Medical Electives

Electives Talk from IT Services Tuesday, 14 May 2013

MBChB 1

Practical Data Collection

Medical ElectivesData Collection

The Practical Aspects

John S. Lemon

IT Services


Preparation – the 5 ‘P’s• Poor Preparation Produces Poor

Performance

or

Prior Preparation Produces Perfect Products

• Applies to ALL aspects of the elective–Including collecting and analysing your

data.


Relevance of Data Collection• “What bearing do these pictures have

on your elective ?”


MBChB 2


Previous Electives• All places where

previous electives have taken place–Sunburn / skin

cancer on Bondi beach

–Altitude sickness in La Paz, Bolivia

–Medical provision in Nepal / Annapurna


Previous Electives• Not everywhere provides the same as

Aberdeen


Which facilities would you expect at each place ?


MBChB 3


Which do you actually get ?

What 2 students found

Laptops / wireless hotspots and internet cafes almost everywhere – BUT -


Facilities for Data Collection• Don’t always assume that the facilities

will be similar to Aberdeen for:–Hardware–Software

• Extremely variable• May cost you to use

–Internet cafes –Wireless hotspots–University facilities–Laptop


Laptop• Problems / limitations

–Security – theft–Climate – heat / dust / humidity–Power – reliable

• 1 hr / day in some places –Software – licenced for use

• Compatibility with ‘remote’ facilities


MBChB 4


Software• Always adopt the KISS technique

–Keep It Supremely Simple• But always use the best tool for the job


Software• Questionnaires

–SNAP not Word• Storing data

–SPSS not Access–Perhaps Excel if no access to SPSS

• Statistics and Charts–SPSS not Excel

• In ALL cases learn early BEFORE you go away / start writing up


Writing up• Make sure you have access to Word

–or some form of wordprocessor• Prepare as much as possible before

leaving Aberdeen–References – use Refworks –Produce outline, Introduction and

literature review• Do NOT leave until last minute.


MBChB 5


Timings• Avoid the ‘traditional’ student approach

of:lastminute.com

• It seldom works• Do NOT

–Fly back from New Zealand on Thursday when you submit on Monday

–Start to learn SPSS / SNAP/ Refworks two days before flying to Vanuatu

–Expect anyone to drop everything for you


Possible solutions• Get a laptop and install the right

software–Student versions of Microsoft Office–SPSS - site licence for staff and students

• Create questionnaire in SNAP:–Collect on paper and type into laptop–Type data into web version from abroad


What should you do ?• Plan early:

–Travel - to allow for submission on time• writing up takes longer than you think

–Determine what computing facilities you will / may have access to

• Seek help on how to collect, store and analyse your data

• Ask people who have experience of assisting with projects

• NOT ‘friends’


MBChB 6


Why so much Data ‘stuff’ ?

“Deciding on how to store your data or consulting a statistician** after the data has been collected is like hiring a physician for a patient who is in the morgue. He may be able to tell you what went wrong, but he is unlikely to be able to fix it”

**Decide on analysis before collecting data.


Two areas to consider• Data Handling - an overview

–Glossary of terms–Quantity, Structure, Storage etc

• Data Handling systems–Which system suits which application

• Use the proper tools for the job ‘Horses for courses’


Glossary of Terms • Different names for collections of data• Components of collections of data -

what makes up a data set• Software types - the names for what

does what !


MBChB 7


Glossary of Terms • The components of collections of data

are -Column Variable Observation

Row Cell Value Data Item

Case Value Data Item Cell

Record Data Item Cell Value

Collections of data - can be called Matrix File Table


Glossary of Terms • A related set of tables / matrices may

be called–Data base–Data bank

Does NOT mean that to handle data you need a

Data Base Management System ( DBMS )

such as Access


Software types • Types to be discussed -

–Word processors–Spreadsheets–Data base management systems–Statistical packages

• An overall description which outlines -–Functionality –Strengths and weaknesses


MBChB 8


Software - Word Processors• Designed for the specific purpose of

text handling• NOT for storing data except to

present as a document ( i.e. a data ‘display’ tool )


Software - Spreadsheets • Essentially computer manipulated grids• A ‘general purpose tool’

