Measuring Nursing Quality

Institute of Nursing Science www.nursing.unibas.ch

Measuring Nursing Quality

Prof. Dr. Michael Simon

Directorate of Nursing/AHP – Nursing Research Unit

Prof. Dr. Michael Simon 2

Inselspital Bern – Directorate of Nursing/AHP- Nursing Research Unit ~ Institute of Nursing Science, University of Basel

Content

•  Background Quality Measurement

•  Example USA: NDNQI

•  Example UK: Safety Thermometer

•  Example GER: PTVS

•  Outlook and conclusions



What’s constitutes a great indicator? I

1.  Importance of the Measure

–  Relevance for stakeholders

–  Health importance

–  Potential for improvement

–  Susceptibility of being influenced



What’s constitutes a great indicator? II

2.  Scientific Soundness

–  Explicitness of evidence

–  Strength of evidence

–  Reliability

–  Validity

–  Allowance for stratification or case-mix adjustment if appropriate.

–  Comprehensible



What’s constitutes a great indicator? III

3.  Feasibility

–  Explicit specification

–  Data availability



Florence Nightingale

Nightingale, Florence. (1863). Notes on hospitals (3d ed.). London: Longman, Roberts, and Green.



“Nursing-sensitive performance measures are processes and outcomes— and structural proxies for these processes and outcomes (e.g., skill mix, nurse staffing hours)—that are affected, provided, and/or

influenced by nursing personnel, but for which nursing is not exclusively responsible. Nursing-

sensitive measures must be quantifiably influenced by nursing personnel, but the relationship is not

necessarily causal.”

“Nursing Sensitivity”

National Quality Forum. National Voluntary Consensus Standards for Nursing-Sensitive Care: An Initial Performance Measure Set. Washington, DC: NQF; 2004. 7



Donabedian’s S-P-O model

Donabedian, A. (1992). "The role of outcomes in quality assessment and assurance." QRB Qual Rev Bull 18(11): 356-360.



Public Reporting Model

BERWICK, D. M., JAMES, B. & COYE, M. J. 2003. Connections between quality measurement and improvement. Medical care, 41, I30-8.



„The bitterness of poor quality remains long

after the sweetness of low price

is forgotten.“

Benjamin Franklin



11

No of falls per hospital

fall Min. : 17.00 1st Qu.: 33.00 Median : 55.00 Mean : 57.62 3rd Qu.: 80.00 Max. :112.00



12

No of falls per hospital

Patient days Min. :4481 1st Qu.:4967 Median :5362 Mean :5296 3rd Qu.:5644 Max. :6074



13

Falls per 1,000 patient days

fall.rate Min. : 3.034 1st Qu.: 6.503 Median :10.186 Mean :10.944 3rd Qu.:14.604 Max. :22.242

Hosp.A

Hosp.B



Quality Measurement for Selection (Provider Profiling)

ModifiziertnachVANDISHOECK,A.-M.,LINGSMA,H.F.,MACKENBACH,J.P.&STEYERBERG,E.W.2011.RandomvariaPonandrankabilityofhospitalsusingoutcomeindicators.BMJQualSaf,20,869-874.

ObservedDifferences

Unexplaineddifferences

PaPentcharacterisPcs

Chance/Uncertainty

ResidualesConfounding

RegistraPonBias

QualityofCare

Meanonorganisa-Ponallevel

StraPficaPon

RiskstandardizaPon,

O/E

OLS,GLM

EmpiricalBayes

MulPlevel,GLMM

Unexplaineddifferences

Concepts

Methods

Hosp.A

Hosp.B x



Quality Measurement for Quality Improvement

Observeddifferences

Chance

PaPentCharacterisPcs

ResidualesConfounding

QualityofCare

StaPsPcalProcessControl(SPC)

Regression

Concepts

Methods

HospA

Pme

t1

t2

t3



IN GOD WE TRUST; ALL OTHERS MUST BRING DATA. W. EDWARDS DEMING

16



Example: % of patients with fall event 1.  Crude mean 2.  Risk-adjusted standardized rate 3.  Empirical Bayes



