Copyright State of Victoria, Department of Human Services, Printed by Big Print, 50 Lonsdale St, Melbourne VIC 3000.

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1 A guide health c usg June 2008

2 Publhed by Rural Regional Health Aged C Services Divion, Vicrian Government Department Human Services, Melbourne, Vicria. June 2008 Th website booklet at available pdf mat may downloaded from VQC Copyright State Vicria, Department Human Services, 2008 Th accdance publication copyright. provions No part may Copyright reproduced Act 1968 by any process except Authed by Vicrian Government, 50 Lonsdale St., Melbourne Prted by Big Prt, 50 Lonsdale St, Melbourne VIC rcc_ Vicrian Phone 1300 Quality 135 Council 427 Secretariat Website vqc@dhs.vic.gov.au

3 Acknowledgements Th resource has en developed Vicrian Quality Council by: Project Health Fiona Lgren, auth Jessie Murray, research documentation Its development has en overseen by a reference group comprg: Vicrian Quality Council memrs Associate (Clical Epidemiology Press Carole Health Br, Service Chair (Centre Research Excellence Patient Evaluation Safety) Unit, Melbourne Health) Ms (Mary Kerry MacKillop Bradley Aged C) Dr (Royal Peter Children s McDougall Hospital) Associate ( Royal Press Women s Les Hospital) Reti External experts Dr ( Chr Western Ba Central Melbourne Integrated Cancer Service) Ms (Department Anna Donne Human Services) Ms ( Mary Royal Draper Women s Hospital) Ms (Clical Pollyanna Epidemiology Hardy Biostattics Unit, Murdoch Children s Research Institute) Dr (Conial Joseph Liaon Ibrahim Services, Vicrian Institute Fensic Medice) Mr (Department Steven McConchie Human Services) Project suppt was provided by Vicrian Quality Council Management Group Mr Oliver Furness Ms Jo Heard Ms Anna Laird contributions those who reviewed draft resource gratefully acknowledged. 1

4 Contents 2 1. INTRODUCTION Data 1.2 Purpose scope guide 1.3 About Vicrian Quality Council 5 2. MEASURING AND IMPROVING QUALITY IN HEALTH CARE 2.1 What? What role? Usg help defi ne project Usg evaluate extg processes identify opptunities Usg mulate priite terventions Usg measure impact Usg guide sustaed GETTING STARTED PLANNING YOUR DATA-RELATED ACTIVITIES Takg a systematic approach Gettg right advice Stayg on track COLLECTING AND STORING DATA Where can access need? Extg ternal Extg external Data collection techniques ols Process mappg Brasrmg 20 How brasrm 23 How create an affi nity diagram Cause effect techniques 23 How create a cause affect diagram 23 How use fi ve why technique Audit (cludg clical recd reviews observations) Surveys questionnaires Focus groups key mant terviews 36 How use key mant terviews 26 How use focus groups Good what it how get it Attributes good collection ols Samplg Data entry, checkg cleang Srg managg 30

5 5. ANALYSING AND PRESENTING DATA Analysg numerical (quantitative) Counts sums Ratios, rates percentages 32 Usg ratios, rates percentages make comparons Measures centre 34 Mean average 34 Median 34 Mode Measures variability spread 36 Range 36 Interquartile range 36 Stard deviation Usg stattics make comparons 37 How use terpret confi dence tervals 37 How use terpret p values Or measures causation 39 How use crelation coeffi cients Presentg Tabulatg Graphg chartg 42 How use pie charts 43 How use bar graphs 43 How use bar charts make comparons 45 How use box plots 46 How use hgrams hgraphs 47 How use a scatter diagram 48 How use le graphs time charts Analysg qualitative INTERPRETING AND USING THE DATA APPENDICES 53 Appendix 1. Data planng template 54 Appendix 2. National/state bases regtries 55 Appendix 3. Useful resources 57 Appendix 4. Glossary 59 Appendix 5. References Data Quality now a drivg ce health c 3

6 01 Introduction Section 01 Collectg analysg central function any health service. 4

7 Introduction 1.1 Data Quality c an essential now aspect a drivg service ce delivery health levels. Put simply, everyone s busess. at all But, what unless improve we measure, wher it s diffi we cult have know fact exactly achieved processes, must driven so efts by reliable improve. systems only enables us accurately identify problems, Data it also not assts enables objective priite assessment wher itiatives change have deed occurred. Collectg analysg ree any central health service. function stattician good news successful don t have. a As th accessible guide demonstrates, understable fundamentals concepts health pressionals can should apply ir all route practice. 1.2 Purpose scope guide purpose health c th team guide underst asst all memrs how apply some role basic techniques efts. usg suppt ir associated guide descris collection, fundamental analys, concepts reptg, how se relate terpretation stages cycle. It various descris how ms tegrates also communication, key aspects people, systems. It assumes cludg a prciples basic understg provides lks detailed those who wh exple pic mation me detail. Underpng recognition cful content planng th guide effective teamwk itiative. also essential elements any focus rar guide than research; on usg however, management prciples also largely applicable research. 1.3 About Vicrian Quality Council 2001 Vicrian as an Quality expert Council strategic (VQC) advy was group establhed safety agenda Vicrian health lead services. council responsible fosterg tter c stakeholders health services develop useful Vicria ols by wkg strategies improve health service safety. Th Promote project stems access from use VQC objective targeted mation, relevant clicians meangful, patients, improve practice, furr, safety asst health. services measure monir Me mation: See VQC website at: Figure 1.1 From action Data raw material from which mation constructed via processg terpretation. Th mation turn provides knowledge on which decions actions based. Data Inmation Knowledge Decion Action DATA TIP: put me eft understg utilg, me rewarded will terms right solvg problem right way. 5

