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Despite the rapid spread of Lean management in health care, few organizations have achieved measurable overall performance improvements with Lean. What differentiates these organizations from those that struggle with realizing the potential benefits of Lean management is unclear. In this qualitative study we explore measuring the impact of Lean and the recommended practices for achieving measurable performance improvements with Lean in health care organizations.Informed by preliminary quantitative results from analyses of high- and low-performing Lean hospitals, we conducted 17 semi-structured interviews with Lean health care experts on the Lean principles and practices associated with better performance. We conducted qualitative content analyses of the interview transcripts based on grounded theory and linking to core principles and practices of the Lean management system.The qualitative data revealed 3 categories of metrics for measuring the impact of Lean: currently used institutional measures, measures tailored to Lean initiatives, and population-level measures. Leadership engagement/commitment and clear organizational focus/prioritization/alignment had the highest weighted averages of success factors. The lack of these 2 factors had the highest weighted averages of biggest barriers for achieving measurable performance improvements with Lean implementation.Leadership engagement and organizational focus can facilitate achieving the organization's performance improvement goals, whereas their absence can considerably hinder performance improvement efforts. Many different approaches have been used to quantify the impact of Lean, but currently used institutional performance measures are preferred by the majority of Lean experts.

BACKGROUND AND OBJECTIVES: The United States has an under-performing healthcare system on both cost and quality criteria in comparison with other developed countries. One approach to improving system performance on both cost and quality is to use the Lean management system based on the Shingo principles originally developed by Toyota in Japan. Our objective is to examine the association between hospital use of the Lean management system and evidence-based or recommended quality improvement care management processes. METHODS: A cross sectional analysis of data from 223 hospitals that responded to both the 2017 National Survey of Healthcare Organizations and Systems (NSHOS) and the 2017 National Survey of Lean/Transformational Performance Improvement in Hospitals (NSL) was conducted. RESULTS: Controlling for hospital organizational and market characteristics, the number of years doing Lean was positively associated with use of electronic health record-based decision support, use of quality-focused information management, use of evidence-based guidelines, and support for care transitions at the p

Background and objectives Lean management in health care organizations attempts to empower staff to generate continuous improvement through incremental but regular improvements in work processes. However, because of the increasing pressure on health care organizations to substantially improve quality of care and patient outcomes while containing costs in the relatively short term, many health care leaders are looking for ways to achieve large breakthrough improvements in their organization's performance. The objective of this research is to understand whether and how Lean management can be used to achieve breakthrough improvements in performance. Methods This study used grounded theory and content analysis of in-depth, semistructured interviews with 10 nationally recognized experts in the use of Lean management in health care organizations. The 10 participants constitute a purposive sample of experts with in-depth understanding of the strengths and limitations of Lean management in health care organizations. Results Two out of 10 participants defined breakthrough improvement as a major change in a performance metric; 2 participants defined it as a fundamental redesign in a process or service; the remaining 6 participants defined breakthrough improvement as having both these characteristics. The extent to which participants believed Lean was an effective means for achieving breakthrough improvement in performance was related to how they defined breakthrough improvement. The 2 participants who defined breakthrough improvement as a significant change in a performance metric believed Lean methods alone were sufficient. The 2 participants who defined breakthrough improvement to be a fundamental redesign tended not to view Lean alone as an effective approach. Rather, they, and the 6 participants who defined breakthrough improvement as having both change-in-metric and process redesign characteristics, viewed human-centered design thinking as the primary or important complementary approach to achieving breakthrough improvement. Participants identified resources, culture change, and leadership commitment beyond what would be required to achieve incremental improvement as the main facilitators and barriers to achieving breakthrough improvements. Conclusion This research reveals some differences in experts' definitions of breakthrough improvement, and illuminates the value of human-centered design thinking, alone or as a complement to Lean management, in achieving breakthrough improvement in health care organizations. Most of our expert participants agreed that supplementing Lean management methods with the contributions of innovation design and investing significant resources, strengthening the organizational culture to support the necessary changes, and providing stronger leadership commitment to the effort are important facilitators for achieving breakthroughs in organizational performance.

