Clinical tools to assess functional capacity before elective non-cardiac surgery: a scoping review protocol.

OBJECTIVE: The objective of this scoping review is to map the evidence on clinical tools to assess functional capacity prior to elective non-cardiac surgery. INTRODUCTION: Functional capacity is a strong prognostic indicator before surgery, which can be used to identify patients at elevated risk of postoperative complications, yet, there is no consensus on which clinical tools should be used to assess functional capacity in patients prior to non-cardiac surgery. INCLUSION CRITERIA: This review will consider any randomized or non-randomized studies that evaluate the performance of a functional capacity assessment tool in adults (≥18 years) prior to non-cardiac surgery. For studies to be included, the tool must be used clinically for risk stratification. We will exclude studies on lung and liver transplant surgery, as well as ambulatory procedures performed under local anesthesia. METHODS: The review will be conducted in line with the JBI methodology for scoping reviews. A peer-reviewed search strategy will be used to query relevant databases (ie, MEDLINE, Embase, EBM Reviews). Additional sources of evidence will include databases of non-peer-reviewed literature and the reference lists of included studies. Two independent reviewers will identify eligible studies in 2 stages: stage 1, based on titles and abstracts; and stage 2, based on full texts. Information on study details, measurement properties, pragmatic qualities, and/or clinical utility metrics will be charted in duplicate onto standardized data collection forms. The results will be presented using descriptive summaries, frequency tables, and visual plots that highlight the extent of evidence and remaining gaps in the validation process of each tool. REVIEW REGISTRATION: Open Science Framework https://osf.io/6nfht.

Socio-demographic characteristics associated with hospitalization for sepsis among adults in Canada: a Census-linked cohort study.

PURPOSE: Sepsis is a considerable health system burden. Population-based epidemiological surveillance of sepsis is limited to basic data available in administrative databases. We sought to determine if routinely collected Census data, linked to hospitalization data, can provide a broad socio-demographic profile of patients admitted to Canadian hospitals with sepsis. METHODS: Linking the 2006 long-form Canadian Census (most recent available for linkage) to the Discharge Abstract Data from 2006/2007 to 2008/2009, we created a population-based cohort of approximately 3,433,900 Canadians. Patients admitted to hospital with sepsis were identified using the Canadian Institute for Health Information administrative data definition. Age-standardized hospital admission rates for sepsis were calculated. Multivariable modelling was used to examine the relationship between Census characteristics and hospitalization with sepsis. RESULTS: Of those individuals successfully linked to the 2006 long-form Canadian Census, 10,400 patients of 18 yr and older were admitted to hospital with sepsis between the fiscal years 2006/2007 and 2008/2009. These individuals represented a weighted count of approximately 49,000 Canadians from all provinces and territories, excluding Quebec. The age-standardized rate of sepsis hospitalization was 96 cases/100,000 population. Of these, 37/100,000 cases were classified as severe sepsis. The association of Census characteristics with sepsis hospitalization varied with age. In all age-specific models, male sex, never being married, visible minority status, having functional limitations, and not being in the labour force were associated with an increased odds of hospital admission. CONCLUSIONS: Census data identified broad socio-demographic risk factors for admission to hospital with sepsis. Consideration should be given to incorporating Census data linked to administrative hospital data in population-based epidemiologic surveillance.

Measuring patient-centred system performance: a scoping review of patient-centred care quality indicators.

OBJECTIVES: The shift to the patient-centred care (PCC) model as a healthcare delivery paradigm calls for systematic measurement and evaluation. In an attempt to develop patient-centred quality indicators (PC-QIs), this study aimed to identify quality indicators that can be used to measure PCC. METHODS: Design: scoping review. DATA SOURCES: studies were identified through searching seven electronic databases and the grey literature. Search terms included quality improvement, quality indicators, healthcare quality and PCC. Eligibility Criteria: articles were included if they mentioned development and/or implementation of PC-QIs. DATA EXTRACTION AND SYNTHESIS: extracted data included study characteristics (country, year of publication and type of study/article), patients' inclusion in the development of indicators and type of patient populations and point of care if applicable (eg, in-patient, out-patient and primary care). RESULTS: A total 184 full-text peer-reviewed articles were assessed for eligibility for inclusion; of these, 9 articles were included in this review. From the non-peer-reviewed literature, eight documents met the criteria for inclusion in this study. This review revealed the heterogeneity describing and defining the nature of PC-QIs. Most PC-QIs were presented as PCC measures and identified as guidelines, surveys or recommendations, and therefore cannot be classified as actual PC-QIs. Out of 502 ways to measure PCC, only 25 were considered to be actual PC-QIs. None of the identified articles implemented the quality indicators in care settings. CONCLUSION: The identification of PC-QIs is a key first step in laying the groundwork to develop evidence-based PC-QIs. Research is needed to continue the development and implementation of PC-QIs for healthcare quality improvement.