8 02 Measurg health improvg c Section 02 Th section guide aims equip readers : recogne key phases cycle underst how cycle suppts each stage underst role people systems management. 6

9 Measurg improvg health c 2.1 What? Quality as extent health which c a health settg c may service defi ned product produces a desired outcome.1 Quality health outcomes achieved a system through by which analysg tter improvg service delivery processes. With th md, it as useful spanng consider a numr key domas. measurement se provide a practical framewk National Health Permance Committee2 ne domas health system permance: identifi ed Effective Accessible Appropriate Contuous Safe Capable Effi cient Sustaable Responsive 2.2 What role? Health systems. service Makg ganations changes improve complex adaptive can ree a complex busess. Fundamentally c it requires delivery us underst our health services, what happeng affect delivery how we can fl uence what m facrs solid achieve evidence. what we In need such a suppt complex decion system, makg, occurrences, rar assumptions, than mation emotion based on politics. olated Figure 2.2 push pull With th md can it both useful reactive consider proactive. F example, routely most across health various services collect domas, thus analyse problems health service ten reacts clear troduce self-evident appropriate s. fection rates Examples a range clude adverse clical events, dicars. In look addition, opptunities health services. likely proactively opptunities come evident when processes se Data outcomes ree helps examed push me closely. by by identifyg identifyg problems, opptunities. Data pull helps us us underst ols descri improve what s our gog service on by givg stards comp our agast permance, previous permance. eir agast known To me underst clearly it useful role consider fi ve cycle. se phases phases descrid briefl y overleaf st viewed as Figure a contuous 2.3. As cycle th fi gure activity shows, as illustrated take place, rely upon, an overall phases ganational context. Data ree plays an helps imptant us : role each se phases, tackle right problem (phases 1 2) implement right strategies/solutions (phase 3) demonstrate contued required (phases outcome 4 5). monir 7

10 followg sections descri me detail how can used at each phases cycle. phases cycle 1. Project defi nition phase What question problem? Th volves identifyg a terest potential problem a. 2. Diagnos phase What can we improve? Th problems volves / evaluatg opptunities extg processes. a terest diagnose potential 3. Intervention phase How can we achieve? Th volves: determg potential terventions processes require defi ng permance measures implementg terventions monirg progress. 4. Impact measurement phase Have we achieved? Th volves evaluatg impact terventions on predetermed permance measures. 5. Sustaability phase Have we sustaed? Th volves monirg process refi ensure ng terventions improved as processes well as providg tegrated feedback health der c susta delivery as appropriate. Figure 2.3 cycle 8 Source: NSW Health 2001, clician s olkit improvg patient c Note: P = Plan, D = Do, S = Study, A = Act Source: clician s NSW Health olkit 2001, improvg Note: P = Plan, patient D c S = Study, A = Act = Do,

11 Figure 2.4 Plan-Do-Study-Act cycle Source: enhancg Langley ganational G, Nolan K, permance, Nolan T, Nman Jossey C, Bass Provost Publhers, L 1996, San Francco. guide: a practical approach 2.3 What problem Are question? Usg at our clients clic? satfi ed current waitg times help defi ne Is project at our use hospital sedatives how on can dcharge it improved? appropriate As mentioned earlier, helps push With (good) can: by identifyg problems, pull assess permance current gaps permance identify by identifyg opptunities. Without address we can only guess what sues we should underst stakeholders needs opions health service nefi t patients/clients/residents, stakeholders. priite problems projects considerg domas provide a framewk establh overall aims targets service. what problems might ext health examples Table 2.1 provides some examples, cludg makg. types may guide decion establh. a clear case need level se can applied at both a clical team as well as an ganational level. Organg direct sues focus relevant supptg itiatives. will help All a question, example: activities start a problem How products can we improve atre use le blood clical practice guideles? current Why our hospital/department post-surgery fection than rate higher hospitals/departments? comparable 9

12 10 Table (based 2.1 on Identifyg domas as concern - National Quality Committee2) Quality doma/criteria Effective C, tervention action achieves desired outcome. Appropriate C/tervention/action client s needs based provided on establhed relevant stards. Safe actual avoidance potential reduction harm from health acceptable c management limits environment which health c delivered. Effi cient Achievg desired results most cost-effective use resources. Responsive Service It cludes provides respect respect dignity, all confi dentiality, client ientated. participation amenities, access choices, social promptness, suppt choice provider. netwks Accessible Ability right people time irrespective obta health come, c physical at right location place cultural background. Contuous Ability service provide across unterrupted, programs, practitioners, codated ganations c levels over time. Capable An service dividual s based on service s skills capacity knowledge. provide a health Sustaable System frastructure ganation s such as wkce, capacity facilities provide equipment, novative respond needs (research, monirg). emergg identify What /types priite measures might help projects? Clical dicars Benchmarkg agast services/departments Mbidity mtality meetgs/repts Clical dicars based Audits guideles agast ternational stards/evidence- Benchmarkg agast services/departments Service utilation Adverse events cidents Sentel events Clical dicars Benchmarkg agast services/departments Mbidity mtality meetgs/repts Accreditation repts Service utilation Expenditure Audits equipment/resource usage Cusmer complats Waitg times Failure--attend rates Service utilation Cusmer complats Waitg times Failure--attend rates Accreditation repts Service utilation Cusmer complats Waitg times Failure--attend rates Service mappg Clician feedback Adverse events Waitg times Adverse events Accreditation repts Accreditation repts Organational sce boards Integration systems Busess plans/resource allocation

