CNESERIES. Instructions for Contniuing Nt4rsiii¿J! Education Eontact Houraap&Won page 254¿

Use of a Clinical Decision SupportSystem to Improve Hypoglycemia

ManagementRoberta L Harrison, 5on/o L Stalker, Rochelle Henderson, and Frank Lyeria

Currently, over 10.9 millionU.S. residents age 65 or olderhave a diagnosis of diabetes.

An estimated 79 million U.S. resi-dents age 20 or older have pre-dia-betes (Centers for Disease Controland Prevention [CDC], 2011). In theUnited States, diabetes remains the7th leading cause of death. Seriouscomplications also are associatedwith diabetes, including heart dis-ease, kidney failure, vision loss, andamputation (CDC, 2011). A currentdebate centers on whether practi-tioners should enforce stringentglycémie control. A recent meta-analysis (Murad et al, 2012) foundstringent glycémie control carries anincreased risk of hypoglycemia.Therefore, one of the concernsaround stringent blood glucose con-trol is the increased risk for hypo-glycémie events. In the hospital set-ting, paper-based guidelines oftenpromote normal blood glucose.However, adherence to the paper-based hypoglycemia treatment guide-lines has been poor (Maynard,Huynh, & Renvall, 2008).

In this study, the research teamimplemented a nursing clinical deci-sion support system (CDSS) in theform of electronic hypoglycemiamanagement guideline advice.Interactive guidelines were embed-ded within the nursing documenta-tion section of the electronic healthrecord (EHR). The primary purposewas to improve nursing adherence tohypoglycemia management guide-lines and improve compliance track-ing. The secondary purpose was todetermine the impact of change ofwork shift on guideline adherence.

The number of persons with diabetes who enter the health care sys-tem continues to grow. Stringent glycémie management increasesthe risk for hypoglycemia. The use of a clinical decision support sys-tem to assist nurses in treating hypoglycemia accurately may beuseful in improving adherence to specific hypoglycemia manage-ment guidelines and compliance tracking.

Review of the Literature

HypoglycemiaHypoglycemia is defined as blood

glucose of less than 70 mg/dL(Pagana & Pagana, 2010). In the hos-pitalized patient, hypoglycemia isassociated with adverse drug reac-tions, decreased caloric intake, fail-ure to adjust medications that lowerblood glucose, and missing mealsdue to diagnostic testing requiringthe patient to be away from the unit(Anthony, 2007). More than 4O'K) ofpatients experiencing one hypo-glycémie episode will experience asecond episode during the same hos-pitalization (Maynard et al., 2008).

GuidelinesGuidelines to manage hypogly-

cémie episodes have been developedto allow nurses to intervene immedi-ately without having to contact the

physician first. Nurses who continueto use the paper-based guidelinesinternalize a process and no longerreview the document but ratherrely on memory (Rycroft-Malone,Fontenia, Seers, & Bick, 2009). Inaddition, these guidelines typicallyare housed in policy and proceduremanuals; as a result, nursing utiliza-tion and documentation have beensub-optimal. In a study examiningnursing adherence to practice guide-lines, Anthony (2007) found nurseshad poor compliance with paper-based hypoglycemia treatmentguidelines. In this descriptive study,210 retrospective medical recordreviews were completed; not onerecord was compliant with allrequirements in the practice guide-line. One proposed solution to thisproblem is to embed guidelineswithin the nursing documentationsection of a patient's EHR.

Roberta L. Harrison, PhD, RN, is Associate Professor, Southern Illinois University-Edwardsville, School of Nursing, Edwardsville, IL.

Sonia L. Stalker, MSN, CDE, APN-BC, is Diabetes Specialist, Anderson Hospital, Maryville, IL.

Rochelle Henderson, PhD, is Lecturer, Public Administration and Policy Analysis, SouthernIllinois University-Edwardsville, Edwardsville, IL.

Frank Lyeria, PhD, RN, is Associate Professor, School of Nursing, Southern Illinois University-Edwardsville, Edwardsville, IL.