Simulated data • 50 units • 1500-2000 patients per hospital • Fall risk: 0-73% • Mean fall probability: 0.03 • Length of stay: Poisson, mean=3



Plain mean: % patient with a fall

Min. :0.009 1st Qu. :0.019 Median :0.030 Mean :0.033 3rd Qu. :0.043 Max. :0.065



+ Standardized Rate (risk adjusted)


Min. :0.020 1st Qu.:0.026 Median :0.028 Mean :0.033 3rd Qu.:0.041 Max. :0.059



+ Empirical Bayes (sample size + risk adjusted)

21









Summary

• Under given assumptions: – Plain fall rates over estimate differences – Risk-adjusted rates have smaller differences – Empirical Bayes when fall rates are intended to be used for provider profiling



NDNQI Example USA



•  Founded 1998 by the American Nurses Association (ANA)

•  Administered by University of Kansas School of Nursing

•  05/2014 sold to Press-Ganey

•  ~2000 hospitals

•  >20.000 units

• Quarterly benchmark reports

•  Annual nurse survey (n=>400,000)

• NQF-developer

• Relevant for CMS‘ payment

National Database of Nursing Quality Indicators (NDNQI®)



• Skill mix: – Registered Nurses (RNs) – Licensed Practical/Vocational Nurses (LPN/LVNs) – Unlicensed Assistive Personnel (UAP)

• Nursing Hours per Patient Day • RN Education/Certification • Nurse Turnover • RN Survey:

– Practice Environment Scale – Job Satisfaction Scales

NDNQI-Indicators I



• Patient Falls/Injury Falls • Hospital/Unit-Acquired Pressure Ulcers • Physical/Sexual Assault • Pain Assessment/Intervention/Reassessment Cycles • Peripheral IV Infiltration • Physical Restraints • Healthcare-Associated Infections:

– Catheter-Associated Urinary Tract Infection – Central Line-Associated Bloodstream Infection – Ventilator-Associated Pneumonia – Ventilator-Associated Events

NDNQI-Indicators II



SAFETY THERMOMETER Examples UK



Example UK: Safety Thermometer

• “Harm free care” • Since 2012 • P4P (CQUIN) • Pressure ulcers, falls, CAUTI, VTE • <10 Minutes per patient • 1.8 Mio patients in 2013 • „Open data“



Copyright © 2014, Health & Social Care Information Centre. All rights reserved. i

Appendix 1: Definitions Data Recording Data is recorded monthly for every NHS-funded patient in participating organisations. It is recorded by ward or team name, organisation code, and organisation name.

The following table describes the data recorded for each patient:

Table 1: NHS Safety Thermometer Patient data

Field Values Notes

Age Band: 1 = <18, 2 = 18-70, 3 = >70

Sex: 1 = F, 2 = M

Old PUs 1 = None, 2 = Cat 2, 3 = Cat 3, 4 = Cat 4

New PUs 1 = None, 2 = Cat 2, 3 = Cat 3, 4 = Cat 4

Falls 1 = No Fall, 2 = No Harm, 3 = Low Harm, 4 = Moderate Harm, 5 = Severe Harm, 6 = Death

A value of ‘2’ is not a Harm

UTIs 1 = No UTI, 2 = Old UTI, 3 = New UTI

Catheters 1 = No Catheter, 2 = 1-28 days, 3 = >28 days, 4 = Days Not Known

VTE Risk Assessment

1 = No, 2 = Yes, 3 = N/A

VTE Prophylaxis 1 = No, 2 = Yes, 3 = N/A

VTE Treated 1 = No VTE, 2 = Old DVT, 3 = Old PE, 4 = Old Other, 5 = New DVT, 6 = New PE, 7 = New Other

Values 5 to 7 are New Harms Values 2 to 4 are not Harms

The following count as harms: old or new pressure ulcers, falls with harm, catheters with UTIs, and new VTEs.