13 So itiative how do should actually addressed decide next? what A mal useful. exerce Best conducted called as a impact group, analys impact can analys a structured a consideration brasrmg-type activity potential problems enables service. opptunities Based on lt problems potential health asked itiatives identify: supptg, group may fi ve thgs done frequently fi ve thgs volve rk fi ve thgs concern staff clients. on Participants frequency, n rk asked level sce general each level item based 1 concern. 3, where Scg 1 low may frequency,, example, rk concern from scg 3 pics high frequency should dicate rk concern. priity pics highest address attention. a range activity may criteria also such adapted clical effectiveness. as cost As all volve brasrmg all relevant activities, stakeholders it imptant avoid bias. See section me mation. th activity DATA TIP: Settg targets Use help set clear itiative. measurable targets Make objectives. sure targets lked aims Be able realtic elimate expectations all adverse events won t appropriate admsions. all Express. target F example, as a value, if basele not as a throughput percentage a improve clic by fi ve 10%, patients n per state hour target as want patients per hour. 5.5 Reassess prepd targets modify throughout m light project experience consultation stakeholders. 2.4 What can we improve? Usg evaluate extg processes identify opptunities With (good) can: defi ne processes processes people volved identify problem steps process identify priite opptunities establh process clear steps objectives identify barriers enablers change. Once have agreement have identifi ed problem a concern, wthy associated attention, processes next step suffi cient analyse detail meet sue needs project. Th prece diagnos nature phase will cause enable problem establh identify where process s need made. might Tools understg likely useful processes gag a tter opptunities clude: brasrmg: present recd memrs ideas respect what, team where how problem potential solutions process identifi ed mappg: analysed steps process surveys, groups: stakeholder key mant put terviews sought regardg focus problem potential solutions, as well as potential barriers change audits: practice specifi processes, c gaed comparon regardg extg permance stards set control extg charts:, monired process permance, over time based tween on populations identify problems patterns nchmarkg: outcomes similar comp services. extg processes/ 11

14 12 se overall techniques targets will also help project refi ne process develop steps. specifi F c example, objectives relation a broad various improvg access service, process target may identify specifi c opptunities such as: analys allocatg establhg appotment triage procedures times urgent systematically cases priite urgent cases expg me effective use role medical practice personnel nurse time suppt remdg reduce failure--attend cusmers ir rates. appotment times F section me 4 mation th guide. on se techniques, see 2.5 How can we improve? Usg mulate priite terventions With (good) can: determe address most particular appropriate problem terventions situation suit priite implementation terventions strategies comp implementation nefi ts strategies. alternative terventions When processes have a good opptunities understg, service terventions well placed establh select implementation most appropriate strategies ability select suit appropriate particular terventions situation. Your implementation strategies relies heavily on mation collected diagnos phase, as descrid above. F durg example, diagnos through audit phase, process may identify mappg outpatient adequate appotments mation received presents on a barrier referrals terventions providg timely may ree appropriate clude service. starded Your referral pressionals templates, itiatg educatg central referrg triage health Without, may well have approached systems. scenario a different way. th help techniques trial proposed descrid terventions section on 2.4 a small also scale refi nement determe e applyg ir impact m on guide a wider furr Good particularly imptant durg th scale. ensure able draw right conclusions phase about tervention what happeng wher as a result fi ndgs can applied broader service population. What implementation difference strategies? tween terventions We talk, about clical desired strategies clical suppted terventions, from practice stards, evidence-based by guidele derived recommendations example, terventions literature reduce me pressure generally. ulcers F clude usg a sk tegrity assessment, pressurerelievg underlays promotg cidental activity. may, We strategies also talk about achieve implementation desired change strategies, clical practice. awness se education strategies strategies, might clude decion clician ols, monirg reptg processes. suppt re but it imptant ten a blurrg recogne overlap tween difference. terms In implementation particular it imptant clical terventions recogne will depend successful on strategies selectg suit designg particular appropriate circumstances. implementation