Note: The authors received the AMSN Phillips Healthcare Research Grant for the researchreported in this article.

250 July-August 2013 • Vol. 22/No. 4 M E D S U R GisTTjns I isra.

Use of a Clinical Decision Support System to Improve Hypoglycemia Management CNELyerla, LeRouge, Cooke, Turpin,

and Wilson (2010) developed aCDSS with an embedded protocol toimprove nursing adherence to guide-lines preventing ventilator-assistedpneumonia. The embedded protocolin the CDSS prompted the nurse toposition the angle of the bed correct-ly for ventilator-dependent patientsand document the angle in the clin-ical record. The study was completedin three phases, with 105 observa-tions of documentation and head-of-bed angles recorded at each phase.Participants included 42 patientsand 33 registered nurses. Adherenceto documentation and head-of-bedelevation was measured before inter-vention, 1-2 months after interven-tion, and 4-5 months after interven-tion. Significant improvements werenoted in protocol adherence at 1 and5 months after implementation.

In another study, Kwok, Dinh,Dinh, and Chu (2009) evaluated theuse of an asthma protocol embeddedinto clinical documentation. In thisstudy, 50 patients with asthma werecompared to a historical controlgroup of 50 patients with a dischargediagnosis of asthma. The 50 patientswith asthma who presented in theemergency department over a 6-month period were assessed byphysicians using the Asthma ClinicalAssessment Form and Electronicdecision support CDSS. Followingimplementation of the CDSS, themedical records of the study patientswere compared to a control group. Asignificant improvement in docu-mentation of key clinical parametersfor asthma management was notedin the study group.

Clinical Decision SupportSystem

An interactive guideline embed-ded within an electronic healthrecord is an example of a CDSS. Aclinical decision support system is acomputerized program utilized with-in the health care setting to supportdecision making. A nursing CDSS isused within the context of nursing tosupport nursing decision making.CDSS programs are based upon if-then rules that tell the computer whatactions to take given certain informa-tion (Kumar, Singh, & Sanyal, 2009).

Information is accessed and storedwithin the knowledge base compo-nent of the CDSS. CUnical decisionsupport systems often are used to gen-erate alerts, reminders, or advice.Information used and generated by aCDSS should be evidence based, cur-rent, and have the ability to be updat-ed. In this study, the diaberic educatorwas responsible for maintaining cur-rent evidence associated with hypo-glycemia management. As the man-agement standards changed, the dia-betic educator was charged to workwith programmers to ensure nurseshad access to current hypoglycemiamanagement guidelines.

Methods

study Design and SettingThe study took place at a small

community hospital in the Midwest.Approval from the hospital's institu-tional review board was obtainedprior to study iniriation. Subjectswere limited to hospitalized hypo-glycémie subjects over age 18.Patients who experienced blood glu-cose below 70 mg/dL but werereceiving intravenous (IV) insulinand following the IV insulin proto-col were excluded from the study asthe treatment protocol was differentfrom the hypoglycemia protocolused in this study. Using an inter-rupted time series design, three dif-ferent samples of 150 or more med-ical records of patients with diabeteswho had at least one incident ofblood glucose below 70 mg/dL werereviewed for hypoglycemia protocolimplementation and documenta-tion. The first review was completed6 months prior to implementing theintervention; the second review wascompleted 6 months followingimplementation; and the last reviewwas completed 7-12 months afterimplementation. The intent of thefinal review was to determine ifguideline adherence rates persistedover time.

InterventionThe purpose of this study was to

develop and integrate a nursingCDSS for managing hypoglycemiawithin the EHR to facilitate adher-

ence to the guideline. The CDSSinvolved a hypoglycémie manage-ment protocol embedded within theelectronic nursing documentationsection of the patient's EHR. TheCDSS was activated when a bloodglucose level of 70 mg/dl or lowerwas entered. The nurse then wouldbe asked a series of questions, eachone followed by advice in accor-dance with the programmed hypo-glycémie management guidelines.For example, an initial questionasked if the patient can swallow. Ifthe answer was "yes," oral glucosewould be included in the treatmentrecommendation. If the answer was"no," intravenous glucose would belisted as a recommended interven-tion. Additional information on thedevelopment and implementationof this CDSS is published elsewhere(Harrison & Lyeria, 2012).

