On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement.

Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information.

There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

This dataset contains annual Excel pivot tables that display summaries of the inpatients treated in each hospital. The summary data include discharges, discharge days, average length of stay, age groups, race groups, sex, expected payer, type of care, do not resuscitate orders, admission source, admission type, discharge disposition, principal diagnosis groups, principal procedure groups, and principal external cause of injury/morbidity groups. The data can also be summarized statewide or for a specific hospital county, bed size grouping, and/or type of control.

Warning: Large file size (over 1GB). Each monthly data set is large (over 4 million rows), but can be viewed in standard software such as Microsoft WordPad (save by right-clicking on the file name and selecting 'Save Target As', or equivalent on Mac OSX). It is then possible to select the required rows of data and copy and paste the information into another software application, such as a spreadsheet. Alternatively, add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets, can be used. The Microsoft PowerPivot add-on for Excel is available from Microsoft http://office.microsoft.com/en-gb/excel/download-power-pivot-HA101959985.aspx Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it may take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet. What does the data cover? General practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): - the total number of items prescribed and dispensed - the total net ingredient cost - the total actual cost - the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to GP practices. GP practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation.

The Single-Family Portfolio Snapshot consists of a monthly data table and a report generator (Excel pivot table) that can be used to quickly create new reports of interest to the user from the data records. The data records themselves are loan level records using all of the categorical variables highlighted on the report generator table. Users may download and save the Excel file that contains the data records and the pivot table.The report generator sheet consists of an Excel pivot table that gives individual users some ability to analyze monthly trends on dimensions of interest to them. There are six choice dimensions: property state, property county, loan purpose, loan type, property product type, and downpayment source.Each report generator selection variable has an associated drop-down menu that is accessed by clicking once on the associated arrows. Only single selections can be made from each menu. For example, users must choose one state or all states, one county or all counties. If a county is chosen that does not correspond with the selected state, the result will be null values.The data records include each report generator choice variable plus the property zip code, originating mortgagee (lender) number, sponsor-lender name, sponsor number, nonprofit gift provider tax identification number, interest rate, and FHA insurance endorsement year and month. The report generator only provides output for the dollar amount of loans. Users who desire to analyze other data that are available on the data table, for example, interest rates or sponsor number, must first download the Excel file. See the data definitions (PDF in top folder) for details on each data element.Files switch from .zip to excel in August 2017.

Information on accidents across Leeds. Data includes location, number of people and vehicles involved, road surface, weather conditions and severity of any casualties.

Please note

• The Eastings and Northings are generated at the roadside where the accident occurred. Sometimes due to poor internet connectivity this data is may not be as accurate as it could be. If you notice any errors please contact accident.studies@leeds.gov.uk.

Due to the format of the report a number of figures in the columns are repeated, these are:

• Reference Number
• Easting
• Northing
• Number of Vehicles
• Accident Date
• Time (24hr)
• 1st Road Class
• Road Surface
• Lighting Conditions
• Weather Conditions

Reference Number

Grid Ref: Easting

Grid Ref: Northing

Number of vehicles

Accident Date

Time (24hr)

21G0539

427798

426248

5

16/01/2015

1205

21G0539

427798

426248

5

16/01/2015

1205

21G1108

431142

430087

1

16/01/2015

1732

21H0565

434602

436699>

1

17/01/2015

930

21H0638

434254

434318

2

17/01/2015

1315

21H0638

434254

434318

2

17/01/2015

1315

Therefore the number of vehicles involved in accident 21G0539 were 5, and in accident 21H0638 were 2. Overall in the example above a total of 9 vehicles were involved in accidents

A useful tool to analyse the data is Excel pivot tables, these help summarise large amounts of data in a easy to view table, for further information on pivot table visit here.

Further Information

• Please see the guidance document for further information on categories.

Information on accidents casualites across Calderdale. Data includes location, number of people and vehicles involved, road surface, weather conditions and severity of any casualties.

Please note

• The Eastings and Northings are generated at the roadside where the accident occurred. Sometimes due to poor internet connectivity this data is may not be as accurate as it could be. If you notice any errors please contact accident.studies@leeds.gov.uk.

Due to the format of the report a number of figures in the columns are repeated, these are:

• Reference Number
• Easting
• Northing
• Number of Vehicles
• Accident Date
• Time (24hr)
• 1st Road Class
• Road Surface
• Lighting Conditions
• Weather Conditions

Reference Number

Grid Ref: Easting

Grid Ref: Northing

Number of vehicles

Accident Date

Time (24hr)

21G0539

427798

426248

5

16/01/2015

1205

21G0539

427798

426248

5

16/01/2015

1205

21G1108

431142

430087

1

16/01/2015

1732

21H0565

434602

436699>

1

17/01/2015

930

21H0638

434254

434318

2

17/01/2015

1315

21H0638

434254

434318

2

17/01/2015

1315

Therefore the number of vehicles involved in accident 21G0539 were 5, and in accident 21H0638 were 2. Overall in the example above a total of 9 vehicles were involved in accidents

A useful tool to analyse the data is Excel pivot tables, these help summarise large amounts of data in a easy to view table, for further information on pivot tables visit here.