Objectives Severe post-operative pain is common after total knee arthroplasty. Patient-controlled analgesia is an alternative method of pain management, whereby a patient administers his or her own pain medication. Patients seem to prefer this method over nurse-administered analgesia. However, it remains unclear whether patients using patient-controlled analgesia devices use higher or lower doses of opioids compared to patients treated with oral opioids. Methods This retrospective study examined 164 patients undergoing total knee arthroplasty. Post-operatively, 82 patients received oxycodone via intravenous patient-controlled analgesia devices, while the pain medication for 82 patients in the control group was administered by nurses. The main outcome measure was the consumption of intravenous opioid equivalents within 24 h after surgery. Secondary outcome measures were the use of anti-emetic drugs and the length of stay. Furthermore, we evaluated opioid-related adverse event reports. Results The consumption of opioids during the first 24 h after surgery and the use of anti-emetic drugs were similar in both groups. The median opioid dose of intravenous morphine equivalents was 41.1 mg (interquartile range (IQR): 29.5–69.1 mg) in the patient-controlled analgesia group and 40.5 mg (IQR: 32.4–48.6 mg) in the control group, respectively. The median length of stay was 2 days (IQR: 2–3 days) in the patient-controlled analgesia group and 3 days (IQR: 2–3 days) in the control group (p=0.02). The use of anti-emetic drugs was similar in both groups. Conclusions The administration of oxycodone via intravenous patient-controlled analgesia devices does not lead to increased opioid or anti-emetic consumptions compared to nurse-administered pain medication after total knee arthroplasty. Patient-controlled analgesia might lead to shortened length of stay.

Lean management is growing in popularity in the healthcare sector worldwide, yet healthcare organizations are struggling with assessing the maturity of their Lean implementation and monitoring its change over time. Most existing methods for such assessments are time consuming, require site visits by external consultants, and lack frontline involvement. The original Lean Healthcare Implementation Self-Assessment Instrument (LHISI) was developed by the Center for Lean Engagement and Research (CLEAR), University of California, Berkeley as a Lean principles-based survey instrument that avoids the above problems. We validated the original LHISI in the context of Finnish healthcare. Background Lean management is growing in popularity in the healthcare sector worldwide, yet healthcare organizations are struggling with assessing the maturity of their Lean implementation and monitoring its change over time. Most existing methods for such assessments are time consuming, require site visits by external consultants, and lack frontline involvement. The original Lean Healthcare Implementation Self-Assessment Instrument (LHISI) was developed by the Center for Lean Engagement and Research (CLEAR), University of California, Berkeley as a Lean principles-based survey instrument that avoids the above problems. We validated the original LHISI in the context of Finnish healthcare. Methods The original HISI survey was sent over a secure organizational email system to the over 26,000 employees of the Hospital District of Helsinki and Uusimaa in March 2020. The data were randomly split with one part used to carry out an exploratory factor analysis (EFA), and the other for testing the resulting model using confirmatory factor analysis (CFA). Results A total of 6073 employees responded to the LHISI survey, for an overall response rate of 23%. The results indicated that the 43 items used in the original LHISI can be reduced to 25 items, and these items measure a five-dimensional model of the progress of Lean implementation: leadership, commitment, standard work, communication, and daily management system. In comparison with a single-factor model, the fit measures for the 5-factor model were better: smaller X-2, larger comparative fit index (CFI), smaller root mean square error of approximation (RMSEA), and smaller standardized root mean square residual (SRMR). Conclusions The 25 item LHISI is valid and feasible to use in the context of Finnish healthcare. The LHISI allows the organization to self-monitor the progress of its Lean implementation and provides the leadership with actionable knowledge to guide the path towards Lean maturity across the organization. Our findings encourage further studies on the adoption and validation of the LHISI in healthcare organizations worldwide.