Data CollectionReview of discharged electronic

health records was conducted forpatients who had a primary or sec-ondary diagnosis of diabetes ftomFebruary 2010 to August 2011. Adata collection tool was developedand used by the researchers. Bloodglucose documentation was re-viewed in each record for evidence ofhypoglycemia episodes (below 70mg/dL). Episodes occurring withinthe intensive care unit were exclud-ed because a different intravenousglucose protocol was utilized. Allepisodes and documented treat-ments were collected via the datacollection tool.

Testing/TrainingTen nurse volunteers tested the

initial CDSS prototype. Nurses wereprovided hypoglycemia scenariosand asked to follow the steps provid-ed by the CDSS. A debriefing sessionthen was held to gather feedback toguide changes regarding the se-quence of questions and associatedrecommendations. Once the finalversion of the CDSS had been identi-fied, a training manual and instruc-tional videos were created. Manualsand videos were placed on each unitas well as uploaded to the organiza-tion's intranet.

MEDSURG July-August 2013 • Vol. 22/No. 4 251

CNEData Analysis

All data were entered, stored, andanalyzed using SPSS vl9 (StatisticalPackage for the Social Sciences - IBM,Armonk, NY). All subjects' identify-ing information was removed fiomthe data collection tool before enter-ing the data in a computer database.Data were collected via a chart audittool created by the research team.Collected data included subject visitnumber, date and time of initialepisode, recorded blood glucosevalue, level of consciousness, initialtreatment (4 or 8 ounces of orange orapple juice, three graham crackers,25 ml of 50% dextrose IV, 50 ml of50% dextrose IV, or 1 mg glucagonintramuscularly), swallowing ability,IV access, initiation of IV fluids, needfor follow-up blood glucose adminis-tration within 15 minutes, repeatedfollow-up actions if indicated, andphysician notification. A compliancescore was assigned to each observa-tion for each of the data collectionphases. A grace period of 5 minutesbefore or after the 15-minute follow-up mark was allowed. Observationswere grouped into those that oc-curred within 1 hour of a shiftchange and those that did not. Chi-square statistics were used to deter-mine significance of the interventionas well as a change of shift impact.Analysis of variance (ANOVA) wasused to compare mean blood glucosevalues across each phase and t testswithin phases. The statistical analy-sis concluded with a logistic regres-sion model to control for variablesfound to be significant. All p valueswere two-tailed and were comparedto a 0.05 alpha.

ResultsOf the 585 hypoglycémie episodes

reviewed, 284 were reviewed in phase1, 150 were reviewed in phase 2, and158 reviewed in phase 3. Althoughcompliance was not as high as theresearchers had hoped, the increasefiom 4% to 13% and then fiom 13%to 25% was statistically significant(x2=42.16,p£0.001) (see Figure 1).

Only 34% (n=68) of the 201 hypo-glycémie episodes recorded in thestudy occurred during a shift change.However, 95% (n=191) of those

FIGURE 1.Protocol Compliance by Phase

100%

•o(0

'ö.LUOO)D)

5c0)u

80%

60%

40%

20%

Not Followed

Followed

Phase 1 (n=284)

96%

4%

Phase2(n=151)

87%

13%

Phase 3 (n=150)

75%

25%

FIGURE 2.Episodes Occurring at Siiift Change and Protocol Compliance

45%

40%

% 35%

•2 30%

ü! 25%og, 20%

1 ''''o 10%

5%

0

• Not Followed

• Followed

B Overall

Phase 1

43%

42%

43%

0Phase 2

30%

32%

30%

Phase

wÊ—3

20%

34%

23%

occurred during the morning shiftchange. The percentage of hypo-glycémie episodes occurring at shiftchange for phase 1 was 43%, 30% forphase 2, and only 23% for phase 3(see Figure 2). The relationshipbetween compliance level and shiftchange was not statistically signifi-cant (x2=0.005, p=0.946).