Identifying Canadian patient-centred care measurement practices and quality indicators: a survey.

BACKGROUND: Patient-centred quality indicators allow health care systems to monitor and evaluate patient-centred care practices and identify gaps in health care quality. Our objective was to determine whether Canadian provinces and territories measure patient-centred care, identify patient-centred quality indicators currently being used and compare patient-centred care practices and measurement in Canada to those of health care systems in other countries. METHODS: An online survey was developed to collect data on demographic characteristics, patient-centred care practices, and indicators used at quality improvement organizations and health care authorities. The survey was conducted with quality improvement leads in Canada and 4 other countries. Content analysis methods were used to analyze and report the data. Patient-centred quality indicators were identified and categorized according to the Donabedian framework (structure, process, outcome). RESULTS: The survey had a response rate of 47/67 (70%) and a completion rate of 58/60 (97%). We obtained completed surveys from 12 of the 13 provinces and territories in Canada. Respondents from most provinces indicated their organization used patient-centred care measures to inform practices. Respondents in only 4 provinces/territories reported using patient-centred quality indicators, for a total of 61 unique indicators. Most indicators used across Canada assessed aspects of care related to the Donabedian components of process and outcome. Findings for Canada were comparable to those for Sweden, England, Australia and New Zealand, where many measures are still in development. INTERPRETATION: This study provided greater insight into patient-centred care measurement across Canada, Sweden, England, Australia and New Zealand and helped us to identify patient-centred quality indicators currently in use. These results will inform the development of a standard set of patient-centred quality indicators for implementation by health care organizations to improve the quality of health care.

Correction: The effects of patient cost sharing on inpatient utilization, cost, and outcome.

[This corrects the article DOI: 10.1371/journal.pone.0187096.].

Coding reliability and agreement of International Classification of Disease, 10th revision (ICD-10) codes in emergency department data.

INTRODUCTION: Administrative health data from emergency departments play important roles in understanding health needs of the public and reasons for health care resource use. International Classification of Disease (ICD) diagnostic codes have been widely used to code reasons of clinical encounters for administrative purposes in emergency departments. OBJECTIVE: The purpose of the study is to examine the coding agreement and reliability of ICD diagnosis codes in emergency department records through auditing the routinely collected data. METHODS: We randomly sampled 1 percent of records (n=1636) between October and December 2013 from 11 emergency departments in Alberta, Canada. Auditors were employed to review the same chart and independently assign main diagnosis codes. We assessed coding agreement and reliability through comparison of codes assigned by auditors and hospital coders using proportion of agreement and Cohen's kappa. Error analysis was conducted to review diagnosis codes with disagreement and categorized them into six groups. RESULTS: Overall, the agreement was 86.5% and 82.2% at 3 and 4 digits levels respectively, and reliability was 0.86 and 0.82 respectively. Variations of agreement and reliability were identified across different emergency departments. The major two categories of coding discrepancy were the use of different codes for same condition (23.6%) and the use of codes at different levels of specificity (20.9%). CONCLUSIONS: Diagnosis codes in emergency departments show high agreement and reliability, although there are variations of coding quality across different hospitals. Stricter coding guidelines regarding the use of unspecified codes are needed to enhance coding consistency.

Identifying Cases of Sleep Disorders through International Classification of Diseases (ICD) Codes in Administrative Data.