Background It is assumed that the implementation of health information technology introduces new vulnerabilities within a complex sociotechnical health care system, but no international consensus exists on a standardized format for enhancing the collection, analysis, and interpretation of technology-induced errors. Objective This study aims to develop a classification for patient safety incident reporting associated with the use of mature electronic health records (EHRs). It also aims to validate the classification by using a data set of incidents during a 6-month period immediately after the implementation of a new EHR system. Methods The starting point of the classification development was the Finnish Technology-Induced Error Risk Assessment Scale tool, based on research on commonly recognized error types. A multiprofessional research team used iterative tests on consensus building to develop a classification system. The final classification, with preliminary descriptions of classes, was validated by applying it to analyze EHR-related error incidents (n=428) during the implementation phase of a new EHR system and also to evaluate this classification’s characteristics and applicability for reporting incidents. Interrater agreement was applied. Results The number of EHR-related patient safety incidents during the implementation period (n=501) was five-fold when compared with the preimplementation period (n=82). The literature identified new error types that were added to the emerging classification. Error types were adapted iteratively after several test rounds to develop a classification for reporting patient safety incidents in the clinical use of a high-maturity EHR system. Of the 427 classified patient safety incidents, interface problems accounted for 96 (22.5%) incident reports, usability problems for 73 (17.1%), documentation problems for 60 (14.1%), and clinical workflow problems for 33 (7.7%). Altogether, 20.8% (89/427) of reports were related to medication section problems, and downtime problems were rare (n=8). During the classification work, 14.8% (74/501) of reports of the original sample were rejected because of insufficient information, even though the reports were deemed to be related to EHRs. The interrater agreement during the blinded review was 97.7%. Conclusions This study presents a new classification for EHR-related patient safety incidents applicable to mature EHRs. The number of EHR-related patient safety incidents during the implementation period may reflect patient safety challenges during the implementation of a new type of high-maturity EHR system. The results indicate that the types of errors previously identified in the literature change with the EHR development cycle.

Background Persistent postsurgical pain after total knee arthroplasty is a common problem and a major reason for patient dissatisfaction. This secondary analysis aimed to investigate the effects of anesthesia (spinal vs. general) and tourniquet use on persistent pain after total knee arthroplasty. Methods In this secondary analysis of a previously presented parallel, single-center, randomized trial, 404 patients scheduled for total knee arthroplasty were randomized to spinal versus general anesthesia and no-tourniquet versus tourniquet groups. Patients assessed pain using the Brief Pain Inventory–short form preoperatively and 3 and 12 months postoperatively. The prespecified main outcome was the change in “average pain” measured with numerical 0 to 10 rating scale 1 yr postoperatively. The threshold for clinical importance between groups was set to 1.0. Results The change in average pain scores 1 yr postoperatively did not differ between the spinal and general anesthesia groups (–2.6 [SD 2.5] vs. –2.3 [SD 2.5], respectively; mean difference, –0.4; 95% CI, –0.9 to 0.1; P = 0.150). The no-tourniquet group reported a smaller decrease in the average pain scores than the tourniquet group (–2.1 [SD 2.7] vs. –2.8 [SD 2.3]; mean difference, 0.6; 95% CI, 0.1 to 1.1; P = 0.012). After 1 yr, the scores concerning the mean of four pain severity variables (numerical rating scale) decreased more in the spinal than in the general anesthesia group (–2.3 [SD 2.2] vs. –1.8 [SD 2.1]; mean difference, –0.5; 95% CI, –0.9 to –0.05; P = 0.029) and less in the no-tourniquet than in the tourniquet group (–1.7 [SD 2.3] vs. –2.3 [SD 2.0]; mean difference, 0.6; 95% CI, 0.2 to 1.0; P = 0.005). None of the differences in pain scores reached the threshold for clinical importance. Conclusions The type of anesthesia (spinal vs. general) or tourniquet use has no clinically important effect on persistent postsurgical pain after total knee arthroplasty. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Background Health-care organizations around the world are striving to achieve transformational performance improvement, often through adopting process improvement methodologies such as lean management. Indeed, lean management has been implemented in hospitals in many countries. But despite a shared methodology and the potential benefit of benchmarking lean implementation and its effects on hospital performance, cross-national lean benchmarking is rare. Health-care organizations in different countries operate in very different contexts, including different health-care system models, and these differences may be perceived as limiting the ability of improvers to benchmark lean implementation and related organizational performance. However, no empirical research is available on the international relevance and applicability of lean implementation and hospital performance measures. To begin understanding the opportunities and limitations related to cross-national benchmarking of lean in hospitals, we conducted a cross-national case study of the relevance and applicability of measures of lean implementation in hospitals and hospital performance. Methods We report an exploratory case study of the relevance of lean implementation measures and the applicability of hospital performance measures using quantitative comparisons of data from Hospital District of Helsinki and Uusimaa (HUS) Helsinki University Hospital in Finland and a sample of 75 large academic hospitals in the USA. Results The relevance of lean-related measures was high across the two countries: almost 90% of the items developed for a US survey were relevant and available from HUS. A majority of the US-based measures for financial performance (66.7%), service provision/utilization (100.0%) and service provision/care processes (60.0%) were available from HUS. Differences in patient satisfaction measures prevented comparisons between HUS and the USA. Of 18 clinical outcome measures, only four (22%) were not comparable. Clinical outcome measures were less affected by the differences in health-care system models than measures related to service provision and financial performance. Conclusions Lean implementation measures are highly relevant in health-care organizations operating in the USA and Finland, as is the applicability of a variety of performance improvement measures. Cross-national benchmarking in lean healthcare is feasible, but a careful assessment of contextual factors, including the health-care system model, and their impact on the applicability and relevance of chosen benchmarking measures is necessary. The differences between the US and Finnish health-care system models is most clearly reflected in financial performance measures and care process measures.