–easy data entry–powerful computation facilities–data storage–data manipulation

• limited to sorting and crude subsetting

• Statistical functionalityVery SUSPECT


Software – Data Base Management Systems

• Basically a way of ‘linking’ two or more‘spreadsheets’ / tables / matrices

–almost unlimited data storage–powerful data manipulation including

• subsetting• sorting

• Too powerful for most users and application


MBChB 9


Software - Statistical packages • Typically ‘spreadsheet like’ appearance• Designed for statistical analysis• Usually have powerful data

manipulation• Charting and graphing facilities• Presentation quality output which can

be easily incorporated into word processed documents

• Some may produce Web pages directly


Glossary & Software types • Not an exhaustive glossary but

sufficient for this part of the lecture• Now move on to aspects of Data

Handling in general


Six Key Areas• Structure• Quantity• Source• Type• Storage• Analysis

MUST consider as a WHOLE –NOT individually


MBChB 10


• Structure• Quantity• Source• Type• Storage• Analysis

Cannot omit ANY aspect without problems

Six Key Areas


Six Key Areas - Structure• Structure• Quantity• Source• Type• Storage• Analysis


Structure - Simple / Related• Simple rectangular Matrix - most common

form– questionnaire– lab or field work measurements

• Related matrices– two or more rectangular matrices linked by

common data items– eg. “University experience” survey - 1st, 2nd,

3rd, Final yearCommon item(s)- Matriculation Number- Age, sex, place of birth, degree


MBChB 11


Structure within data sets

• Repeating variables– common mistake to set out in this format– can cause problems in analysis

• SPSS may be able to ‘correct’ wrong layout• but - NOT guaranteed

North East South West Species Season51 34 25 27 Oak Spring

42 31 20 22 Oak Summer

43 33 20 21 Oak Autumn

49 37 22 24 Oak Winter

58 42 28 30 Beech Spring

53 39 25 27 Beech Summer


Structure within data sets

• Repeating cases– more flexible– easily analysed– may be only format /

structure that can beanalysed

– initially seems to involve more data entry

• BUT – may save time

Season Species Location Lichen

Spring Oak North 51

Spring Oak East 34

Spring Oak West 25

Spring Oak South 27

Summer Oak North 42

Summer Oak East 31

Summer Oak West 20

Summer Oak South 22

Autumn Oak North 43

Autumn Oak East 33

Autumn Oak West 20

Autumn Oak South 21

Winter Oak North 49

Winter Oak East 37

Winter Oak West 22

Winter Oak South 24

Spring Beech North 58

Spring Beech East 42

Spring Beech West 28

Spring Beech South 30

Summer Beech North 53

Summer Beech East 39

Summer Beech West 25

Summer Beech South 27


Six Key Areas - Quantity• Structure• Quantity• Source• Type• Storage• Analysis


MBChB 12


Quantity - Simple• Rectangular matrix

Cells = Columns x RowsCells = Questions x Respondents

–Long narrow matrices GOOD• Few columns / measurements Many rows /

cases

–Wide short matrices BAD• Many columns Few rows


Quantity – how many cases ?• Are there enough patients / cases ?• Prospective

–In your 6 weeks data collection will there be enough ?

–e.g – how many cases of obstetric coleostatis per year ?

• Retrospective –Get more cases but has:

• Protocol changed• Staffing levels etc.


Quantity – how many cases ?• For electives use the “Rule of four”• You need a minimum of 4 cases /

rows per column• 20 questions = 80 cases / patients• Remember

–Long and Narrow–NOT short and fat

• Must calculate at every stage in design and execution of a project


MBChB 13


Quantity - Data entry• How

–Keyboard–Optical Mark / Character Reader (scanner) –?

• Who–You –?

• Keystrokes 100 = 4 keystrokes


Quantity - Related data• ‘To collect or not to collect’

‘That is the question’‘Whether you collect all you can’‘Or discard the irrelevant’

• Will it enhance or subtract from the study• Effect on the ‘shape’ of the data• For example - do you need these items ?