The following count as new harms: new pressure ulcers, falls with harm, catheters with new UTIs, and new VTEs.

Guidance included in the NHS Safety Thermometer tool Pressure Ulcers The Safety Thermometer asks you to record the patient's worst old pressure ulcer and worst new pressure ulcer. An 'old' pressure ulcer is defined as being a pressure ulcer that was present when the patient came under your care, or developed within 72 hours of admission to your organisation. A 'new' pressure ulcer is defined as being a pressure ulcer that developed 72 hours or more after the patient was admitted to your organisation. To collect the data, you should examine the patient for any skin damage and ask them about any skin damage they have experienced as well as consulting their notes or handover documents.

HSCIC (2014). NHS Safety Thermometer: Patient Harms and harm free care



Falls in general medical wards

~2/3 of wards don’t have any falls

~3% of patients fell

~1% of patients falls with injuries



Hospital level comparison Org.Code

RGRRW3RTPRVYRFSRLNRBTRMPRJFRL4RLQRTDRDERWHRBLRH8RD1RTGRC9RM3RWYRA7RDZREMRCFRDDRC3RCXRA9RWWVM0C0RY5RYWRWPRJERN3RJ1RASRXQRJDRBDRN7RNLRXKRQWR1HRKBRR7RRFRWFRC1RVRRBKRFFRWNRHWRM1RA2RDURXWRKERFWRGNRJ6RVVVLYJ5RD8RWJRBAREFRNZRVJRTERJZRTKRV3RA4RA3RQ6RBNRGTRXRRH5RXCRK5RLTRVLRYRRNARNQRM2RWDR1GRQMRJ2RP5RJNRWGRTXRFRRAJRXPRXFRHM

−0.5 0.0 0.5 1.0

(Intercept)