The average blood glucose valuein each of the three phases ranged

from 56 to 57 mg/dl and was notstatistically significant (ANOVA,f=0.146, p=0.864) (see Figure 3).However, across patients in phase 2, astatistically significant differenceexisted between blood glucose forthose episodes where the protocolwas followed (51 mg/dl) and thosewhere it was not (58 mg/dl) (T test,i=4.85,p=0.010).

252 luly-August 2013 • Vol. 22/No. 4 M E D S U R G

Use of a Clinical Decision Support System to Improve Hypoglycemia Management CNEFIGURE 3.

Blood Glucose Average and Protocol Compliance

60

È 56

i f 54(J ni

Ö ¿. 52T3

§ 50m

48

46

• NoDYes• Overall

ïPhase

H

1

;

56

53

56

1Phase

2*

;

58

51

57

Phase 3

57

54

56

* statistically significant p < 0.05

TABLE 1.Logistic Regression Controlling for Blood Glucose

RegressionCoefficient (B)

' Statistically significant p < 0.05

Blood glucose was controlled by itsinclusion in the logisfic regressionanalysis (see Table 1). Researchersfound no greater likelihood forimproved compliance as a result ofdifterent blood glucose values (0.973).The odds rafio for phase 2 indicatedthe protocol was almost twice as like-ly (OR=1.843) to be followed than inphase 1 and almost three times aslikely (OR=2.818) in phase 3.

DiscussionClinical guidelines and protocols

for managing hypoglycemia are usedroutinely in health care practice.Nursing adherence to these guide-lines has been less than optimal

Phase 1

Phase 2

Phase 3

Blood Giucose

Constant

Reference Category

0.611*

1.036*

-0.028*

0.250*

0.193

0.177

0.011

0.597

1.843

2.818

0.973

1.025

(Anthony, 2007; Maynard et al.,2008). The purpose of this study wasto improve nursing adherence to aclinical guideline on hypoglycemiamanagement using CDSS and toimprove the ability to track compli-ance. In this study, a statistically sig-nificant improvement was notedbefore and after implementation ofthe hypoglycemia managementCDSS; however, the improvementwas not significant ftom a compli-ance standpoint (25% compliance).Nurses documenting hypoglycemiacontinued using the first page of thedocumentation tool for recordingthe blood glucose value and at timesnarratively added a treatment withinan open text box. Once the page

with the recorded blood glucosevalue was completed, however, nurs-es often failed to continue to the sec-ond page to complete the area inwhich the hypoglycemia protocolCDSS was embedded. Additionally,no statistical difterence was found incompliance levels when hypo-glycémie episodes occurred aroundshift change. However, trackingcompliance after implementing thenew CDSS required navigation toonly one screen, where all applicablecomponents of the hypoglycemiaguideline were located. This wasmuch improved ftom the previousdocumentation that required navi-gating to multiple screens to capturecompliance data. Compliance incompleting the training was initiallya concern for researchers. However,the study site reported 97% of staffdid complete the training.

During the CDSS development,nurses at the study site opted to keepthe original blood glucose reportingpage that included a text box for thecurrent blood glucose value and anopen text box for the nurse to add ashort narrative response. The CDSSfor hypoglycemia management wasadded as a second page or link thatwas consistent with other areas ofnursing documentation. No alertswere built into the system to requirethe nurse to go beyond the first pagewhere text boxes were located.

Current evidence-based educa-tion on the management of hypo-glycemia was made available to allstaft nurses prior to implementingthe new CDSS (Manchester, 2008). APowerPoint presentation about thehypoglycemia protocol, newly de-veloped CDSS (including screenshots), and case study examples weredeveloped, recorded, and transferredto a DVD. Copies of the DVD weredistributed to all nursing units. Afternurses watched the DVD, a 10-itempost-test was completed using anonline educational platform. Train-ing manuals including Screenshotsof the CDSS also were distributed toall the nursing units. Live trainingsessions were not conducted at therequest of nurse leaders, who alreadyhad scheduled a number of trainingsessions related to other changes inthe clinical documentation system.

