is done to evaluate and validate complication data (ICD-10 codes) used for primary outcome measures.
|Original Secondary Outcome Measures ICMJE||Same as current|
|Current Other Pre-specified Outcome Measures
||Length of hospital stay (days) as a measure of checklist use. [ Time Frame: One year ]
Length of hospital stay will be measured both before and after checklist use to evaluate if such use may have effects on hospital stay.
|Original Other Pre-specified Outcome Measures||Same as current|
|Brief Title ICMJE||Effects of Checklists in Surgical Care - a Study on Complications, Death and Quality of Patient Administrative Data|
|Official Title ICMJE||Effects of Checklists in Surgical Care - a Study on Morbidity, Mortality and Data Quality|
This project aims to produce a systematic review on present knowledge on effects of using safety checklists in medicine. Implementation of a checklist system throughout surgical care may reduce patient morbidity and mortality. The reliability of patient data is crucial to make firm conclusions as to such effects. This project aims to investigate if such morbidity and mortality effects are obtainable in two Norwegian hospitals while at the same time making a crucial evaluation of the patient data used in this study itself.
1.0 Background Surgical procedures are high risk events and patients may suffer complications or die post operatively. A report from an on-going patient safety campaign "In Safe Hands" lead by the Norwegian Knowledge Centre for the Health Services reveals that approximately 16 % of all Norwegian hospital admissions in 2010 involved an adverse event (AE) (Deilkås, 2011). A review study on AEs in 2008 included a wide range of in-hospital patients from Australia, Canada, New Zealand, the United Kingdom, and the United States of America (US) (de Vries et al., 2008). 9 % of the patients experienced an AE, with 7. 4 % of these ending fatally. The majority of the AEs occurred during surgical treatment or was related to drug administration. The authors claimed that almost half of these could have been prevented if checklists covering the entire surgical pathway had been used (de Vries et al., 2008). Implementation of such a system, called the Surgical Patient Safety System (SURPASS) did in fact result in a reduction of in-hospital morbidity (from 27.3% to 16.7%) and mortality (from 1.5 % to 0.8 %) (de Vries, 2010).
Patient safety checklists have been introduced and recommended as a standard of surgical care (Birkmeyer, 2010; de Vries et al., 2011). Studies based on data from electronic patient administrative systems show that checklist use may reduce mortality and morbidity in surgery (de Vries et al., 2010; van Klei et al., 2012; Haynes et al., 2009). Safe Surgery checklists have been recommended by the World Health Organization (WHO) since 2008 as a strategy to avoid adverse events (AE) during surgery. More than 6000 hospitals have implemented Safe Surgery checklists in their operating theatres (OTs) (http://www.who.int/patientsafety/safesurgery/en/), including Haukeland University Hospital (HUH).
This multicentre research project will also introduce a system of patient safety checklists at each point of care during the surgical patients' stay, not only in the operating theatres (OTs). The system combines new checklists on patient care (parts of SURPASS) with the already established Safe Surgery checklist (WHO) in the OTs. At the same time securing reliability, validity and quality of the patient, morbidity and mortality data will be an essential part of the study.
Today the discharging physician reviews the medical journal and makes a medical summary including coding diseases and complications relevant for the current admission. International Classification of Diseases (ICD-10) codes are used to set diagnoses for clinical, epidemiological and quality purposes (http://www.who.int/classifications/icd/ICD10Volume2_en_2010.pdf). The ICD-10 codes are also used for registrations on national mortality and morbidity in the Norwegian National Patient Register (NPR). Questions have been raised as to the accuracy and quality of the data in such registers in Norway, e.g. in patients with sepsis (Flaatten, 2004), and intensive care patients (Aardal et al., 2005). In a Danish study on relations between ICD-10 coding in the National Registry of Patients and the hospitals' discharge summary and medical records, a high reliability between ICD-10 scores and co-morbidity was found (Thygesen et al., 2011). To our knowledge similar studies have not been done in Norway. As a crucial part of this investigation we concurrently will evaluate the reliability and validity of our patient administrative data by comparing the post discharge ICD-10 codes to actual data available directly from medical journal systems as documented by health care personnel in the journal texts.
The main objectives of this study are to:
3.0 Methods 3.1 The projects and design
3.2 Intervention study sample Three surgical units at HUH (Department of Neurosurgery, Orthopaedic Clinic, and Department of Gynaecology and Obstetrics) will have the checklist system implemented. Approximately 3700 patients will be included before and 3700 patients after checklist implementation. The Control Group includes 7400 patients.