ward.id

RJ2:QEW WARD 15ARFR:A5RBT:WARD 7RXP:1 UHNDRTE:RYEWORTHRXF:QUEEN ELIZABETH HOUSERFS:16RRF:INCERWP:WAMURWD:LINCOLN WARD BURTONRWW:A8RTE:4BRFS:5RXP:6 BAHRWD:LINCOLN WARD DIXONRGR:G4RCX:PENTNEYRXP:52 DMHRP5:WARD 26RDD:ECMBRBK:WARD 03RWP:WAVON3RTD:FH WARD 16RFS:1RCX:TERRINGTONRNQ:HARROWDEN AREM:MAURVR:EGH − CHUTER EDE AMURLN:B28RNL:LARCH CRBT:WARD 2RXR:C9RJE:WARD 210REF:MED 2 WCHRDD:EFMBRWG:WHITE 2RA3:KEWSTOKER1H:PLASHETRQM:EDGAR HORNERHM:AMU2RLN:E53RVR:EGH − CROFT WARDRNL:JENKINRD1:CHESELDENRYR:ASHLINGRXC:BAIRDRVR:EGH − BUCKLEY WARDRTP:HAZELWOODRBN:2ARTD:FH WARD 17RA9:SIMPSONRCF:WARD 15RQW:LISTERRLQ:ROSS COMMUNITY HOSPITALRK5:SCONCERCX:MAURDE:NAYLANDRN3:NEPTUNERC9:WARD 11RWF:CHAUCER WARDREF:GRENVILLERGR:F7 AMU AND SHORT STAYRWH:DIGSWELLRH5:BURNHAMR1G:NEWTON ABBOT TEMPLARRLT:MELLY GASTRORDD:WHMBRAJ:GORDON HOPKINSRTP:GODSTONE WARDRXK:D41RM2:F12RWP:WASURFS:14RJ6:AMURTX:FGH WARD 6RQW:RAYRFW:OSTERLEY 1RDU:F9RR7:24RGN:A10RVJ:WARD 107RP5:WARD A4RBT:WARD 4RA7:BHI WARD 54RL4:C19RKB:20RMP:WARD 41RC9:WARD 12RFR:B1RR7:25RGR:F10RD8:WARD 8RLT:FELIX HOLTRTD:FH WARD 18RLQ:ARROW WARDRDU:F3RWF:WARD 21RMP:WARD 42RGR:G5RTD:RVI WARD 31RJE:WARD 218 (123)RWD:GRANTHAM WARD 2RTG:306RNL:HONISTERRXR:C3RTE:7ARFW:AMURWY:WARD 6 HRIRQW:LOCKERMP:WARD 44RCF:AMURWG:AAU L3 BLUERNQ:CLIFFORDRDD:ORSETTRTE:8BRA7:BRI WARD 15RNQ:CRANFORDRBD:ABBOTSBURYRXP:44 DMHRJ2:QEW WARD 15BRXP:14 DMHRTP:AMURC3:6 SOUTHRFF:28RM2:F14RTE:6BRBK:WARD 17RH5:LYDEARDRJE:WARD 123 (122)VM0C0:UNIT ONE AND TWORL4:C16RNZ:REDLYNCHRBK:WARD 12RH5:CREWKERNER1G:TAVISTOCKRXC:WELLINGTONRXC:NEWINGTONRBD:EMURWY:WARD MAU CRHRXR:C6RLQ:WYE WARDRXR:MAURBT:WARD 14RWH:AAURP5:WARD 24RBL:WARD 26RNL:WILLOW BRJF:WARD 3RHM:AMU3RGT:C4RN7:OAKRC3:AMURYR:AMU WORTHINGRGT:EAU4RVY:9BRVY:14BRMP:WARD 40RWJ:A1RXF:38 PGHRTP:TANDRIDGE WARDRR7:1RH5:SWINBANKSRDE:DEDHAMRJ6:DUPPASRW3:ACUTE MEDICAL UNITRGN:CARDIAC WARDRDE:LANGHAMRY5:MANBY WARDRP5:WARD A5RJN:MEDICAL ASSESSMENT UNITRXP:RICHARDSON LOWSONRDZ:RB01RN7:ROSEWOODRVR:STH − MARY MOORE WARDRTE:7BRH8:LOWMANRLN:F61RGT:D5RTE:6ARGT:F6RVY:7ARXR:C8RWP:AMAUMRVV:KCH INVICTARKB:HOSKYNRWH:MAURC9:WARD 10RXC:SEAFORD 2 