15 2.6 Have we achieved? Usg measure impact With (good) can: assess implementation impacts strategies terventions demonstrate project stakeholders. success In God we trust all s brg. Th a popular sayg among particularly those volved th phase. Without, simply cannot relevant determe demonstrate impact success. change itiatives But will need it imptant demonstrate underst success what st itiative. F example, will lookg many troduce a clical tervention projects patient has outcomes already en such demonstrated as those featured improve practice guideles. An example might preventg clical deep ve Best thrombos practice guideles accdg measures prevention outled venous thromboembolm.3 collection analys Thus will on focus determg wher accdg change guideles, clical practice less emphas has occurred on expected clical nefi impact. ts In terms circumstances, patient outcomes where may requirements less defi ned, differently. may need defi ne In ger th phase, furr repeated surveys,key audits may mant a feature, terviews terventions. focus Repeated groups, analys assess extg impact presentations) (such as through also likely. control charts In some th phase analytical will need ols come basic grips stattics comparg presentation what techniques happeng used service describg as a result will need analyse present terventions. effectively You appropriate der draw action. appropriate You will also conclusions need able take facrs articulate affectg nefi success ts outcomes tervention identify its application ganation. 2.7 Have we sustaed? Usg guide sustaed With (good) can: provide demonstrate feedback nefi ts rece clicians change clients/patients identify need slippage repeated tervention practice tervention approach. change Data monir has an permance, ongog role susta helpg asst planng. Not same all way. F example, projects ongog will use measurement particular feedback problems permance sues, may particularly necessary volvg conditions treatments associated those high rk, high utilation high cost, such as particular cidence diagnostic caesan procedures section, use broad-spectrum antibiotics. use F appropriate sues, periodic assess sustaed measurement may appropriateness clical practice approaches. assess contug 13

16 03 Gettg planng started -related activities Section 03 Th section guide aims equip readers : underst imptance planng -related activities underst key considerations planng underst how source necessary experte. 14

17 Gettg started planng -related activities Good planng activities. key Th successful particularly management aspects project, so which complex resource tensive. So, need can start end md. Assumg targets, have ma identifi planng ed sues overall objectives consider relation management will : need population people relevant question what problem will able need judge accurately assess appropriate methods collectg srg when/how ten will need collect how presented demonstrate should ganed, extent analysed problem impact itiatives ethical need considerations, secure ethics approval cludg wher project. will 3.1 Takg a systematic approach Planng systematic always structured easier if way. it approached To asst a regard, a planng template cluded Appendix th 1 table mat guide. template can modify presented accdg a simple needs particular project. steps clude: 1. mulatg overall goal 2. identifyg specifi criteria c objectives 3. identifyg clical terventions target populations both implementation strategies 4. based identifyg on objectives need target collect populations, measure problem measure 5. collection determg methods sources 6. srage determg requirements analys techniques 7. cludg determg skills, computer/stw resources required resources accdgly, fi nancial resources. A wked table provides example an also overview shown Table 3.1. requirements appropriate use a project prophylactic aimed antibiotics at creasg surgery. Note me th less an example complex only dependg on plan nature may no universal rules about what project. re need how need go about it it simply must collect meet objectives needs key components project, so get overall right goal outset. from Subsequent would want itial undertake overall planng, furr detailed it likely planng objective usg measurement a similar template a. each project Imptantly, overall planng planng will tegrate itiative, cludg change strategies. implementation You may clical ree terventions want exp planned template terventions. summare Or fi ndgs dimensions identify clude stakeholder consultation communication. address 3.2 Gettg right advice Th guide collection provides analys mation techniques about commonly, as such, used Dependg a useful startg on complexity pot project project, planng. it management might also experte a good at idea planng secure some stage heartache later on. It likely will nefi save from specifi c guidance relation sues such as: t a literature review choosg samplg appropriate appropriate numr numr observations make results meangful people questionnaire design clical audit design spreadsheets collection bases srage ols such as Excel accessg extg through health service ethical privacy sues me sophticated stattical analys methods. 15

18 Data analys Data resource needs comparon Qualitative current documented 0.5 manager EFT project procols recent evidence months 12 volvement (cludg analys Quantitative implementation) aspects tervention pre- post-tervention Database recd prescribg breakdown, prescribg analyse Independent by combidities, type surgery; facilitar op fection. post staff um conduct matic feedback analys staff ums from relation barriers attitudes 16 Table 3.1 Example a planng framewk management Improvement project: Prophylactic antibiotics surgery Target populations Data requirements methods Data collection Overall goal Objectives/ criteria surgeons Initial meetg staff identify concern a over Prospective two weeks, audit pri three months tervention, followg ne Current procedures Nature current undergog surgery strategies Implementation surgical all staff nursg Clical all patients tervention procedures how y comp (rapeutic st practice Increase patients percentage crect receivg prophylax antibiotic Increase patients percentage receivg Improve use antibiotics appropriate across surgical all surgical prophylax as guideles) Actual practice clical Type surgery Duration surgery Increase percentage prophylax e commencg at months followg Process mappg identify as Staff present ums, gauge itial attitudes barriers change antibiotic Nature restrictions current Fancial antibiotic repts expenditure operation charactertics Patient (age, combidities gender, facrs likely need fl uence antibiotics) Wher prescrid antibiotics not If prescrid admtration time antibiotic; fi rst dose antibiotic; choice antibiotic; dose frequency duration admtration, appropriate patients receivg prophylax duration negative Improvement/no on posperative impact fection rates Reduce patients percentage receivg prophylax antibiotic appropriately cludg dcharge Post-operative fection Current surgical attitudes staff Human analys facrs