OBJECTIVES: Prevalence, and associated morbidity and mortality of chronic sleep disorders have been limited to small cohort studies, however, administrative data may be used to provide representation of larger population estimates of disease. With no guidelines to inform the identification of cases of sleep disorders in administrative data, the objective of this study was to develop and validate a set of ICD-codes used to define sleep disorders including narcolepsy, insomnia, and obstructive sleep apnea (OSA) in administrative data. METHODS: A cohort of adult patients, with medical records reviewed by two independent board-certified sleep physicians from a sleep clinic in Calgary, Alberta between January 1, 2009 and December 31, 2011, was used as the reference standard. We developed a general ICD-coded case definition for sleep disorders which included conditions of narcolepsy, insomnia, and OSA using: 1) physician claims data, 2) inpatient visit data, 3) emergency department (ED) and ambulatory care data. We linked the reference standard data and administrative data to examine the validity of different case definitions, calculating estimates of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: From a total of 1186 patients from the sleep clinic, 1045 (88.1%) were classified as sleep disorder positive, with 606 (51.1%) diagnosed with OSA, 407 (34.4%) with insomnia, and 59 (5.0%) with narcolepsy. The most frequently used ICD-9 codes were general codes of 307.4 (Nonorganic sleep disorder, unspecified), 780.5 (unspecified sleep disturbance) and ICD-10 codes of G47.8 (other sleep disorders), G47.9 (sleep disorder, unspecified). The best definition for identifying a sleep disorder was an ICD code (from physician claims) 2 years prior and 1 year post sleep clinic visit: sensitivity 79.2%, specificity 28.4%, PPV 89.1%, and NPV 15.6%. ICD codes from ED/ambulatory care data provided similar diagnostic performance when at least 2 codes appeared in a time period of 2 years prior and 1 year post sleep clinic visit: sensitivity 71.9%, specificity 54.6%, PPV 92.1%, and NPV 20.8%. The inpatient data yielded poor results in all tested ICD code combinations. CONCLUSION: Sleep disorders in administrative data can be identified mainly through physician claims data and with some being determined through outpatient/ambulatory care data ICD codes, however these are poorly coded within inpatient data sources. This may be a function of how sleep disorders are diagnosed and/or reported by physicians in inpatient and outpatient settings within medical records. Future work to optimize administrative data case definitions through data linkage are needed.

How to practice person-centred care: A conceptual framework.

BACKGROUND: Globally, health-care systems and organizations are looking to improve health system performance through the implementation of a person-centred care (PCC) model. While numerous conceptual frameworks for PCC exist, a gap remains in practical guidance on PCC implementation. METHODS: Based on a narrative review of the PCC literature, a generic conceptual framework was developed in collaboration with a patient partner, which synthesizes evidence, recommendations and best practice from existing frameworks and implementation case studies. The Donabedian model for health-care improvement was used to classify PCC domains into the categories of "Structure," "Process" and "Outcome" for health-care quality improvement. DISCUSSION: The framework emphasizes the structural domain, which relates to the health-care system or context in which care is delivered, providing the foundation for PCC, and influencing the processes and outcomes of care. Structural domains identified include: the creation of a PCC culture across the continuum of care; co-designing educational programs, as well as health promotion and prevention programs with patients; providing a supportive and accommodating environment; and developing and integrating structures to support health information technology and to measure and monitor PCC performance. Process domains describe the importance of cultivating communication and respectful and compassionate care; engaging patients in managing their care; and integration of care. Outcome domains identified include: access to care and Patient-Reported Outcomes. CONCLUSION: This conceptual framework provides a step-wise roadmap to guide health-care systems and organizations in the provision PCC across various health-care sectors.

The effects of patient cost sharing on inpatient utilization, cost, and outcome.

BACKGROUND: Health insurance and provider payment reforms all over the world beg a key empirical question: what are the potential impacts of patient cost-sharing on health care utilization, cost and outcomes? The unique health insurance system and rich electronic medical record (EMR) data in China provides us a unique opportunity to study this topic. METHODS: Four years (2010 to 2014) of EMR data from one medical center in China were utilized, including 10,858 adult patients with liver diseases. We measured patient cost-sharing using actual reimbursement ratio (RR) which is allowed us to better capture financial incentive than using type of health insurance. A rigorous risk adjustment method was employed with both comorbidities and disease severity measures acting as risk adjustors. Associations between RR and health use, costs and outcome were analyzed by multivariate analyses. RESULTS: After risk adjustment, patients with more generous health insurance coverage (higher RR) were found to have longer hospital stay, higher total cost, higher medication cost, and higher ratio of medication to total cost, as well as higher number and likelihood that specific procedures were performed. CONCLUSION: Our study implied that patient cost-sharing affects health care services use and cost. This reflects how patients and physicians respond to financial incentives in the current healthcare system in China, and the responses could be a joint effect of both demand and supply side moral hazard. In order to contain cost and improve efficiency in the system, reforming provide payment and insurance scheme is urgently needed.

Protocol for a scoping review study to identify and classify patient-centred quality indicators.

INTRODUCTION: The concept of patient-centred care (PCC) is changing the way healthcare is understood, accepted and delivered. The Institute of Medicine has defined PCC as 1 of its 6 aims to improve healthcare quality. However, in Canada, there are currently no nationwide standards in place for measuring and evaluating healthcare from a patient-centred approach. In this paper, we outline our scoping review protocol to systematically review published and unpublished literature specific to patient-centred quality indicators that have been implemented and evaluated across various care settings. METHODS AND ANALYSIS: Arksey and O'Malley's scoping review methodology framework will guide the conduct of this scoping review. We will search electronic databases (MEDLINE, EMBASE, the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Social Work Abstracts, Social Services Abstracts), grey literature sources and the reference lists of key studies to identify studies appropriate for inclusion. 2 reviewers will independently screen all abstracts and full-text studies for inclusion. We will include any study which focuses on quality indicators in the context of PCC. All bibliographic data, study characteristics and indicators will be collected and analysed using a tool developed through an iterative process by the research team. Indicators will be classified according to a predefined conceptual framework and categorised and described using qualitative content analysis. ETHICS AND DISSEMINATION: The scoping review will synthesise patient-centred quality indicators and their characteristics as described in the literature. This review will be the first step to formally identify what quality indicators have been used to evaluate PCC across the healthcare continuum, and will be used to inform a stakeholder consensus process exploring the development of a generic set of patient-centred quality indicators applicable to multiple care settings. The results will be disseminated through a peer-reviewed publication, conference presentations and a one-day stakeholder meeting.

Comparison of risk adjustment methods in patients with liver disease using electronic medical record data.

BACKGROUND: Risk adjustment is essential for valid comparison of patients' health outcomes or performances of health care providers. Several risk adjustment methods for liver diseases are commonly used but the optimal approach is unknown. This study aimed to compare the common risk adjustment methods for predicting in-hospital mortality in cirrhosis patients using electronic medical record (EMR) data. METHODS: The sample was derived from Beijing YouAn hospital between 2010 and 2014. Previously validated EMR extraction methods were applied to define liver disease conditions, Charlson comorbidity index (CCI), Elixhauser comorbidity index (ECI), Child-Turcotte-Pugh (CTP), model for end-stage liver disease (MELD), MELD sodium (MELDNa), and five-variable MELD (5vMELD). The performance of the common risk adjustment models as well as models combining disease severity and comorbidity indexes for predicting in-hospital mortality was compared using c-statistic. RESULTS: Of 11,121 cirrhotic patients, 69.9% were males and 15.8% age 65 or older. The c-statistics across compared models ranged from 0.785 to 0.887. All models significantly outperformed the baseline model with age, sex, and admission status (c-statistic: 0.628). The c-statistics for the CCI, ECI, MELDNa, and CTP were 0.808, 0.825, 0.849, and 0.851, respectively. The c-statistic was 0.887 for combination of CTP and ECI, and 0.882 for combination of MELDNa score and ECI. CONCLUSIONS: The liver disease severity indexes (i.e., CTP and MELDNa score) outperformed the CCI and ECI for predicting in-hospital mortality among cirrhosis patients using Chinese EMRs. Combining liver disease severity and comorbidities indexes could improve the discrimination power of predicting in-hospital mortality.

Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data.

OBJECTIVE: Administrative health data are important for health services and outcomes research. We optimised and validated in intensive care unit (ICU) patients an International Classification of Disease (ICD)-coded case definition for sepsis, and compared this with an existing definition. We also assessed the definition's performance in non-ICU (ward) patients. SETTING AND PARTICIPANTS: All adults (aged ≥ 18 years) admitted to a multisystem ICU with general medicosurgical ICU care from one of three tertiary care centres in the Calgary region in Alberta, Canada, between 1 January 2009 and 31 December 2012 were included. RESEARCH DESIGN: Patient medical records were randomly selected and linked to the discharge abstract database. In ICU patients, we validated the Canadian Institute for Health Information (CIHI) ICD-10-CA (Canadian Revision)-coded definition for sepsis and severe sepsis against a reference standard medical chart review, and optimised this algorithm through examination of other conditions apparent in sepsis. MEASURES: Sensitivity (Sn), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were calculated. RESULTS: Sepsis was present in 604 of 1001 ICU patients (60.4%). The CIHI ICD-10-CA-coded definition for sepsis had Sn (46.4%), Sp (98.7%), PPV (98.2%) and NPV (54.7%); and for severe sepsis had Sn (47.2%), Sp (97.5%), PPV (95.3%) and NPV (63.2%). The optimised ICD-coded algorithm for sepsis increased Sn by 25.5% and NPV by 11.9% with slightly lowered Sp (85.4%) and PPV (88.2%). For severe sepsis both Sn (65.1%) and NPV (70.1%) increased, while Sp (88.2%) and PPV (85.6%) decreased slightly. CONCLUSIONS: This study demonstrates that sepsis is highly undercoded in administrative data, thus under-ascertaining the true incidence of sepsis. The optimised ICD-coded definition has a higher validity with higher Sn and should be preferentially considered if used for surveillance purposes.