MSSURHW:SIDMOUTH WARDRBT:WARD 18RW3:WARD 46RWD:PILGRIM WARD CDURWJ:A14RXW:7RWP:WAVON4RJ6:PURLEY 1RJZ:OLIVERRGR:F9RFS:21RC1:WHITBREAD WARDRKE:ITURGT:N2RYR:DITCHLINGRQW:HARVEYRRF:ASTLEYRMP:WARD 31RGT:N3RNA:C8 ST 2RNA:C7 ST 3RWG:GADERXQ:WARD 10 SMHRKE:EXTRA WARDRXR:C4RA3:HARPTREE EASTR1H:NIGHTINGALERNZ:WHITEPARISHRTE:WOODMANCOTERXP:RICHARDSON STARLINGR1H:CURIERC1:HARPUR WARDR1H:11FRWP:AMAUFRFS:20RH5:HADSPENRWG:AAU 1 YELLOWRWJ:A11RWW:A1RH5:LUKER1H:STRATFORDRH8:OKEMENTRWW:A2RWH:9BRYR:ERRINGHAMRVY:11BRM3:SHC L3RJF:WARD 7RWG:AAU L3 YELLOWRDZ:RB24RM3:SHC L6 DIAB ENDORW3:AM4RJ1:ALBERTRAS:PINEWOODRLQ:REDBROOK WARDRJF:WARD 6RWF:ROMNEYRWP:A5RH5:EXMOORRKB:CDURR7:4RRF:WINSTANLEYRGR:G9 (FORMERLY F7)RH5:COATESRW3:WARD 5MRGN:B1 ISOLATIONRRF:ASURW3:WARD 30MRKB:2RWH:SSURLT:ADAM BEDE (DOLLY)RNL:BEECH ARXR:C11RD1:MSSURJZ:BROM MEDICAL 9RDU:G1RA7:BRI WARD 17RR7:11RJ6:FAIRFIELD 2RWH:6BRD8:CDURBL:AAURJF:WARD 12RM3:SHC H2 RESPRA7:BRI WARD 12R1G:BRIXHAMRW3:WARD 32MRP5:WARD 14 MSSRTP:CAPEL WARDRV3:TOPASRVY:7BRTE:KEMERTONRC1:ARNOLD WHITCHURCH WARDRA7:BRI WARD 7RW3:WARD 45RBL:AMURWF:CORNWALLISRC1:GODBER WARDRWW:B18RR7:14ARWP:WLAU2RAS:DRAYTONRVJ:F WARDRTK:MAYRH8:DYBALLRTX:FGH MEDICAL ADMISSIONS UNITRM3:NR H3 RENALRKB:3RC9:WARD 3RTG:409RYR:BURLINGTONRAS:BEVAN WARDRJ6:FAIRFIELD 1RJZ:LONSDALERW3:AM3RFF:23RM3:SURG H8 IFURKE:MARY SEACOLE SOUTHRC3:8 SOUTHRM3:CSS M3 DERMRTP:CHARLWOODRJZ:TWININGRNA:C8 ST 3RMP:WARD 30RL4:C17RVJ:K ANNEXER1G:TEIGNMOUTHRH5:BRENDONRKE:MARY SEACOLE NORTHRXW:32ERH5:ATHLONERYW:MHH W4RCF:WINTER WARDRYR:BOSHAMRVV:WHH OXFORDRW3:WARD 16 TRAFFORDRRF:CCURWH:10BSRWJ:B2RXF:20 PGHRV3:WOODHILLRYW:WARD 7RN3:SHALBOURNE SUITERW3:OMU − OBSERVATIONAL MED. UNITRTE:9ARWJ:C2RTG:PIURTD:RVI WARD 51RTK:MAURW3:WARD 31MRW3:WARD 31RRJD:AMURWD:LINCOLN WARD MEAURL4:A7RVJ:WARD 205RNQ:HARROWDEN CRBN:5DRJ2:QEW WARD 16RWY:WARD 6A CRHRTX:RLI WARD 39RXP:41 DMHRXQ:MEDICAL SHORT STAY SMHRFS:3RNQ:HC PRETTY ARWG:SARRATT WARDRXF:MAU DDHRP5:WARD C1RXF:6 DDHRAJ:STAMBRIDGERXW:22 SRRXF:5 DDHRXP:43 DMHRXP:6 UHNDRWN:HMP BEDFORDRWP:A6RDE:LAYER MARNEYRXP:3 UHNDRA4:WARD 9BRAJ:BLENHEIMRNZ:PITTONRWD:GRANTHAM WARD EAURAJ:ELEANOR