– Age, Sex, Place of Residence, Marital Status etc.• Remember 4 more cases per extra item / column

– Weather data


Six Key Areas - Source• Structure• Quantity• Source• Type• Storage• Analysis


MBChB 14


Source – existing records

• Transfer to your system for analysis• Paper – you have to transfer carefully to

avoid transcription errors.• Export from computer system

– Format– Relevance– Permissions / ethics– Who does it and when


Source – Questionnaires**

• Simple– single response questions

** Believed to be an easy option – but it isn’t to do it right !!


Multiple Choice• Single question with more than one

response

Actually Eight separate questions


MBChB 15


Response Grids• Typical questions show little thought

• Couch potatoes 1 Eager beavers 5+


Response grids• Alphabetic list caused problems

–Aerobics – Athletics – Ballet – Brownies -.. - Walking

• Revised question shows more thought and an effective pilot


Six Key Areas - Type• Structure• Quantity• Source• Type• Storage• Analysis


MBChB 16


Type - numeric• Integer - whole numbers

– 1 -15 237 -1,297,428• Real - decimal point

– 0.19 -2.7 200.45 -1,435,276.783• Date / Time

31 12 2006 not 31 12 0610:00 AM or 23:33:00

• ensure software allows calculations ( e.g. days difference between one date and

another )


Type - String / Character• String - Categorical

Y = ‘Yes’ cf. 1 ( or 2 )AB = ‘Blood group AB’ 5AB155 ‘West End of Aberdeen’

• String - Free text“To be or not to be,Whether ‘tis nobler in the mind,To suffer the strings and arrows .....”

University Office, Regent Walk, ABERDEEN


Type - Other• Qualitative

‘Please state what you thought of ....’‘Other - please specify’

• Use ‘Other please specify’ with care !!


MBChB 17


Six Key Areas - Storage• Structure• Quantity• Source• Type• Storage• Analysis


Storage - choices• Paper

vs.– ideal for small

studies – requires no

facilities–minimal learning

to get started

• Computer– few restrictions

on size –high Initial level

of learning–software Capacity–hardware

Capacity–cost– transferability


Six Key Areas• Structure• Quantity• Source• Type• Storage• Analysis


MBChB 18


Analysis - Choices• Paper / Hand

vs– small studies– minimal

learning

• Computer– involves a high initial level of

learning• Software and hardware

must be -– simple to use– widely recognised– have good Support available

• Spreadsheet NO• Statistical package YES


Analysis - Preliminary steps• Explore data before proceeding further• Basic statistics

–Min / Max / Means continuous data

Descriptive Statistics

891 11.16 56.06 22.5974 5.09680

1068 17 65 27.24 10.569

870

Body Mass IndexAge of respondent

(years)Valid N (listwise)

N Minimum Maximum Mean Std. Deviation



–Frequencies discrete data

Sex of respondent

643 58.4 59.2 59.2443 40.2 40.8 100.0

1086 98.6 100.015 1.4

1101 100.0

FemaleMale

Total

Valid

SystemMissingTotal

Frequency Percent Valid PercentCumulative

Percent


MBChB 19



–Crosstabulation - 2 way tables discrete data

Sex of respondent * Age of Respondent (grouped) Crosstabulation

Count

194 277 70 55 29 3 628102 217 56 20 25 9 429296 494 126 75 54 12 1057

FemaleMale

Sex of respondent

Total

Under 20 21 - 30 31 - 40 41 - 50 51 - 60 Over 60Age of Respondent (grouped)

Total


Analysis - Preliminary steps• Explore data before proceeding

further• Basic statistics

–Means / Max / Min within subgroupsboth

Report

22.0400 26.94507 628

4.91115 10.30123.3391 27.68

373 4295.29771 10.94722.5907 27.24

880 10575.11612 10.569

MeanNStd. DeviationMeanNStd. DeviationMeanNStd. Deviation

Sex of respondentFemale

Male

Total

Body MassIndex

Age ofrespondent

(years)


Analysis - safe working method

• Check for integrity of data to exclude -–pregnant males–10 year old pensioners

• You may think your data is correct - BUT –

• In 99.9% of cases it ISN’T !!!


MBChB 20


Analysis - safe working method

• Correct any invalid data items• Run checks again to search for items missed

/ masked by previous errors• Repeat previous two steps until OK

– NB. You may get rid of the 10 year old pensioner but leave the 16 year old !!

• Only when no suspect data items can the analysis be performed

• The checking process CANNOT be neglected


Summary• Think constantly about

– Structure ( Shape )– Quantity ( Size )– Source( From )– Type ( What )– Storage ( Where )– Analysis ( How )

If you do not consider the six key areas at ALL stages you risk the chance of failure


The two areas to consider• Data Handling - an overview

–glossary of terms–Quantity, Structure, Storage etc

Data Handling systems which system suits which application the wrong choice can cost

–time - to restart the project–money - in labour costs, training and software

purchase


MBChB 21


How to choose - basic rules• Best way to illustrate is to use examples• This is not a definitive or exhaustive list• Seek advice as every application is different • Do not rely on ‘friends’• Remember - use the right tools for the job

Would you plough a field with a racehorse ?


The choices - software names / types

• Software names referring to types–Access relational data base

management system (rDBMS)–Word Word processor–Excel Spreadsheet

• Most people use Microsoft Office and are unaware of alternatives–Star or Open Office Free – but …..


The choices - software names / types

• Software names referring to specifics–SPSS Statistical package

• There are other statistical packages available but there may well be:–NO local support–NO local purchasing agreements for

discounts–So could end up being very expensive


MBChB 22


Bibliographic / reference managers

• References are data• Can manage by hand but a lot of work• Collect and store from day 1 of project • Must store and present references

correctly• Three approaches

–Buy PC based software ( Procite, Endnote etc. )

–Refworks web-based


Bibliographic / reference managers

• Specialist software e.g. Reference Manager– Designed for the task– Provides the tools required for handling

references– Initial cost is high but offset by savings in time

and effort incurred trying to use the wrong tool !!

• Refworks – web based


Access - relational system• Multiple linked tables

e.g. Student - course - lecturer• Powerful reporting and querying facilities• Appears easy to use – ‘friends’

recommendation's• Part of Microsoft Office / “everyone uses it”

- so must be good ( Is this really true ? )• Many hospitals / researchers use it for the

reasons above• Power and features are potential causes for

disasters


MBChB 23


Why is power potential for disaster ?

• Few software packages will warn of stupid or inconsistent actions

• Access like any relational system has many hidden features

• A relational system is like an icebergA lot is hiddenready to strike

when you least expect it.


Questionnaire research - SPSS• SPSS - statistical package ( for analysis )

– designed and developed for this task– fairly intelligible output– can produce ‘presentation quality output’– used and supported world wide– reputation built on quality and reliability

Beware of ‘friends’ recommendations or ‘free’ software downloaded from Web


SPSS


MBChB 24


Questionnaire design - SNAP• One integrated step from Q to A• Creates questionnaires ( Questions )• Collects the data

–paper–scanner–WWW

• Perform the analysis ( Answers )


Why use SNAP instead of .... ?• Designing questionnaires with WORD• Storing and analysing the data with -

Excel - BADSPSS - Better

• Not designed for the whole job• Inflexible and not integrated

–cannot re-order questions easily–need to re-define data for the analysis

package


Why use SNAP instead of .... ?Q 5 W h a t i s y o u r a r e a o f s t u d y

Ar ts & S o c i a lSc iences. .. .. ... .. ... .. .. ..

Educat ion . .. ... .. ... .. .. ..

E n g i n e e r i n g . ... .. .. ... .. .

Div in i ty .. .. ... .. ... .. .. ... .. .

L a w ... .. ... .. ... .. .. ... .. ... ..

Life Sc iences .. ... .. ... ..

Medic ine ... .. ... .. ... .. .. ..

Sc iences ... .. ... .. ... .. .. ..

Q 6 D o y o u h a v e y o u r o w n c o m p u t e r a t u n i v e r s i t y ?

Yes .. .. ... .. .. ... .. . N o. .. .. ... .. ... .. ... .

Q 7 D o y o u h a v e I n t e r n e t a c c e s s o n y o u r o w n c o m p u t e r ?

Yes .. .. ... .. .. ... .. . N o. .. .. ... .. ... .. ... .

Q 8 W h a t i s t h e s t a t e o f y o u r h e a l t h ?

VeryGood . ... .. ..

G o o d .. .. ... . N e i t h e rGood n o r

Bad .. ... .. .. .

Bad ... .. ... .. Very Bad .. C a n ' tc h o o s e . ... .

Section 2 - ( General questions about NHS )

Q 9 W h i c h o n e o f t h e s e s e r v i c e s p r o v i d e d b y t h e N H S h a v e y o u h e a r d o f ?

NHS DIRECT / N H S24 (Phone L i n e ) .. .. .. ..

N H S W A L K I NCL IN IC .. .. ... .. ... .. .. ... .. .

N H S n e t . .. ... .. .. ... .. ... .. Onl ine appo in tmen tserv ice .. ... .. ... .. ... .. .. ..

Q 1 0 H o w o f t e n h a v e y o u u s e d a n y s e r v i c e p r o v i d e d b y t h e N H S i n t h e p a s t y e a r ?

0 . .. ... .. ... .. .. ... .. . 1-3 .. .. ... .. ... .. ... . 4 - 7 . ... .. .. ... .. ... .. 8-10 . .. ... .. ... .. .. . More t han 1 0t imes ... .. ... .. ... .

Q 1 1 N H S a n d G e n e r a l P r a c t i c e d o c t o r s

Do you h a v e a genera l p rac t i t i one r that you p r e f e r to see i f y o u

h a v e to v is i t the doctor

Yes No Not Sure

Do you f e e l you h a v e loyalty towards you r own regu la r pract i t ioner

Do you h a v e conf idence in the serv ices prov ided by you r generalpract i t ioner

W o u l d you say you f e e l that you t rust you r genera l p rac t i t i oner

W o u l d you say you fe l t ' loyalty ' t owards the N H S

Do you f e e l that the N H S i s a loyal serv ice

Do you h a v e conf idence in the serv ices prov ided by the N H S

Section 3 - NHS DIRECT / NHS 24

NHS Direct/24 is a new 24-hour service telephone advice line staffed by nurse. It was established toprovide easier and faster information for people about health, illness and help themselves and their

families.

Q 1 2 H a v e y o u e v e r u s e d t h i s s e r v i c e ?

Yes .. .. ... .. .. ... .. . N o. .. .. ... .. ... .. ... .


MBChB 25


SNAP - integrated package


SNAP - other advantages ?• WYSIWYG questionnaire design• Default styles, layouts and templates• Results can be displayed in many

different formats–tables–charts–as numbers on questionnaires

• Direct creation of SPSS files for further analysis


SNAP - Percentages or counts


MBChB 26


SNAP - Charts


SNAP - switch between views


SNAP - difficult to use ?• A little more difficult than Word• Not as hard as Access• Perhaps the same as PowerPoint• Some commands are SNAP specific but

that is only to be expected• Latest version has many improvements


MBChB 27


Which would you use for ?1) Commuting within Aberdeen

2) Building a motorway

3) Formula 1 racing at Silverstone(a) (b) (c)


The changing times - hardware

1978 - New university machineCost £1.5 millionRoom Tennis court size - air conditionedSupport Engineers, systems staff ( 10+ )

3 shifts of 4 operatorsSoftware Fortran, Cobol, IDS/II - batch mode Specification - 16 Mbytes RAM, 486 processor

3.2 GBytes disk1998 - equivalent

£150 ( a second hand laptop )2013 – iPhone or iPad – far more capacity !!


The changing times - software• 1978 –

– Mainly user programmes written in• Algol• Fortran• System code / Assembler

– Batch compilations and execution sometimes taking hours

– Very few Packages• 2013

– No programming / Apps– Windows / GUI / ‘point and click’ / touch screen– ‘Instant’ results


MBChB 28


What if ??• If transport had changed at the same

rate as computing• No steering wheel, gearchange, brakes

etc.• Just display a map, click on it and• Fly there !!!

• Think of the chaos !!!


John S. Lemon

Edward Wright BuildingDunbar Street

Aberdeen01224 273350 or (76)3350

[email protected]

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Medical Electives