19 Sources th experte might clude: librarian at health service university health mation services (medical recds) department manager mation technology department managers research personnel experts designg usg qualitative an ethics committee extg stattics staff skills terest epidemiology a stattician at university. 3.3 Stayg on track In addition cful essentials planng, re should a ar numr se md throughout reiterated throughout th guide project. summared low. DATA management TIP: If experience can, clude on someone project team. Start terests by surveyg establh staff determe extg ir skills skills bank. Data management essentials tips keep on track 1. Plan cfully Plan collection analys activities cfully e start, considerg: scope purpose project specifi c questions answered availability resources, cludg personnel IT resources target audience stakeholders, cludg consumers. 2. Learn from s Don t revent wheel. Search literature projects have tackled similar sues. Investigate extg sources e itiate a new collection activity. re If need a wide collect range new audit, ols vestigate olkits, extg which validated likely collection relevant methods project (see Appendix 3, Useful resources). 3. Try thgs out avoid mtakes Test Th might clude: collection analys techniques on a small scale identify crect any problems. conductg a pilot survey triallg an audit m establhg wher can access as planned through ganation. 4. Involve team consider impact on nmal wk fl ow requirements Integrate extg reasons wk where possible collection ensure resultg everyone nefi knowledgeable ts. about measurement As far as possible, should mime used impact speed collection up, not exerce slow thgs on nmal down. wk Rememr, goal, not develop a measurement system. 5. Don t afraid ask help Get management advice when process need useful it, particularly contacts clude planng IT department, design phase librarian, contacts at a local university. department Seek feedback at all steps management project. 17

20 04 Collectg srg Section 04 Th section guide aims equip readers : underst potential sources extg identify at various how stages various collection ols may cycle used underst it can achieved imptance how underst options srg managg. Furr each mation section available Appendix via 3, Useful lks resources. at botm 18

21 Collectg srg 4.1 Where can access need? Collectg time eft, from so scratch vestigate can all take possible a great sources deal extg collection mation processes. e itiate any new Extg ternal Useful repted ternal routely by may already health service. collected Th may accessed from mary hospital reptg bases departments, from may systems clude: dividual adverse sentel events events, cident repts fection rates, olates length patient stay a range clical dicars service pharmacy, utilation specifi c procedures cludg diagnostics, clical outcomes from clical regtries waitg times surgery waitg times emergency department cusmer complats expenditure repts use high-cost medication items. Additional repted on a route bas not collated may also mally but may accessible through service available, computer departments. system Th may through clude systems clical regtries particular bases clical mation. providg access a range To fi nd out what Organation, already speak g collected fi nance departments as well as managers IT health mation services. Inmation recds may available also considered paper-based as extg client medical though considerable eft will required access, it section through 4.2.4). retrospective prospective review (see Extg external Extg national state project, may also particularly useful permance terms defi ng national problem averages. Appendix comparg cludes many bases regtries 2 currently Rememr mataed each locally source nationally. different time period terms over which se elements collected collected, how reliable accurate. Read small prt, population cludg which defi it applies. nitions Admtrative clical? Data both may imptant admtrative useful clical nature projects. Admtrative services helps deliver. defi It ne ten available population service bases cludes items such as: through client location, demographics cultural background cludg age, gender, service duration delivery client contacts; such as dates frequency times services; waitg times fi nancial readmsion, length stay. Clical population relates health-related health needs impact services. It cludes items such as: mtality mbidity rk facrs adverse events treatment diagnostic practices, tests cludg drug usage fection rates. DATA TIP: Talk managers mation services health e establh start already what service. exts 19

22 20 DATA TIP: Where use ols possible, validated constency, seek ols out used examples similar projects. 4.2 Data collection techniques ols If a wide fi nd range need methods collect new ols, available. re which simplest can collection used recd ol counts a simple observations. check sheet, A numr th section. common methods descrid Some mappg methods, focus such groups, as brasrmg, collect qualitative process about nature reasons problem. collection Many analys se functions. techniques Ors, serve like both clical practices audit, collect quantitative outcomes. about patients, clical Most a numr methods projects applied will der require adequately impacts defi ne sue itiatives. measure Useful F furr resources. mation see Appendix 3, Process mappg Process mation mappg about a way current collectg processes. It team an volved activity service should delivery, conducted usually by takes place cycle. diagnostic phase Process steps mappg extg volves processes outlg der analysg : confi we make rm what crect currently assumptions happeng about (sometimes happeng) what identify problems process identify processes how people (human teract facrs analys) extg systems establh identify opptunities causes se. problems thus Process an mappg helps required. It may hone volve on where developg simplest fl ow process diagrams mappg usg ol matrices. chart, which outles steps a given basic process fl ow at identifi end es decion process. pots affect outcome Me cpate complex additional process dimensions mappg techniques such as: who team responsible each step how review long each technique step takes PERT (program chart) evaluation most process imptant steps sub-procedures potential costsassociated terventions. various steps Quantitative qualitative? Data Examples may clude quantitative, length patient, numerical stay, numr nature. patients qualitative treated descriptive, fection example, rates. Data attitudes may also clients. opions Both types health c staff, valuable feedback mg from itiatives. Me mation: See mappg: Vicrian a guide Quality health Council service guide, staff, Process available at: downloads/process_mappg.pdf Brasrmg Brasrmg ) about aims a particular generate subject a lot a sht ideas period (a m technique time. It may as it also can volve seen processg as a analys decions draw conclusions. make Brasrmg may process, used at various example, phases : identify itial problems as concern (phase 1) identify potential causes a problem (phase 2) identify problem potential (phases terventions 2 3) address exame terventions reasons (phases success 3 4). we Brasrmg it delirately structured not a nmal ga meetg ideas from all participants avoid bias.