3.4 Data collection For the study on mortality and morbidity we will extract ICD-10 codes used at discharge from the hospitals NPR file, as all Norwegian hospitals report their ICD-10 codes and procedure codes to NPR. In addition to registering all ICD-10 codes on each patient, we will collect demographic data (age, gender, height and weight), American Society of Anaesthesiologists Physical Health Classification (ASA), dates of admission and discharge, and all surgical procedures and major treatments. Data will be processed through Webport using a system previously developed locally for the WHO Surgical Safety Checklist project.
The primary end points, morbidity and mortality, are registered during hospitalization and postoperatively up to 30 days. Morbidity will be registered as major complications according to the American College of Surgeons' National Surgical Quality Improvement Program (http://www.facs.org/cqi/outcomes.html): organ/space surgical site infection, wound dehiscence, deep vein thrombosis, pulmonary embolism, pneumonia, re-intubation, ventilator use longer than 24 hours, cardiac arrest, myocardial infarction, sepsis, shock, coma longer than 24 hours, prosthetic/graft failure, and bleeding. Additional complications to these, as reported by de Vries (2010) will be included in order to make comparisons possible.
The study investigating reliability and validity of the ICD-10 codes will be done in detail: A prospective random selection of 700 patients, 200 patients from Health Trust Førde and 500 patients from the HUH, all having undergone major surgery. Present knowledge should suggest one or several major complications caused by procedures or iatrogenic causes in at least 17 % the surgical patients (de Vries, 2010). Then an inclusion of 700 patients is needed in order to find such complications in 119 cases. We will identify all post discharge ICD-10 codes for each patient. These codes will be thoroughly reviewed for accuracy and completeness by comparing to the actual information as documented by physicians and nurses in the EPJs throughout the total hospital stay. Primary outcome is here to investigate that registered ICD-10 codes have adequate sensitivity and specificity compared to the information in the patients' medical journal.
3.5 Statistics Descriptive and inferential statistical methods will be used to analyse data. Confidence intervals (95% CI) for sensitivity and specificity will be calculated using the normal approximation for the standard error of proportions.
Mortality and morbidity will be analysed as to time of measurement, e.g. pre and post intervention, and surgical unit, i.e. using or not using the checklist. Multiple regression analysis and other appropriate statistical tools will be used to adjust for covariates to mortality and morbidity. Calculation of sample size and power, with an expected mortality rate decrease (0.015 vs. 0.008) requires a sample size of 3641 patients in both baseline and post intervention groups with an alpha (0.05, 2-tailed), power is 80%. To calculate sample size and power for morbidity mitigation from 27% to 17% (de Vries et al., 2010) requires a much smaller sample size of 234 in baseline and post intervention groups to constitute an 80% power with alpha at 0.05, 2-tailed. Statistical analysis will be conducted with appropriate statistical software e.g. Statistical Package for the Social Sciences, Stata or R.
|Study Type ICMJE||Interventional|
|Study Phase ICMJE||Not Applicable|
|Study Design ICMJE||Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Prevention
|Intervention ICMJE||Other: The comprehensive patient safety checklist system
The comprehensive patient safety checklist system follows each patient from admission to discharge with separate short checklists at each point of care: On admission to the hospital and ward (operating theatre nurse, ward doctor, surgeon, anaesthesiologist, ward nurse - 5 lists), in the operating theatre (here covered by the WHO-Safe Surgery checklist), at the recovery/ICU unit (nurse- 1 list), at discharge from the hospital (ward doctor, ward nurse - 2 lists).
|Study Arms ICMJE||
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Recruitment Status ICMJE||Completed|
|Actual Enrollment ICMJE
|Original Estimated Enrollment ICMJE
|Actual Study Completion Date ICMJE||March 2015|
|Actual Primary Completion Date||March 2015 (Final data collection date for primary outcome measure)|
|Eligibility Criteria ICMJE||
|Ages ICMJE||Child, Adult, Older Adult|
|Accepts Healthy Volunteers ICMJE||No|
|Contacts ICMJE||Contact information is only displayed when the study is recruiting subjects|
|Listed Location Countries ICMJE||Norway|
|Removed Location Countries|
|NCT Number ICMJE||NCT01872195|
|Other Study ID Numbers ICMJE||REK Vest 2012/560
Regional Health Authority ( Other Grant/Funding Number: 911755 )
|Has Data Monitoring Committee||No|
|U.S. FDA-regulated Product||Not Provided|
|IPD Sharing Statement ICMJE||Not Provided|
|Responsible Party||Haukeland University Hospital|
|Study Sponsor ICMJE||Haukeland University Hospital|
|Collaborators ICMJE||Not Provided|
|PRS Account||Haukeland University Hospital|
|Verification Date||June 2015|
ICMJE Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP