Carbon Sequestration by Reforesting Legacy Grasslands on Coal Mining Sites

Future carbon management during energy production will rely on carbon capture and sequestration technology and carbon sequestration methods for offsetting non-capturable losses. The present study quantifies carbon sequestration via reforestation using measurements and modeling for recent and legacy surface coal mining grasslands that are re-restored through tree planting. This paper focuses on a case study of legacy coal mining sites in the southern Appalachia the United States. This five million-hectare region has a surface mining footprint of approximately 12% of the land area, and the reclamation method was primarily grassland. The results of the soil carbon sequestration rates for restored forest soils approach 2.0 MgC ha−1 y−1 initially and average 1.0 MgC ha−1 y−1 for the first fifty years after reclamation. Plant, coarse root and litter carbon sequestration rates were 2.8 MgC ha−1 y−1 with plant carbon estimated to equilibrate to 110 MgC ha−1 after forty years. Plant, root and litter carbon stocks are projected to equilibrate at an order of magnitude greater carbon storage than the existing conditions, highlighting the net carbon gain. Reforestation of legacy mine sites shows carbon sequestration potential several orders of magnitude greater than typical land sequestration strategies for carbon offsets. Projections of future scenarios provide results that show the study region could be carbon neutral or a small sink if widespread reforesting during reclamation was implemented, which is contrary to the business-as-usual projections that result in a large amount of carbon being released to the atmosphere in this region

The underlying structure of the English Cancer Patient Experience Survey: Factor analysis to support survey reporting and design

BACKGROUND: The English Cancer Patient Experience Survey (CPES) is a regularly conducted survey measuring the experience of cancer patients. We studied the survey's underlying structure using factor analysis to identify potential for improvements in reporting or questionnaire design. METHODS: Cancer Patient Experience Survey 2015 respondents (n = 71,186, response rate 66%) were split into two random subgroups. Using exploratory factor analysis (EFA) on the first subgroup, we identified the survey's latent structure. EFA was then applied to 12 sets of items. A first ("core") set was formed by questions that applied to all participants. The subsequent sets contained the "core set" plus questions corresponding to specific care pathways/patient groups. We used confirmatory factor analysis (CFA) on the second data subgroup for cross-validation. RESULTS: The EFA suggested that five latent factors underlie the survey's core questions. Analysis on the remaining 11 care pathway/patient group items also indicated the same five latent factors, although additional factors were present for questions applicable to patients with an overnight stay or those accessing specialist nursing. The five factors models had an excellent fit (comparative fit index = 0.95, root mean square error of approximation = 0.045 for core set of questions). Items loading on each factor generally corresponded to a specific section or subsection of the questionnaire. CFA findings were concordant with the EFA patterns. CONCLUSION: The findings suggest five coherent underlying sub-constructs relating to different aspects of cancer health care. The findings support the construction of evidence-based composite indicators for different domains of experience and provide options for survey re-design

GPAQ-R: development and psychometric properties of a version of the general practice assessment questionnaire for use for revalidation by general practitioners in the UK.

BACKGROUND: The General Practice Assessment Questionnaire (GPAQ) has been widely used to assess patient experience in general practice in the UK since 2004. In 2013, new regulations were introduced by the General Medical Council (GMC) requiring UK doctors to undertake periodic revalidation, which includes assessment of patient experience for individual doctors. We describe the development of a new version of GPAQ - GPAQ-R which addresses the GMC's requirements for revalidation as well as additional NHS requirements for surveys that GPs may need to carry out in their own practices. METHODS: Questionnaires were given out by doctors or practice staff after routine consultations in line with the guidance given by the General Medical Council for surveys to be used for revalidation. Data analysis and practice reports were provided independently. RESULTS: Data were analysed for questionnaires from 7258 patients relating to 164 GPs in 29 general practices. Levels of missing data were generally low (typically 4.5-6%). The number of returned questionnaires required to achieve reliability of 0.7 were around 35 for individual doctor communication items and 29 for a composite score based on doctor communication items. This suggests that the responses to GPAQ-R had similar reliability to the GMC's own questionnaire and we recommend 30 completed GPAQ-R questionnaires are sufficient for revalidation purposes. However, where an initial screen raises concern, the survey might be repeated with 50 completed questionnaires in order to increase reliability. CONCLUSIONS: GPAQ-R is a development of a well-established patient experience questionnaire used in general practice in the UK since 2004. This new version can be recommended for use in order to meet the UK General Medical Council's requirements for surveys to be used in revalidation of doctors. It also meets the needs of GPs to ask about patient experience relating to aspects of practice care that are not specific to individual general practitioners (e.g. receptionists, telephone access) which meet other survey requirements of the National Health Service in England. Use of GPAQ-R has the potential to reduce the number of surveys that GPs need to carry out in their practices to meet the various regulatory requirements which they face