BACKGROUND It is assumed that the implementation of health information technology introduces new vulnerabilities within a complex sociotechnical health care system, but no international consensus exists on a standardized format for enhancing the collection, analysis, and interpretation of technology-induced errors. OBJECTIVE This study aims to develop a classification for patient safety incident reporting associated with the use of mature electronic health records (EHRs). It also aims to validate the classification by using a data set of incidents during a 6-month period immediately after the implementation of a new EHR system. METHODS The starting point of the classification development was the Finnish Technology-Induced Error Risk Assessment Scale tool, based on research on commonly recognized error types. A multiprofessional research team used iterative tests on consensus building to develop a classification system. The final classification, with preliminary descriptions of classes, was validated by applying it to analyze EHR-related error incidents (n=428) during the implementation phase of a new EHR system and also to evaluate this classification’s characteristics and applicability for reporting incidents. Interrater agreement was applied. RESULTS The number of EHR-related patient safety incidents during the implementation period (n=501) was five-fold when compared with the preimplementation period (n=82). The literature identified new error types that were added to the emerging classification. Error types were adapted iteratively after several test rounds to develop a classification for reporting patient safety incidents in the clinical use of a high-maturity EHR system. Of the 427 classified patient safety incidents, interface problems accounted for 96 (22.5%) incident reports, usability problems for 73 (17.1%), documentation problems for 60 (14.1%), and clinical workflow problems for 33 (7.7%). Altogether, 20.8% (89/427) of reports were related to medication section problems, and downtime problems were rare (n=8). During the classification work, 14.8% (74/501) of reports of the original sample were rejected because of insufficient information, even though the reports were deemed to be related to EHRs. The interrater agreement during the blinded review was 97.7%. CONCLUSIONS This study presents a new classification for EHR-related patient safety incidents applicable to mature EHRs. The number of EHR-related patient safety incidents during the implementation period may reflect patient safety challenges during the implementation of a new type of high-maturity EHR system. The results indicate that the types of errors previously identified in the literature change with the EHR development cycle.

Background We investigated the effects of spinal and general anaesthesia and surgical tourniquet on acute pain and early recovery after total knee arthroplasty (TKA). Methods Patients (n=413) were randomised to four parallel groups: spinal anaesthesia with or without tourniquet, and general anaesthesia with or without tourniquet. The primary outcome was patient-controlled i.v. oxycodone consumption over 24 postoperative hours. Results Results from 395 subjects were analysed. Median i.v. oxycodone consumption did not differ between the four groups (spinal anaesthesia without [36.6 mg] and with tourniquet [38.0 mg], general anaesthesia without [42.3 mg] and with tourniquet [42.5 mg], P=0.42), between spinal (37.7 mg) and general anaesthesia (42.5 mg) groups (median difference –3.1, 95% confidence interval [CI] –7.4 to 1.2, P=0.15) and between tourniquet and no-tourniquet groups (40.0 vs 40.0 mg, median difference –0.8, CI –5.1 to 3.5, P=0.72). Vomiting incidence was higher with spinal than with general anaesthesia (21% [42/200] vs 13% [25/194], CI 1.05 to 3.1, P=0.034). The mean haemoglobin decrease was greater without than with tourniquet (–3.0 vs –2.5 g dl−1, mean difference –0.48, CI –0.65 to –0.32, P Conclusions For TKA, spinal and general anaesthesia with or without tourniquet did not differ in 24-h postoperative opioid consumption, pain management, blood transfusions, in-hospital complications, and length of hospital stay. Vomiting incidence was higher in the spinal than in the general anaesthesia group. Tourniquet use caused smaller decreases in haemoglobin levels. Clinical trial registration EudraCT 2016-002035-15.

