Upgrade StorageTrying to import Endnote export file
Thank you for your help. I haven't been able to import the file that Endnote exported. I've pasted the first two entries of this file below. Would someone please let me know if anything looks off to you?
TY - JOUR
AB - CONTEXT: Hospitals are under pressure to increase revenue and lower costs, and at the same time, they face dramatic variation in clinical demand. OBJECTIVE:: We sought to determine the relationship between peak hospital workload and rates of adverse events (AEs). METHODS: A random sample of 24,676 adult patients discharged from the medical/surgical services at 4 US hospitals (2 urban and 2 suburban teaching hospitals) from October 2000 to September 2001 were screened using administrative data, leaving 6841 cases to be reviewed for the presence of AEs. Daily workload for each hospital was characterized by volume, throughput (admissions and discharges), intensity (aggregate DRG weight), and staffing (patient-to-nurse ratios). For volume, we calculated an "enhanced" occupancy rate that accounted for same-day bed occupancy by more than 1 patient. We used Poisson regressions to predict the likelihood of an AE, with control for workload and individual patient complexity, and the effects of clustering. RESULTS: One urban teaching hospital had enhanced occupancy rates more than 100% for much of the year. At that hospital, admissions and patients per nurse were significantly related to the likelihood of an AE (P < 0.05); occupancy rate, discharges, and DRG-weighted census were significant at P < 0.10. For example, a 0.1% increase in the patient-to-nurse ratio led to a 28% increase in the AE rate. Results at the other 3 hospitals varied and were mainly non significant. CONCLUSIONS: Hospitals that operate at or over capacity may experience heightened rates of patient safety events and might consider re-engineering the structures of care to respond better during periods of high stress.
AD - Institute for Health Policy, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. jweissman@partners.org
AN - 17446831
AU - Weissman, J. S.
AU - Rothschild, J. M.
AU - Bendavid, E.
AU - Sprivulis, P.
AU - Cook, E. F.
AU - Evans, R. S.
AU - Kaganova, Y.
AU - Bender, M.
AU - David-Kasdan, J.
AU - Haug, P.
AU - Lloyd, J.
AU - Selbovitz, L. G.
AU - Murff, H. J.
AU - Bates, D. W.
DA - May
DO - 10.1097/01.mlr.0000257231.86368.09
00005650-200705000-00011 [pii]
ET - 2007/04/21
KW - Aged
Bed Occupancy/statistics & numerical data
Diagnosis-Related Groups
Female
Hospitals, Teaching/*standards/utilization
Humans
Male
Medical Audit
Medical Errors/statistics & numerical data/*trends
Middle Aged
Personnel, Hospital/psychology/*utilization
Poisson Distribution
Quality of Health Care
Safety Management
United States
Workload/*statistics & numerical data
L1 - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17446831
http://graphics.tx.ovid.com/ovftpdfs/FPDDNCMLGBFAJF00/fs047/ovft/live/gv024/00005650/00005650-200705000-00011.pdf
LA - eng
IS - 5
N1 - Weissman, Joel S
Rothschild, Jeffrey M
Bendavid, Eran
Sprivulis, Peter
Cook, E Francis
Evans, R Scott
Kaganova, Yevgenia
Bender, Melissa
David-Kasdan, JoAnn
Haug, Peter
Lloyd, Jim
Selbovitz, Leslie G
Murff, Harvey J
Bates, David W
1 R01 HS12035/HS/AHRQ HHS/United States
R01 HS12035-02-S1/HS/AHRQ HHS/United States
Research Support, U.S. Gov't, P.H.S.
United States
Medical care
Med Care. 2007 May;45(5):448-55.
PY - 2007
SN - 0025-7079 (Print)
SP - 448-55
ST - Hospital workload and adverse events
T2 - Med Care
TI - Hospital workload and adverse events
UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17446831
http://graphics.tx.ovid.com/ovftpdfs/FPDDNCMLGBFAJF00/fs047/ovft/live/gv024/00005650/00005650-200705000-00011.pdf
VL - 45
ID - 3145
ER -
TY - JOUR
AB - The state of California has recently mandated minimum nurse-staffing ratios, raising concerns about possible affects on hospital efficiency. In this study, we examine how market factors and quality were related to staffing levels in California hospitals in 1995 (prior to implementation of the new law). We are particularly interested in the affect of managed care penetration on this aspect of hospital efficiency because the call to legislative action was predicated on fears that hospitals were reducing staffing below optimal levels in response to managed care pressures. We derive a unique measure of excess staffing in hospitals based on a data envelopment analysis (DEA) production function model, which explicitly includes ancillary care among the inputs and outputs. This careful specification of production is important because ancillary care use has risen relative to daily hospital services, with the spread of managed care and advances in medical technology. We find that market share (adjusted for size) and market concentration are the major determinants of excess staffing while managed care penetration is insignificant. We also find that poor quality (outcomes worse than expected) is associated with less efficient staffing. These findings suggest that the larger, more efficient urban hospitals will be penalized more heavily under binding staffing ratios than smaller, less-urban hospitals.