Abstract

The purpose of the WASH KAP survey was to collect primary data on several indicators related to the WASH Program implemented in the refugee and host communities of Palabek Settlement, Uganda. The survey aimed at assessing the level of improvement on the accessibility of WASH facilities after a 2 year intervention project.

The survey used cross-sectional design used and both qualitative and quantitative techniques such as use of UNHCR standard WASH questionnaires, field visits and observations were employed during the study. In the 2019/20, the LWF provided WASH services to both refugee settlements and host community living in and around Palabek settlement. In order to gauge the coverage, the LWF conducted this KAP survey. The respondents were drawn from the host community (238 households) and the refugee settlement (446 households).

Geographic coverage

Palabek

Analysis unit

Households

Universe

Refugees and host community

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample size of 578 respondents was determined using the sample size calculator for the survey with a 4% margin of error and an 95% confidence level. Through the entire exercise, the survey process however reached a total of 684 respondents. Analysis, interpretation, and presentation of data were undertaken using Microsoft Excel Pivot tables and chats.

Mode of data collection

Computer Assisted Personal Interview [capi]

Plant species collected throughout Benin were published on GBIF site. Data concerning those species were downloaded from GBIF site. Using Excel dynamic pivot table we derived and achieved the checklist of plant species of Benin from the dataset downloaded.

Stream Temperature: Site: Gwynns Falls at Gwynnbrook (GFGB):

   In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe.

   Stream temperature is continuously measured throughout the Gwynns Falls watershed along with supplemental sites around Baltimore County/City. A total of 22 sites contain sensors (HOBO Pro v2 Water Temperature Data Logger - U22-001) that take an instantaneous temperature reading every 2 minutes. These data are downloaded on a monthly basis. 

   This dataset is for at Gwynnbrook/Delight. This site samples drainage from approximately 1,000 ha of old and new suburban and suburbanizing land use. 


   A detailed description of this site is posted at: http://md.water.usgs.gov/BES/ 01589197/.


   Streamflow data for this site are posted at: http://waterdata.usgs.gov/md/nwis/nwisman?site_no=01589197


   Purpose: Long-term monitoring of stream temperature in a suburban catchment. 

   Theme keywords: stream, watershed, temperature, suburban, Baltimore Ecosystem Study

   Coordinates: Lat/Long

   39.4430 (39 26 35)  (-)76.7834 (-76 47 00)


   Review process for BES stream temperature data:

   Raw data were recorded and logged every 2-minutes using HOBO Pro v2 Water Temperature Data Logger - U22-001. 

   Data are exported into Microsoft Excel documents. 

   Then organized by site and by month

   Each month's data were entered into a pivot table in Microsoft Excel and daily means and counts of daily data points were calculated. 

   Plots were graphed of sites with close geographic proximity on the same graph to illustrate possible outlier data. 

   Missing and odd data were flagged, and notes taken from the field visits are provided where applicable.

This dataset contains annual Excel pivot tables that display summaries of the patients treated in each hospital-based and freestanding Ambulatory Surgery Clinic licensed by the California Department of Public Health (CDPH). The summary data includes discharge disposition, expected payer, preferred language spoken, age groups, race groups, sex, principal diagnosis groups, principal procedure groups, and principal external cause of injury/morbidity groups. The data can also be summarized statewide or for a specific facility county, type of control, and/or type of license (hospital or clinic). Note: Physician-owned ambulatory surgery clinics do not report their data to HCAI and, therefore, are not included in the statewide frequencies.

Stream Temperature: Site: Gwynns Falls at Villa Nova (GFVN):

   In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe.

   Stream temperature is continuously measured throughout the Gwynns Falls watershed along with supplemental sites around Baltimore County/City. A total of 22 sites contain sensors (HOBO Pro v2 Water Temperature Data Logger - U22-001) that take an instantaneous temperature reading every 2 minutes. These data are downloaded on a monthly basis. 

   This dataset is for the Gwynns Falls at Villa Nova. This site samples drainage from approximately 7,400 ha of old and new suburban and suburbanzing land use. Streamflow at this station has been monitored continuously by the USGS since 1957 (with a hiatus from 1988 - 1995). This station is the boundary between the urban and suburban portions of the Gwynns Falls. 


   A detailed description of this site is posted at: http://md.water.usgs.gov/BES/01589300/.


   Streamflow data for this site are posted at: http://waterdata.usgs.gov/md/nwis/nwisman?site_no=01589300


   Purpose: Long-term monitoring of stream temperature in a watershed. 

   Theme keywords: stream, watershed, temperature, Baltimore Ecosystem Study

   Coordinates: Lat/Long

   39.3459 (39 20 45)    -76.7333 (-76 43 60)


   Review process for BES stream temperature data:

   Raw data were recorded and logged every 2-minutes using HOBO Pro v2 Water Temperature Data Logger - U22-001. 

   Data are exported into Microsoft Excel documents. 

   Then organized by site and by month

   Each month's data were entered into a pivot table in Microsoft Excel and daily means and counts of daily data points were calculated. 

   Plots were graphed of sites with close geographic proximity on the same graph to illustrate possible outlier data. 

   Missing and odd data were flagged, and notes taken from the field visits are provided where applicable.