Should measures of patient experience in primary care be adjusted for case mix? Evidence from the English General Practice Patient Survey.

OBJECTIVES: Uncertainties exist about when and how best to adjust performance measures for case mix. Our aims are to quantify the impact of case-mix adjustment on practice-level scores in a national survey of patient experience, to identify why and when it may be useful to adjust for case mix, and to discuss unresolved policy issues regarding the use of case-mix adjustment in performance measurement in health care. DESIGN/SETTING: Secondary analysis of the 2009 English General Practice Patient Survey. Responses from 2 163 456 patients registered with 8267 primary care practices. Linear mixed effects models were used with practice included as a random effect and five case-mix variables (gender, age, race/ethnicity, deprivation, and self-reported health) as fixed effects. MAIN OUTCOME MEASURES: Primary outcome was the impact of case-mix adjustment on practice-level means (adjusted minus unadjusted) and changes in practice percentile ranks for questions measuring patient experience in three domains of primary care: access; interpersonal care; anticipatory care planning, and overall satisfaction with primary care services. RESULTS: Depending on the survey measure selected, case-mix adjustment changed the rank of between 0.4% and 29.8% of practices by more than 10 percentile points. Adjusting for case-mix resulted in large increases in score for a small number of practices and small decreases in score for a larger number of practices. Practices with younger patients, more ethnic minority patients and patients living in more socio-economically deprived areas were more likely to gain from case-mix adjustment. Age and race/ethnicity were the most influential adjustors. CONCLUSIONS: While its effect is modest for most practices, case-mix adjustment corrects significant underestimation of scores for a small proportion of practices serving vulnerable patients and may reduce the risk that providers would 'cream-skim' by not enrolling patients from vulnerable socio-demographic groups.The study was funded by a grant from the UK Department of Healt

Common patterns of morbidity and multi-morbidity and their impact on health-related quality of life: evidence from a national survey.

BACKGROUND: There is limited evidence about the impact of specific patterns of multi-morbidity on health-related quality of life (HRQoL) from large samples of adult subjects. METHODS: We used data from the English General Practice Patient Survey 2011-2012. We defined multi-morbidity as the presence of two or more of 12 self-reported conditions or another (unspecified) long-term health problem. We investigated differences in HRQoL (EQ-5D scores) associated with combinations of these conditions after adjusting for age, gender, ethnicity, socio-economic deprivation and the presence of a recent illness or injury. Analyses were based on 831,537 responses from patients aged 18 years or older in 8,254 primary care practices in England. RESULTS: Of respondents, 23 % reported two or more chronic conditions (ranging from 7 % of those under 45 years of age to 51 % of those 65 years or older). Multi-morbidity was more common among women, White individuals and respondents from socio-economically deprived areas. Neurological problems, mental health problems, arthritis and long-term back problem were associated with the greatest HRQoL deficits. The presence of three or more conditions was commonly associated with greater reduction in quality of life than that implied by the sum of the differences associated with the individual conditions. The decline in quality of life associated with an additional condition in people with two and three physical conditions was less for older people than for younger people. Multi-morbidity was associated with a substantially worse HRQoL in diabetes than in other long-term conditions. With the exception of neurological conditions, the presence of a comorbid mental health problem had a more adverse effect on HRQoL than any single comorbid physical condition. CONCLUSION: Patients with multi-morbid diabetes, arthritis, neurological, or long-term mental health problems have significantly lower quality of life than other people. People with long-term health conditions require integrated mental and physical healthcare services

Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS)

BACKGROUND Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR. MATERIAL AND METHODS Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8). RESULTS There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality. CONCLUSIONS Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR

Web-based textual analysis of free-text patient experience comments from a survey in primary care.