The Lean management system is being adopted and implemented by an increasing number of US hospitals. Yet few studies have considered the impact of Lean on hospitalwide performance.A multivariate analysis was performed of the 2017 National Survey of Lean/Transformational Performance Improvement in Hospitals and 2018 publicly available data from the Agency for Healthcare Research and Quality and the Center for MedicareMedicaid Services on 10 quality/appropriateness of care, cost, and patient experience measures.Hospital adoption of Lean was associated with higher Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) patient experience scores (b = 3.35, p0.0001) on a scale of 100-300 but none of the other 9 performance measures. The degree of Lean implementation measured by the number of units throughout the hospital using Lean was associated with lower adjusted inpatient expense per admission (b = -38.67; p0.001), lower 30-day unplanned readmission rate (b = -0.01, p0.007), a score above the national average on appropriate use of imaging-a measure of low-value care (odds ratio = 1.04, p0.042), and higher HCAHPS patient experience scores (b = 0.12, p0.012). The degree of Lean implementation was not associated with any of the other 6 performance measures.Lean is an organizationwide sociotechnical performance improvement system. As such, the actual degree of implementation throughout the organization as opposed to mere adoption is, based on the present findings, more likely to be associated with positive hospital performance on at least some measures.

RESEARCH OBJECTIVE: Lean implementation assessment is needed to understand the depth and breadth of Lean deployment and guide organizations in strengthening Lean implementation and its potential to improve organizational performance. To assist health care leaders to understand the extent to which Lean management has been implemented in their organizations, we developed the Lean Healthcare Implementation Self‐Assessment Instrument (LHISI), a 34‐item survey instrument that assesses Lean implementation across six dimensions. STUDY DESIGN: Following a review of extant measures of Lean implementation, an initial list of 101 items was compiled and reviewed by Lean implementation experts, reflecting behaviors linked to 14 principles of Lean management from the Shingo and 4P models of Lean. Two rounds of item selection surveys were completed by health care managers and clinicians to identify the most important items, which were included in LHISI version 1 (V1). Managers and clinicians in 7 different organizations completed two rounds of V1 pilot testing used to perform test‐retest analyses, exploratory factor analysis (EFA), and other statistical tests to develop V2. Finally, managers and clinicians at two large teaching hospitals pilot tested V2, and their responses were divided into half and used for EFA and confirmatory factor analysis (CFA), respectively. POPULATION STUDIED: Item selection and pilot testing surveys were completed by managers and clinicians in seven health care organizations currently implementing Lean management. The two rounds of item selection included 36 and 39 respondents; V1 pilot testing included 232 respondents (including 34 retests); and V2 pilot testing included 914 respondents. PRINCIPAL FINDINGS: Expert review and two rounds of item selection testing reduced the number of survey items from 101 to the 48 items included in V1. Each item reflects an important core principle of Lean (eg, In my unit/department, work processes are standardized; across my hospital/clinic, leaders at all levels create a safe environment for exposing problems; and in my unit/department, frontline staff use visual displays to understand their unit’s performance). V1 pilot testing analyses suggested removal of 5 items: 2 items did not load on a factor in exploratory factor analysis, and 3 items had insufficient test‐retest reliability (the remaining items had Pearson’s r 0.72‐0.85). Consequently, LHISI V2 included 43 items, and the 914 responses were randomly divided and used for EFA and CFA. EFA demonstrated six underlying factors encompassing 34 items (9 items did not fit well with any factor): organizational culture (10 items), commitment to Lean (7 items), standard work (5 items), huddles (4 items), unit culture (4 items), and visual management (4 items). Each of the subscales demonstrates good internal consistency, with Cronbach alphas ranging from .89 to .97. CFA model fit comparisons supported the above six‐factor model over single factor and seven‐factor models. CONCLUSIONS: The 34‐item LHISI demonstrates good content validity, internal consistency, test‐retest reliability, and appropriate factor clusters. IMPLICATIONS FOR POLICY OR PRACTICE: The LHISI provides an accessible way for health care leaders to assess Lean implementation in their organization and to identify targets for improvement. Ongoing research will further explore the characteristics of the instrument, including the relationship between LHISI scores and performance.