MEDSURG isnmsiisro. July-August 2013 • Vol. 22/No. 4 253

Instructions ForContinuing Nursing

Education Contact HoursUse of a Clinical Decision

Support System to ImproveHypoglycemia Management

Deadline for Submission:August 31, 2015

MSN J1316

To Obtain CNE Contact Hours1. For those wishing to obtain CNE contact

hours, you must read the article and com-plete the evaluation through AMSN'sOnline Library. Complete your evaluationonline and print your CNE certificateimmediately, or later. Simply go towww.amsn.org/library

2. Evaluations must be completed online byAugust 31, 2015. Upon completion of theevaluation, a certificate for 1.3 contacthour(s) may be printed.

Fees - Member: FREE Regular: $20

ObjectivesThis continuing nursing educational (CNE)activity is designed for nurses and otherhealth care professionals who are interest-ed in a clinical decision support system toimprove hypoglycemia management. Afterstudying the information presented in thisarticle, the nurse will be able to:1. Discuss hypoglycemia management

guidelines and clinical decision supportsystems (CDSS).

2. Summarize a study examining the out-come of interactive guidelines to im-prove nursing adherence to hypo-glycemia management guidelines andimprove compliance tracking.

3. Describe implications for medical-surgi-cal nurses of a CDSS embedded withinthe nursing documentation section ofthe electronic health record.

Note: The authors, editor, and educationdirector reported no actual or potentialconfiict of interest in relation to this con-tinuing nursing education article.

This educational activity has been co-provid-ed by AMSN and Anthony J. Jannetti, Inc.

Anthony J. Jannetti, Inc. is a providerapproved by the California Board of RegisteredNursing, provider number CEP 5387. Licenseesin the state of CA must retain this certificate forfour years after the CNE activity is completed.

Anthony J. Jannetti, Inc. is accredited as aprovider of continuing nursing education by theAmerican Nurses' Credentialing Center'sCommission on Accreditation.

This article was reviewed and formatted forcontact hour credit by Rosemarie Marmion,MSN. RN-BC, NE-BC, AMSN EducationDirector. Accreditation status does not implyendorsement by the provider or ANCC of anycommercial product.

CNELimitations

This retrospective interrupted timeseries design had several limitafions.First, the study was conducted duringthe same time a number of other clin-ical documentation changes wereoccurring. This made staft educationchallenging as members already wereinvolved in multiple training ses-sions. Additionally, although theCDSS was included as a second pageto the documentation, the initialpage for blood glucose value docu-mentation remained unchanged.This may have been confusing tonurses; with no alert system in place,they could stop easüy after docu-menting the blood glucose value, ashad been done in the past. Only afterthe training videos were developedand distributed were the principalinvesfigators notified that audio capa-bilifies were limited on some of thenursing units. The study also had nocontrol group. Finally, with one facil-ity as the study site, results are notgeneralizable to other insfitufions.

Nursing ImplicationsThe results of this study indicate a

CDSS embedded within the nursingdocumentation section of the EHRcan improve adherence to hypo-glycemia management guidelines.However, to achieve maximum ben-efit, researchers must track the ex-pected outcomes following CDSSimplementation to determine ifadditional user training or systemalterations are needed. Medical-sur-gical nurses routinely manage hypo-glycémie events. This study demon-strated a CDSS could be used to assistnurses as they choose the mostappropriate actions to take during ahypoglycémie event.

Finally, current government man-dates require health care facilities toprepare reports indicating the mean-ingful use of their electronic healthrecords. The Centers for Medicare &Medicaid Services established objec-tives for meeting the meaningful usecriteria. One of the meaningful usecore objectives includes the devel-opment of CDSS rules similar tothose used in this study (U.S.Department of Health & HumanServices, 2010). This study found a

significant improvement in nursingguideline adherence following theimplementation of a CDSS. Otherhealth care facilities can use this asan exemplar in meeting this govern-ment mandate.