23 Example process mappg Process analys an thopaedic outpatient clic specialt In th example, appotments service osteoarthrit delivery team patients at an outpatient as a thopaedic sue. clic sue noted was waitg identifi ed times by comparg waitg possible times decle patients services conditions as well while as feedback y were from waitg referrg an GPs appotment patients. was Concern also a facr. about admtration, team underok from receipt a process mappg GP referral, exerce identify appotment all steps specialt. service provion A delivery simple process. fl ow chart Or was developed, considered which cluded: enabled group consider various steps service creasg average waitg waitg times times (up appotments 20 weeks) over past 12 months th showed a trend wards rates failure attend over past 12 months (tween 15% 20% per month). group identifi ed a numr opptunities cludg: identifyg managg urgent cases communicatg GPs reducg failure attend through improved communication patients GPs usg assessment limited specialt as well as services education me effectively through volvg non-specialt staff aspects identifyg signifi cant deteriation through monirg patients waitg an appotment. A It highlights matrix (see proposed Figure 4.1) new representg activities activities changes undertaken extg process by memrs help identify team opptunities was developed.. Th med bas developg terventions. 21

24 Figure 4.1 Matrix representg activities undertaken by memrs team thopaedic outpatient clic Activities Clerk Nurse Docr Physio Pri appotment Receipt recd referral on base New Triage referral establh urgency Make appotment Improved dicatg waitg Letter time GP acknowledgg requestg X-ray referral, any mation New Patient mation sent pre-appotment questionnaire New remd Patient m phoned day e appotment At appotment New hry Clical conservative assessment management, (weight, height, questionnaire) review Clical assessment (specialt) Referrals conservative management New accessg Education referred about services self-management Follow-up appotment as appropriate After appotment Improved cludg referrals Letter GP schedulg regardg outcome, if relevant surgery New establh Patient deteriation periodically monired need by follow-up phone (if required) 22

25 How brasrm A group brought ger people appropriate address a specifi project Appropriate representation stakeholders c sue. equal an imptant contribution consideration, from all participants. so o ensurg recded group on asked a whiteboard contribute fl ip ideas chart. se success g given session freedom depends express on ideas participants restriction judgement, thus skilled facilitation out may domate, required. a variation If some may participants volve askg likely participant contribute one idea at a time movg each around An approach, table until called all ideas brawritg, exhausted. team memrs recd a specifi c numr requires ideas dcussed. (say, fi ve Th ideas) approach se nefi written cial up it promotes provides open anonymity expression contributions ideas. ree All repetitive. contributions recded, even if related When lt examed all ideas have dcussed en thoughly determe exhausted which ideas wth takg furr. How create an affi nity diagram F brasrmg complex session may also volve projects, stg ideas on key objectives. categies Th results help focus thkg an affi nity diagram, which simply production related ideas ger categies. means ideas groupg usually recded on sticky notes, categed by about group nature dcussed categies reach consensus place ideas categies. where activities concept mappg md Similar which descri gang concepts ideas mappg, y may tter undersod. so Where a particular brasrmg problem, addresses it may used causes acause effect diagram (see section 4.2.3). produce Cause effect techniques An about valuable processes ol collectg concerned processg cause effect diagram, also known fi shbone diagram. as How create a cause affect diagram from effect process mappg problem exerce have identifi ed collection technique. causes may identifi a brasrmg session by me mal ed collection effect techniques. diagrammatically causes produce matched representation problem, which can a vual considered possible solutions by (see group example terms overleaf). identifyg How use fi ve why technique fi establhg ve why technique causes an identifi ed approach It wks by askg fi ve why questions problems. each answer leadg an why question. succession, st explaed by example: Th atre where power phones was remaed lost out atre after an telephone cident circuits. communication system durg a planned test 1. Why? on programmg mboard stw failed. backed by a battery 2. Why? battery had not en mataed properly. 3. Why? matenance contract had effectively lapsed. 4. Why? re contract was transfer. an absence documentation a past 5. Why? re gaps documentation. a person dependant culture, along Me mation: NHS Improvement Netwk, East Midls. ols--use-here DATA TIP: re many easy-use now ( free) stw cheap packages generate help pressional-lookg affi as nity well diagrams diagrams as charts. Have a fl look ow on ternet. 23

26 Example cause effect diagram Post-surgical delirium older patients In older th patients example, a service general delivery surgical team ward. identifi ed a problem cidence post-surgical delirium among Participants group conducted session a brasrmg cluded nursg, session surgical identify possible pharmacy causes staff as well opptunities as non-clical suppt. As preparation brasrmg session, participants were provided a copy recent clical guideles staff. on delirium relatg cidence post-surgical delirium establhed through a recent audit. Ideas generated. freely Furr generated dcussion durg helped session identify were collated priities under tervention. headgs a cause effect diagram was Figure 4.2 Cause effect diagram 24