BACKGROUND Patient-reported preoperative factors hold promise in improving the prediction of postoperative adverse events, but they have been poorly studied. OBJECTIVE To study the role of patient-reported factors in the preoperative risk stratification of elective craniotomy patients. METHODS A prospective, unselected cohort of 322 adult patients underwent elective craniotomy in Helsinki, Finland. We preoperatively recorded the American Society of Anesthesiologists (ASA) score, Helsinki ASA score, and 3 questionnaire-based patient-reported factors including overall health status, ability to climb 2 flights of stairs, and cognitive function (Test Your Memory test). Outcome measures comprised in-hospital major and overall morbidity. Receiver-operating characteristic curves served to calculate area under the curve (AUC) values for a composite score of patient-reported factors and both ASA scores with regard to outcomes. RESULTS In-hospital major and overall morbidity rate was 15.2%. Only preoperatively diminished cognitive function remained a significant predictor of major morbidity after multivariable logistic regression analysis (P < .001, odds ratio 1.1, confidence interval 1.0-1.1). A composite score of our 3 patient-reported factors had a higher AUC (0.675) for major morbidity than original ASA score (0.543) or Helsinki ASA score (0.572). In elderly patients, the composite score had an AUC of 0.726 for major morbidity. CONCLUSION Preoperative patient-reported factors had higher sensitivity for detecting major morbidity compared to the ASA scores in this study. Particularly, the simple composite score seems to predict adverse outcomes in elective cranial surgery surprisingly well, especially in the elderly. These results are interesting and worth confirming in other centers.

IntroductionTotal knee arthroplasty is a highly effective treatment for end-stage knee osteoarthritis, and it is usually performed under spinal or general anaesthesia with or without a surgical tourniquet. Some debate about the preferred mode of anaesthesia regarding patient outcomes remains. The aim of this study, which compares general and spinal anaesthesia with and without a tourniquet on the outcomes of total knee arthroplasty, is to determine the optimal type of anaesthesia regimen and assess the effect of a tourniquet on the patient’s recovery following total knee arthroplasty.Methods and analysisThis study is a randomised, controlled, parallel-group, four-arm study comparing spinal and general anaesthesia with and without a tourniquet in 400 patients undergoing fast-track total knee arthroplasty, with a 12-month follow-up. The primary outcome is cumulative intravenous oxycodone consumption by patient-controlled analgesia during the first 24 postoperative hours. Secondary outcomes include postoperative nausea and vomiting, the length of hospital stay, the duration of the surgery, blood loss, demand for surgical unit resources, complications, readmissions, postoperative knee function, range of motion, health-related quality of life, prolonged pain and mortality.Ethics and disseminationThis study’s protocol is in accordance with the declaration of Helsinki. The results of this study will be disseminated in international peer-reviewed journals.Trial registration numberNCT03364088; Pre-results.

The role of patient-reported outcomes (PROs) in elective cranial neurosurgery has been poorly studied, and their significance in reflecting complication rates is unclear.A prospective, consecutive, and unselected cohort of 418 adult patients underwent elective intracranial operations between 7 December, 2011 and 31 December, 2012 in Helsinki University Hospital, Finland. The questionnaire-based PROs included subjective postoperative assessments of overall health, cognitive function, and subjective change in functional status. Outcome measures included in-hospital major morbidity (including mortality) and in-hospital overall morbidity. We compared the usefulness of PROs with postoperative modified Rankin Scale (mRS) score.In univariable analyses, all recorded PROs and 30-day mRS scores ≥ 3 were associated with in-hospital major and overall morbidity. After multivariable analyses, postoperative deterioration of subjective functional status remained associated with in-hospital major morbidity (P = 0.001, odds ratio [OR] 4.9, confidence interval [CI] 1.9-12.0, sensitivity 71%, and specificity 70%) and overall in-hospital morbidity (P0.001, OR 5.7, CI 3.1-10.7, sensitivity 59%, and specificity 84%). Postoperatively impaired functional status was more sensitive but less specific in detecting in-hospital major and overall morbidity than the widely used mRS cut-off value of 2. A simple composite score combining the 3 recorded PROs was highly sensitive and specific in detecting in-hospital major (sensitivity 87%, specificity 98%) and overall (sensitivity 72%, specificity 99%) morbidity.In elective craniotomy patients, PROs seem promising patient-centered tools for outcomes reporting. Furthermore, neurosurgery-specific patient-reported outcome measures (PROMs) can perhaps be implemented to clinical use to improve patient safety and outcome comparisons in elective cranial neurosurgery.