ConclusionAdherence to current clinical

guidelines is an important facet ofquality improvement. Nurses needquick access to specific guidelines ina format that allows them to docu-ment in an accurate and efficientmanner. The use of a CDSS can meetthis need and also can provide ameans for tracking documentationcompliance easily. This study result-ed in improved nursing compliancewith hypoglycemia guideline docu-mentation, although opportunityexists for continued improvement.As a result of the project, nurse lead-ers at the study site removed theopen text box on the first page of theCDSS and added directions to pro-ceed to the second page. Removal ofthe open text box may yield a high-er compliance score in the future.Hypoglycemia guideline compliancenow is measured and reportedmonthly during meetings of thesite's quality council. In the future,the timing in presenting a new CDSSwill be considered so training can becompleted through a live in-servicewith demonstration and returndemonstration rather than a videoformat. CHZl

REFERENCESAnthony, M. (2007). Treatment of hypo-

glycemia in hospitalized adults. TheDiabetes Educator, 33(4), 709-715.doi:10.1177/0145721707303806

Centers for Disease Control and Prevention(CDC). (2011). 2011 nationai diabetesfact sheet Retrieved from http://www.cdc.gov/diabetes/pubs/referencesi 1 .htm

Harrison, R.L., & Lyeria, F. (2012). Using nurs-ing clinical decision support systems toachieve meaningful use. Computers,Informatics, Nursing, 30(7), 380-385.doi:10.1097/NCN.0b013eb813

Kumar, A.K., Singh, Y, & Sanyal, S. (2009).Hybrid approach using case-based rea-soning and rule-based reasoning fordomain independent clinical decisionsupport in ICU. Expert Systems withAppiications, 36(1), 65-71. doi: 10.1016/i.eswa.2007.09.054

continued on page 263

254 July-August 2013 • Vol. 22/No. 4 M E D S U R Gisrxj:R s iisrcs.

Signal-to-Noise Ratio: Filtering Out Ineffective Communication

• Tells the recipient what cannot be done.• Has a subtle tone of blame.• Includes words like can't, won't, unable to, which tell

the recipient what the sender cannot do.• Does not stress positive actions that would be appro-

priate, or positive consequences. (Bacal, 2013, p. 2)Positive phrasing and language have the following

qualities:• Tells the recipient what can be done.• Suggests alternatives and choices available to the

recipient.• Sounds helpful and encouraging rather than bureau-

cratic.• Stresses positive actions and positive consequences

that can be anficipated. (Bacal, 2013, p. 2)

Filtering SNPIn today's health care environments', the art of listen-

ing and paying attention can be lost due to distractionsfrom many sources. Effective nurse managers have the artand skill of dealing with SNR. They can identify a legiti-mate signal versus noise. They know the strength of thesignal in the workplace in no way indicates the impor-tance of the message being delivered. Some employees

may speak softly or rarely, but have an important mes-sage. The SNR actually may be reversed, with the noiselevel far exceeding the softly delivered signal. Noise maybe more apparent and noticed due to its intensity and/orfrequency, but that does not mean soft signals should bediscounted. They may be the most significant of all. Thequiet, unassuming employee needs to be heard just asmuch as the loud staff member. Unfortunately, unlikeelectrical systems, loudness and fiequency do not consti-tute legitimacy. Understanding and appropriately filter-ing SNR represent both an opportunity and a fundamen-tal skill of the successful manager. HIM

REFERENCESAudio Precision. (2012). Signal-to-noise ratio. Retrieved from http://

www.ap.com/solutions/introtoaudiotest/snrBacal, R. (2013). Using positive ianguage. Retrieved trom http:/A f̂ork

911 .com/articles/poslan.htmManagement Study Guide. (2013). Roie of communication barriers

in ineffective communication. Retrieved from http://www.managementstudyguide.com/role-of-communication-barriers-in-inetfective-communication.htm