27 4.2.4 reviews Audit (cludg observations) clical recd Audit permance usually descris measured a process agast a by known which stard current nchmark. Audits may used: at diagnos problems, phase cludg identify establh quantify pri tervention basele at impact tervention phase establh effect sustaed at sustaability. phase monir Recd mation review retrospectively a common audit prospectively method whereby from extg client system recds. limitation collected recd recded review some some may variables recded may not constently, required. F thus th a reason degree it imptant terpretation up a collection m so set as constently as possible sues regardg collected constency can fl agged. Audits practice may also (such as based h on washg). observations review, ensurg constency collection As recd should guided by a stard collection m, vital as rules. well As as clear all defi collection nitions methods, collection imptant test audit ms procedures it also on a small scale fi rst. Increasgly on askg questions future, computer-based recd reviews patient will based recds, useful which will make m activities. far me effi cient Me mation: Clical Healthc. audit Available how from guides. NHS United Brl Surveys questionnaires Surveys about charactertics, questionnaires attitudes provide mation a group dividuals. y useful haviours m diagnos phase garg tervention. Surveys project may assess admtered changes followg cusmers, suppliers stakeholders. staff, Surveys seek extg not surveys easy develop, have en so wherever validated. possible You particular may need needs, but adapt ar an extg md survey if make changes, survey no longer validated. DATA collection TIP: Consider analys ethical should sues... comply Data human research ethical stards only mation necessary measure collect practice. assurance F me mation health c see require When does dependent Medical Research ethical review? Council, National Health from: Available e46syn.htm If guidance do have from someone write own experience survey, seek comment. Also sure test survey on a ask small group terpretation target audience understg. identify As problems collection techniques, it imptant establh all objectives e write survey. It also imptant : make see sure tips overleaf have used good ask survey advice questions someone survey experience from appropriate optime response delivery rates mechanms through appropriate (onle, hardcopy) length, follow-up make sure collectg it clear audience nefi why ir participation ts make sure design, collection have addressed analys confi dentiality processes. 25

28 26 DATA TIP: Free hostg onle websites survey savg now available, eft design time dtribution. Good survey questions: specifi c easy read underst ask knowledge opion, not both knowledge appropriate understg target audience s level not loaded leadg do ( double-barrelled not ask me than questions) one question do not clude jargon acronyms allow delirately choice seekg only numerous one option options) (unless provide response reasonable options ranges variation unlikely elicit socially desirable answers appropriate age, culture literacy provide will adequate help analyse demographic mation meangful way. a me Me mation: See Appendix 3, Useful resources mant Focus terviews groups key Focus common groups methods key gag mant qualitative terviews itiatives. y can used guide staff, solicit clients/patients, views, sights technical recommendations stakeholders, ree providg valuable experts put all phases process. How use key mant terviews Key -depth mant mation terviews from a limited generally numr used wellmed ga understg, people. se can experts, provide sight ir knowledge problem give recommendations nature solutions. y may also helpful alertg previous thus savg wk time a avoidg sources duplication mation, eft. Key focus mant groups terviews when frank used -depth preference required, when a larger group dynamic answers might expected structured limit semi-structured bias dcussion. y most may commonly script guided lts by open-ended a survey-like questions. prma Interviews face. Face may face conducted most frequently by telephone used face Choice as it me trag conducive a terviewer free exchange an ideas. imptant appropriate consideration level dcussion. der assure an open How use focus groups Focus various groups phases also valuable mg project. sue y can gag provide an put understg diagnosg amount perspectives time. y various also stakeholders useful identifyg a sht planned explg change barriers resolvg implementation problems are. Focus unanticipated groups sues provide a fl exible allow mat teraction exple participants, group remas however imptant. a clearly A dadvantage stated objective focus groups can domated dcussion by can some come participants. sidetracked diffi cult analyse c must taken Fdgs generale comments whole population. not Me mation: some UCLA useful Center brief Health guidance Policy material Research relatg has as focus well as groups a numr key mant techniques, terviews see:

29 4.3 Good what it how get it Good constently refl ects what accurately, really happeng reliably population service studyg. To get good need : use appropriate good measurement collection techniques, struments cludg appropriate samplg techniques ols ensure entered sred accurately out duplications constently errs collection Attributes ols good Good reliable F, a ol useful need measurg confi dent meang its ability get repeatable results its reliability when subsequent don t measurements expect a change same have thg, occurred., Only what reliable measurements observg can true situation, confi dent terventions what represents measure after a true. Unreliable example results a poly come designed from unreliable survey ols, m, which may completed differently audit by differently different people by (ter-observer same person at reliability) times (tra-observer reliability). different Similarly,, identify want a change ol when use it has occurred. responsive, reliability nature responsiveness question may fi eld. related example, a description dease clical F may ambiguous may ree terpreted outcome differently defi nitions by different imptant people. Clear rules fi elds should establhed from outset. A useful exerce a defi nition set rules up a dictionary various cludes Table 4.1 overleaf). fi elds (see lat a m survey also imptant ensurg reliable completion, so o triallg struments identify reliability problems. Good valid Validity measurement an ol. imptant Validity simply attribute means a good measures what it supposed measure. ol Many physical thgs quantities we measure such as height, temperature medication directly directly use. se usg an readily appropriate observable strument, eir thus tendg we confi measure. dent Testg we validity measurg comes what we imptant such as however life when range we lookg motion at variables suppt, sce measurements se facrs social from dependent person on person ir defi nitions, which way y may vary measured. different answers, Different struments rag question may ree what result right answer? Validatg which we determe an strument confi scale dence a process which by make ferences about people based on scale. we A strument dcussion scale how we yond go about scope validatg th an suffi ce it say, should, wherever possible, guide out validated struments conduct seek self wher wk. it has When en choosg tested agast an strument a gold ask stard accepted measurement ol. Good unbiased Bias measures created true when result, a ol leadg over measures an valid under Bias can occur as a result survey questions result. researchers lead know participants treatment a certa g way used when expectations fl uence ir observations. Bias can ir also not represent result from choosg broader sample population populations (see Table 4.1). do 27