HOBBSRXP:1 CLSRA3:BERROWRXP:2 SBHRN7:BEECHRQ6:AMURN7:EBONYRP5:ATCRM1:GUISTRTD:FH WARD 15RFS:18RN3:TEAL TRAUMA UNITRYR:PETWORTHRWW:A3RTD:RVI WARD 30RQM:DAVID ERSKINERWP:AECURA2:TILFORDRK5:34RVL:LARCHRYR:AMU ST RICHARDSRJ2:MULBERRYRWD:PILGRIM WARD 7BR1G:PAIGNTONRXK:L5RC3:5 NORTHRBK:WARD 14RWP:A12RYR:BOXGROVERJZ:MARY RAYRP5:C2 CARDIO & ENDORCX:STANHOERLT:BOB JAKINRTD:RVI WARD 48RFW:OSTERLEY 2RTK:MSSUR1H:11CRGN:B12RYR:LAVANTRP5:MAU DRIRWD:LINCOLN WARD CARLTON COLEBYRVJ:WARD 106RXR:C2RLQ:LUGG WARDRCF:WARD 07RTE:HAZELTONRJ2:ALDERRDD:M WARRENRYR:EARTHAMRTE:9BRAS:GRANGE−ADMISSIONSRWG:CROXLEY WARDREF:CARNKIERW3:WARD 6 TRAFFORDRD8:WARD 3RFS:13RYR:BROOKLANDSRXP:11 UHNDRVJ:WARD 30RHW:REDLANDS ESCALATION WARDRGT:C5RXC:FOLKINGTONRFS:17RM2:A7RNL:PATTERDALE PILLARR1G:DAWLISHR1H:11ERWF:MERCERRBN:1BRH5:MARY ROBERTSONRJ6:HEATHFIELD 1RWH:9ARWH:STANBOROUGHRXP:SEDGEFIELDRVJ:WARD 206RWD:LINCOLN WARD NAVENBYRJZ:ANNIE ZUNZRR7:22RNA:C6RWW:C22R1H:MARYRBD:HINTONRR7:12RNL:WILLOW ARQW:HENRY MOORERC9:WARD 4RLT:CCURXR:C7RNA:C7 ST 2VLYJ5:GENERAL UNITRM3:SHC L2 GASTRORMP:WARD 46RBA:WARD 1RRF:LOWTONRXW:AMU PRHRJN:WARD 3RR7:MAU SSURDU:AMURCX:TILNEYRNA:C7 ST 1RVR:C5RDU:F15RTE:ACUARNA:C8 ST 1RFF:17RH5:MARSHFIELDRWP:WLAU3RNL:LARCH ABRGT:R2RA4:WARD8ARTK:MAPLERD8:WARD 2RJZ:BROM MEDICAL 7RGT:D10RFR:A4RA7:BRI WARD 21RFR:A1RFW:LAMPTONRXF:10 DDHRLT:ELIZABETHRWF:MAU TWHRQW:WINTERRHM:E2RDD:FNMBRLT:MARY GARTHRWG:PURPLE &GREENRM2:F11RWP:WAVON2RJE:WARD 230RP5:WARD 17RXP:WEARDALERRF:STANDISHRQ6:7ARYR:EASTBROOKRTE:GW 1RBK:WARD 15RBT:WARD 3 AMURWD:PILGRIM WARD 8ARQM:AAURVV:KCH HARBLEDOWNRGN:A8RGT:K3RC1:ELIZABETH WARDRXR:D1RNZ:DURRINGTONREF:MED 1 WCHR1G:NEWTON ABBOT TEIGNRBN:2DRVR:STH − ACUTE MEDICAL UNITRJ2:ASPENRV3:WICURXP:5 UHNDR1G:TOTNESRKE:MERCERS WARDRHM:D5RKB:1RH5:WELLINGTONRQM:NELL GWYNNERTX:RLI ACUTE MEDICAL UNITRM2:F4RJ2:CHESNUT 1RWD:GRANTHAM WARD 1RVL:CDUMAU BHRAJ:ROCHFORDRJ6:PURLEY 2RXP:4 UHNDRH5:CATHEDRALRHM:D6RXR:B4RHM:D7RTX:FGH WARD 9RA3:CHEDDARRK5:36RTE:GUITINGRWJ:A10RXF:STROKE REHAB UNIT PGIRXF:MONUMENT HOUSERP5:WARD 27RXF:A1RJN:WARD 9RHM:D8RFR:A2RAJ:ESTUARYRXP:51 DMHRXC:CUCKMERERWG:GREEN LEVEL 1RNQ:MAU