TechTarget. (2013a). Signal-to-noise ratio (S/N or SNR). Retrieved fromhttp://searchnetworking.techtarget.com/detinition/signal-to-noise-ratio

TechTarget. (2013b). Signai. Retrieved from http://searchnetworking.techtarget.com/detinitbn/signal

Improved Hypoglycemia Managementcontinued from page 254

Kwok, R., Dinh, M., Dinh, D., & Chu, M. (2009). Improving adherence toasthma clinical guidelines and discharge documentation fromemergency departments: Implementation of a dynamic and inte-grated electronic decision support system. Emergency MedicineAustraiasia, 21, 31-37. doi:10.1111/¡.1742-6723.2008.01149.x

Lyeria, R, LeRouge, C, Cooke, D.A., Turpin, D., & Wilson, L (2010). Anursing clinical decision support system and potential predictors onhead of bed positioning for mechanically ventilated patients.American Journal of Criticai Care, 79(1), 39-47. doi:10.4037/ajcc2010836

Manchester, CS. (2008). Diabetes education in the hospital:Establishing professional competency. Diabetes Spectrum, 21(4),268-271. doi:10.2337/diaspect.21.4.268

Maynard, G., Huynh, M., & Renvall, M. (2008). latrogenic inpatient hypo-glycemia: Risk factors, treatment, and prevention. DiabetesSpectrum, 21(4), 241-247. doi: 10.2337/diaspect.21.4.241

Murad, M.H., Coburn, J.A., Coto-Yglesias, F., Dzyubak, S., Hazem, A.,Lane, M.A., ... Montori, V.M. (2012). Giycemic control in non-criti-caliy ill hospitalized patients: A systematic review and meta-analy-sis. Journai of Clinicai Endocrinoiogy and Metaboiism, 97(1), 49-58. doi:10.1210/jc.2011-2100

Pagana, K.D., & Pagana, TJ. (2010). Mosby's manual of diagnostic andlaboratory tests. St. Louis, MO: Mosby Elsevier

Rycroft-Malone, J., Fontenia, M., Seers, K., & Bick, D. (2009). Protocol-based care: The standardization of decision-making? Journal ofClinical Nursing, 18,1490-1500. doi:10.1111/j.1365-2702.2008.02605.x

U.S. Department of Health and Human Sen/ices, Centers for Medicare& Medicaid Services. (2010). Medicare and Medicaid programs:electronic health record incentive program: final rule. EederaiRegister, 75(144). Retrieved from http://www.gpo.gov/fdsys/pkg/FR-2010-07-28/html/2010-17207.htm

ADDITIONAL READINGAnthony, M. (2008). Relationships among nurse staffing, adherence to

practice guidelines, and patient outcomes in the treatment of hypo-glycemia. Quaiity Management in Heaithcare, 77(4), 312-319doi:10.1097/01.QMH.0000338552.13136.1e

A Conceptual Modelcontinued from page 220

Queensland Nursing Council. (2005). The scope of practice - frameworkfor nurses and midwives QNC. Retrieved from http://www.health.qId.gov.au/parrot/html/Documents/NursingScPrac.pdf

Pelchat, D. (2010). PRIFAM: A shared experience leading to the trans-formation of everyone involved. Journal of Child Health Care,74(3), 211-224.

Shea, C.A. (2008). Psychiatric nursing education at a distance. Journaiof the American Psychiatric Nurses Association, 14(1), 36-38.

Tilus, S.L. (2002). The influence of nursing education on collaborativedischarge planning. Journal for Nurses in Staff Development,78(5), 274-281.

Williams, S. (2008). The roie of patient education in the rehabilitation ofpeople with spinai cord injuries, international Journai of Therapyand Rehabilitation, 75(4), 174-179.

Wittmann-Price, R.A., & Fisher, K.M. (2009). Patient decision aids: Toolsfor patients and professionals. American Journai of Nursing,709(12), 606-663.

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