30 28 Table 4.1 Sample dictionary Variable lal name Data type Defi nition/ purpose Possible values checks Restrictions/ Patient mation Gender Categical Male female M F Must M F Age Numerical Age nest years year years numr Must a whole Height Numerical Height centimetres 0 300cm decimal Measure pot one Weight Numerical Weight kilograms 0 250kg decimal Measure pot one Operation Operation Description Name operation Text (refer checklt) checklt Must from Surgeon Description itial Surname fi rst Text (refer checklt checklt Must from Duration Numerical Duration operation anaessia from hours full Hours pot To one decimal mutes Antibiotics admtered Antibiotic Description antibiotic Full generic name Text (refer checklt) checklt Must from Dose Numerical Dose milligrams antibiotic Any numr Must a whole Numr doses Numerical Numr antibiotic given doses 0 10 numr Must a whole Frequency Numerical Numr dered per doses period 24-hour 0 6 numr Must a whole Qualitative Barriers change Description terviews Barriers identifi ed Text characters Up 100

31 4.3.2 Samplg Samplg hearts one those stattically terms unitiated strikes fear good reason it a complex a can come very technical. imptant it will feasible thg underst collect on all it relevant unlikely patients will ree services have wk target a sample population. You will have give some consideration wher sample select reasonably representative population affected by project. If population,selection samplg not bias representative likely occur, affect validity conclusions. Selection which bias will might occur if, example: a time choose period exame not a representative sample group durg usual practice, such as durg holiday on weekends period brasrmg health pressionals activity do participatg not represent all maj stakeholders speakg survey clients. respondents do not clude non-englh Samplg subjects refers as well as how numr y observations probably heard rom samplg, chosen. which You ve means population. subjects Th st chosen st at rom samplg, from based on will have assumption an equal chance all subjects g selected. population In as terms exactly sample how many size, subjects re no should magic numr It will depend on a range facrs cludg: cluded. mation nature g question collected g asked demonstratg degree confi dence any change want a have not just nmal variation true change, easy amount it will mation obta g mation collected, how resources available. Sample might size useful calculars when tryg (available determe on ternet) an appropriate seek advice sample from a size, stattician, but st particularly approach if measure planng effects a e an tervention. after In collection it will imptant samples select th case, e after studies not only representative overall population but comparable each. Me mation: See Useful resources. various stattical references Appendix 3, Data entry, checkg cleang Data management entry an process imptant step can a source Appropriate considerable trag err if not undertaken entry personnel cfully. imptant, y cludg enterg. ensurg a basic dictionary understg mentioned earlier imptant th regard. Aumatic ensurg edit checks accuracy. a Programmers furr means add rules base programs : can prevent shouldn t certa fi elds from g fi lled out when y restrict entered mat range values can ensure completeness recd. Manually advable. edit Th checkg can done by scanng also a spreadsheet (such as detect gaps unusual values) tables might can identify, done by example, creatg where tables. re se an it might unacceptable identify crect level msg values; mation an age value 125 likely crect (refer example, section Tabulatg ). also If problems identifi ed will n need : vestigate reasons bad determe wher how it can crected perm collection accuracy ol checks entered comp. igal DATA TIP: EpiData ( public an easy--use program doma permits detailed control entry, checks. 29

32 30 DATA TIP: Data use tip computer- Wher srage paper-based sure methods, a copy take If make a. mtake calculations accidentally erase part will have, igal go. It s also a good back idea copy fi le give a different name. 4.4 Srg managg Data one srage should an addressed imptant early consideration project planng. sred F paper straightward recds. Computer-based projects, may some kd a practical safe approach. srage three ma choices: re spreadsheet Lotus 1-2-3, programs Quattro Pro) (such as Microst Excel, base Lotus Approach, programs Filemaker, (such as Ability Microst Database) Access, stattical Social programs Sciences (such SPSS, as Stattical SAS). Package Table 4.2 Data srage/analys options Srage method advantages Features/ Spreadsheet programs Easy enter set up Can simple produce graphs Readily most ganations available A ons range available add via enhance ternet applications Database programs Inmation as complete sred recd Can query easily Readily many available ganations Stattical packages Enables analys as entry srage well as Enables manipulation, comparons analys stattical st option collection project will depend on skills nature resources available. Bee make a about decion, options speak already someone available what ganation might st suit project. options Wher means, structure collectg by a paper logical, relatable electronic way. ger F example, keep keep all all related related a ward patients If doubt, seek asstance it tter set ger. properly fi rst place. up Dadvantages Typical usage Skills required not Inmation sred as complete recd a projects Straight ward limited variables termediate Basic requirements limited computer required skills setup comparon analys analys Specifi set up c skills Me undertake diffi cult analys user requires as knowledge run a query how trag Needs specifi c Often explicitly needs purchased can expensive projects Me complex collected especially over pots multiple time me Projects complex requirg analys, example, associations fi nd tween outcomes variables Specifi c trag required set up Trag system use processes stattical approaches