BACKGROUND Patient-reported experience is often used as a measure for quality of care, but no reports on patient satisfaction after cranial neurosurgery exist. OBJECTIVE To study the association of overall patient satisfaction and surgical outcome and to evaluate the applicability of overall patient satisfaction as a proxy for quality of care in elective cranial neurosurgery. METHODS We conducted an observational study on the relationship of overall patient satisfaction at 30 postoperative days with surgical and functional outcome (modified Rankin Scale [mRS] score) in a prospective, consecutive, and unselected cohort of 418 adult elective craniotomy patients enrolled between December 2011 and December 2012 at Helsinki University Hospital, Helsinki, Finland. RESULTS Postoperative overall (subjective and objective) morbidity was present in 194 (46.4%) patients; yet almost 94% of all study patients reported high overall satisfaction. Low overall patient satisfaction at 30 days was not associated with postoperative major morbidity in elective cranial neurosurgery. Dependent functional status (mRS score ≥3) at 30 days, minor infections, poor postoperative subjective overall health status, and patient-reported severe symptoms (double vision, poor balance) may contribute to unsatisfactory patient experience. CONCLUSION Overall patient satisfaction with elective cranial neurosurgery is high. Even 9 of 10 patients with postoperative major morbidity rated high overall patient satisfaction at 30 days. Overall patient satisfaction may merely reflect patient experience and subjective postoperative health status, and therefore it is a poor proxy for quality of care in elective cranial neurosurgery.

BACKGROUND: Multiple nationwide outcome registries are utilized for quality benchmarking between institutions and individual surgeons. OBJECTIVE: To evaluate whether nationwide quality of care programs in the United Kingdom and United States can measure differences in neurosurgical quality. METHODS: This prospective observational study comprised 418 consecutive adult patients undergoing elective craniotomy at Helsinki University Hospital between December 7, 2011 and December 31, 2012.We recorded outcome event rates and categorized them according to British Neurosurgical National Audit Programme (NNAP), American National Surgical Quality Improvement Program (NSQIP), and American National Neurosurgery Quality and Outcomes Database (N(2)QOD) to assess the applicability of these programs for quality benchmarking and estimated sample sizes required for reliable quality comparisons. RESULTS: The rate of in-hospital major and minor morbidity was 18.7% and 38.0%, respectively, and 30-d mortality rate was 2.4%. The NSQIP criteria identified 96.2% of major but only 38.4% of minor complications. N(2)QOD performed better, but almost one-fourth (23.2%) of all patients with adverse outcomes, mostly minor, went unnoticed. For NNAP, a sample size of over 4200 patients per surgeon is required to detect a 50.0% increase in mortality rates between surgeons. The sample size required for reliable comparisons between the rates of complications exceeds 600 patients per center per year. CONCLUSION: The implemented benchmarking programs in the United Kingdom and United States fail to identify a considerable number of complications in a high-volume center. Health care policy makers should be cautious as outcome comparisons between most centers and individual surgeons are questionable if based on the programs.