−2 0 2 4

(Intercept)

Ward level comparison



PTVS Example Germany



• >13,000 Nursing homes in Germany • Since 2009 annual inspections of the Medical Advisory

Services of the Statutory Health Insurance • 82 pre-defined criteria and summarised by grades (PTVS) • Critique: Emphasis on structures and processes and its

limited ability to differentiate between nursing homes.

Background



•  “Care transparency agreement home care” • Overall Quality Rating --

• Medical & Nursing Care • Dementia Care • Social environment and daily activities • Room and board services --

• Resident interviews

PTVS data



•  Internal Quality Management Monitoring of a not-for-profit organisation in Germany

• 83 Nursing homes • Annual Survey of staff • % of residents with a fall

3Q-Study



Overall Quality

PTVS Overall Rating Nur

se p

erce

ived

qua

lity

bette

r

better



Risk assessment (measured by PTVS) vs. % residents with fall

bette

r

better



Fall prevention (measured by PTVS) vs. % residents with fall

bette

r

better



Falls vs. different criteria from PTVS

! !%! O/E!

r! p! r! p!

Falls!

(QGS)! Overall!Score! 0,04! 0,60! 0,09! 0,25!

(QB1)! Medical!and!nursing!care! 0,01! 0,88! D0,01! 0,92!

(T24)! Fall!risk!assessment! D0,03! 0,75! 0,01! 0,90!

(T25)! Documentation! D0,03! 0,73! 0,01! 0,90!

(T26)! Fall!prevention! D0,06! 0,46! D0,02! 0,81!

!



Summary

• “The good, the bad and the ugly”

• Educational needs

• Research on indicators

• Research on implementation

• Health policy



Literatur •  Berwick, D. M., B. James and M. J. Coye (2003). "Connections between quality measurement and improvement."

Med Care 41(1 Suppl): I30-38. •  Bouldin, E. L., E. M. Andresen, N. E. Dunton, M. Simon, T. M. Waters, M. Liu, M. J. Daniels, L. C. Mion and R. I.

Shorr (2013). "Falls Among Adult Patients Hospitalized in the United States: Prevalence and Trends." Journal of Patient Safety 9(1): 13-17.

•  Dixon-Woods, M., R. Baker, K. Charles, J. Dawson, G. Jerzembek, G. Martin, I. McCarthy, L. McKee, J. Minion, P. Ozieranski, J. Willars, P. Wilkie and M. West (2013). "Culture and behaviour in the English National Health Service: overview of lessons from a large multimethod study." BMJ Quality & Safety.

•  Donabedian, A. (1988). "The quality of care. How can it be assessed?" JAMA : the journal of the American Medical Association 260(12): 1743-1748.

•  Donabedian, A. (1992). "The role of outcomes in quality assessment and assurance." QRB Qual Rev Bull 18(11): 356-360.

•  Normand, S.-L. T., M. E. Glickman and C. A. Gatsonis (1997). "Statistical Methods for Profiling Providers of Medical Care: Issues and Applications." Journal of the American Statistical Association 92(439): 803-814.

•  Normand, S.-L. T. and D. M. Shahian (2007). "Statistical and Clinical Aspects of Hospital Outcomes Profiling." Statistical Science 22(2): 206-226.

•  Simon, M. and N. Dunton (2014). Entwicklung, Erprobung und Anwendung von Qualitätsindikatoren der Pflege im Krankenhaus: das Beispiel NDNQI® aus den USA. Qualitätsentwicklung in der Pflege - Methoden und Instrumente. D. Schiemann, M. Moers and A. Büscher, Kohlhammer.

•  Simon, M., S. Klaus, B. J. Gajewski and N. Dunton (2013). "Agreement of Fall Classifications Among Staff in U.S. Hospitals." Nursing Research 62(2): 74-81.

•  Simon, M., S. Schmidt, C. G. G. Schwab, H.-M. Hasselhorn and S. Bartholomeyczik (2013). "Messung der Pflegequalität in der Langzeitpflege - Eine vergleichende Analyse von Pflegetransparenzkriterien, bewohnerbezogenen Indikatoren und Beurteilungen der Mitarbeiter." Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 56(8): 1088-1097.

•  van Dishoeck, A. M., H. F. Lingsma, J. P. Mackenbach and E. W. Steyerberg (2011). "Random variation and rankability of hospitals using outcome indicators." BMJ Qual Saf 20(10): 869-874.

Documents

Measuring Nursing Quality