BACKGROUND: Open-ended questions eliciting free-text comments have been widely adopted in surveys of patient experience. Analysis of free text comments can provide deeper or new insight, identify areas for action, and initiate further investigation. Also, they may be a promising way to progress from documentation of patient experience to achieving quality improvement. The usual methods of analyzing free-text comments are known to be time and resource intensive. To efficiently deal with a large amount of free-text, new methods of rapidly summarizing and characterizing the text are being explored. OBJECTIVE: The aim of this study was to investigate the feasibility of using freely available Web-based text processing tools (text clouds, distinctive word extraction, key words in context) for extracting useful information from large amounts of free-text commentary about patient experience, as an alternative to more resource intensive analytic methods. METHODS: We collected free-text responses to a broad, open-ended question on patients' experience of primary care in a cross-sectional postal survey of patients recently consulting doctors in 25 English general practices. We encoded the responses to text files which were then uploaded to three Web-based textual processing tools. The tools we used were two text cloud creators: TagCrowd for unigrams, and Many Eyes for bigrams; and Voyant Tools, a Web-based reading tool that can extract distinctive words and perform Keyword in Context (KWIC) analysis. The association of patients' experience scores with the occurrence of certain words was tested with logistic regression analysis. KWIC analysis was also performed to gain insight into the use of a significant word. RESULTS: In total, 3426 free-text responses were received from 7721 patients (comment rate: 44.4%). The five most frequent words in the patients' comments were "doctor", "appointment", "surgery", "practice", and "time". The three most frequent two-word combinations were "reception staff", "excellent service", and "two weeks". The regression analysis showed that the occurrence of the word "excellent" in the comments was significantly associated with a better patient experience (OR=1.96, 95%CI=1.63-2.34), while "rude" was significantly associated with a worse experience (OR=0.53, 95%CI=0.46-0.60). The KWIC results revealed that 49 of the 78 (63%) occurrences of the word "rude" in the comments were related to receptionists and 17(22%) were related to doctors. CONCLUSIONS: Web-based text processing tools can extract useful information from free-text comments and the output may serve as a springboard for further investigation. Text clouds, distinctive words extraction and KWIC analysis show promise in quick evaluation of unstructured patient feedback. The results are easily understandable, but may require further probing such as KWIC analysis to establish the context. Future research should explore whether more sophisticated methods of textual analysis (eg, sentiment analysis, natural language processing) could add additional levels of understanding

Rural and urban differences in stage at diagnosis of colorectal and lung cancers

There is evidence that patients living in outlying areas have poorer survival from cancer. This study set out to investigate whether they have more advanced disease at diagnosis. Case notes of 1323 patients in north and northeast Scotland who were diagnosed with lung or colorectal cancer in 1995 or 1996 were reviewed. Of patients with lung cancer, 42% (69/164) living 58 km or more from a cancer centre had disseminated disease at diagnosis compared to 33% (71/215) living within 5 km. For colorectal cancer the respective figures were 24% (38/161) and 16% (31/193). For both cancers combined, the adjusted odds ratio for disseminated disease at diagnosis in furthest group compared to the closest group was 1.59 (P = 0.037). Of 198 patients with non-small-cell lung cancer in the closest group, 56 (28%) had limited disease (stage I or II) at diagnosis compared to 23 of 165 (14%) of the furthest group (P = 0.002). The respective figures for Dukes A and B colorectal cancer were 101 of 196 (52%) and 67 of 172 (39%) (P = 0.025). These findings suggest that patients who live remote from cities and the associated cancer centres have poorer chances of survival from lung or colorectal cancer because of more advanced disease at diagnosis. This needs to be taken into account when planning investigation and treatment services. © 2001 Cancer Research Campaign http://www.bjcancer.co