AD - Center for Health Economics Research, Research Triangle Institute, Research Triangle Park, North Carolina 27709-2194, USA. mobley@rti.org
AN - 12148662
AU - Mobley, L. R.
AU - Magnussen, J.
DA - Summer
ET - 2002/08/01
KW - Bed Occupancy/*statistics & numerical data
California
Economic Competition
Efficiency, Organizational/*statistics & numerical data
Health Care Sector
Health Services Research
Humans
*Managed Care Programs/economics/utilization
Models, Statistical
Nursing Staff, Hospital/*supply & distribution
Organizational Innovation
Outcome Assessment (Health Care)
Personnel Staffing and Scheduling/standards/*statistics & numerical data
Quality of Health Care/*statistics & numerical data
L1 - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12148662
http://proquest.umi.com/pdf/e65fa928cd4b98bda4b6e5fd4409a544/1247357290//share4/pqimage/pqirs101/20090711193809213/19881/out.pdf
LA - eng
IS - 4
N1 - Mobley, Lee R
Magnussen, Jon
Research Support, Non-U.S. Gov't
United States
Journal of health care finance
J Health Care Finance. 2002 Summer;28(4):24-42.
PY - 2002
SN - 1078-6767 (Print)
SP - 24-42
ST - The impact of managed care penetration and hospital quality on efficiency in hospital staffing
T2 - J Health Care Finance
TI - The impact of managed care penetration and hospital quality on efficiency in hospital staffing
UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12148662
http://proquest.umi.com/pdf/e65fa928cd4b98bda4b6e5fd4409a544/1247357290//share4/pqimage/pqirs101/20090711193809213/19881/out.pdf
VL - 28
ID - 2872
ER -
TY - JOUR
AB - CONTEXT: Hospitals are under pressure to increase revenue and lower costs, and at the same time, they face dramatic variation in clinical demand. OBJECTIVE:: We sought to determine the relationship between peak hospital workload and rates of adverse events (AEs). METHODS: A random sample of 24,676 adult patients discharged from the medical/surgical services at 4 US hospitals (2 urban and 2 suburban teaching hospitals) from October 2000 to September 2001 were screened using administrative data, leaving 6841 cases to be reviewed for the presence of AEs. Daily workload for each hospital was characterized by volume, throughput (admissions and discharges), intensity (aggregate DRG weight), and staffing (patient-to-nurse ratios). For volume, we calculated an "enhanced" occupancy rate that accounted for same-day bed occupancy by more than 1 patient. We used Poisson regressions to predict the likelihood of an AE, with control for workload and individual patient complexity, and the effects of clustering. RESULTS: One urban teaching hospital had enhanced occupancy rates more than 100% for much of the year. At that hospital, admissions and patients per nurse were significantly related to the likelihood of an AE (P < 0.05); occupancy rate, discharges, and DRG-weighted census were significant at P < 0.10. For example, a 0.1% increase in the patient-to-nurse ratio led to a 28% increase in the AE rate. Results at the other 3 hospitals varied and were mainly non significant. CONCLUSIONS: Hospitals that operate at or over capacity may experience heightened rates of patient safety events and might consider re-engineering the structures of care to respond better during periods of high stress.
AD - Institute for Health Policy, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. jweissman@partners.org
AN - 17446831
AU - Weissman, J. S.
AU - Rothschild, J. M.
AU - Bendavid, E.
AU - Sprivulis, P.
AU - Cook, E. F.
AU - Evans, R. S.
AU - Kaganova, Y.
AU - Bender, M.
AU - David-Kasdan, J.
AU - Haug, P.
AU - Lloyd, J.
AU - Selbovitz, L. G.
AU - Murff, H. J.
AU - Bates, D. W.