OBJECT Patients undergoing craniotomy are routinely assessed preoperatively, yet the role of these assessments in predicting outcome is poorly studied. This study aimed to identify preoperative factors predicting in-hospital outcome after cranial neurosurgery. METHODS The study cohort consisted of 418 consecutive adults undergoing elective craniotomy for any intracranial lesion. Apart from the age criteria (≥ 18 years), almost all patients were considered eligible for the study to increase external validity of the results. The studied preoperative assessments included various patient-related data, routine blood tests, American Society of Anesthesiologists (ASA) Physical Status Classification system, and a local modification of the ASA classification (Helsinki ASA classification). Adverse outcomes were in-hospital mortality, in-hospital systemic or infectious complications, and in-hospital CNS deficits. Resource use was defined as length of stay (LOS) in the intensive care unit and overall LOS in the hospital. RESULTS The in-hospital mortality rate was 1.0%. In-hospital systemic or infectious complications and permanent or transient CNS deficits occurred in 6.7% and 11.2% of the patients, respectively. Advanced age (≥ 60–65 years), elevated C-reactive protein level (> 3 mg/L), and high Helsinki ASA score (Class 4) were associated with in-hospital systemic and infectious complications, and a combination of these could identify one-fourth of the patients with postoperative complications. Moreover, this combination of preoperative assessment parameters was significantly associated with increased resource use. CONCLUSIONS In this first prospective and unselected cohort study of outcome after elective craniotomy, simple preoperative assessments identified patients with a high risk of in-hospital systemic or infectious complications as well as extended resource use. Presented risk assessment methods may be widely applicable, also in low-volume centers, as they are based on composite predictors and outcome events.

BACKGROUND: The modified Rankin Scale (mRS) was developed to monitor functional recovery after stroke, but nowadays it is a treatment outcome measure in elective neurosurgery. Our objective was to study how mRS changes associate with short-term postoperative outcome. METHODS: Preoperative, in-hospital, and 30-day mRS scores came from a prospective, consecutive and unselected cohort of 418 adult elective craniotomy patients enrolled between December 2011 and December 2012 in Helsinki, Finland. Recorded data included subjective and objective postoperative in-hospital complications as well as changes in mRS score after surgery. RESULTS: Minor or major complications were detectable in 46% of the patients. In-hospital and 30-day postoperative increases in mRS score were inconsistent; among patients with no complications, 17% had a greater mRS score at discharge and 24% at 30 days, whereas 28% of the patients with major complications showed no increase in mRS score at discharge. Of individual complications, only new or worsened hemiparesis, silent stroke, and pneumonia were associated with postoperative increase (>2) in mRS score after multivariable analysis. For mRS-score difference >1 at discharge in detecting major complications (including mortality), sensitivity was 45% and specificity 94%. CONCLUSIONS: The mRS changes after elective cranial neurosurgery are inconsistent. The mRS seems to represent functional changes, which do not necessarily associate with detected in-hospital complications.

Preoperative risk scores are designed to guide patient management by providing a means of predicting operative outcome. Several risk scores are used in neurosurgery, but studies on their clinical relevance are scarce. Therefore, it is not clear whether these risk scores are beneficial or helpful in predicting outcome after elective cranial neurosurgery. In this review, we summarize the current scientific evidence for using preoperative risk scores in elective cranial neurosurgery.A systematic review of the MEDLINE, Embase, and PubMed databases in November 2013 yielded 25 relevant studies with a minimum of 30 patients per study. The studies evaluated the value of the preoperative ASA physical status classification, the Karnofsky performance score (KPS), the Charlson comorbidity score, the modified Rankin Scale and the sex, KPS, ASA physical status classification, location, and edema (SKALE) score in assessing postoperative outcome in cranial neurosurgery. Surgery-related and nonsurgical complications were assessed separately whenever reported in the original article. For this purpose, the studies were placed into 4 categories based on the reported outcome: surgery-related outcome, nonsurgical outcome, morbidity, and mortality. The Preferred Reporting Items for Systematic reviews and Meta-analyses guidelines for systematic reviews were followed.KPS has the strongest support in the literature for predicting surgery-related outcomes. There is no strong support in the literature for the use of any preoperative scores in predicting nonsurgical outcomes after elective craniotomies. KPS and ASA physical status classification seem to predict early (≤ 30-day) morbidity of intracranial tumor patients. The Charlson comorbidity score may be applicable in predicting mortality of elective intracranial aneurysm patients. Only 4 studies were prospective in design.Large prospective studies are needed to validate the use of the reviewed risk scores in elective cranial neurosurgery. It appears, however, that the patient's preoperative physical and functional status can be used to predict the short- and long-term outcome in elective cranial neurosurgery.