Assessing the association between occupancy and outcome in critically Ill hospitalized patients with sepsis.

BACKGROUND: Sepsis has a high prevalence, mortality-rate and cost. Sepsis patients usually enter the hospital through the Emergency Department (ED). Process or structural issues related to care may affect outcome. METHODS: Multi-centered retrospective observational cohort study using administrative databases to identify adult patients (> = 18 years) with sepsis and severe sepsis admitted to Alberta Health Services Calgary zone adult multisystem intensive care units (ICU) through the ED between January 1, 2006 and September 30, 2009. We examined the association between ICU occupancy and hospital outcome. We explored other associations of hospital outcome including the effect of ED wait time, admission from ED during weekdays versus weekends and ED admission during the day versus at night. RESULTS: One thousand and seven hundred seventy patients were admitted to hospital via ED, 1036 (58.5 %) with sepsis and 734 (41.5 %) with severe sepsis. In patients with sepsis, ICU occupancy > 90 % was associated with an increase in hospital mortality even after adjusting for age, sex, triage level, Charlson index, time of first ED physician assessment and ICU admission. No differences in hospital mortality were found for patients who waited more than 7 h, were admitted during the day versus night or weekdays versus weekends. CONCLUSIONS: In patients with sepsis admitted via the ED, increased ICU occupancy was associated with higher in-hospital mortality.

Validity of administrative data in recording sepsis: a systematic review.

INTRODUCTION: Administrative health data have been used to study sepsis in large population-based studies. The validity of these study findings depends largely on the quality of the administrative data source and the validity of the case definition used. We systematically reviewed the literature to assess the validity of case definitions of sepsis used with administrative data. METHODS: Embase and MEDLINE were searched for published articles with International Classification of Diseases (ICD) coded data used to define sepsis. Abstracts and full-text articles were reviewed in duplicate. Data were abstracted from all eligible full-text articles, including ICD-9- and/or ICD-10-based case definitions, sensitivity (Sn), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV). RESULTS: Of 2,317 individual studies identified, 12 full-text articles met all eligibility criteria. A total of 38 sepsis case definitions were tested, which included over 130 different ICD codes. The most common ICD-9 codes were 038.x, 790.7 and 995.92, and the most common ICD-10 codes were A40.x and A41.x. The PPV was reported in ten studies and ranged from 5.6% to 100%, with a median of 50%. Other tests of diagnostic accuracy were reported only in some studies. Sn ranged from 5.9% to 82.3%; Sp ranged from 78.3% to 100%; and NPV ranged from 62.1% to 99.7%. CONCLUSIONS: The validity of administrative data in recording sepsis varied substantially across individual studies and ICD definitions. Our work may serve as a reference point for consensus towards an improved and harmonized ICD-coded definition of sepsis.

Productivity of ephemeral headwater riparian forests impacted by sedimentation in the southeastern United States coastal plain.

Riparian forests serve an essential function in improving water quality through the filtering of sediments and nutrients from surface runoff. However, little is known about the impact of sediment deposition on productivity of riparian forests. Sediment inputs may act as a subsidy to forest productivity by providing additional nutrients for plant uptake or may act as a stress by creating anoxic soil conditions. This study determined how sediment deposition affected riparian forests along ephemeral headwater streams at Ft. Benning, Georgia, USA. Above- and belowground productivity, leaf-area index (LAI), and standing crop biomass for fine roots, shrubs, and trees were compared along a gradient of present sedimentation rates in 17 riparian forests. Annual litterfall production was determined from monthly collections using 0.25- m(2) traps; woody biomass was determined from annual diameter at breast height (DBH) measurements using species-specific allometric equations; fine root productivity was determined using sequential coring; LAI was measured by expanding specific leaf area by annual litterfall production; and shrub biomass was determined using species-specific biomass equations based on height and root collar diameter. Significant declines in litterfall, woody biomass production, fine root production, LAI, and shrub biomass were found with as little as 0.1 to 0.4 cm yr(-2) sedimentation. We conclude that the levels of sedimentation in this study do not subsidize growth in ephemeral headwater riparian forests but instead create a stress similar to that found under flooded conditions.