DA - May
DO - 10.1097/01.mlr.0000257231.86368.09
00005650-200705000-00011 [pii]
ET - 2007/04/21
KW - Aged
Bed Occupancy/statistics & numerical data
Diagnosis-Related Groups
Female
Hospitals, Teaching/*standards/utilization
Humans
Male
Medical Audit
Medical Errors/statistics & numerical data/*trends
Middle Aged
Personnel, Hospital/psychology/*utilization
Poisson Distribution
Quality of Health Care
Safety Management
United States
Workload/*statistics & numerical data
L1 - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17446831
http://graphics.tx.ovid.com/ovftpdfs/FPDDNCMLGBFAJF00/fs047/ovft/live/gv024/00005650/00005650-200705000-00011.pdf
LA - eng
IS - 5
N1 - Weissman, Joel S
Rothschild, Jeffrey M
Bendavid, Eran
Sprivulis, Peter
Cook, E Francis
Evans, R Scott
Kaganova, Yevgenia
Bender, Melissa
David-Kasdan, JoAnn
Haug, Peter
Lloyd, Jim
Selbovitz, Leslie G
Murff, Harvey J
Bates, David W
1 R01 HS12035/HS/AHRQ HHS/United States
R01 HS12035-02-S1/HS/AHRQ HHS/United States
Research Support, U.S. Gov't, P.H.S.
United States
Medical care
Med Care. 2007 May;45(5):448-55.
PY - 2007
SN - 0025-7079 (Print)
SP - 448-55
ST - Hospital workload and adverse events
T2 - Med Care
TI - Hospital workload and adverse events
UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17446831
http://graphics.tx.ovid.com/ovftpdfs/FPDDNCMLGBFAJF00/fs047/ovft/live/gv024/00005650/00005650-200705000-00011.pdf
VL - 45
ID - 3145
ER -
TY - JOUR
AB - The state of California has recently mandated minimum nurse-staffing ratios, raising concerns about possible affects on hospital efficiency. In this study, we examine how market factors and quality were related to staffing levels in California hospitals in 1995 (prior to implementation of the new law). We are particularly interested in the affect of managed care penetration on this aspect of hospital efficiency because the call to legislative action was predicated on fears that hospitals were reducing staffing below optimal levels in response to managed care pressures. We derive a unique measure of excess staffing in hospitals based on a data envelopment analysis (DEA) production function model, which explicitly includes ancillary care among the inputs and outputs. This careful specification of production is important because ancillary care use has risen relative to daily hospital services, with the spread of managed care and advances in medical technology. We find that market share (adjusted for size) and market concentration are the major determinants of excess staffing while managed care penetration is insignificant. We also find that poor quality (outcomes worse than expected) is associated with less efficient staffing. These findings suggest that the larger, more efficient urban hospitals will be penalized more heavily under binding staffing ratios than smaller, less-urban hospitals.
AD - Center for Health Economics Research, Research Triangle Institute, Research Triangle Park, North Carolina 27709-2194, USA. mobley@rti.org
AN - 12148662
AU - Mobley, L. R.
AU - Magnussen, J.
DA - Summer
ET - 2002/08/01
KW - Bed Occupancy/*statistics & numerical data
California
Economic Competition
Efficiency, Organizational/*statistics & numerical data
Health Care Sector
Health Services Research
Humans
*Managed Care Programs/economics/utilization
Models, Statistical
Nursing Staff, Hospital/*supply & distribution
Organizational Innovation
Outcome Assessment (Health Care)
Personnel Staffing and Scheduling/standards/*statistics & numerical data
Quality of Health Care/*statistics & numerical data
L1 - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12148662
http://proquest.umi.com/pdf/e65fa928cd4b98bda4b6e5fd4409a544/1247357290//share4/pqimage/pqirs101/20090711193809213/19881/out.pdf
LA - eng
IS - 4
N1 - Mobley, Lee R
Magnussen, Jon
Research Support, Non-U.S. Gov't
United States
Journal of health care finance
J Health Care Finance. 2002 Summer;28(4):24-42.
PY - 2002
SN - 1078-6767 (Print)
SP - 24-42
ST - The impact of managed care penetration and hospital quality on efficiency in hospital staffing
T2 - J Health Care Finance
TI - The impact of managed care penetration and hospital quality on efficiency in hospital staffing
UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12148662
http://proquest.umi.com/pdf/e65fa928cd4b98bda4b6e5fd4409a544/1247357290//share4/pqimage/pqirs101/20090711193809213/19881/out.pdf
VL - 28
ID - 2872
ER -
Also, have you tried chopping the larger file up in pieces? We've had many cases where there are just 2 or 3 malformatted entries that cause Zotero to hang up on the import
(which isn't great, but apparently rather hard to avoid - ideally Zotero would import what it could and tell you where it failed).
"An error occurred while trying to import the selected file. Please ensure that the file is valid and try again."
I can try importing only a portion of the file tomorrow. Not sure how long it would take to identify the problematic references, since I have 3,646 of them.
A separate question I have... Will Zotero also import the groups that I use in Endnote to categorize my references? These groupings are key for me.
How quickly you can get the rest imported depends on the number of problems - this is really a problem of Endnote exporting messy RIS. Standard RIS is, of course, imported without problems.